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Abstract: The pulp and paper industry is one of the most energy-intensive industries worldwide. In 2007, it accounted for 5% of total global industrial energy consumption and 2% of direct industrial carbon dioxide (CO2) emissions. An energy audit is a primary step toward improving energy efficiency at the facility level. This paper describes a plant-wide energy audit aimed at identifying energy conservation and CO2 mitigation opportunities at a paper mill in Guangdong province, China. We describe the energy audit methods, relevant Chinese standards, methods of calculating energy and carbon indicators, baseline energy consumption and CO2 emissions of the audited paper mill, and nine energy-efficiency improvement opportunities identified by the audit. For each of the nine options, we evaluate the energy conservation and associated CO2 mitigation potential. The total technical energy conservation potential for these nine opportunities is 967.8terajoules (TJ), and the total CO2 mitigation potential is equal to 93,453tonnes CO2 annually, representing 14.4% and 14.7%, respectively, of the mill’s total energy consumption and CO2 emissions during the audit period. [Copyright &y& Elsevier]

Abstract: This paper studies allocation of fuel costs and CO2-emissions to heat and power in a CHP plant producing heat to an integrated pulp and paper mill and electricity to the liberalized electricity markets (or to the mill by the market price). The CHP plant and the mill are considered to be two separate economical units and both the mill and the CHP plant perspectives are discussed. Fuel costs and CO2-emissions are allocated using the energy, exergy and market based methods. The CHP plant purchases black liquor and bark from the mill. It also purchases oil from the markets to cover the whole fuel demand of the plant. The results indicate that the marked based method can be recommended as a “neutral” cost allocation method, because with that, the energy producer is not collecting extra margins from selling steam. This means that heat pricing is cost based. The results also indicate that depending on the emission factor and efficiency of alternative energy production form, the marked based method or the exergy method allocate the lowest CO2-emissions to heat. Therefore, the use of market based method for allocating costs and CO2 emissions can be recommended in order to use one single approach in both. [Copyright &y& Elsevier]

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. We demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times. • Implementation of a practical MPC for a heat pump-based dual fuel system in a small commercial building. • Experimental demonstration of a practical MPC with low-cost sensor retrofits for 2 winter months. • Achievement of 27% energy cost saving and 23% load shifting from occupied-peak time to non-occupied-non-peak time. • Elimination of natural gas usage with GHG emissions reduction of ∼ 52 kgCO2/month. [ABSTRACT FROM AUTHOR]

Substituting renewable energy for coal power under the carbon neutrality goal is an inevitable path for power system transformation, while the high share of renewable energy leads to a rapid rise in system flexibility demand. Currently, coal-fired power is still one of the most economical and reliable large-scale flexible resources in China. Therefore, the issue of how to mitigate the conflict between cleanliness and flexibility for coal-fired power is urgent to be solved. Accordingly, this paper established an optimization framework for the retirement and technology adoption of coal-fired power units with high spatial-temporal resolution, and the regional carbon emission budget is estimated from a top-down perspective. Secondly, a dynamic carbon quota allocation method considering technological innovation and adoption is proposed. The carbon trading cost of the units is evaluated from a bottom-up perspective, to realize the interaction between the obligatory policy constraints of the top-level target and the flexible incentives of the market mechanism. Finally, the empirical analysis was conducted in the Beijing-Tianjin-Hebei region of China. The optimal solution achieved by proposed method results in a substantial 27% reduction in total costs while keeping the increase in carbon emissions below 3%. By analyzing the dynamic evolution path of coal and the scale of diffusion of multi-type technologies, the differences in the roles coal power assuming at various stages of decarbonization are discussed. The robustness of the model and the validity of the proposed method were verified by comparing the dynamic/static carbon quota allocation. Overall, this study provides an effective optimization model for investigating the low-carbon technology adoption timing for coal power in Beijing-Tianjin-Hebei region, and offers valuable insights for other coal-dominated emerging economies seeking for power system transformation roadmap in the forthcoming net-zero carbon age. • A decision-making optimization model of CCPs low-carbon technology is proposed. • A dynamic CET system with upper-lower layer interaction is introduced. • The proposed dynamic CET system results in 27% reduction in total costs. • The high-resolution data of coal power in Beijing-Tianjin-Hebei region are used. • The strategy to solve the conflict between cleanliness and flexibility is given. [ABSTRACT FROM AUTHOR]

This study assesses alternative energy technologies (i.e., PV and battery systems, electric heat pumps, hybrid gas heating with solar thermal energy) in terms of profitability and CO 2 emissions, for the case of two simulated typical households living in detached houses in Germany. Under the status-quo regulatory framework, the energy transition in the heating sector is fostered through grants for replacing old heating systems, whereas PV generation is fostered by feed-in tariffs and indirect subsidies for self-consumption. This study considers an alternative regulatory scenario with a more market-oriented approach, finding that a CO 2 -oriented reform of energy surcharges and taxes, as well as a reform of network charges, can support a more cost-efficient energy transition in the residential sector. The paper concludes with a discussion of the consistency, cost efficiency and effectiveness of past and current policies underpinning the energy transition in the residential sector. • Assessment of home energy systems across 2 households and 2 regulatory scenarios. • Consideration of PV, batteries, heat pumps and hybrid gas-solar heating systems. • Comparison of subsidies and flat energy tariffs vs. cost-reflective, dynamic tariffs. • Market-oriented approach incentivizes far more cost-efficient CO 2 emission reduction. • The German residential energy sector needs a consistent regulatory framework. [ABSTRACT FROM AUTHOR]

This paper aims at evaluating the best allocation of potential biomethane generation for the decarbonization of the transport system, presenting a case study in Italy. The country has some peculiar features, such as several operating biogas plants, additional potential feedstock for biogas/biomethane generation, a well-developed natural gas network and established relevant natural gas uses in different final sectors, including transport. Based on current estimates for sustainable biomethane potential by 2030, ranging from 2.3 to 7.6 billion cubic meters depending on the scenario, the analysis compares technologies for the generation, distribution and final use of biomethane. The results of the analysis confirm the potential interesting contribution of biomethane in decarbonizing the Italian transport system: a billion cubic meters of biomethane can lead to 2.33–4.37 Mt CO 2 e savings, depending on the feedstock mix and the application. On a national basis, annual climate emission savings in 2030 range from 10.0 to 26.7 Mt CO 2 e , depending on the scenario. Additional 3.1–8.1 Mt CO 2 of emissions can be avoided if the CO 2 captured during the biomethane upgrading can be stored or reused. The proposed methodology could be used to extend the analysis to other countries, and to the European context. • We analyze the climate emissions of biomethane for different supply chains. • We evaluate the effects of feedstock, distribution strategy and electricity mix. • The results confirm the important role of biomethane for transport decarbonization. • We discuss the best allocation in transport segments based on emissions savings. • We compare alternative biomethane scenarios for Italy in 2030. [ABSTRACT FROM AUTHOR]

Carbon neutrality is one of the main goals in current power system planning and operation. Many different actions and solutions are presented and implemented so far, incorporating renewable energy sources at all levels of the system. With the raising prices of natural gas and its negative impact on the environment, particularly emphasised over the past two years, new technologies and energy vectors are emerging as potential for its replacement. High importance of the hydrogen energy vector, especially in the decarbonisation of the industry sector, is being put forward due to its advantages of zero greenhouse gas emissions, its capacity for storing energy and capability to balance the production of renewable energy sources. This paper brings a detailed mathematical model of a price driven, demand responsive, multi-energy industry facility, as a logic first implementer of hydrogen technologies due to its high and multi-energy consumption nature. The systematic analyses are conducted over a set of scenarios of local production, considering different hydrogen technologies as well as range of natural gas and electricity prices. The findings of the paper conclude that hydrogen technology implementation into a realistic industrial consumers processes results in zero local emissions production, high level of autonomy and resistance from the market disturbances. When compared with classic industrial layouts, the overall CO 2 footprint is reduced from around 30% to around 85%, depending on the scenario. The sensitivity analysis has proven that hydrogen layouts are comparable to natural gas layouts in terms of total costs, showing that hydrogen options result in lower cost in the range from 25% to 58%, depending on the observed scenario. • Integration of renewables and hydrogen technologies in industrial plant. • Price sensitivity analysis showcasing economic benefits of different hydrogen technologies. • Carbon footprint reduction up to 80% from the business-as-usual approach. • Complete reduction in local GHG emissions using hydrogen technologies. [ABSTRACT FROM AUTHOR]

Highlights • Linkage enables ETS sectors in EU and China to achieve 5% additional carbon reduction without increasing welfare losses. • Unlimited linking hinders the development of renewable energy in EU. • The international competitiveness of energy intensive sectors in China is adversely affected by linking. • Choosing the appropriate limit value a to restrict the tradable permits can reduce the negative impacts of linking. Abstract With the increasing popularity of emission trading system (ETS) worldwide and the necessity of international cooperation on climate change, the interest of linking various ETSs is growing. This paper adopts a multi-regional, general equilibrium model to simulate linkages between China's national ETS and the EU ETS and analyze the emissions, energy and economic impacts of such linkages. In order to study the role of linking in further increasing mitigation ambitions of China and the EU, and compare unlimited linkage with limited linkage, the paper further develops scenarios in which both China and the EU set higher ambition cap for their ETSs and unlimited or limited linkage is established between the two ETSs. The results indicate that unlimited linking can effectively promote the emission reduction ambitions of both China and the EU without inducing additional welfare losses to them. When both China and the EU set more intensified targets for ETS sectors and undertake additional 169 million tons carbon reductions, unlimited linking can make China's welfare remain basically unchanged and the EU's welfare increase by 0.29%, compared to implementing ETS independently under original reduction targets. However, unlimited linking has adverse effects on the competitiveness of China's energy intensive sectors and the development of EU's renewable energy. Compared to unlimited linking, limited linking effectively reduces these adverse effects. The paper concludes that China's national ETS and the EU ETS can establish a linkage to further increase their ambitions, while at the same time use import quotas to limit the permits that can be traded to reduce the negative impacts of linking on the two systems. [ABSTRACT FROM AUTHOR]

Highlights: • This paper analyses the factors affecting CO 2 emissions of OECD. • LMDI decomposition and decoupling analysis methods are combined. • We find that the impact of population distribution on CO 2 emissions is negligible. • Energy intensity and per capita GDP are the main impact factors of CO 2 emissions. • Technical factors have a greater impact on decoupling elasticity. Abstract Under the framework of the Kaya identity, this paper uses the Logarithmic Mean Divisia Index (LMDI 1 Abbreviation: LMDI, the Logarithmic Mean Divisia Index. 1) decomposition method to explore the impacts of CO 2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita Gross Domestic Product (GDP 2 Abbreviation: GDP, Gross Domestic Product. 2), population distribution, and population size on CO 2 emissions in the Organisation for Economic Co-operation and Development (OECD 3 Abbreviation: OECD, the Organisation for Economic Co-operation and Development. 3) from 2001 to 2015. Additionally, the Tapio decoupling analysis is used to explore the decoupling relationships between the above influencing factors and CO 2 emissions. Moreover, the LMDI decomposition formula is embedded into the decoupling analysis to analyze the influences of technical and non-technical factors on above decoupling elasticity. The results indicate that energy intensity and per capita GDP are the main factors affecting CO 2 emissions. The former is the main reason for the decrease in CO 2 emissions, and the latter is the main reason for the increase in CO 2 emissions. The impact of population distribution on CO 2 emissions is negligible. The decoupling states between the overall CO 2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita GDP, and population size and CO 2 emissions during 2001–2015 are recessive decoupling, recessive decoupling, weak negative decoupling, strong decoupling, and strong decoupling, respectively. Moreover, the influence of technical factors is greater than that of non-technical factors, and their influence directions are always opposite. In addition to our primary contributions, there are three marginal contributions in this paper. First, the population distribution is included in LMDI factorization. Second, LMDI decomposition is combined with Tapio decoupling analysis to explore the decoupling relationships between CO 2 emissions and the above factors. Finally, the findings related to the impacts of technical and non-technical factors are novel. [ABSTRACT FROM AUTHOR]

Highlights • Introduction of new proposed indicators and consolidation of available ones. • Proposition of adaptable indicators to various Renewable Energy System modes. • A "cradle-to-grave" study of an integrated photovoltaic and storage system. • Introduction of Stakeholders' needs as part of the proposed Life Cycle Analysis. Abstract During the last years a variety of numerical tools and algorithms have been developed aiming at quantifying and measuring the environmental impact of multiple types of energy systems, as those based on Renewable Energy Sources. Plenty of studies have proposed the use of a Life Cycle Assessment methodology, to determine the environmental impact of renewable installations when coupled with storage solutions, based on a pre-selected repository of Key Performance Indicators. The main scope of this paper is to propose a limited number of best fitting, and at the same time easily adaptable to various configurations, list of Key Performance Indicators for the case of renewable energy systems. This is done by capitalizing on the environmental and energy performance indicators tracked in the open literature (e.g. "Global Warming Potential", "Energy Payback Time", "Battery Total Degradation", "Energy Stored on Invested", "Cumulative Energy Demand") and/or other proposing new simple, scalable and adaptable ones, (e.g. "Embodied Energy for Infrastructure of Materials and for the building system", "Life Cycle CO 2 Emissions", "Reduction of the Direct CO 2 emissions", "Avoided CO 2 Emissions", "CO 2 equivalent Payback Time"). Moreover, the proposed indicators are distributed according to the individual phases of the entire life-cycle of a related component of a renewable energy system, each time the environmental impact refers to, i.e. manufacturing, operational and end-of-life. Apart from that, the current paper presents a necessary base grounded approach, which can be followed for a holistic approach in environmental point of view of renewable-based technologies, by addressing the potential competing interests of the relevant stakeholders (e.g. profit for the market operator in contrast to low-cost services for the consumer). All in all, the scalar quantification of the environmental impact of multiple energy systems, through a list of proposed assessment criteria, being evaluated in terms of the selected repository of indicators, enables the comparison on a fair basis of the available energy systems, irrespective if they are fossil-fuel or renewable based ones. As a typical example, a simple standard model of a photovoltaic integrated with an electric battery is selected, for which indicative indicators are provided. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The mitigation control of the load pulses is designed for SMES converter. • The Load-Following (LF) control applied to Fuel Cell allows reduced battery capacity. • LF control attenuates load dynamics and the variability of renewable energy. • The LF control loop is validated in different scenarios considered. Abstract In this paper it is analyzed the behavior of a battery/Superconducting Magnetic Energy Storage (SMES) hybrid Energy Storage Systems that can be used in a Fuel Cell/Renewable Energy Sources (RESs)/Hybrid Power System under an unknown load profile and variable RES power, which uses the Fuel Cell System as Auxiliary Energy Source. In general, the load demand profile includes large and sharp pulses, especially requested for space and military equipment, communication, and high-tech applications. The sizing and control of the battery/SMES Hybrid Power System under pulsed load are validated by simulations. The variability of the load demand and RES power is mitigated by using the Load-Following control for Auxiliary Energy Source of the RES Hybrid Power System. Thus, if the load power is higher than the RES power, then the battery will operate in charge-sustaining mode due to using the Load-Following control for Auxiliary Energy Source. Otherwise, the battery will operate in charge-increasing mode if the Hybrid Power System does not use an electrolyzer to be supplied with this excess of power. So, a reduced capacity is needed for battery operating in charge-sustaining mode due to use of the Load-Following control. However, the load pulses with large and sharp profile must be mitigated by the appropriate control of the SMES in order to protect the Fuel Cell system. So, the capacity of the SMES to generate (or to absorb) such pulses is analyzed in this paper. The simulation results illustrate the capacity of the SMES to generate different shapes of pulses. Thus, an effective mitigation of the load pulses is proposed here by controlling the SMES converter. Also, the design of the battery/SMES Hybrid Power System under dynamic load is presented. [ABSTRACT FROM AUTHOR]

This paper contributes to emerging local perspectives on energy justice. Examining the critical influence of intermediary organisations, we draw on the nascent concept of a ‘civic energy sector’ to frame ‘local’ engagement in low-carbon energy systems. Applying the three core tenets of energy justice - distributional, procedural and recognition justice - to organisations in the UK city of Bristol’s growing civic energy sector, we demonstrate the explanatory power and real-world applicability of energy justice at the local level. The paper draws on a set of rich qualitative data collected over 18 months during 2015–2017, using methods from the Participatory Action Research methodology. This includes both in-depth interviews (n = 12) and a focus group (n = 7) with key civic energy actors in Bristol, alongside embedded activist researcher approaches and document analysis of important outputs and publications from civic energy actors. Using the three tenets, the paper shows how intermediaries act as a critical bridge between local low-carbon energy initiatives and deprived communities; raise awareness of funding opportunities to otherwise excluded community groups, and, where possible, seek to localise the emerging economic benefits of low-carbon transitions. The paper finishes with a call for energy justice researchers to collaborate more closely with organisations facilitating local low-carbon transitions, alongside suggesting efforts are needed to push for a commonly understood framework of energy justice within civic energy networks. It also offers critical reflections on the dominant theoretical framing of energy justice and the limitations of intermediaries under austerity, while providing policy-relevant recommendations to facilitate energy justice. [ABSTRACT FROM AUTHOR]

The transition to a deeply decarbonized energy system requires coordinated planning of infrastructure investments and operations serving multiple end-uses while considering technology and policy-enabled interactions across sectors. Electricity and natural gas (NG), which are vital vectors of today's energy system, are likely to be coupled in different ways in the future, resulting from increasing electrification, adoption of variable renewable energy (VRE) generation in the power sector and policy factors such as cross-sectoral emissions trading. This paper develops a least-cost investment and operations model for joint planning of electricity and NG infrastructures that considers a wide range of available and emerging technology options across the two vectors, including carbon capture and storage (CCS) equipped power generation, low-carbon drop-in fuels (LCDF) as well as long-duration energy storage (LDES). The model incorporates the main operational constraints of both systems and allows each system to operate under different temporal resolutions consistent with their typical scheduling timescales. We apply our modeling framework to evaluate power-NG system outcomes for the U.S. New England region under different technology, decarbonization goals, and demand scenarios. Under a global emissions constraint, ranging between 80%–95% emissions reduction compared to 1990 levels, the least-cost solution relies significantly on using the available emissions budget to serve non-power NG demand, with power sector using only 14%–23% of the emissions budget. Increasing electrification of heating in the buildings sector results in greater reliance on wind and NG-fired plants with CCS and results in similar or slightly lower total system costs as compared to the business-as-usual demand scenario with lower electrification of end-uses. Interestingly, although electrification reduces non-power NG demand, it leads to up to 24% increase in overall NG consumption (both power and non-power) compared to the business-as-usual scenarios, resulting from the increased role for CCS in the power sector. The availability of low-cost LDES systems reduces the extent of coupling of electricity and NG systems by significantly reducing fuel (both NG and LCDF) consumption in the power system compared to scenarios without LDES, while also reducing total systems costs by up to 4.6% for the evaluated set of scenarios. • A decarbonized joint electric power and natural gas model is developed. • Impact of electrification, coupling constraints, and new technologies are analyzed. • Joint planning with cross-sectoral emission limit is the most cost-effective pathway. • Increased use of carbon capture technologies can increase overall NG consumption. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to modeling the gradual reduction in heat demand and the evolving expansion of district heating (DH) grids for assessing the DH potential in EU member states (MS). It introduces new methodological elements for modeling the impact of connection rates below 100% on heat distribution costs in both dense and sparse areas. The projected heat demand in 2050 is derived from a decarbonization scenario published by the EU, which would lead to a reduction in demand from 3128 TWh in 2020 to 1709 TWh by 2050. The proposed approach yields information on economic DH areas, DH potential, and average heat distribution costs. The results confirm the need to expand DH grids to maintain supply levels in view of decreasing heat demand. The proportion of DH potential from the total demand in the EU-27 rises from 15% in 2020 to 31% in 2050. The analysis of DH areas shows that 39% of the DH potential is in areas with heat distribution costs above 35 EUR/MWh, but most MS have average heat distribution costs between 28 and 32 EUR/MWh. The study reveals that over 40% of the EU's heat demand is in regions with high potential for implementing DH. • A novel method for analyzing district heating potential in the EU-27 is presented. • District heating can cover 31% of heat demand (non-industry) in EU-27 up to 2050. • Grid expansion is needed in economically favorable areas to reduce specific costs. • A yearly investment of €11.7B at the EU level is required for the grid expansion. [ABSTRACT FROM AUTHOR]

In light of the global energy and climate crises, integration of low-carbon technologies into energy systems is being considered to mitigate the high energy costs and carbon footprint. The wide range of available capacities, efficiencies, and investment costs of these technologies and their different possible operating schedules can unlock several pathways towards decarbonisation. This paper presents an optimisation framework for a public healthcare facility to determine the optimal operation schedule of the site's energy system. A detailed techno-economic analysis of low-carbon power generation, conversion, and energy storage technologies that can be incorporated into the system based on real historical data was carried out for different scenarios. The results reveal that a heat pump with a capacity of 1800 kW can replace gas boilers on-site to meet the heat demand while recovering the investment in 5 years and providing an operating and carbon cost saving of 22.47% compared to the base case. The analysis shows that a more electrified mode of operation is favoured during high gas prices, thus making electrical energy storage more attractive than thermal energy storage. While handling real data, the optimisation algorithm was sensitised to discriminate conventional energy supplies from clean energy sources by considering their carbon impact so that it minimises energy bills in a smart and eco-friendly way. The optimisation algorithm and the subsequent techno-economic analysis provide a comprehensive framework to decision-makers for facilitating energy investment decisions. The framework can be used based on the short and long term goals of the energy system, visualising the evolution of financial benefits over equipment lifetime, and understanding the environmental impacts of integrating renewable energy. • Heat pumps are the most favourable decarbonisation technology for the hospital. • The moderate variations in energy demand limit the scope of energy storage. • Fuel price surcharge favours EES over TES and reduces payback period of retrofits. • PVT's savings scale linearly with roof space until 3 times the available capacity. • Monetising the carbon footprint shortens the DPP of clean retrofit technologies. [ABSTRACT FROM AUTHOR]

The growing penetration of 5G base stations (5G BSs) is posing a severe challenge to efficient and sustainable operation of power distribution systems (PDS) due to their huge energy demand and massive quantity. To tackle this issue, this paper proposes a synergetic planning framework for renewable energy generation (REG) and 5G BS allocation to support decarbonizing development of future PDS. The problem is formulated as a multi-objective interval optimization (MOIO) model, wherein the 5G BS siting and sizing are co-optimized with the REG capacity allocation and their operating strategies to minimize the total economic cost and carbon emissions of the PDS. The potential flexibility benefits achievable from 5G BS operation (as responsive load demands to PDS) are explicitly considered in the proposed planning formulation by accounting for the effects of both transmit power control and on-site energy storage battery dispatch. Moreover, we adopt an interval approach to capture the uncertainties involved in the system (including REG output, market prices, carbon emissions factor, and power/communication load demands). In order to solve the proposed MOIO problem efficiently, a constrained interval multi-objective optimization evolutionary algorithm based on decomposition (CIMOEA/D) is developed by combining constraint handling, interval-based Tchebycheff aggregation function and interval ensemble comparison, which could achieve Pareto optimal solutions and an interval-formed Pareto front to the problem with all the uncertain information fully preserved in the decision-making process. The proposed model is demonstrated on a modified IEEE 33-bus test case, and the simulation results verified the effectiveness of the suggested approach. • Modeling of 5G BS operational flexibility considering both energy and communication characteristics. • Proposing a MOIO formulation to allow synergetic renewable and 5G BS integration. • Uncertainties are considered via the interval optimization approach. • A constrained interval multi-objective optimization evolutionary algorithm based on decomposition is developed. • Effectiveness of the proposed approach is verified via comparative analysis. [ABSTRACT FROM AUTHOR]

Negative emissions systems differ from net-zero systems by deploying significantly more negative emission technologies. The emerging literature on negative emission power systems assumes straight transition pathways from the present systems to final negative emissions systems. Such straight transition paths are unlikely, as deployment of negative emission technologies such as direct air capture might occur via crash course to respond to climate crises and utilities are investing towards net-zero systems instead of negative emissions systems. In this paper, to inform policymakers of the different outcomes of planning for negative emissions systems at different timelines, we quantify the value of planning for a negative emissions power system beginning now versus after achieving a net-zero emissions system in 2050. We apply a macro-scale capacity expansion planning model to the Eastern Interconnection power system to quantify the technological deployments and cost consequences of these two decarbonization pathways to reach a negative emission power system. We find advanced planning for a negative emissions system favors more deployment of storage technologies, which increases system flexibility and allows for better utilization of renewable generation to reduce investments in other technologies, including transmission lines. This change in distribution of investments across technologies leads to small annual cost saving of $6 billion, or 1%. We also find that further delay in planning for a negative emission system after reaching net-zero by 5, 10, and 15 years could significantly increase total system cost by 29%, 35%, and 41% respectively due to higher deployment of negative emission technologies. Our results indicate that, given small annual cost saving from advanced planning for a negative emission power system, economically utilities are on the right path in planning for a net-zero power system by 2050. However, planning should not be delayed further after reaching net-zero to avoid missing cumulative emission targets or significant cost consequences. • We compare negative emissions Eastern power system planned now versus after net-zero. • Advanced planning increases system flexibility by increasing storage deployments. • Advanced planning reduces investments in non-storage technologies. • Advanced planning reduces total annual system cost by $6 billion (1%) across scenarios. • Delayed planning for a negative emission system after net-zero incurs significant costs. [ABSTRACT FROM AUTHOR]

This paper assesses the separation of CO 2 from ambient air from a technical and economic standpoint. Reducing CO 2 emissions and their sequestration from the atmosphere is vital to counteract ongoing climate change. The most promising technological options for CO 2 separation are first identified by reviewing the literature and comparing the most important technical and economic parameters. The results point to amines/imines as adsorbing agents to separate CO 2 from ambient air. A system layout is then designed and a technical analysis conducted by solving mass and energy balances for each component. An economic analysis is then performed by applying a specifically-developed model. The total energy demand of the system discussed here is calculated as 3.65 GJ/t CO2 . This high energy demand mainly derives from the system-specific implementation of two compressors that compress air/CO 2 and overcome the pressure losses. The second-law efficiency calculated ranges of 7.52–11.83 %, depending on the option of heat integration. The costs of avoiding CO 2 emissions vary between $ 824 and 1333/t CO2 , depending on the energy source applied. The results of this work present higher values for energy demand and costs compared to other values stated in literature. The reasons for this deviation are often insufficient and overoptimistic assumptions in other literature on the one hand, but also relate to the specific system design investigated in this paper on the other. Further case studies reveal that enormous land requirements and investments would be needed to reduce potential CO 2 quantities in the atmosphere to contemporary levels. A comparison between CO 2 removal from the atmosphere and carbon capture and storage technology for coal power plants shows that this technology is not yet able to economically compete with carbon capture and storage. Furthermore, the impact of CO 2 separation on the production costs of industrial commodities like cement and steel demonstrates that CO 2 removal from the atmosphere is not yet a viable alternative to solving the climate change problem. In the long-term, CO 2 separation from ambient air may still play an important role in the sequestration of CO 2 from diluted and dispersed sources, as the technology has the potential for significant further development and optimization. [ABSTRACT FROM AUTHOR]

Traditional energy planning methods are mostly related to newly-built area. However, in most already-built regions, the existing district energy systems (DESs) need to be ameliorated due to insufficient capacity and low efficiency. This paper investigates the methodology of expansion planning, which can offer planners a viable way to expand existing DESs. The term “expansion” aims to increase the supply capacity of the energy forms, e.g., steam, hot water and electricity, which cannot be accessed from national or urban energy supply network, and meanwhile increase energy utilization efficiency and cut CO 2 emission. Three parts of the methodology, including problem analysis in current DESs, demand side analysis and the existing DES expansion, are introduced in this paper. New concepts of load structure and evaluation system of the whole district are proposed in this methodology. A case analysis of Ningbo Hi-Tech District, China is conducted to shed light on the application of this method. [ABSTRACT FROM AUTHOR]

The benefits of decentralised energy systems can be realised through the optimal siting of distributed energy systems and the design of highly interlinked district heating networks within existing electrical and gas networks. The problem is often formulated as a Mixed Integer Linear Programming (MILP) problem. MILP formulations are efficient and reliable, however the computational burden increases drastically with the number of integer variables, making detailed optimisation infeasible at large urban scales. To tackle complex problems at large scale the development of an efficient and robust simplification method is required. This paper presents an aggregation schema to facilitate the optimisation of urban energy systems at city scale. Currently, spatial and/or temporal aggregation are commonly employed when modelling energy systems at spatio-temporal resolutions from plant scheduling up to national scenarios. This paper argues for solving different scales separately using a bottom-up approach, while keeping track of the error made by reducing the resolution when moving from building to urban scale. Novel modelling formulations and optimisation techniques are presented. They enable drastic reduction of the computational time (by up to a factor of 100) required to find an optimal solution in reasonable time without sacrificing the quality of the results (no more than 1% loss in accuracy). A density-based clustering algorithm enables intelligent division of a large city-scale problem into sub-optimisation problems by creating clusters of different density. In each cluster, the trade-off between centralised and decentralised energy systems and the associated district heating network design is evaluated. A solution is selected based on a local optimisation of the network costs. Demand profiles of each building are assigned appropriately, then at an upper level the energy optimisation problem is solved considering the network losses at lower levels. This method enables large-scale modelling of urban energy systems while taking into account building-scale levels of detail. The clustering method enables assessment of the potential of district heating networks on city scale based on building characteristics and available urban energy systems. [ABSTRACT FROM AUTHOR]

Environmental issues and the prospect of an energy crisis inspire humans to exploit wind power. However, with the increase of wind power penetration level, operating power systems securely and reliably is a serious challenge due to the inherent nature of wind power intermittency. Wind power intermittency has been the major barrier for large scale wind power integration. This paper reviews past research on wind power intermittency, including its impacts on power system, how it is measured, and mitigation solutions. It has been found that as wind power integration increase, the system reverses and costs consequently increase, while the system reliability and CO 2 reductions decrease. In order to mitigate wind power intermittency, studies on intermittency measurements and mitigation solutions are necessary. Existing measurements of wind power intermittency are summarized firstly. Considering the limitations of existing methods, new definitions and metrics are proposed based on our study. Then, various wind power intermittency mitigation solutions are comprehensively reviewed, including wind farms, generation-side, demand-side and energy storage. In the final part of this paper, the further work on wind power intermittency is discussed in detail. In summary, wind power intermittency can be effectively mitigated using various technological and managerial approaches based on an in-depth understanding of intermittency. [ABSTRACT FROM AUTHOR]

Demand-side management (DSM) has the potential to reduce electricity costs and the carbon emissions associated with electricity use for industrial consumers. It also has an important role to play in integrating variable forms of generation, such as wind and solar, into the grid. This will be a key part of any grid decarbonisation strategy. This paper describes a method that can be used to develop a new production schedule for a wide range of manufacturing facilities. The new schedule minimises either electricity costs or electricity-derived CO 2 emissions. It does so by rescheduling production to low cost or low carbon periods, without loss of overall production, within the constraints of available inventory storage. A case study of a single cement plant in the UK was performed in order to determine the potential benefits of increased load-shifting DSM using this method. The alternative production scheduled showed the potential to decrease electricity costs by 4.2%. Scaled to values from a typical plant this would lead to a cost saving of £350,000, a substantial saving. A schedule optimised to minimise carbon emissions would save an estimated 2000 tonnes per year of CO 2 , a 4% decrease in electricity-derived emissions. It was also observed that the actual electricity consumption of the plant was considerably higher than the minimum consumption predicted by the model. This could indicate potential for significant savings in both cost and CO 2 due to improvements in energy efficiency. The potential savings from DSM doubled when the prices passed to the plant were replaced with a price that varied in proportion to the wholesale cost of electricity. This indicates that a potential mutual benefit exists for both industrial consumers and electricity generators by passing on more of the variation in price. A larger share of generation from wind and solar will also lead to increased variation in prices and grid carbon intensity in future. The value of applying the method described in this paper is therefore likely to increase further in future. [ABSTRACT FROM AUTHOR]

System inertia reduction, driven by the integration of renewables, imposes significant challenges on the primary frequency control. Electrification of road transport not only reduces carbon emission by shifting from fossil fuel consumption to cleaner electricity consumption, but also potentially provide flexibility to facilitate the integration of renewables, such as supporting primary frequency control. In this context, this paper develops a techno-economic evaluation framework to quantify the challenges on primary frequency control and assess the benefits of EVs in providing primary frequency response. A simplified GB power system dynamic model is used to analyze the impact of declining system inertia on the primary frequency control and the technical potential of primary frequency response provision from EVs. Furthermore, an advanced stochastic system scheduling tool with explicitly modeling of inertia reduction effect is applied to assess the cost and emission driven by primary frequency control as well as the benefits of EVs in providing primary frequency response under two representative GB 2030 system scenarios. This paper also identifies the synergy between PFR provision from EVs and “smart charging” strategy as well as the impact of synthetic inertia from wind turbines. [ABSTRACT FROM AUTHOR]

This paper forms a Virtual Energy Storage System (VESS) and validates that VESS is an innovative and cost-effective way to provide the function of conventional Energy Storage Systems (ESSs) through the utilization of the present network assets represented by the flexible demand. The VESS is a solution to convert to a low carbon power system and in this paper, is modelled to store and release energy in response to regulation signals by coordinating the Demand Response (DR) from domestic refrigerators in a city and the response from conventional Flywheel Energy Storage Systems (FESSs). The coordination aims to mitigate the impact of uncertainties of DR and to reduce the capacity of the costly FESS. The VESS is integrated with the power system to provide the frequency response service, which contributes to the reduction of carbon emissions through the replacement of spinning reserve capacity of fossil-fuel generators. Case studies were carried out to validate and quantify the capability of VESS to vary the stored energy in response to grid frequency. Economic benefits of using VESS for frequency response services were estimated. [ABSTRACT FROM AUTHOR]

The interest in bio-CCS technologies is growing due to their potential to reduce CO 2 emission in power generation. Oxy-co-firing in fluidized-bed units is one of the available techniques to develop bio-CCS, offering wide fuel flexibility and low SO 2 and NO x emissions. This paper discusses the results of an experimental campaign carried out in a lab-scale fluidized bed reactor. The work focuses on the influence of limestone when oxy-firing blends of lignite and corn stover. Two different types of limestone with two Ca:S molar ratios were tested, and operational conditions were selected to compare the mechanisms governing desulphurization. Emissions of SO 2 , NO and HCl, together with deposition rates and ash mineralogy are studied in the paper. SO 2 capture increases with the Ca:S ratio and bed temperature, but to a different extent depending on the limestone fragmentation. The amount of NO emitted rises with the Ca:S ratio and the presence of calcined limestone (indirect desulphurization). The HCl concentration in the gas phase is dominated by alkali sulfation. Finally, the conditions for the highest desulphurization efficiency diminished the deposition rates, but increased the risk for chlorine-induced corrosion. [ABSTRACT FROM AUTHOR]

Calculating carbon dioxide ( CO 2 ) emissions associated with electricity is a key component in the field of Life Cycle Assessment (LCA), but is often cited as challenging due to the complex nature of electricity systems despite its importance to the outcome. While calculating the operational CO 2 emissions associated with electricity generation is an active research field, the embodied CO 2 emissions, typically referred to as embodied carbon, of network assets has far less representation in the literature. This paper focuses on the CO 2 emissions aspect of LCA to calculate the embodied CO 2 of network assets in relation to the operational grid CO 2 over time. Several functional units are defined: CO 2 per operational year, CO 2 per asset cost, CO 2 per functional unit of electricity (kW h) and the relationship between embodied emissions and operational emissions in an electricity system over time. Hybrid functional units are then applied in order to better attribute the embodied carbon to the network functions. The hybrid functional units involve network asset lifetime and the issue of temporal horizons. Several suitable horizons are suggested and the comparison of results highlight the importance of the timeframe on results. The relationship between temporal horizons and environmental discounting is discussed and recommendations are made on the appropriate level of discounting depending on the temporal horizon and the purpose of the LCA. The paper uses data from the Great Britain electricity system where planned investment in network assets is £12bn at distribution level (Dx) and £16.4bn at transmission level (Tx) over the next eight years. By using GB network data for embodied carbon, demand and asset data, as well as data from the decarbonisation of electricity generation, indicative results are provided into the way in which embodied carbon impacts could change over time, showing that by 2035, the embodied carbon of the transmission network could contribute almost 25% of total emissions associated with electricity. On a regional basis, DNO level network assets could reach anywhere between 40% and 130%. This network data is also used to show that new network investment could account for up to 6.5% of DNO level network embodied carbon when front loaded during the RIIO-ED1 period. [ABSTRACT FROM AUTHOR]

Climate change mitigation is a key issue in formulating global environmental policies. Energy production and consumption are the main sources of greenhouse gas (GHG) emissions in Europe. Energy consumption and energy-related GHG emissions from agriculture are an important concern for policymakers, as the agricultural activities should meet food security goals along with proper economic, environmental, and social impacts. Carbon dioxide (CO 2 ) emission is the most significant among energy-related GHG emissions. This paper analyses the main drivers behind energy-related CO 2 emission across agricultural sectors of European countries. The analysis is based on aggregate data from the World Input-Output Database. The research explores two main directions. Firstly, Index Decomposition Analysis (IDA), facilitated by the Shapley index, is used to identify the main drivers of CO 2 emission. Secondly, the Slack-based Model (SBM) is applied to gauge the environmental efficiency of European agricultural sectors. By applying frontier techniques, we also derive the measures of environmental efficiency and shadow prices, thereby contributing to a discussion on CO 2 emission mitigation in agriculture. Therefore, the paper devises an integrated approach towards analysis of CO 2 emission based upon advanced decomposition and efficiency analysis models. The research covers eighteen European countries and the applied methodology decomposes contributions to CO 2 emission across of regions and factors. Results of IDA suggest that decreasing energy intensity is the main factor behind declines in CO 2 emission. According to the SBM, the lowest carbon shadow prices are observed in France, Finland, Sweden, Denmark, the Netherlands, Poland, and Belgium. These countries thus have the highest potential for reduction in CO 2 emission. The results imply that measures to increase energy efficiency are a more effective means to reduce CO 2 emissions than are changes in the fuel-mix. [ABSTRACT FROM AUTHOR]

The production of precipitated calcium carbonate (PCC) from steel slag has been proposed as a potential method of simultaneously reducing the CO 2 emissions from the steelmaking process and turning its waste stream into a valuable product. On average the production of one ton of steel results in two tons of CO 2 emissions and 600 kg of slag. Globally, more than 400 Mt of steel slag are produced annually. If all the slag were used for the production of PCC, 64 Mt CO 2 could be utilized and 145 Mt of calcium carbonate would be produced. In 2014 the research group Energy Engineering and Environmental Protection at Aalto University in Finland has designed, constructed and tested the world’s first mineral carbonation pilot plant test facility that converts steel slag and CO 2 into PCC. In batch mode the pilot plant can handle up to 20 kg of solid steel slag and 190 L of liquid solvent, and it can produce about 10 kg of calcium carbonate. The solvent can be regenerated and reused in the calcium extraction stage, which makes the process economically more feasible. Almost 80% of the calcium in the slag was extracted, while more than 70% of the CO 2 was utilized and converted into PCC. In high temperature carbonation tests, ammonia gas was detected from the flue gases. At 60 °C more than 2 vol.% of NH 3 was detected in the flue gas, and at 50 °C it was 0.65 vol.%, while at 45 °C the NH 3 concentration in the flue gas was only 0.11 vol.%. To avoid ammonia evaporation, aragonite PCC can be produced at 45 °C by optimizing the CO 2 flow rate. The paper presents the process design as well as the early results achieved from the pilot plant. The paper also presents technical challenges that occurred during the scale-up work and experiments. [ABSTRACT FROM AUTHOR]

[Display omitted] • A multi-energy operation simulation model with biomass energy flow balance is established. • An optimal planning strategy is developed to determine the portfolio of solar, biomass, etc. • A thermodynamics-based model is formulated to characterize the heat transfer in biogas production. • An ordinary least squares approach is applied to linearize the biogas production model. Recent years have witnessed an increasing proliferation of biomass technologies since biomass is recognized as a natural carbon-neutral fuel. Existing studies have paid extensive attention to the concept and modeling of zero-carbon energy systems or buildings. However, few studies have explored the multi-energy coupling method and techno-economic evaluation of biomass to achieve near-zero carbon systems. Therefore, we propose an optimal sizing framework for integrating waste-to-biogas in regional energy systems to achieve near-zero carbon emissions. To establish energy balance between supply and demand and regional self-sufficiency, biomass is added to the existing natural gas energy framework. Biomass produces biogas through anaerobic digestion reactions, and the biogas output can be constructed as an analytical function related to the anaerobic reaction environment temperature and reactant volume. Furthermore, this paper constructs a planning model with the goal of minimizing the investment and operating costs of biomass, solar and storage, respecting carbon emission constraints induced by local electricity and gas energy flows. The impact of carbon emission regulations on the investment of each component of the energy system is determined using a sensitivity analysis of carbon emissions. To solve the nonlinearity issues of the biogas production function, we propose a convexification method based on least squares fitting. Case studies based on realistic datasets demonstrate that, under the constraints of carbon emissions, the integration of biogas can significantly improve the supply adequacy of the energy system, reduce investment costs by up to 77.07%, and carbon emission reduction intensity is 5.11 kg CO 2 kg-1 Biogas, all while lowering the Levelized Cost of Energy (LCOE). In comparison to prior research, the model provided in this paper more accurately portrays the biogas production process, lowers the system investment cost and LCOE, and emphasizes the benefits of biomass. [ABSTRACT FROM AUTHOR]

Highlights • A new approach for the calculation of quarter-hourly CO 2eq intensity is presented. • Effects of charging strategies on the environmental impact of BEVs are derived. • Large amounts of CO 2eq emissions are saved by optimizing the charging time. • The temporal variation of CO 2eq intensity in winter is small compared to summer. • The CO 2eq savings potential is significantly greater during the day than at night. Abstract In many countries, the replacement of internal combustion engine vehicles (ICEVs) with battery electric vehicles (BEVs) offers an opportunity to reduce CO 2 equivalent (CO 2eq) emissions in traffic. BEVs have significantly greater energy conversion efficiency from energy storage to wheel (tank-to-wheel [TTW]) and zero tailpipe emissions; these features are in stark contrast to the environmental burdens posed by vehicle production and electricity generation (well-to-tank [WTT]). Since CO 2eq emissions from vehicle use of BEVs account for the majority of the entire life cycle emissions, it is important to closely examine the CO 2eq intensity of electricity generation, which varies based on the sources of energy in the electricity mix of each country and time of day. This paper compares the environmental impact of diesel and electric buses in the city of Aachen throughout their life cycles and analyzes the effects of electricity generation with reference to variation in charging time. Based on recorded driving profiles, the vehicle dynamics of the longitudinal motion are simulated, and the energy demand as a function of the altitude profile and ambient temperature is calculated. The calculation of the quarter-hourly CO 2eq intensity is combined with the vehicle life cycle model in order to examine the effects of electricity generation on BEV life cycle emissions. To analyze the correlation between charging time and BEV environmental impact, different charging scenarios are defined, and CO 2eq savings from replacing ICEVs with BEVs are estimated. Scenario analyses are conducted over both short- and long-term time scales to predict the future environmental and economic benefits and costs of BEVs compared to ICEVs. The results demonstrate a significant dependency of BEV environmental impact on charging time, which varies by time of day and season. At night, the contribution of renewable energies to the electricity mix is low, and the variation in CO 2eq intensity is limited; therefore, the environmental impact of charging time is lower compared to charging at noon. The larger CO 2eq emissions of BEV production are compensated for all scenarios within the first year of operation. However, if BEVs are charged with electricity generated exclusively by lignite-fired power plants, more CO 2eq emissions are released over their lifetimes compared to ICEVs; this scenario also holds when ICEVs are fueled with biodiesel. Overall, the positive environmental balance of BEVs is not based on a low CO 2eq intensity, but on the greater energy conversion efficiency and the possibility of recuperating braking energy. These properties are particularly advantageous in urban traffic. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A new evaluation model of Nearly Zero Energy Cities (nZEC-EATEP) was presented. • nZEC-EATEP model contributes in the study of the energy self-sufficiency of cities. • nZEC-EATEP model extends the Zero Energy concept from buildings to cities. • The evaluation of a Nearly Zero Energy model for Barcelona city was presented. • PV self-consumption of Prosumers help to reduce energy consumption of cities. Abstract As a contribution to the study of the urban energy transition, this paper proposes a novel model of energy-economic evaluation of the cities self-sufficiency and presents its application in the form of a case study. The objective of this study was to analyse the scope of the investment in the photovoltaic self-consumption of buildings in order to promote the creation of Prosumers communities within the cities. The operation of this model is based on the scalability of the Nearly Zero Energy concept from buildings to cities and seeks to evaluate Nearly Zero Energy Cities (nZEC): cities made up of Nearly Zero Energy Buildings (nZEB) and other installations of distributed generation to cover their energy demand by use of local renewable resources to the detriment of external resources. By using public data, we apply this model with the aim of economically evaluating the investment of six packages of energy rehabilitation and photovoltaic self-consumption in 17% of the residential buildings (37,800) in the city of Barcelona. To do this, we simulated 37 years of electricity distribution among Consumers, Producers and a hypothetical peer-to-peer community of Prosumers during the period 2014–2050 in hourly time intervals. The results indicated that the photovoltaic self-consumption and the local markets of Prosumers help to reduce primary energy consumption, the energy costs, and the CO 2 emissions. [ABSTRACT FROM AUTHOR]

Highlights • Local CO 2 emission factors of China's coal chemical products are published. • The total CO 2 emission from China's coal chemical industry was 607 Mt in 2015. • The spatial disparity of CO 2 emission from China's coal chemical industry is great. • CO 2 emission from modern coal chemical industry is predicted to be 417 Mt in 2020. • Carbon capture, utilization, and storage has great potential to reduce its emission. Abstract As the largest producer of coal chemical products in the world, China faces tremendous pressure to reduce its carbon emission. An accurate quantification of the carbon dioxide (CO 2) emission of coal chemical industry in China is therefore necessary. However, due to the variety of coal chemical products and limitations of CO 2 emission factors, the total CO 2 emission of coal chemical industry has yet to be determined. In this study, local CO 2 emission factors of coal chemical products in China are published based on first hand data from twenty-three coal chemical enterprises and the total CO 2 emission of China's coal chemical industry is extrapolated. The provincial-level spatial distribution of the CO 2 emission of coal chemical industry is presented to assist the government in identifying key emission reduction areas. Additionally, scenario analysis of CO 2 emission for China's modern coal chemical industry in 2020 is conducted to determine whether the development of the modern coal chemical industry will have a significant impact on future CO 2 emission, as well as the effect of carbon capture, utilization and storage technologies on the reduction in carbon emission. The estimate shows that the total CO 2 emission of the coal chemical industry in 2015 was 607 million tonnes (Mt), accounting for approximately 5.71% of China's total CO 2 emission. The figure is higher than the total annual CO 2 emission of a country such as Canada (555 Mt) or Brazil (486 Mt). Quantifying the emission of the coal chemical industry is therefore critical to understand the global carbon budget. The spatial distribution shows that Shandong, Inner Mongolia and Shanxi release one-third of the coal chemical industry's total CO 2 emission. Considering the development of the modern coal chemical industry, its CO 2 emission is predicted to be as high as 416.52 million tonnes in 2020. However, the CO 2 emission could be reduced by 317.98 million tonnes when carbon capture, utilization and storage are applied to process and energy systems simultaneously. This paper quantifies the CO 2 emission of the coal chemical industry in China for the first time, identifies key chemical products and the provinces in which they are produced, explores the carbon reduction potential by scenario analysis, and provides specific data to support the assessment of effective CO 2 reduction policy. [ABSTRACT FROM AUTHOR]

Highlights • A calcium looping process with energy storage for peak shaving in a coal-fired power plant was proposed and assessed. • The boiler always operates at MCR to ensure the highest boiler efficiency is achieved. • The proposed system can reduce the net efficiency penalty from 6.96% LHV to 5.98% LHV. • The proposed system with cryogenic O 2 storage has a wide peaking capability. Abstract CO 2 capture and peak shaving are two of the main challenges for coal-fired power plants in China. This paper proposed a calcium looping (CaL) combustion system with cryogenic O 2 storage for simultaneous flue gas decarbonization and peak shaving for a 1000 MW e coal-fired power plant. The philosophy of this concept is that: (1) the boiler always operates at maximum continuous rating (MCR) to ensure the highest boiler efficiency; (2) during off-peak times, the excess energy output from coal combustion is used to provide heat for the calciner and produce pure oxygen for energy storage; (3) at peak times, the O 2 produced is used to capture CO 2 in the flue gas via the CaL process and reduce the CO 2 abatement penalty; and (4) any excess O 2 is treated as a by-product for commercial utilization. The whole system was simulated in Aspen Plus® which shows that the net electric efficiency of the proposed system without cryogenic O 2 storage system is 35.52% LHV (LHV, low heating value), while that of the conventional CaL system is 34.54% LHV. The proposed system can reduce the methane consumption rate by 38.5 t/h when methane is used as fuel in the calciner. Including the cryogenic O 2 storage system, the peaking capability of the proposed system can range from 534.6 MW e to 1041 MW e. Correspondingly, the net electric efficiency is improved from 18.98% LHV to 36.97% LHV. Increasing the rate of oxygen production can reduce the minimum net power output to lower than 534.6 MW e. The peaking capability can be regulated by the rate of oxygen production where excess oxygen serves as a byproduct. [ABSTRACT FROM AUTHOR]

Highlights • Hourly-resolved model to investigate highly-renewable electricity generation in Spain. • Correlation analysis of time series to create 900 combinations used in simulations. • Transition paths evaluated based on security of supply, CO 2 emissions, and renewable share. • Short-term phase-out of nuclear and coal power plants proven to be feasible. Abstract Two alternative paths to achieve highly-renewable electricity generation in peninsular Spain are investigated in this paper. Every transition path comprises a description of the installed and decommissioned generation and storage capacities, from 2017 to 2030, as well as a hypothesis on the evolution of the electricity demand. The electricity mix for every hour within the transition path is determined through a dispatch algorithm that prioritizes electricity from renewable energy sources. The simulation is run for 900 different combinations of time series representing the hourly capacity factors of different technologies, as well as the electricity demand. This robust approach allows the evaluation of the transition paths based on the statistical distribution of several defined assessment criteria, such as security of supply, CO 2 emissions or renewable share in electricity generation. The feasibility of a Spanish power system with high renewable penetration is investigated not only in a future reference year but throughout the transition path. In particular, a progressive and simultaneous phase-out of nuclear and coal power plants in the short-term is proven to be feasible. Furthermore, the results sensitivity is analyzed including scenarios with a delayed nuclear phase-out, lower hydroelectricity generation due to more frequent and severe droughts caused by climate change and higher annual increment for the electricity demand. [ABSTRACT FROM AUTHOR]

Highlights • Carbon abatement cost is considered to measure carbon abatement task allocation. • Carbon abatement cost is estimated based on the shadow price of carbon emission. • A data envelopment analysis considering regional collaboration is proposed. • The approach is applied to measure industrial carbon allocation in China. • Conflicts among regional collaboration targets are discovered in empirical study. Abstract China's commitment to significantly reducing carbon emissions faces the twin challenges of focusing costly reduction efforts, whilst preserving the rapid growth that has defined the country's recent past. However, little work has been able to meaningfully reflect the collaborative way in which provinces are assigned targets on a sub-national regional basis. Suggesting a modified data envelopment analysis (DEA) approach which recognises the two objectives of income maximization and pollution abatement cost minimisation, this paper introduces the potential collaboration between industrial units to the modelling framework. Our theoretical work exposits the roles collectives of industrial decision making units may play in optimising against multiple target functions. Considering the period 2012–2014, we illustrate clearly how China's three regional collaborations interact with the stated aims of national policy. Developed eastern China may take on greater abatement tasks in the short-term, thus freeing central and western China to pursue the economic growth which will then support later abatement. Policy-makers are thus given a tool through which an extra layer of implementation can be evaluated between the national allocation and setting targets for regional individual decision making units. China's case perfectly exemplifies the conflicts which must be accounted for if the most economical and efficient outcomes are to be achieved. [ABSTRACT FROM AUTHOR]

Highlights • Energy consumption in higher education institutions (HEIs) modelled. • For the first time, panel data used, with cross-sectional and time-series variations. • Over time and across HEIs, energy use increases as income and size increase. • Economies of scale as HEIs grow, but energy use still rising with sector growth. • Research universities more energy intensive. Abstract Among the various sustainability goals of higher education institutions (HEIs), reducing energy use and carbon emissions are particularly important. However, not much is known about energy demand from the higher education sector – especially since there is a lack of robust models of energy demand in this sector. This paper, the first to utilize a panel dataset and advanced panel econometric techniques in order to model energy use in higher education, investigates variations in energy use between HEIs (cross-sectional analysis), and also changes in energy use over time (temporal analysis), using the UK as a case study. We argue that panel dataset and methods are more useful for understanding growth (and reduction) in energy use within the HE sector than the methods used within previous cross-sectional studies. Results show that, over time and also across the sector, energy consumption in the HEIs increases with increases in income and floor space, but at a slower rate. As HEIs grow overall (in terms of income, floor space, student and staff number) over time, they become more 'energy efficient' (using less energy per unit of area, population or income), indicating economies of scale in the temporal dimension. Results also show that after controlling for income and size, research intensive HEIs consume more energy. We also find a small but statistically significant effect of energy prices on energy consumption, as might be expected. Simulation using the model parameters for an example scenario suggests that energy consumption will continue to increase unless there is a significant change in the policies driving income growth and spatial expansion in the HE sector in the UK. [ABSTRACT FROM AUTHOR]

Highlights • Partially premixed combustion was applied on a multi-cylinder engine. • Different injection strategies should be adapted at different engine loads. • During stable operations, a peak gross indicated efficiency of 51% was achieved. • During transient operations, an average net indicated efficiency of 47.5% was demonstrated. Abstract Modern transportation requires advanced powertrain systems to reduce the production of greenhouse gas CO 2. Partially premixed combustion (PPC) is one of the most promising methods to achieve low emission and low fuel consumption of internal combustion engines. The present paper evaluated the effects of the calibration parameters on the efficiency and emissions of a multi-cylinder engine using PPC during stable operations, and the performance of the engine during transient operations. The peak gross indicated efficiency of 51.5% and the peak net indicated efficiency of 48.7% were achieved under stable operating conditions. The transient results also demonstrate an average net indicated efficiency of 47.5%. The nitrogen oxides (NOx), carbon monoxide (CO), and hydrocarbon (HC) conform with the Euro VI emission legislation in the case of most transient operations except some low load points. [ABSTRACT FROM AUTHOR]

Highlights • Model predictive control was applied to study the thermal efficiency of buildings. • Latent heat thermal energy storage was charging with solar energy. • The heating demand of buildings was estimated using EnergyPlus software. • Smart control was effective for domestic, office and service buildings, respectively. • Through a 7-day simulation, cost savings of about 12–57% was achieved for different buildings. Abstract In recent years, the concept of energy-efficient buildings has attracted widespread attention due to growing energy consumption in different types of buildings. The application of thermal energy storage (TES) systems, especially latent heat energy storage (LHES), has become a promising approach to improve thermal efficiency of buildings and hence reduce CO 2 emissions. One way to achieve this, could be by implementing a model predictive control (MPC) strategy, using weather and electricity cost predictions. To this end, a heat exchanger unit containing a phase change material (PCM) as a LHES medium, thermally charged by solar energy was incorporated into three versions of a standard building. This paper reports on the use of EnergyPlus software to simulate the heating demand profile of these buildings, with Solving Constraint Integer Programs (SCIP) as the optimization tool. After applying MPC strategy, the energy costs of different building types were evaluated. Furthermore, the effect of prediction horizon and decision time step of MPC strategy, and PCM mass capacity on the performance of the MPC were all investigated in 1 and 7-day simulations. Results showed that by increasing the prediction horizon and PCM mass, more cost saving could be obtained. However, in terms of decision time step, although the study revealed that increasing it led to a higher energy saving, it made the system more sensitive to sharp changes as it failed to provide an accurate reading of the parameters and variables. [ABSTRACT FROM AUTHOR]

Highlights • Review of decomposition studies on CO 2 emissions from electricity generation. • Lack of consensus on preferred decomposition identity. • Systematic analyses of differences and linkages across decomposition identities. • Implications of findings on decomposition identity selection. • Future extension of studies on drivers of CO 2 emissions from electricity generation. Abstract The quantification of drivers of CO 2 emissions from the electricity generation sector is an area that has attracted a great deal of attention among researchers and policy makers. Index decomposition analysis is a technique that has been widely used for this purpose. The increasing interest, however, has led to the usage of a variety of formulae in the decomposition. In this paper, a literature survey on the related publications is first compiled. Based on the survey, key features of studies and development trends are discussed. The decomposition formulae used are systematically analysed to elucidate the differences and relationships among them. An approach which quantifies the share of fossil fuels in the electricity mix and considers the generation efficiency by fuel type is recommended as it leads to the most comprehensive and meaningful decomposition results. Further extensions to the current practice to include factors such as transmission and distribution losses as well as carbon capture and storage are also discussed. The findings and recommendations provide insights into the analysis of CO 2 emissions from the electricity generation sector where major structural changes are expected to take place in future. [ABSTRACT FROM AUTHOR]

Highlights • Carbon capture utilization storage (CCUS) supply chain problem is studied. • All stages for carbon capture, transport and storage are taken into account. • The model is applied to a realistic case study of Northeast China. • Scenarios assessing toward different CO 2 reduction level are implemented. • The intermediate sites for CCUS supply chain lessen transportation and total costs. Abstract In recent years, several strategies have been developed and adopted in a bid to diminish the carbon dioxide (CO 2) released into the atmosphere. Carbon capture, utilization and storage (CCUS) system is one of the options. In this paper, we develop a CCUS supply chain superstructure by introducing more comprehensive transportation routes as well as the resultant system deployment schemes. A mixed integer linear programming (MILP) model is proposed to optimize the strategic CCUS deployment in Northeast China by making simultaneous selection of emission sources, capture facilitates, CO 2 pipeline, intermediate transportation sites, utilization and storage sites. The CCUS cost includes the cost of flue gas dehydration, CO 2 capture, transportation and injection, and revenue from CO 2 utilization through enhanced oil recovery (CO 2 -EOR). The overall network is economically optimized over a 20 years' life span to provide the geographic distribution and scale of capture, utilization and sequestration sites as well as the transportation routes for different scenarios. The results suggest that it is economic feasible to reduce 50% of the current CO 2 emissions from the stationary sources at a total annual cost $2.30 billion accompanied with $0.77 billion of revenue generated annually through CO 2 -EOR. Overall, the optimal CCUS supply chain network correspond to a net cost of $23.53 per ton of CO 2. The results are compared with source-sink model and it can be observed that the total annualized net cost is reduced from $1.62 billion to $1.53 billion and the transportation cost are reduced from $0.27 billion to $0.19 billion. [ABSTRACT FROM AUTHOR]

Highlights • RDE were measured over urban, rural and motorway routes with variable road grade. • Road grade greatly influences NOx and CO 2 emissions of Euro 5 diesel vehicles. • Linear and symmetric correlation was found between CO 2 and road grade. • NOx as function of road grade is best fitted by a 2th order polynomial law. Abstract On-road real driving emissions (RDE) testing was used to study the effects of many parameters not taken into account by laboratory testing but which can greatly influence vehicle pollutant emissions. Among these, road grade plays a key role. This paper investigates the effects of positive and negative road grades on the exhaust emissions of two Euro 5 diesel vehicles. Both vehicles were tested in the laboratory on the chassis dynamometer and on the road along a mixed route in Naples (Italy). The circuit includes urban, extra-urban and motorway driving in order to comply with Euro 6 RDE requirements. Laboratory testing aimed to assess emissions during current type approval driving cycles; on-road tests using portable analysers were used to determine real emissions as a function of road gradient. Vehicle Specific Power (VSP) analysis revealed that with respect to positive road grades, negative ones explain a higher share of total VSP. For −4% to +5% road gradients, the percentage variation of carbon dioxide emissions is linearly correlated with variations in slope. The same correlation for nitrogen oxides is vehicle dependent and well explained by a second-order polynomial function. [ABSTRACT FROM AUTHOR]

Highlights • Waste heat recovery from diesel engines by Organic Rankine Cycle is mentioned. • Working fluids are aggregated and classified to meet the requirement of each system. • Thermodynamic and economic analysis of engine-Organic Rankine Cycle is reported. • Main components of engine-Organic Rankine Cycle are presented for each selection. Abstract Diesel engines play an important role in transport, small medium-size stationary generator, agriculture, as well as generate the biggest CO 2 emission and environmental pollution. However, in fact, more than 60% of energy from air-fuel mixture combustion is not used to produce the mechanical work and is released into the environment as waste heat. Therefore, the conversion of waste heat from diesel engines into useful work along with engine development is to improve the efficiency and thermal management strategies. This review paper is to aim at giving an overview of the latest technology of the engine-Organic Rankine Cycle system in the applications of waste heat recovery from the heat sources with different temperatures, with particular concentration on diesel engines. About 25% of maximum thermal efficiency is found from the literature as using conventional standalone engine-Organic Rankine Cycle system. However, about 90% of overall thermal efficiency is reported from combined recovery system of waste heat sources. Moreover, the reports of working fluid selection, thermodynamic analysis, main components selection, and Organic Rankine Cycle system design/architecture based on the technology, economic and environmental aspects are gathered and presented to give the most suitable design point for the selected applications. [ABSTRACT FROM AUTHOR]

Highlights • The mechanism on electricity sector can hardly affect GDP and CO 2 emissions. • The impact of changing allocation on the aggregate economy is relatively small. • The allocation mechanism on electricity based on emission intensity is suggested. Abstract Global warming has necessitated the quest for CO 2 mitigation globally. Emission Trading Scheme (ETS) is a market-oriented strategy which may be effective for CO 2 mitigation. This study establishes a Computable General Equilibrium (CGE) model to analyze the impact of different ETS quota allocation scheme on the electricity industry and determine the best choice of quota allocation scheme for the electricity industry in China. The research on China's carbon trading market may provide an important case for the global carbon trading market. The results show that different quota allocation schemes have impacts on electricity price, and there are some spillover effects to other industries. Higher Annual Decline Factor (ADF) will reduce carbon rights than lower ones. Changes in the quota allocation schemes of a single industry (electricity) can hardly affect aggregate GDP and CO 2 emissions. Moreover, ETS quota allocation scheme in the electricity sector based on historical emission intensity could have better performance in commodity price, electricity supply, ETS price, GDP and social welfare. Thus, this paper suggests that the best choice of ETS quota allocation scheme in the electricity sector is the scheme that is based on historical emission intensity which ADF is 0. [ABSTRACT FROM AUTHOR]

Highlights • The input–output model and ecological network analysis (ENA) are integrated. • The control and dependence conditions of economic sectors in China are analyzed. • The key regions and sectors for carbon mitigation of China are identified. Abstract In this paper, multi-regional input–output analysis (MRIO) and ecological network analysis (ENA) are combined to assess carbon flows within China and identify key regions and sectors in the context of spatial heterogeneity for effective carbon mitigation. An interregional carbon network model is established by articulating the directions and magnitudes of carbon flows based on MRIO. ENA is then used to unveil indirect carbon flows and mutual relationships among regions. The results show that the northwest is the largest controller for most regions in China. Most carbon emissions in the rest of China are induced by the east’s final demand and substantial consumption. In addition, at sectoral level, the control and dependence abilities vary by region in China. This study provides an integrated framework to investigate interregional carbon emission structure, identify efficient pathways for coordinated emission mitigation, and reduce global carbon inequality across regions. [ABSTRACT FROM AUTHOR]

Highlights • Proposed a new method to balance carbon tax and technology upgrade cost. • Optimised the enterprise's technology upgrade strategy under carbon tax. • Tax rate is more sensitive to enterprise with a stricter control on expected cost. • Low tax rate hardly promotes enterprise with a loose control to reduce emission. • Excessive carbon tax makes enterprise give up its technology upgrade plan. Abstract Reducing CO 2 emissions is a hot topic, and an important policy to achieve this target is carbon tax. When an enterprise is subject to a carbon tax, it has to pay this extra fee for the long-term if it does not upgrade its production technology. It needs to pay a certain upgrade fee in the short-term if it chooses to upgrade its plant. Thus, it has been an important problem for enterprises seeking to balance the trade-off between the ‘long-term tax fee’ and the ‘short-term upgrade fee’. This paper explores how to optimise an enterprise’s production technology upgrade strategy based on existing low-carbon technologies, to minimise the total upgrade cost subject to an expected total cost per product. An integer programming model is proposed to formulate the problem, and a ‘multi-agent system – genetic algorithm’ method is presented for its solution. The model is applied to a numerical example and the results indicate that the proposed method is feasible. The impacts of carbon tax and enterprise’s expected cost on its technology upgrade strategy are further discussed. [ABSTRACT FROM AUTHOR]

As of July 2017, the emissions type-approval of light-duty vehicles in Europe is based on the Worldwide Harmonized Light-duty vehicles Test Procedure (WLTP), introduced to replace the old and outdated New European Driving Cycle (NEDC) test procedure. Since some elements of the European Legislation are still based on the NEDC (2020 CO 2 emission targets, vehicle labelling, national vehicle taxation policies, etc.) in order to allow sufficient lead time to vehicle manufacturers and national authorities to adapt to the new procedure, a simulation-based approach was chosen to calculate CO 2 emissions and fuel consumption according to the NEDC regime in the period 2017–2020. To achieve this objective without significantly increasing the cost and duration of the certification procedure, existing regulation foresees that vehicles are tested over the WLTP for CO 2 emissions, the test results are used as input in a simulation model that then calculates the corresponding CO 2 according to the NEDC test protocol. A dedicated vehicle simulation model (CO 2 MPAS) was developed for the purpose and is currently used for the type-approval of new vehicles in Europe. The development specifications of CO 2 MPAS were challenging, as it had to be highly accurate, exhibit fast operation, and function with a limited number of input data. This paper presents the development principles and process followed, details of the physical models employed in CO 2 MPAS, and provides information regarding its accuracy, validity and in use operation. CO 2 MPAS achieves low errors in the prediction of the NEDC cycle that in the controlled sample used for its development are of the order of 1% with a standard deviation of 3%, while the respective in-use numbers are of the order of 1.5% and 5%. In parallel, random sampling and testing of a 10% of the type-approved vehicles also occurs in order to guarantee the quality of the CO 2 MPAS results and the validity of the process. It is concluded that CO 2 MPAS can be used to accurately estimate emissions of conventional vehicles within a ±4% accuracy range, even when limited input data are available. In addition, the in-use data analyzed suggest that the use of the tool enables the certification of about 2/3 of the new vehicle models without the need of additional experimental tests. This is an important achievement as it reduces the costs and time necessary to certify light-duty vehicle CO 2 emissions during the transitional period. Finally, it can be concluded that the use of CO 2 MPAS does not affect the declared CO 2 emissions of vehicles over NEDC conditions. [ABSTRACT FROM AUTHOR]

In response to the oil crises of the 1970s, energy accounting experienced a revolution and became the much broader field of energy analysis, in part by expanding along the energy conversion chain from primary and final energy to useful energy and energy services, which satisfy human needs. After evolution and specialization, the field of energy analysis today addresses topics along the entire energy conversion chain, including energy conversion systems, energy resources, carbon emissions, and the role of energy services in promoting human well-being and development. And the expanded field would benefit from a common analysis framework that provides data structure uniformity and methodological consistency. Building upon recent advances in related fields, we propose a physical supply-use table energy analysis framework consisting of four matrices from which the input-output structure of an energy conversion chain can be determined and the effects of changes in final demand can be estimated. Real-world examples demonstrate the physical supply-use table framework via investigation of energy analysis questions for a United Kingdom energy conversion chain. The physical supply use table framework has two key methodological advances over the building blocks that precede it, namely extending a common energy analysis framework through to energy services and application of physical supply-use tables to both energy and exergy analysis. The methodological advances enable the following first-time contributions to the literature: (1) performing energy and exergy analyses on an energy conversion chain using physical supply-use table matrices comprised of disaggregated products in physical units when the last stage is any of final energy, useful energy, or energy services; (2) performing structural path analysis on an energy conversion chain; and (3) developing and utilizing a matrix approach to inhomogeneous units. The framework spans the entire energy conversion chain and is suitable for many sub-fields of energy analysis, including net energy analysis, societal energy analysis, human needs and well-being, and structural path analysis, all of which are explored in this paper. [ABSTRACT FROM AUTHOR]

Economic and environmental impact of a combined cooling, heating and power (CCHP) system depends not only on its structure but also on the way it is operated. In this paper, a novel methodology which utilizes overall optimal partial loads of power generation unit (PGU) and novel performance curves (NPC) is proposed to optimize CCHP operation. The PGU overall optimum partial loads for demands below and above the CCHP operating curve are determined based on the optimization criteria and system characteristics. Proposed methodology is flexible and adaptable; it accounts for energy prices, carbon dioxide emissions, primary energy consumption factors and load variations with the weather conditions. Other strategies, such as following match performance, hybrid load, electric load, and thermal load strategies are shown to be the special cases of the NPC methodology. The performance of a CCHP system which operates based on the NPC methodology is compared to the CCHP performances when following match performance, hybrid load, electric load, and thermal load strategies. The comparison is carried out for two small hotel buildings in San Francisco and Miami and residential buildings in Dalian having different energy demand profiles. These locations have different energy prices, carbon dioxide emissions and primary energy consumption factors. The proposed methodology leads to the best operation when compared to other operating strategies based on operating cost, carbon dioxide emissions, primary energy consumption and a combination of them which is not always the case for other operating strategies. Proposed methodology provides a unifying framework which includes all previously operating strategies. [ABSTRACT FROM AUTHOR]

Conventional combined cooling, heating and power (CCHP) systems based on fossil fuels, with an acceptable energy performance, however, intensify the greenhouse effect worldwide. Using solar energy in distributed energy systems has the potential to further reduce fossil fuels consumption, and ease carbon emissions. This paper proposes a novel CCHP system by combining concentrated photovoltaic/thermal (PV/T) technology with an advanced air-handling process that realizes independent control of temperature and humidity. The heat produced from a PV/T collector is for desiccant regeneration in a two-stage liquid desiccant cycle in summer, and can be directly supplied to nearby users in winter. An office building under typical climate conditions of Beijing in 2002 was adopted to determine its various energy demands. Due to the efficient use of solar energy, annual energy saving ratio and CO 2 emissions reduction ratio are predicted to be 73.28% and 74.55%, respectively. Two extreme conditions determining whether the excess heat from the PV/T collector is used were compared to demonstrate the top and bottom limitations of economic performance. The integrated performance, considering energy, environment and economic factors, reaches 37.48% when no excess heat from PV/T collector is used, and it can be further improved by thermal storage or recovering the excess heat to produce other products. This study provides a new solar utilization technology for trigeneration with advanced integrated performance. [ABSTRACT FROM AUTHOR]

Fuel cell based micro-combined heat and power (CHP) units used for domestic applications can provide significant cost and environmental benefits for end users and contribute to the UK’s 2050 emissions target by reducing primary energy consumption in dwellings. Lately there has been increased interest in the development of systematic methods for the design of such systems and their smoother integration with domestic building services. Several models in the literature, whether they use a simulation or an optimisation approach, ignore the dwelling side of the system and optimise the efficiency or delivered power of the unit. However the design of the building services is linked to the choice of heating plant and its characteristics. Adding the dwelling’s energy demand and temperature constraints in a model can produce more general results that can optimise the whole system, not only the micro-CHP unit. The fuel cell has various heat streams that can be harvested to satisfy heat demand in a dwelling and the design can vary depending on the proportion of heat needed from each heat stream to serve the energy demand. A mixed integer non-linear programming model (MINLP) that can handle multiple heat sources and demands is presented in this paper. The methodology utilises a process systems engineering approach. The model can provide a design that integrates the temperature and water flow constraints of a dwelling’s heating system with the heat streams within the fuel cell processes while optimising total CO 2 emissions. The model is demonstrated through different case studies that attempt to capture the variability of the housing stock. The predicted CO 2 emissions reduction compared to a conventionally designed building vary from 27% to 30% and the optimum capacity of the fuel cell ranges between 1.9 kW and 3.6 kW. This research represents a significant step towards an integrated fuel cell micro-CHP and dwelling design. [ABSTRACT FROM AUTHOR]