Search

This paper proposes that the gas economics in East Asia (including Southeast Asia and Northeast Asia) is different from standard economics due to its exogenous oil-indexed pricing and certain region-specific and industry-specific factors. Based on a hypothesis of distinctive economics, this paper proposes an analytical framework that studies East Asian gas markets. We demonstrate this framework through a case study of the effects of a low oil prices. The qualitative and quantitative results demonstrate that low oil prices, and subsequent oil-indexed gas prices, have affected gas supply and demand, and trade and pricing dynamics in ways that can be explained by the distinctive gas economics. This paper demonstrates that the distinctive economics may cause market failure and that the analytical framework based on the distinctive economics can be used to assess policy options to address these market failures. [ABSTRACT FROM AUTHOR]

Abstract: The application of Carbon Capture and Storage (CCS) technology to energy-intensive processes is starting to attract attention, presenting an opportunity for developing multi-user CO2 transportation networks. Recognising that most industrial facilities have not been designed with CCS in mind, this paper begins by looking at the practical issues associated with retrofitting CCS to industrial facilities. It then explores the technical and legal issues associated with building a CO2 network. This is followed by an analysis of the costs involved. Having identified the key issues, a case study from North East England is presented as an example of what is possible in an area of high CO2 emissions. The paper concludes by considering the issues involved in sizing a CO2 network which can evolve to meet future needs and linking that to the development of policy. [Copyright &y& Elsevier]

Abstract: This paper presents rigorous experimental outdoor performance of a 2.32kWP stand-alone photovoltaic (SAPV) system in New Delhi (India) for four weather types in each month such as clear, hazy, partially cloudy/foggy and fully cloudy/foggy weather conditions respectively. The daily power generated from the existing SAPV system was experimentally found in the range of 4–6kWh/day depending on the prevailing sky conditions. The number of days and daily power generated corresponding to four weather types in each month were used to determine monthly and subsequently annual power generation from the existing SAPV system. There are three daily load profiles with and without earth to air heat exchanger suitable for three seasons like summer (3.75–6.15kWh/day), winter (2.79–5.19kWh/day) and rainy (3.75kWh/day). The hourly efficiency of the SAPV system components are determined and presented in this paper. The life cycle cost (LCC) analysis for the existing typical SAPV system is carried out to determine unit cost of electricity. The effect of annual degradation rate of PV system efficiency is also presented in this paper. The energy production factor (EPF) and the energy payback time (EPBT) of the SAPV system was also determined and presented in this paper. [ABSTRACT FROM AUTHOR]

Abstract: Changes in complex industrial energy systems require adequate tools to be evaluated satisfactorily. The MIND method (Method for analysis of INDustrial energy systems) is a flexible method constructed as decision support for different types of analyses of industrial energy systems. It is based on Mixed Integer Linear Programming (MILP) and developed at Linköping University in Sweden. Several industries, ranging from the food industry to the pulp and paper industry, have hitherto been modelled and analyzed using the MIND method. In this paper the principles regarding the use of the method and the creation of constraints of the modelled system are presented. Two case studies are also included, a dairy and a pulp and paper mill, that focus some measures that can be evaluated using the MIND method, e.g. load shaping, fuel conversion and introduction of energy efficiency measures. The case studies illustrate the use of the method and its strengths and weaknesses. The results from the case studies are related to the main issues stated by the European Commission, such as reduction of greenhouse gas emissions, improvements regarding security of supply and increased use of renewable energy, and show great potential as regards both cost reductions and possible load shifting. [Copyright &y& Elsevier]

Abstract: The exploitation of the energy potential in biomass in a specific geographical region is frequently constrained by high production costs and the amount of land required per unit of energy generated. In addition, the distributed nature of the biomass resource and its normally low energy density may result in large transportation costs. Biomass also requires large land areas to collect and process the incoming solar radiation before the energy can be harvested. Previously published works on regional energy clustering (REC) and the Regional Resources Management Composite Curve, RRMCC (in this paper shortened to RMC), have been extended in this paper to tackle simultaneously the issues of the biomass supply chain, transportation, and land use. The RMC is a tool for supporting decision making in regional resource management. It provides a complete view of energy and land availability in a region, displaying their trade-offs in a single plot. The extension presented in this work has been developed in two steps. The first step presents the Regional Energy Cascade Analysis, which estimates the energy target within regional supply chains and provides the result for energy exchange flows between zones, the quantity of energy required to be imported/exported, and the locations of the demands. In the second step, the initial results are analysed against potential measures for improving the energy and land use targets by using the RMC and a set of rules for its manipulation. The presented method provides the option to assess the priorities: either to produce and sell the surplus energy on the fuel market or use the land for other purposes such as food production. This extended approach is illustrated with a comprehensive case study demonstrating that with the RMC application it is possible to maximise the land use and to maximise the biofuel production for the requested energy demand. [ABSTRACT FROM AUTHOR]

Abstract: This paper assesses the energy and water consumption practices of existing housing in Saudi Arabia, with the ultimate aim of establishing guidelines for delivering sustainable residential buildings in the near future. In order to achieve this aim the current status of a typical Saudi residence (i.e. an apartment complex) is investigated in terms of energy and water consumption using simulation software packages. The paper then examines the prospects for applying various measures to the typical Saudi residence to manage energy and water use more sustainably. This research identifies several design-related faults common to Saudi Arabian house design. These faults contribute to an inefficient use of energy and domestic water resources. Finally, the paper puts forward a set of recommendations and guidelines, design-related and otherwise, to enhance the sustainability of future Saudi residential buildings. [ABSTRACT FROM AUTHOR]

Abstract: This paper concerns the structural developments and the direction of technological change of the energy innovation system, based on the studies of Kuhn’s model of scientific change and Schumpeter’s model of technological change. The paper uses the case study of Thai government agencies for understanding the way governments can facilitate technological innovation. The analyses are based on a pre-foresight exercise to examine the potential of the bio-based energy and investigate a set of development policies necessary for the direction of energy system development. The results have shown that bio-based energy is seen as the next new wave for future businesses and one of the solutions to the problem of high oil prices to improve the world’s economic security and sustainable development. [Copyright &y& Elsevier]

Model predictive control (MPC) offers an optimal control technique to establish and ensure that the total operation cost of multi-energy systems remains at a minimum while fulfilling all system constraints. However, this method presumes an adequate model of the underlying system dynamics, which is prone to modelling errors and is not necessarily adaptive. This has an associated initial and ongoing project-specific engineering cost. In this paper, we present an on- and off-policy multi-objective reinforcement learning (RL) approach that does not assume a model a priori , benchmarking this against a linear MPC (LMPC — to reflect current practice, though non-linear MPC performs better) - both derived from the general optimal control problem, highlighting their differences and similarities. In a simple multi-energy system (MES) configuration case study, we show that a twin delayed deep deterministic policy gradient (TD3) RL agent offers the potential to match and outperform the perfect foresight LMPC benchmark (101.5%). This while the realistic LMPC, i.e. imperfect predictions, only achieves 98%. While in a more complex MES system configuration, the RL agent's performance is generally lower (94.6%), yet still better than the realistic LMPC (88.9%). In both case studies, the RL agents outperformed the realistic LMPC after a training period of 2 years using quarterly interactions with the environment. We conclude that reinforcement learning is a viable optimal control technique for multi-energy systems given adequate constraint handling and pre-training, to avoid unsafe interactions and long training periods, as is proposed in fundamental future work. • An integrated control strategy enables the efficient use of energy at lower costs. • Model-predictive control and reinforcement learning have common mathematical ground. • Reinforcement learning-based energy management does not require a priori models. • Reinforcement learning can outperform model-predictive control after training. • Safety and fast convergence remain as challenges in reinforcement learning. [ABSTRACT FROM AUTHOR]

Abstract: A virtual power plant aggregates various local production/consumption units that act in the market as a single entity. This paper considers a virtual power plant consisting of an intermittent source, a storage facility, and a dispatchable power plant. The virtual power plant sells and purchases electricity in both the day-ahead and the balancing markets seeking to maximize its expected profit. Such model is mathematically rigorous, yet computationally efficient. The offering problem is cast as a two-stage stochastic mixed-integer linear programming model which maximizes the virtual power plant expected profit. The uncertain parameters, including the power output of the intermittent source and the market prices, are modeled via scenarios based upon historical data. The proposed model is applied to a realistic case study and conclusions are drawn. [Copyright &y& Elsevier]

Abstract: Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the users’ requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method. [Copyright &y& Elsevier]

Abstract: This paper proposes a parametric frontier approach to estimating economy-wide energy efficiency performance from a production efficiency point of view. It uses the Shephard energy distance function to define an energy efficiency index and adopts the stochastic frontier analysis technique to estimate the index. A case study of measuring the economy-wide energy efficiency performance of a sample of OECD countries using the proposed approach is presented. It is found that the proposed parametric frontier approach has higher discriminating power in energy efficiency performance measurement compared to its nonparametric frontier counterparts. [Copyright &y& Elsevier]

Abstract: Electrical generators of renewable electricity resources are quiet, clean and reliable. Optimal placement of renewable electricity generators (REGs) results in reduction of objective functions like losses, costs of electrical generation and voltage deviation. Because of recent technology developments of photovoltaic units, wind turbine and fuel cell units, only these generators are considered in this paper. This work presents a multiobjective optimization algorithm for the siting and sizing of renewable electricity generators. The objectives consist of minimization of costs, emission and losses of distributed system and optimization of voltage profile. This multiobjective optimization is solved by the Improved honey bee mating optimization (HBMO) algorithm. In the proposed algorithm, an external repository is considered to save non-dominated (Pareto) solutions found during the search process. Since the objective functions are not the same, a fuzzy clustering technique is used to control the size of the repository within the limits. This algorithm is executed on a typical 70-bus test system. Results of the case study show the proper siting and sizing of REGs are important to improve the voltage profile, reduce costs, emission and losses of distribution system. The main feature of the algorithm refers to its accuracy and calculation speed. [Copyright &y& Elsevier]

Abstract: This paper establishes a carbon capture and storage (CCS) investment evaluation model based on real options theory considering uncertainties from the existing thermal power generating cost, carbon price, thermal power with CCS generating cost, and investment in CCS technology deployment. The model aims to evaluate the value of the cost saving effect and amount of CO2 emission reduction through investing in newly-built thermal power with CCS technology to replace existing thermal power in a given period from the perspective of power generation enterprises. The model is solved by the Least Squares Monte Carlo (LSM) method. Since the model could be used as a policy analysis tool, China is taken as a case study to evaluate the effects of regulations on CCS investment through scenario analysis. The findings show that the current investment risk of CCS is high, climate policy having the greatest impact on CCS development. Thus, there is an important trade off for policy makers between reducing greenhouse gas emissions and protecting the interests of power generation enterprises. The research presented would be useful for CCS technology evaluation and related policy-making. [Copyright &y& Elsevier]

Abstract: Assessing the correct operation of PV grid-connected systems (PVGCS) is paramount not only for mere energy and profitability concerns but also for safety reasons. Intended to this purpose, the IEC 62446 standard is open to some tests to be required in some circumstances, in addition to those stated in this document. Our work proposes a procedure to carry out quality checks in PVGCS complying with this standard and dealing with some tests not mentioned in it – namely, PV generator peak power measurement, inverter response and earth electrode measurement – so that the verification of the system gets more comprehensive. This procedure was carried out in six PV plants sited in different locations with a Mediterranean climate in Spain. The most remarkable results of this experimental campaign may be summarized as follows: an excellent on-site behavior of the inverters, in general very good figures for the isolation and earth electrode resistance and a scarcely relevant existence of hot spots. On the down side, some figures for the peak power of the tested PV generators well below their nominal value were found. The procedure described in this paper has proved to be a useful tool to assist in the verification of a PVGCS after installation and for subsequent re-inspection or maintenance. [Copyright &y& Elsevier]

Abstract: We present a bilevel optimization approach to designing effective and efficient incentive policies for stimulating investment in renewable energy. The effectiveness of an incentive policy is its capability to achieve a goal that would not be achievable without it. Renewable portfolio standards are used in this paper as the policy goal. The efficiency of an incentive policy is measured by the amount of policy intervention, such as taxes collected or subsidies paid, to achieve the policy goal. We obtain the most effective and efficient incentive policies in the context of generation expansion planning, in which a centralized planner makes investment decisions for the energy system to serve projected demand of electricity. A case study is conducted on integrated coal transportation and electricity transmission networks representing the contiguous United States. The numerical analysis from the case study provides insights on the comparison of various incentive policies. The sensitivity of the incentive policies with respect to coal production cost, wind energy investment cost, and transmission capacity is also studied. [Copyright &y& Elsevier]

Abstract: This article analyzes the optimal choice of the tilt angle for the solar panel in order to collect the maximum solar irradiation. In this paper, the collector surface is assumed to be facing toward equator. The study is based upon the measured values of daily global and diffuse solar radiation on a horizontal surface. It is shown that the optimal angle of tilt (βopt ) for each month, allows us to collected the maximum solar energy for Madinah site. Annual optimum tilt angle is found to be approximately equal to latitude of the location. It is found that the loss in the amount of collected energy when using the yearly average fixed angle is around 8% compared with the monthly optimum tilt βopt . [ABSTRACT FROM AUTHOR]

Abstract: Wind power – a renewable energy source increasingly attractive from an economic viewpoint – constitutes an electricity production alternative of growing relevance in current electric energy systems. However, wind power is an intermittent source that cannot be dispatched at the will of the producer. Modeling wind power production requires characterizing wind speed at the sites where the wind farms are located. The wind speed at a particular location can be described through a stochastic process that is spatially correlated with the stochastic processes describing wind speeds at other locations. This paper provides a methodology to characterize the stochastic processes pertaining to wind speed at different geographical locations via scenarios. Each one of these scenarios embodies time dependencies and is spatially dependent of the scenarios describing other wind stochastic processes. The scenarios generated by the proposed methodology are intended to be used within stochastic programming decision models to make informed decisions pertaining to wind power production. The methodology proposed is accurate in reproducing wind speed historical series as well as computationally efficient. A comprehensive case study is used to illustrate the capabilities of the proposed methodology. Appropriate conclusions are finally drawn. [Copyright &y& Elsevier]

Abstract: Although the Brazilian Federal Government has been increasing investments in the housing sector since 2004, there has been a significant increase in the housing deficit as well. In 2007 this deficit had already reached 7.2 million dwellings. The majority (84%) consists of families with monthly income under three minimum wages. However, none of the traditional lines of credit considers families up to that monthly income level for building their own dwellings. In 2004, a program was created to subsidize low-cost housing (“Programa de Subsídio à Habitação de Interesse Social – PSH”) with a maximum subsidy of about US$ 2500 for the construction of ‘do-it-yourself’ units. The present research had the general purpose of conceiving, constructing and evaluating the performance of a low-cost prototype consisting of wood and plywood panels. The object of analysis in this case study was a building prototype located in Canoinhas, in the South of Brazil (26°10′38″S, altitude 765m above sea level), which was built within the scope of a program for subsidized low-cost housing. The present paper is concerned with evaluating the thermal performance of the finished prototype by means of onsite measurements and performing computer simulations for testing improvements of the original building prototype. From obtained results, general guidelines were drawn for improving indoor comfort conditions. [Copyright &y& Elsevier]

Abstract: In this paper, we perform Simulated Annealing (SA) algorithm for optimizing size of a PV/wind integrated hybrid energy system with battery storage. The proposed methodology is a heuristic approach which uses a stochastic gradient search for the global optimization. In the study, the objective function is the minimization of the hybrid energy system total cost. And the decision variables are PV size, wind turbine rotor swept area and the battery capacity. The optimum result obtained by SA algorithm is compared with our former study’s result. Consequently, it is come up with that the SA algorithm gives better result than the Response Surface Methodology (RSM). The case study is realized for a campus area in Turkey. [Copyright &y& Elsevier]

Abstract: Our strong dependence on fossil fuels results from the intensive use and consumption of petroleum derivatives which, combined with diminishing oil resources, causes environmental and political concerns. The utilization of agricultural residues as raw materials in a biorefinery is a promising alternative to fossil resources for production of energy carriers and chemicals, thus mitigating climate change and enhancing energy security. This paper focuses on a biorefinery concept which produces bioethanol, bioenergy and biochemicals from two types of agricultural residues, corn stover and wheat straw. These biorefinery systems are investigated using a Life Cycle Assessment (LCA) approach, which takes into account all the input and output flows occurring along the production chain. This approach can be applied to almost all the other patterns that convert lignocellulosic residues into bioenergy and biochemicals. The analysis elaborates on land use change aspects, i.e. the effects of crop residue removal (like decrease in grain yields, change in soil N2O emissions and decrease of soil organic carbon). The biorefinery systems are compared with the respective fossil reference systems producing the same amount of products/services from fossils instead of biomass. Since climate change mitigation and energy security are the two most important driving forces for biorefinery development, the assessment focuses on greenhouse gas (GHG) emissions and cumulative primary energy demand, but other environmental categories are evaluated as well. Results show that the use of crop residues in a biorefinery saves GHG emissions and reduces fossil energy demand. For instance, GHG emissions are reduced by about 50% and more than 80% of non-renewable energy is saved. Land use change effects have a strong influence in the final GHG balance (about 50%), and their uncertainty is discussed in a sensitivity analysis. Concerning the investigation of the other impact categories, biorefinery systems have higher eutrophication potential than fossil reference systems. Based on these results, a residues-based biorefinery concept is able to solve two problems at the same time, namely find a use for the abundant lignocellulosic residues and ensure a mitigation effect for most of the environmental concerns related to the utilization of non-renewable energy resources. Therefore, when agricultural residues are used as feedstocks, best management practices and harvest rates need to be carefully established. In fact, rotation, tillage, fertilization management, soil properties and climate can play an important role in the determination of the amount of crop residue that can be removed minimizing soil carbon losses. [Copyright &y& Elsevier]

Abstract: The goal of this paper is to examine the determinants of oil consumption for a panel consisting of six Australian States and one territory, namely Queensland, New South Wales, Victoria, Tasmania, South Australia, Western Australia, and the Northern territory, for the period 1985–2006. We find that oil consumption, oil prices and income are panel cointegrated. We estimate long-run elasticities and find that oil prices have had a statistically insignificant impact on oil consumption, while income has had a statistically significant positive effect on oil consumption. [Copyright &y& Elsevier]

Abstract: This paper investigates thermal performance of an existing eco-friendly and low embodied energy vault roof passive house (or mud-house) located at Solar Energy Park of IIT Delhi, New Delhi (India). Based on embodied energy analysis, the energy payback time for the mud-house was determined as 18 years. The embodied energy per unit floor area of R.C.C. building (3702.3MJ/m2) is quiet high as compared to the mud-house (2298.8MJ/m2). The mud-house has three rooms with inverted U-shape roof and remaining three rooms with dome shape roof. A thermal model of the house consisting of six interconnected rooms was developed based on energy balance equations which were solved by using fourth order Runge Kutta numerical method. The predicted six room air temperatures were found in good agreement with the experimental observed data on hourly basis in each month for one year. The annual heating and cooling energy saving potential of the mud-house was determined as 1481 kWh/year and 1813kWh/year respectively for New Delhi composite climate. The total mitigation of CO2 emissions due to both heating and cooling energy saving potential was determined as 5.2 metric tons/year. The annual carbon credit potential of mud-house was determined as € 52/year. Similar results were obtained for the different climatic locations in India. [Copyright &y& Elsevier]

Abstract: To improve the energy efficiency of buildings via compliance to regulation in Iran, Code No. 19 was devised in 1991. The code lacks high level aims and objectives, addressing the characteristics of Iranian buildings. As a consequence, the code has been revised and is not completely implemented in practice, and still remains inefficient. As with any energy coding system, this code has to identify the right balance between the different energy variables for the Iranian climate and way of life. In order to assist improvements to high level objectives of Code 19, this code is compared with ISO 9164, EN 832, German regulation, TS 825 of Turkey and China’s GB 50189 to understand how these have adapted international standards to national features. In order to test the appropriateness of Code 19, five case study buildings in Iran are assessed against Code 19 as well as Turkish standard TS 825 and the results are compared. The results demonstrate that Code 19 is efficient in calculations of building envelope, but it needs improvements in the areas of ventilation, gains from internal and solar sources. The paper concludes by offering suggestions for improving the code. [Copyright &y& Elsevier]

Abstract: In recent years, energy systems have been undergoing a development trend characterised by privatisation of the most important energy sectors (electricity and natural gas) that has turned former monopolies into free-market competitors. Furthermore, community awareness of environmental impact caused by large conventional power plants is growing, together with a greater interest in distributed-generation (DG) technologies based upon renewable energy sources (RES) and cogeneration. In this context, renewable energy technologies are emerging as potentially strong competitors for more widespread use. Despite the remarkable progress attained over the past decades, RES have not yet been fully integrated into the power sector. Some RES-technologies have already achieved a significant market share. The industry is now quite mature, although far from having developed its global potential. This paper deals with the current status of DG in Greece and the presentation of a 60kWp PV power station, developed under Law 3468/06 “Production of Electricity from Renewable Energy Sources, High Efficiency Cogeneration of Heat and Power and Other Deνices”. This application is the first DG installation with fixed PV modules implemented in the country after the approval of Law 3468/06. Cash flow economic analysis of the developed DG installation is performed and the experiences related to the potential of DG in Greek electricity market is presented and discussed. [Copyright &y& Elsevier]

Abstract: In this paper, size of a PV/wind integrated hybrid energy system with battery storage is optimized under various loads and unit cost of auxiliary energy sources. The optimization is completed by a simulation based optimization procedure, OptQuest, which integrates various heuristic methods. In the study, the main performance measure is the hybrid energy system cost. And the design parameters are PV size, wind turbine rotor swept area and the battery capacity. The case study is realized for Izmir Institute of Technology Campus Area, Urla, Turkey. The simulation model of the system is realized in ARENA 12.0, a commercial simulation software, and is optimized using the OptQuest tool in this software. Consequently, the optimum sizes of PV, wind turbine and battery capacity are obtained under various auxiliary energy unit costs and two different loads. The optimum results are confirmed using Loss of Load Probability (LLP) and autonomy analysis. And the investment costs are investigated how they are shared among those four energy sources at the optimum points. [Copyright &y& Elsevier]

Distributed photovoltaic systems can cause adverse distribution system impacts, including voltage violations at customer locations and thermal overload of lines, transformers, and other equipment resulting from high current. The installed capacity at which violations first occur and above which would require system upgrades is called the hosting capacity. Current static methods for determining hosting capacity tend to either consider infrequent worst-case snapshots in time and/or capture coarse time and spatial resolution. Because the duration of violations cannot be captured with these traditional methods, the metric thresholds used in these studies conservatively use the strictest constraints given in operating standards, even though both worse voltage performance and higher overloads may be temporarily acceptable. However, assessing the full details requires accurately capturing time-dependence, voltage-regulating equipment operations, and performance of advanced controls-based mitigation techniques. In this paper, we propose a dynamic distributed photovoltaic hosting capacity methodology to address these issues by conducting power flow analysis for a full year. A key contribution is the formulation of time aware metrics to take these annual results and identify the hosting capacity. Through a case study, we show that this approach can more fully capture grid impacts of distributed photovoltaic than traditional methods and the dynamic hosting capacity was 60%–200% higher than the static hosting capacity in this case study. • Proposed dynamic study can more accurately capture a feeder's hosting capacity. • Proposed time aware metrics comply more closely with interconnection standards. • Traditional static methods cannot capture grid impacts like annual energy losses. • Static studies cannot assess the efficacy of smart inverter-based control schemes. • Case study and sensitivity analysis show the scalability of the proposed approach. [ABSTRACT FROM AUTHOR]

• Open source data are used to model distributed generation. • The standard deviation of the residual load is a surrogate for required storage. • Even shares of wind and solar minimize storage for Philadelphia. • Philadelphia needs more storage than Oldenburg for comparable renewable share. In this paper, an open source tool is introduced to represent urban energy infrastructure in the City of Philadelphia, and different renewable energy scenarios are compared with respect to minimization of the standard deviation of the residual load. Renewable energy sources play a critical role in the world's ongoing energy transition in response to climate change. Urban Energy Systems may be particularly sensitive to this transition due to the high energy demand density associated with urban environments. Open energy analysis and modeling tools can provide important information that can be used by urban energy planners, policy makers, and other stakeholders during this transition. In the present study, we apply FlexiGIS, an open energy modeling tool developed in a European context, to a case study in the City of Philadelphia. Due to the importance of open access to energy data, we pay particular attention to open energy data sources. Notably, OpenStreetMap was incomplete in its spatial coverage, but alternate open data resources were identified. This work conducts an optimization of the renewable energy mix to minimize the amount of balancing energy required for the residual load. We observe that Philadelphia has an optimal mix of renewables that favors a roughly even share of wind and solar, but that, compared to a previous case study in Oldenburg, Germany, requires more balancing energy at comparable levels of renewable penetration. [ABSTRACT FROM AUTHOR]

• Impact of carbon pricing on biomass supply chain optimization models is analyzed. • Several propositions are proved mathematically and validated using a case study. • Denser forms of biomass are prescribed when carbon price increases. • Carbon tax and cap-and-trade models have equal emissions for equal carbon price. • In carbon offset model, the compliance target is the lower bound of optimum emissions. Carbon tax, carbon cap-and-trade, and carbon offset are the main carbon pricing policies in practice. Several studies analyzed the impacts of these policies on optimum solutions of biomass supply chain models. However, due to the focus on specific case studies, insights from these studies may not be general. In this paper, the impact of carbon pricing policies on the optimum solutions of case-independent biomass supply chain models is studied. Several propositions that discuss the impact of carbon pricing policies on optimum cost and emissions of biomass supply chain models are presented and proved mathematically. Next, mathematical models are developed to determine the optimal feedstock mix of a biomass-fed district heating plant. The case study results are used to numerically confirm all propositions. When the carbon price increases, the models prescribe the replacement of natural gas with biomass. Carbon tax and carbon cap-and-trade models result in equal optimum decision variables and emissions for equal carbon prices. The carbon cap-and-trade model has less cost than the carbon tax model if the carbon price is more than the price of initial allowance. Careful allotment of the compliance target is important for the carbon offset model because it bounds the optimum emissions. [ABSTRACT FROM AUTHOR]

• Real-world functional implementation of smart charging technology. • Development of scalable electric vehicle-to-building integration platform. • Proven demand charge mitigation using real-time electric vehicle charging. • Extensive economic analysis on installation and operation cost of smart charging. Higher electric vehicle (EV) adoption will stress the importance of demand flexibility to achieve more economic, efficient, and reliable grid operation. Charging technologies will be paramount in shifting temporally to better fit the variable generation of wind and solar. Therefore, analysis is warranted on the benefits of EV charge scheduling with respect to installation cost, operation cost, difficulty of implementation, and grid flexibility. We tackle this by analyzing the cost savings of implementing an EV charge scheduling infrastructure to reduce demand charges and installation costs. In this paper, we analyze a case study for operation of 16 level 2 chargers and 1 fast charger for two different building types. We then evaluate various test phases for controlling building and charging loads using an adaptive charging network (ACN) algorithm to characterize the ACN's potential to reduce overall project cost. [ABSTRACT FROM AUTHOR]

• A regulatory framework has been embedded in the energy management system (EMS) • The EMS has been applied to a low voltage microgrid (MG) to optimise its management. • The Spanish self-consumption scheme has been used as a case study. • The results obtained by the new EMS corroborate the importance of the new approach. • The model was validated at the MG Research Laboratory of Aalborg University. This paper proposes for the first time to analyse the impact of embedding the regulatory framework constraints inside a model for the energy management optimization of a microgrid. As a case study, a low voltage microgrid using solar energy under the Spanish self-consumption scheme has been selected. The proposed model is based on a previous one elaborated by the authors, which did not include the regulatory framework. The results provided by the former and the new model have been compared, corroborating the importance of taking into account the economic aspects of the regulatory constraints when managing the facility. Furthermore, the results also highlight the urgency to extrapolate this approach to other countries, in order to enhance the economic feasibility of these facilities and aid to their deployment. In addition, the performance of the model has been experimentally validated at the Microgrid Research Laboratory of Aalborg University. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a novel multi-time-stage input–output-based modeling framework for simulating the dynamics of bioenergy supply chains. One of the key assumptions used in the model is that the production level at the next time-stage of each segment of the energy supply chain adjusts to the output surplus or deficit relative to targets at the current time period. Furthermore, unlike conventional input–output models, the technology matrix in this approach need not be square, and thus can include coefficients denoting flows of environmental goods, such as natural resources or pollutants. Introducing a feedback control term enables the system to regulate the dynamics, thus extending the model further. This is an important feature since the uncontrolled dynamic model exhibits oscillatory or unstable behavior under some conditions; in principle, the control term allows such undesirable characteristics to be suppressed. Numerical simulations of a simple, two-sector case study are given to illustrate dynamic behavior under different scenarios. Although the case study uses only a hypothetical system, preliminary comparisons are made between the simulation results and some broad trends seen in real bioenergy systems. Finally, some of the main policy implications of the model are discussed based on the general dynamic characteristics seen in the case study. In particular, insights from control theory can be used to develop policy interventions to impart desirable dynamic characteristics to nascent or emerging biofuel supply chains. These interventions can be used to guide the growth of bioenergy supplies along final demand trajectories with minimal fluctuation and no instability. [Copyright &y& Elsevier]

Abstract: This paper summarizes the research of Monte Carlo simulation-based Economic, Energy and Environmental (3E) Life Cycle Assessment (LCA) of the three Biomass-based Fuel Ethanol (BFE) projects in China. Our research includes both theoretical study and case study. In the theoretical study part, 3E LCA models are structured, 3E Index Functions are defined and the Monte Carlo simulation is introduced to address uncertainties in BFE life cycle analysis. In the case study part, projects of Wheat-based Fuel Ethanol (WFE) in Central China, Corn-based Fuel Ethanol (CFE) in Northeast China, and Cassava-based Fuel Ethanol (CFE) in Southwest China are evaluated from the aspects of economic viability and investment risks, energy efficiency and airborne emissions. The life cycle economy assessment shows that KFE project in Guangxi is viable, while CFE and WFE projects are not without government’s subsidies. Energy efficiency assessment results show that WFE, CFE and KFE projects all have positive Net Energy Values. Emissions results show that the corn-based E10 (a blend of 10% gasoline and 90% ethanol by volume), wheat-based E10 and cassava-base E10 have less CO2 and VOC life cycle emissions than conventional gasoline, but wheat-based E10 and cassava-based E10 can generate more emissions of CO, CH4, N2O, NO x , SO2, PM10 and corn-based E10 can has more emissions of CH4, N2O, NO x , SO, PM10. [Copyright &y& Elsevier]

Abstract: The on-going climate change concerns have stimulated heavy interest in biofuels, and supporters of biofuels hail that they are considered naturally carbon-neutral. Critiques on the other hand cry that the large-scale production of biofuels can not only strain agricultural resources, but also threaten future food security. People who live in the drylands of India are often faced with challenges and constraints of poverty. Foremost among the challenges are the marginal environmental conditions for agriculture, often influenced by low and erratic rainfall, frequent droughts, poor soil condition, unreliable irrigation water supply, and rural migration to urban areas in search of work. In this paper, we have analyzed a case study of community lift irrigation practiced in India and its impact in boosting agricultural productivity and enhancing local food security. The lift-irrigation model practiced in the drylands of India to grow food crops can be adopted for the expansion of biofuel crops that has the potential to eradicate poverty among farming communities if appropriate sustainable development measures are carefully implemented. [Copyright &y& Elsevier]