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Integrated Energy Systems (IES) play a pivotal role in achieving carbon peak and carbon neutrality goals. However, previous research in IES operation has mainly focused on energy flow constraints, neglecting the impacts of renewable energy output, energy prices, carbon emission, and storage status. To bridge this gap, this paper proposes a Comprehensive Self-Adaptive (CSA) operation strategy as a key component of our two-tier synergistic optimization method, optimizing an IES integrated with Concentrated Photovoltaic/Thermal systems. In the upper-tier capacity configuration, the proposed method considers the full life-cycle carbon emissions of equipment. In the lower-tier operational strategy optimization, the CSA operation strategy automatically adjusts energy generation, utilization, and storage by comprehensively evaluating hourly operating costs, hourly carbon emissions, and hourly storage benefits. Compared to traditional operation strategies and other adaptive methods, the newly developed strategy consistently demonstrates superior performance. When contrasted with separate energy systems, IES operating under the CSA operation strategy markedly stands out, achieving a cost savings rate of 25.87 %, a CO2 reduction rate of 61.54 %, and an electricity matching ratio of 91.24 %. Additionally, the paper explores the performance of the CSA operation strategy across various regions, confirming its feasibility and generalizability under diverse load and irradiance conditions. • An integrated energy system combines CPV/T, ORC, and multi-dimensional energy storage solutions. • A CSA operation strategy holistically assesses costs, carbon emissions, and storage benefits during operation. • A two-tier synergistic optimization method simultaneously addresses capacity configuration and operational strategy. • Comparative studies in various regions to validate the feasibility and generalizability of the CSA strategy and CPV/T-IES. [ABSTRACT FROM AUTHOR]

By purchasing emission reduction equipment or reducing production scale, it is possible to effectively decrease CO 2. Therefore, understanding the marginal abatement cost (MAC) associated with these methods is crucial for making decisions. However, previous studies using the directional distance function (DDF) approach often mis-specified production functions and neglected data noise. They also assumed decision-making units (DMUs) to be on the production frontier and used proportional changes in inputs and outputs as abatement paths. This paper addresses these limitations by developing the convex quantile non-radial directional distance function (CQR-NDDF) method, which estimates the MAC of CO 2 and determines optimal abatement paths for DMUs without assuming a specific production function, employing linear programming techniques. Applying this method to 30 provinces in mainland China from 2011 to 2019, the study finds that China's CO 2 MAC increased from 182 to 247 yuan/ton. The lowest-cost abatement path varies by province and time. The club convergence and ordered probit model are employed to conclude that the second industry and urbanization increase the MAC of CO 2 , while factors such as foreign direct investment, openness level, and human capital decrease the MAC. Moreover, the CQR-NDDF method yields significantly lower MAC estimates than the NDDF method. In conclusion, this paper provides new insights into China's CO 2 MAC, emphasizing the importance of considering inefficiency and data noise in MAC estimation. We anticipate that utilizing CO 2 MAC as a benchmark for carbon trading market prices could lead to an increase in prices within China's carbon trading market. • A novel method for estimating CO 2 MAC has been developed. • Ignoring inefficiency will result in an overestimation of CO 2 MAC. • Three different emission reduction pathways are considered in the estimation. • The heterogeneity of the lowest cost abatement pathways has been identified. [ABSTRACT FROM AUTHOR]

The core of the energy transformation under the carbon-neutral vision is the gradual replacement of high-carbon energy by zero-carbon and low-carbon energy. However, the large-scale deployment of clean energy technology in turn relies on key minerals such as copper, aluminum, zinc, and nickel. Based on this, this paper conducts research on the demand for key minerals in clean energy transition and the role of key minerals in clean energy transition. In particular, this paper calculated the demand for mineral supply for China's carbon neutrality target, and the impact of some mineral resource constraints on the carbon neutrality path. Relevant results can provide a decision-making basis for the future development and utilization of key mineral resources, as well as the implementation of future carbon-neutral goals. • We evaluate the impact of crucial mineral resource on the carbon neutrality path. • Copper's availability greatly affects the adoption of new energy technologies. • Limited resources hinder early carbon capture and storage development. • Negative emission technologies are necessary for China's carbon neutrality. [ABSTRACT FROM AUTHOR]

To attain China's target of carbon neutrality by 2060, the implementation of the Energy Consumption Trading (ECT) system serves as an effective approach to improve energy efficiency and mitigate CO 2 emissions. Nevertheless, it is crucial to consider not only the importance of carbon reduction effect caused by ECT system but also the associated cost. Therefore, this paper applies the spatial difference-in-differences (SDID) model to assess the direct and spillover impacts of the ECT policy on the carbon abatement cost, which is measured by shadow price of CO 2 emissions and calculated using SBM-DEA model. Panel data encompassing 279 Chinese cities from 2010 to 2019 are employed for analysis, with additional insights provided through heterogeneity and mechanism analyses. The results show that ECT policy increases the local carbon abatement cost in pilot cities but decreases the cost of surrounding cities. Meanwhile, such a declination effect in neighboring cities with a spatial attenuation boundary of 1000 km. The heterogeneity analysis suggests that the implementation of ECT policy leads to an increase in the carbon abatement cost in cities located in non-Eastern Coastal regions, cities with abundant natural resources and cities with small populations. The mechanism analysis indicates that the ECT policy implementation facilitates the improvement of green technology in the neighboring cities of the pilot project, consequently lowering the carbon abatement cost. Besides, this policy also results in a decrease in the carbon intensity of the pilot cities. Owing to the U-shaped association between carbon intensity and the carbon abatement cost, the policy implementation stimulates an increase in the cost within the pilot cities. • This paper estimates the carbon abatement cost (MAC) using SBM-DEA method. • The SDID model is used to investigate the impacts of ECT policy on carbon MAC. • We test whether green technology and carbon intensity are mediating variables. • ECT policy increases the carbon MAC in pilot cities through carbon intensity. • ECT policy lowers the carbon MAC of adjacent cities through the green technology. [ABSTRACT FROM AUTHOR]

The carbon neutrality agenda requires that carbon lock-in enters an endgame. A well-developed energy system, which is secure, equitable, and sustainable is paramount to getting rid of carbon lock-in and realizing decarbonization. We carry out systematic research to empirically study the possible carbon lock-in reduction effect of energy trilemma based on the instrumental variable-generalized method of moment (IV-GMM) model. We also detect heterogeneous effects in terms of geographical locations and endowments of capital, as well as the impact mechanisms. Moreover, this paper highlights the mediating and threshold role of environmental regulation. We thus get the following conclusions. (1) The paper's primary findings underscore that the continuous increase of energy trilemma exacerbates carbon lock-in and hampers the process of decarbonization; (2) Energy trilemma has a higher stimulating effect on carbon lock-in in provinces that lie in the central region and that have a comparatively low level of physical, social, and human capital; (3) Energy trilemma can also indirectly aggravate carbon lock-in by inhibiting technology innovation and exacerbating carbon emissions intensity; (4) The interaction of environmental regulation and energy trilemma can alleviate the energy trilemma - carbon lock-in nexus, and environmental regulation also shows a significant threshold effect. • We investigate the impact of the energy trilemma on carbon lock-in. • Energy trilemma eradication is an effective way to realize the carbon lock-in endgame. • The nexus between energy trilemma and carbon lock-in is more prominent in provinces with high capital endowments. • Environmental regulation shows significant mediating and threshold effects. • The exacerbate carbon lock-in effect of energy trilemma depends on technology and intensity effect. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality quickly and deal with urban greenhouse effect, it is necessary to study the energy consumption of urban buildings. Energy consumption prediction is an important step in planning and managing energy use in buildings. At present, few studies have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings in urban built-up areas. In this paper, a spatial data-driven framework is introduced for the analysis and assessment of building energy consumption. The framework is grounded in the building centroid and is combined with single photon radar and point of interest data through the utilization of the nearest neighbor classification algorithm. Two megacities, Beijing and Shanghai, are taken as examples to illustrate the method and to generate the regional building energy use database. The results show that: a) building physical feature (geometric form, functional type) have a significant impact on energy consumption, and energy consumption is correlated with the economic level of the region; b) Energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphon effect is obvious in region with high energy consumption. The contribution of the framework is to provide insights into the feasibility of employing multiple spatial data fusion for the analysis of energy consumption within urban built-up areas. This can be employed to address energy planning concerns and help promote sustainable environmental practices in urban areas worldwide. • This paper attempts to provide a feasible framework for analyzing urban building energy use by utilizing real-time urban semantic perception information and building features. • The proposed framework have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings. • The proposed methodology can obtain regional energy consumption stocks and produce spatial distribution results, thus improving the interpretability of the data. • The results show that energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphoning effect is obvious in regions with high energy consumption. [ABSTRACT FROM AUTHOR]

In the background of exhaustion of the traditional fossil energy sources and environmental deterioration, developing renewable energy has become a strategic choice for countries to achieve energy sustainable utilization and carbon neutrality target. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. However, the commonly used weight calculation methods in the existing renewable energy evaluation have obvious shortcomings, such as the randomness of the subjective method is strong and the gap in the weight allocation of the objective method is too large, which affect the reliability and accuracy of the sorting result. In this paper, a novel weight calculation method based on non-dominated sorting genetic algorithm (NSGA-II) is proposed, and is applied to renewable energy evaluation. The study in this paper focuses on methodology. Firstly, for the linear normalized and Zeros normalized evaluation data, the differences between renewable energy plans in the two normalized evaluation data are measured, and the ranking deviations of the two normalized data are calculated. Then, the multi-objective weight solving model is constructed in terms of plans differences minimization and ranking vectors deviations minimization. The NSGA-II algorithm is applied to the optimization of multi-objective functions to find the Pareto non-dominated solution, so as to determine the weight values of each evaluation index. Finally, the TOPSIS method is used to determine the relative closeness value of each plan, and the rankings of renewable energy technical plans are achieved. Based on the actual renewable energy development data of a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some popular renewable energy evaluation methods. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Apply non-dominated sorting genetic algorithm II to determine the index weights. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

It is increasing crucial to improve the sustainable use rate of energy and contribute to carbon neutrality and environmental footprints reduction. This work features cutting-edge selected extended papers and developments that were presented at the 25th Conference on Process Integration, Modelling and Optimization for Energy Saving and Pollution Reduction, held on 5–8 September 2022 in Bol, Croatia. More than 400 papers were accepted and presented at this conference. Out of these papers, the 45 contributions in this Virtual Special Issue represent a selection of the most cutting-edge developments in the topic of the Sustainable Use of Energy Contributes to Carbon Emissions Neutrality and Environmental footprint reduction. This paper provides a review of these contributions and above, and groups them into four research themes: (1) Energy Conversion, Storage, Recovery and Efficiency Improvement, (2) Energy Management, Planning and Optimization, (3) Energy, Environment and Economy, and (4) Heat Transfer, Heat Pumps and Heat Convection. [ABSTRACT FROM AUTHOR]

The current single energy storage approach and market incentives do not fully exploit the potential of diverse energy storage methods and market incentives. Additionally, the traditional operation method often results in a poor alignment between energy supply and demand. Moreover, the conventional solution algorithm struggles to address complex problem-solving involving multiple variables. To address these issues, this paper proposes an improved carbon-neutral energy system (ICNES). Firstly, ICNES enhances residual energy utilization by implementing dual-layer residual power and heat treatment. Secondly, to enhance the effectiveness of market incentives, ICNES incorporates an improved approach that combines a dual-layer carbon capture drive, step carbon penalty, carbon reward, and green certificate trading. Thirdly, to improve the supply–demand matching, ICNES introduces a dynamic hybrid operation approach (DFHL). Finally, the paper proposes a honey badger-pattern search algorithm (HB-PSA) to optimize the configuration of ICNES for the DFHL multivariate scenario. Results indicate that compared to conventional carbon-neutral energy systems, ICNES reduces annual operating costs by 6.686%, CO 2 emissions by 9.538%, primary energy consumption by 12.826%, and energy waste rate by 17.465%. Furthermore, HB-PSA increases the optimization rate from 48.693% to 53.88% of the local optimum. • Dual-layer residual electric and residual heat treatment system is proposed. • Dual-layer carbon treatment for carbon neutrality and carbon profitability. • Carbon markets and green certificate are used in carbon-neutral energy system. • Dynamic hybrid operation to improve the matching of supply and demand. • A honey badger-pattern search algorithm is proposed for solving. [ABSTRACT FROM AUTHOR]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

The proposed targets to achieve peak carbon before 2030 and carbon neutrality before 2060 would require China to accelerate the development of natural gas infrastructure. The forecasted future of natural gas consumption in China will not only help learn about the future usage of natural gas but also guide government departments to conduct more scientific planning and management of natural gas production and pipeline channels. Therefore, this paper fully considers the characteristics of natural gas consumption affected by seasonal factors and uses the 2018–2021 quarterly natural gas consumption time-series data to analyze whether natural gas consumption contains trends and seasonality. It is noticeable that seasons impact China's natural gas consumption, so the moving average method is applied to calculate the seasonal index. Based on this, China's natural gas consumption from 2022 to 2035 is forecasted. As results show, China's gas consumption will continue to grow over the next 14 years but at a slower rate. By 2035, it will double from the 2021 level, reaching 765.4 billion cubic meters, but the growth rate will drop to below 4%, entering a period of low growth. Finally, the paper illustrates current situation of natural gas development combined with rationalized suggestions for future natural gas production and energy security in China. • Natural gas consumption is influenced by seasonal factors. • A seasonal forecasting method is applied. • China's gas consumption will continue to grow by 2035. [ABSTRACT FROM AUTHOR]

The essence of industrial chain structure optimization is to strengthen the synergy and division ability among sectors. It is a crucial factor in reducing energy intensity and achieving carbon neutrality goals. This paper completed the China's non-competitive input-output table from 2000 to 2020, constructed industrial synergy and division index using structural path analysis method and examined its development trend. Combining with a two-way fixed effects model, we explored the influence of industrial synergy and division on energy intensity. The research found that China's industrial synergy and division development level shows an upward trend. The proportion of the low-layer industrial chain decreases, and the peak contribution rate moves to the high-layer industrial chain. Secondly, industrial synergy and division significantly reduces sectoral energy intensity, the results are robust after endogeneity test. Finally, heterogeneity analysis showed that industrial synergy and division can reduce the energy consumption intensity of all sectors, and it is more obvious for sectors with high energy dependence. This research can provide targeted policy suggestions for China to optimize its industrial structure. It also has a reference significance for other countries. • The impact of industrial synergy and division on energy intensity is explored. • This paper extracts China's non-competitive IO table from the global MRIO table. • SPA is applied to construct industrial synergy and division index. [ABSTRACT FROM AUTHOR]

As a developing region, South America's aviation industry has also developed rapidly, and its carbon emissions have a significant role in achieving carbon neutrality in the global aviation industry. However, the problem of carbon transfer caused by passenger flow on international routes has not been addressed, especially in South America. This paper uses the Modified Fuel Percentage Method (MFPM) method and the ICAO standard method to calculate the CO 2 emissions of international routes in South America, containing the emissions of each route and each airline. Then we calculate the carbon emissions transfer and carbon compensations generated from South American international routes. In addition, this paper reasonably predicts the carbon emission data from 2023 to 2027 under three different scenarios (L&2027&100%, M&2026&100%, and H&2027&90%). We find that the five countries receiving the most considerable amount of carbon compensation are Argentina, Brazil, Peru, Colombia, and Chile, which is different from the ranking in 2019–2021. In addition, frequently using old and low-efficient aircraft is also a fundamental reason for excessive carbon emissions. Therefore, this paper provides reliable data support and reasonable emission reduction suggestions for the carbon emission control of South America's aviation industry. • Calculated carbon transfers and offsets for South American international routes. • Argentina, Brazil, Peru, Colombia, and Chile are the five countries receiving the most considerable amount of carbon compensation. • The "H&2027&90%" scenario is optimal for South American aviation. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, energy conservation and carbon reduction in the heating industry have become the focus of attention. However, severe heat loss is currently occurring in the secondary heating system due to hydraulic imbalance, which is unable to supply heat according to users' needs. In view of this, a thermodynamic-hydraulic model of users' demand for heat and flow rate for the heating system is established. Then, a novel method to regulate hydraulic imbalance is proposed, with the dynamic heat demand satisfied by regulating the valve opening based on NSGA-II. The optimization results show that the comprehensive hydraulic imbalance coefficient has been reduced from 23.08 to less than 0.019, which means that almost 100% of users can get heat supplies corresponding to their needs, while the energy consumption is reduced by about 30%. Additionally, when there are 1000 population and iteration steps, good convergence and high speed are presented using this method. In summary, an on-demand optimized model of hydraulic balance for the secondary heating network is put forward, which provides powerful engineering support and guidance for intelligent heating construction. • This paper presents a method to regulate the hydraulic balance of network using NSGA-II according to the heat demand. • This paper combines the demand flow regulation of users with the resistance analysis of the heating network. • The hydraulic balance can be implemented greatly by using the hydraulic imbalance coefficient as the optimization goal. • The number of iteration steps in the algorithm has an effect on the optimization results. [ABSTRACT FROM AUTHOR]

Under the background of "carbon neutrality" and "carbon peak" concepts, China desires to develop a new power system based on renewable energy sources (RES), which will be the primary energy support in prospective China. Thus, it is imperative to improve the peak shaving capability of power system to address the problem of random fluctuation and intermittency of RES by developing various energy storage systems. An innovative approach to enhance the flexibility of the conventional thermal power unit (TPU) through the utilization of flywheel energy storage array (FESA) is presented, simulated, and evaluated in this paper. Using the relatively practical and specific model of TPU and FESA, modified frequency modulation and automatic generation control (AGC) instruction tracing operation scenario models are constructed. A comprehensive control strategy of FESA and a well-designed operation coordinated control method for TPU with FESA are proposed and applied. The simulation results are distinctively processed and evaluated by the methods in "two documents", aiming to assess the real-world operation performance of the model proposed in this paper. The comprehensive analysis of the indicators demonstrates that the FESA can improve the flexibility and economy of the units. This research may guide the usage of FESA to improve the operational flexibility of TPU. • Composition and Control Methods of the flywheel energy storage array are provided. • A coordinated control scheme for the thermal power unit with flywheel energy storage array is proposed. • Frequency modulation and AGC instruction tracking scenario models are constructed and simulated. • AGC regulation indicators are conducted and analyzed to evaluate the unit's performance. [ABSTRACT FROM AUTHOR]

Integrated energy system (IES) is considered as an effective means to improve efficiency and reduce carbon emissions. To further improve the efficiency and low-carbon benefits of IES, this paper proposes a novel low-carbon planning model for the electricity-gas-heat integrated energy system (EGHIES), in which a long-term, multi-stage planning approach is adopted for configuring energy production, conversion, storage equipment and transmission networks. This model mainly realizes the coupling and energy conversion of power, natural gas and heating systems through the combined heat and power (CHP). And the power-to-gas (P2G) model considering reaction heat is established and introduced into IES planning to deepen the coupling degree of the three subsystems, so as to improve the efficiency of P2G and the system. Considering it is difficult to effectively constrain carbon emissions with a fixed carbon trading price, this paper adopts a ladder-type carbon trading mechanism (LTCTM) to strengthen the effect on carbon emissions. To further improve the low-carbon benefits of IES, the carbon capture system (CCS) model installed in coal-fired generation (CG) and coal-fired boiler (CB) is established, and the CO 2 captured by CCS is supplied to P2G for gas production. Finally, the effectiveness of the proposed model is verified by simulation results. [Display omitted] • A long-term, multi-stage approach for the integrated energy system is proposed. • The energy production, conversion, storage equipment and networks are configured. • The power-to-gas model considering reaction heat is established. • The carbon emissions are constrained by the ladder-type carbon trading mechanism. • The low-carbon retrofit is considered in coal-fired equipment. [ABSTRACT FROM AUTHOR]

Carbon capture system (CCS) and power to gas (P2G), as key low-carbon technologies, have obtained the widespread attention. Thus, it is necessary to explore the operation pattern and benefits of CCS and P2G. This paper investigates their roles in the electric-thermal-carbon-natural gas integrated energy system (IES) and focuses on the multi-market participation and multi-energy management. IES participates in the electricity, carbon trading, and natural gas markets. In the electricity market, IES can provide two types of ancillary services: deep peak regulation and frequency regulation services. Then, owing to the small scale of the ancillary service market, the strategic behaviors of IES are discussed. A bi-level model is established to deal with the complex couplings in the peak regulation market. IES's strategic behavior in the frequency regulation market is depicted by the price quota curve. Next, a solution method based on the particle swarm optimization algorithm is proposed to deal with the nonconvexity of the lower-level model. Finally, case studies show that the strategic behavior modeling in this paper can increase the profits of the deep peak regulation and the frequency regulation services. When IES is equipped with CCS and P2G, the operation cost decreases by 16.6%. • The roles of CCS and P2G are investigated in the IES. • IES's ability to provide the ancillary services is considered in the operation model. • The strategic behaviors in the ancillary service markets are modeled. • A solution method based on PSO is designed for the proposed bi-level model. [ABSTRACT FROM AUTHOR]

Clarifying the relationship between new energy and economic growth is an essential prerequisite for achieving the goal of carbon peaking and carbon neutrality. This paper utilizes a combination of nonlinear analysis methods, including transfer entropy, Bai–Perron (BP) structure point breakpoint detection, and complex network theory, to examine the coupling relationship between China's new energy and economy across different stages and sectors. An analysis of the network's topological properties shows that a complex coupling driving relationship exists between the new energy industry and the other 11 economic sectors. In particular, the agricultural sector exerts a significant driving force on the new energy industry, with the most extended duration of influence. Besides, the IT and construction industries also play a driving role in the new energy industry, and the latter's impact is earlier than that of the IT industry. The empirical results can guide the government and makers to formulate long-term sustainable action plans for different economic sectors. • Transfer entropy, BP structure break point detection and complex network are used. • 33 net transfer entropy symbol mode complex networks are constructed. • The coupling relationship between China's new energy and economy is complicated. • The agriculture industry has a large driving force on new energy industry. [ABSTRACT FROM AUTHOR]

The exploration and promotion of new energy constitute a significant initiative for numerous countries in their pursuit of sustainable development and efforts to alleviate climate change. However, the influence of a multitude of uncertain factors on the evolutionary path of new energy is currently poorly studied. By establishing a dynamic evolution model for new energy under polymorphic uncertainty, this paper analyses the complex interaction between new energy, economic growth, and carbon trading over the period 2020–2060, using China as a case study. We employ numerical simulation and sensitivity analysis to investigate the evolutionary trajectories of the new energy system under various parameter value scenarios. We show that the evolutionary trajectories will undergo substantial fluctuations before 2030, subsequently stabilizing from 2030 onwards. The study highlights that an excessively rapid pace of new energy development is detrimental to new energy systems, whereas energy storage system deployment has the opposite effect. There exists a significant risk of the system collapsing as a result of slow new energy development, over-building energy storage facilities, or over-intervening in carbon trading. We also find that overdevelopment of energy storage system may have greater negative impacts on the economic system than underdevelopment. [Display omitted] • Dynamic evolution model of new energy under polymorphic uncertainty is constructed. • New energy production elasticity and energy ratio are innovatively constructed. • Excessive intervention in carbon market can lead to the collapse of new energy system. • Overdeveloped energy storage hinder the synergy of new energy and economic growth. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality goals, the heating process, which contributes to half of energy consumptions, is urgent to achieve electrification under the trend of growing renewable electricity. To replace fossil fuel-fired boilers, the high-temperature heat pump (HTHP) is preferable for industrial heating decarbonization. However, the high-temperature and large-scale challenges propose requirements for critical component development, including the shell-and-tube condenser. The design principle of enhanced structure, which is unique for high-temperature condensation and low-global warming potential (GWP) refrigerant characteristics, still needs to be improved. This paper conducted R1233zd(E) condensing experiments over horizontal tubes and modified the condensation Nusselt formulas based on different structures. The modified models are applied to predict high-temperature film condensation performance. 2D tube with ε = 1.0 (the ration of rib height and pitch) yields the best heat transfer performance among the ε structures of 0.6–1.2. The 3D structure with ε = 1.0 design yields better enhancement performance under condensation temperature lower than 100 °C; when the condensation temperature is over 100 °C, the 2D tube of ε = 1.0 shows similar heat transfer coefficients (HTCs). Characteristics analysis of high-temperature condensation are conducted to prove the optimal rib structure. Due to surface tension decay, gravity gradually dominates as the main driving force for condensate film flowing above 100 °C saturation temperature, resulting in the limited effect of 3D structures. Further, 2D tubes with different rib pitches and heights are analyzed from flooding ratio and effective area enhancement, proving ε = 1.0 and 1 mm rib pitch as the preferable structure for R1233zd(E) high-temperature condensation. • Film condensation Nusselt formulas of R1233zd(E) are modified based on experiments. • Characteristics of high-temperature condensation (100–140 °C) are analyzed in theory. • Gravity gradually dominates as the main driving force above 100 °C. • 2D tubes with ε = 1.0 performs better than 3D tubes for high-temperature condensation. [ABSTRACT FROM AUTHOR]

Hydropower is the dominant renewable energy source, which can significantly reduce carbon dioxide emissions while providing electric energy. It is a crucial way to achieve the dual-carbon goal of carbon peak and carbon neutrality. However, climate change inevitably threatens hydropower, either directly or indirectly. Global climate models (GCMs) and hydrological models (HMs) under different representative concentration pathways (RCPs) have been combined to investigate future hydropower generation responses to climate change. The contribution of multiple uncertainty sources to multi-scale hydropower generation uncertainties with hydrological variations remains unclear. Therefore, to address the above challenge, a three-step framework was proposed in this paper: (1) predicting future inflows to reservoirs using three HMs (HBV, SWAT and XAJ) with different structures driven by six GCMs (BNU-ESM, GFDL-ESM2G, GFDL-ESM2M, CanESM2, MIROC-ESM-CHEM and CSIRO-MK3-6-0) under three RCPs (i.e., RCP2.6, RCP4.5 and RCP8.5); (2) diagnosing future hydrological conditions using the Comprehensive Differential Split-sample Test; (3) predicting future hydropower generation of cascade reservoirs by developing a cascade hydropower generation model and dynamically quantifying the contribution of multiple uncertainty sources to multi-scale hydropower generation uncertainties with hydrological conditions based on the variance decomposition method through subsampling. The results indicate that GCMs, HMs, climate emission scenarios and their interactions significantly impacted the uncertainty of hydropower generation with hydrological variations. In the flood season, the relative contributions of GCMs and HMs were the largest, accounting for about 40 %. The interaction effects of multiple uncertainty sources gradually increased before, after and during the non-flood season, with its relative contribution accounting for about 36 %. These findings can facilitate the active response to the new challenges of strategic hydropower energy development under climate change, reducing the losses caused by climate change. • We assess the potential effect of RCPs and GCMs on multiscale hydropower generation uncertainty in the UYRB from a new angle. • The contribution of multiple uncertainty sources to multiscale hydropower generation uncertainty is dynamically quantified. • Climate and hydrological models, emission scenarios and their interactions greatly impact hydropower generation uncertainty. • Interaction effects of multiple uncertainty sources on the uncertainty increase before, after and during the non-flood season. [ABSTRACT FROM AUTHOR]

Electricity market-oriented reform and carbon emissions trading, as the main policies implemented in China's power sector, have a profound impact on China's green and low-carbon transition by promoting resource allocation efficiency and internalizing external environmental costs, respectively. Therefore, this paper constructed a dynamic recursive CGE model to measure the energy, economic, and environmental impacts of carbon emissions trading and electricity market-oriented reform from electricity market structure and pricing mechanism. The results show that the two policies have a synergistic effect on industrial structure optimization, energy consumption structure optimization, and carbon emission reduction. Specifically, the share of value-added of the tertiary sector, the growth rate of coal consumption, the share of thermal power consumption, and carbon emissions in 2030 are reduced by 5.70 %, 18.29 %, 2.55 %, and 2.838 trillion tons, respectively, compared with the scenario without carbon emissions trading and electricity market-oriented reform. However, imperfectly competitive market structures outperform perfectly competitive market structures in energy consumption structure and carbon emission reduction. Electricity price regulation is also more beneficial to GDP growth and increase in residential disposable income compared to price liberalization. To this end, returning emission trading scheme revenues to residents can effectively mitigate the adverse impacts caused by market-oriented reforms. • EMR is involved in market structure, pricing mechanisms, and market regulation. • EMR and CET have a synergistic effect on carbon reduction. • Energy consumption structure is better in imperfectly competitive market. • Electricity price regulation is more beneficial to GDP growth. • Returning ETS revenue to residents increases per capita disposable income. [ABSTRACT FROM AUTHOR]

The solar chimney power plant (SCPP) provides the approach to achieving carbon neutrality goals. The power generation of the system decreases drastically due to the ambient crosswinds (ACWs). In this paper, three wind resistant structures, including blockage wall, radial partition wall (RPW), and porous wall are adopted to weaken the effects of the ACWs. In addition, the flow characteristics and power generation performance of each system are investigated in the first consideration of the 3D turbine by developing a numerical model. The results reveal that the negative effects caused by the ACWs on the system are attenuated by integrating the three structures. The adverse effect of weak winds on the SCPP is greatly weakened by integrating a blockage wall, but is not significant for robust winds. For SCPP with RPWs, the velocity is slightly increased due to the improved collector flow path by the RPWs at ACW = 0 m/s. The maximum power generation is 93.68 kW, an increase of 1.22 times over the SCPP. The uneven forces on the turbine blades due to the ACWs can be mitigated by integrating porous wall, enhancing turbine stability. In addition, the fluctuation of the power generation is less than 30 % under ACWs. • The performance of the SCPP is studied in open space. • Three structures are adopted to weaken the negative effects of the ACWs. • The effect of ACWs on the SCPP is weakened by integrating a blockage wall. • The maximum power generation increased by 22 % by integrating RPWs. • The fluctuation of the power generation is less than 30 % due to a porous wall. [ABSTRACT FROM AUTHOR]

The widespread use of fossil fuels has substantially contributed to global climate change. One of the most crucial ways to address climate change is to minimize carbon emissions in the energy sector. Power-to-Gas (P2G) technology provides a potential solution. In this context, this paper introduces a novel two-stage P2G planning method for the electric-gas coupling system, using carbon emission flow technology. The carbon emission flow model employed facilitates the distribution of carbon emissions across the entire energy network. Central to our planning strategy is the identification of nodes with reduced carbon emissions for the siting of P2G facilities, predicated on the premise that such nodes are indicative of significant renewable energy utilization. Constructing P2G systems at these particular nodes is strategically advantageous for augmenting renewable energy consumption. In the initial phase, a P2G siting planning methodology predicated on a low-carbon criterion is advanced, resulting in a definitive siting scheme. Subsequently, the second phase involves establishing a P2G capacity optimization model that seeks to strike an economic equilibrium between the utilization of surplus wind power and P2G operational investment. An enhanced pigeon optimization algorithm is employed to resolve the proposed model. Our method is verified by simulation. Compared with other conventional models, the accommodation capacity of renewable energy with the proposed method is enhanced, and the carbon emissions and operating costs of IES are also reduced. • This study introduces a new P2G station siting method centered on the carbon flow model. • The research establishes a P2G capacity planning model focused on cost-effectiveness optimization. • The novel P2G planning model addresses the economic balance between investment costs and the level of new energy absorption. • P2G two-stage planning strategy reduces the operating cost of the system and improves the low carbon of the system. [ABSTRACT FROM AUTHOR]

Coal production and consumption cause methane and carbon dioxide emissions. The high emission cost and the limited renewable energy in some areas restrict the low-carbon energy system development. This paper proposes a double recovery system based on a multi-energy system to promote energy efficiency and emission reduction, considering the life cycle carbon emissions of coal and carbon trading. A nonlinear multi-objective two-stage stochastic programming model and an approximate solution algorithm based on NSGA-II are built to find the economic-ecological balanced strategy for the system investment and operation under uncertainty. Finally, a case study about the collieries in Xianyang City is adopted to test the effectiveness of the proposed model and algorithm. The results show the multi-energy system with a double recovery system can obtain 5%–40% more profits compared with the single energy system when the GHG emission rate requirement is lower than 0.95kgCO 2 e/kwh. And this paper finds that carbon capture and storage has more universal utility in obtaining tradable green certificates, and the efficiency of P2G technology depends on the abundance of renewable energy. The tradable green certificates are effective incentives for coal mine methane utilization. • A multi-energy system with the double recovery of methane and CO 2 is built. • The carbon trading mechanism combining TGC under uncertain conditions is considered. • A multi-objective two-stage stochastic programming with interval variables is built. • An approximate solution algorithm based on NSGA-II is proposed for solution efficiency. • A case study proves the effectiveness of the DRMC-MEPS on profit-emission balance. [ABSTRACT FROM AUTHOR]

In the context of global warming and energy scarcity, regional integrated energy system (RIES) can effectively improve energy utilization efficiency and reduce carbon emissions. However, this leads to the increased complexity of the market transactions. To this end, based on the mixed game strategy, a multi-agent low-carbon optimal dispatch model of RIES is proposed in this paper. Firstly, to fully consider the low-carbon objective of the system, a reward and punishment ladder carbon trading mechanism and a ladder integrated demand response (IDR) model are developed. Then, the decision models of the energy management operator (EMO), multiple energy hub agents (EHAs) and the user load aggregator (ULA) are constructed respectively with the goal of economy, and carbon emission flows are introduced as constraints. The interactive trading process of various stakeholders is simulated by a mixed game with master-slave game nested bidding strategy. Finally, the economics and carbon emissions of the system in different scenarios are analyzed by examples, and the effectiveness of the proposed model is verified. Numerical simulation results show that the proposed method not only has good economic and low-carbon environmental protection benefits, but also ensures the interests of various stakeholders. • A multi-agent energy trading mechanism is proposed to realize low-carbon operation. • A ladder integrated demand respond model considering carbon compensation is developed. • A multi-agent optimization strategy based on mixed game is proposed. [ABSTRACT FROM AUTHOR]

This paper develops a robust and sustainable energy management framework to model a multi-vectored energy hub (MVEH) system. A max-min-based static robust optimization model is developed to counter the uncertainties. Furthermore, a flexible energy demand management program, battery electric vehicles (BEVs), and compressed air battery storage (CABS) are integrated to enhance MVEH's flexibility. Hybrid power-to-X units (electrolyser, methanization reactor and fuel cells) are modelled to reduce green energy spillage and improve operational independence, including heat pumps. Moreover, the emission (carbon cap and trade) market along with carbon capture storage and utilization units (CCS–U), are incorporated to establish a low-emission multi-energy model. Simulation results demonstrate that with flexible resources and power-to-X units, MVEH reduces the operating energy cost by 46.4 % and improves the system independence by 19.06 %. Besides, CCS-U units produce 92 % less emission while increasing the energy cost by 5.1 %. However, MVEH gains the right to sell carbon credits under the emission market. Thus, the multi-vectored system's economical, reliable, and environmental viability are ensured. Finally, sensitivity analysis proves the robustness of the proposed framework against natural gas and carbon price fluctuations. • Robust energy management for multi-vectored energy hubs is proposed. • A max-min uncertainty budget based robust stochastic algorithm is applied. • To reduce green energy spillage, power-to-gas and electric vehicles are modelled. • To model low emission hub, carbon capture units are integrated. • Further, emission markets are developed to make hubs economically viable. [ABSTRACT FROM AUTHOR]

This paper takes 30 provinces in China as the research subjects and constructs a real options model to explore the impact of carbon emissions trading market, energy storage subsidies, and their synergy on the optimal investment decision of household PV-ESS projects. The results show that a single factor has a catalytic effect on project investment, and both together have a better effect. And, project investment benefits are better in areas with abundant light resources and higher than average electricity prices. In addition, a sensitivity analysis is conducted on the initial investment cost, CO 2 price, and energy storage subsidies. The results show that immediate investment in all provincial projects can be achieved when the initial investment cost is reduced by 50%, or the CO 2 price is increased by about 33 times, indicating that the current environment is insufficient to attract investors. The results provide a reference framework for investment in household PV-ESS projects. • Use real options methods to assess investment decisions for household PV-ESS projects. • Explore the role of carbon trading market and energy storage subsidies on investment. • Research the impact of different regional power grids on investment value. [ABSTRACT FROM AUTHOR]

Under the context of carbon peak and carbon neutrality, new energy vehicle (NEV) is considered as ultimate objective in development of automotive industry. To facilitate sustainable growth of automotive market and ensure a smooth transition for fuel vehicle (FV) enterprises, this paper constructs a tripartite evolutionary game model based on tripartite Hoteling model, which involving NEV enterprises, FV enterprises and governments. The herd effect and time-delay effect are considered to improve the tripartite evolutionary game. Results indicate that: (1) Fund feedback to NEV enterprises will counterintuitively decrease probability of active assistance from NEV enterprises. (2) Governments' willingness for strict involvement positively correlates with supervision costs but negatively correlates with additional benefits. (3) Time delay in funds leads to weak effect of high default penalties in promoting active assistance of NEV enterprises in early stage, but opposite situation appears in later stage. (4) Higher NEV production proportion counterintuitively stimulates FV enterprises to give up transition. (5) High rewards drive diffusion of herd effect, further increasing competition among vehicle enterprises leading to FV enterprises giving up transition. (6) Herd effect and time-delay effect increase dependence of FV enterprises on funds results in higher sensitivity of credit trading price compared to credit ratio requirement. [Display omitted] • Consider transition of FV enterprises to a tripartite evolutionary game model. • A tripartite evolutionary game model is integrated with tripartite Hoteling model. • Consider adaptive punishments for FV enterprises during the transition process. • Check impacts of two players on strategy choice of a third player at the same time. • Consider the herd effect and time-delay effect to improve the evolutionary game. [ABSTRACT FROM AUTHOR]

An efficient and reliable multi-microgrid energy mutual aid strategy helps to improve energy utilization efficiency. This paper proposes a two-layer game electrothermal energy sharing strategy for a regional integrated multi-microgrid. First, a distribution network operator (DNO) and an integrated energy microgrid cluster (IEMC) are established. The two-layer game model of DNO and IEMC nests the cooperative game within the horizontal IEMC in the vertical master-slave game between DNO and IEMC. Then, for the integrated energy micro-grid (Integrated energy micro-grid, IEM), a coupled operation framework of cogeneration-power-to-gas-carbon capture is established, combined with a ladder carbon trading mechanism to reduce system carbon emissions, and the IEM is described with opportunity constraints—the uncertainty of new energy output. Secondly, aiming at the game fraud phenomenon in the IEMC internal cooperation game, an intermediary transaction mode is proposed to achieve the fraud equilibrium of each IEM and ensure effective energy cooperation. Finally, the dichotomy method is used to solve the master-slave game between DNO and IEMC, and the alternating direction multiplier method is used to solve the cooperative game within IEMC, which realizes the coordinated operation of DNO and IEMC and the fair energy transaction and benefit distribution between IEMC. © 2017 Elsevier Inc. All rights reserved. • A regional comprehensive energy-based multi-microgrid power and heat trading strategy based on a two-layer game is proposed. • The horizontal multi-IEM cooperative game between IEMC is nested in the vertical master-slave game between DNO and IEMC. • Aiming at the problem of game fraud in IEM cooperation, a transaction model of fraud negotiation between micro-networks is proposed. • Construct a CHP-P2G-CCS coupled operation framework and combine it with the carbon trading mechanism to reduce carbon emissions. • The dichotomy method is used in combination with ADMM to improve the solution efficiency and protect the privacy of all parties. [ABSTRACT FROM AUTHOR]

While the US electric power sector transitioning towards a low-carbon system, the escalated adoption of renewable energy has paradoxically increased water consumption. Consequently, it is imperative to engineer a power generation matrix that mitigates CO 2 emissions and minimizes water utilization. The primary endeavor should be to meticulously identify the variables affecting water consumption changes, especially highlighting and addressing the inherent tension between water conservation and carbon reduction. Employing temporal and spatial Logarithmic Mean Divisia Index methodologies, this study meticulously investigated the factors driving water consumption changes across state-level electricity production sectors in the US from 2010 to 2018. The analysis revealed that the generation mix structure was a predominant factor in escalating water consumption, exerting a more substantial influence than total power generation. Moreover, while the water consumption coefficient initially mitigates the impact of other factors, its effectiveness diminishes over time. Utilizing spatial Logarithmic Mean Divisia Index techniques, this paper further delineated state-level disparities, illuminating the heterogeneous nature of water consumption across regions. Projections up to 2050 suggest that water consumption reductions could be realized even amidst a highly intense scenario. The study's robustness and reliability were further augmented by employing an adaptive Logarithmic Mean Divisia Index. • Temporal-spatial LMDI reveals significant shifts in the US power sector water consumption. • Water consumption coefficient, fuel structure, and generation identified as key drivers. • Scenario analysis forecasts significant water savings potential by 2050. • Findings highlight the necessity for integrated water-energy transition policies. • Study proposes targeted strategies for a sustainable energy-water nexus. [ABSTRACT FROM AUTHOR]

Carbon Capture, Utilization, and Storage (CCUS) is an indispensable technology to achieve carbon neutrality in China, but confined by technology and economy, the offshore CCUS in China is still in the planning stage and has not yet reached the desired scale. Offshore source-sink matching and cost analysis of CCUS is the premise and basis of offshore CCUS deployment. Thus, based on the CO 2 storage potential of offshore sedimentary basins in China, this paper conducts the offshore source-sink matching and cost analysis of CCUS in China under different constraints. The result showed that: ⅰ) the CO 2 storage capacity of China's offshore sedimentary basins is estimated to be 767.3 Gt, which is enough to meet approximately 200 years of coal power CO 2 emissions in China. ⅱ) the CO 2 storage potential could reach 721.9 Mt/a by source-sink matching under different constraints. ⅲ) early opportunities for offshore CCUS would be in the Bohai Bay and Pearl River Mouth Basin, considering the compensation effect of CO 2 -EOR. ⅳ) combined with the CCUS cost and emission reduction in China under different time nodes, it is inferred that deploying offshore CCUS in China between 2030 and 2040 commercially will be advantageous. • The CO 2 storage potential in China's offshore sedimentary basin was evaluated. • The cost of offshore CCUS was analyzed under different technology combinations. • Bohai Bay and Pearl River Mouth Basin would be early opportunities for offshore CCUS. • 2030–2040 would be the favorable time to deploy the large-scale offshore CCUS. [ABSTRACT FROM AUTHOR]

Carbon neutrality has become a global consensus for green development, and solar photovoltaic power generation has increasingly become one of the key technologies for carbon reduction. Large-scale photovoltaic power plants are often built in arid and sandy areas, which carry a large number of dust particles in the air. Dust deposition on photovoltaic modules has a significant impact on the transmittance, temperature, and roughness of photovoltaic modules, reducing their power generation efficiency and service life. The paper has the following structure: i) relevant research all over the world; ii) the mechanism of dust deposition and the influencing factors on photovoltaic modules; and, iii) some current methods of cleaning are summarized, and the mechanism of self-cleaning coatings for dust deposition prevention. It is found that the process of dust deposition is accomplished dynamically and repeatedly under the joint action of several forces. And the diameter of the particle, the installation angle of photovoltaic modules and wind speed have a great influence on the behavior of dust deposition. Self-cleaning coatings have an obvious effect on the prevention of dust deposition. The paper also looks forward to future research methods of particle deposition and cleaning on photovoltaic modules. • The characteristics and the influencing factors of dust deposition are improved. • The mechanism of dust behaviors on photovoltaic modules has been perfected. • The methods for dust removal are studied and integrated. • The mechanism and effect of self-cleaning coatings are studied and integrated. [ABSTRACT FROM AUTHOR]

Public low-carbon travel is of great significance for achieving carbon neutrality and mitigating climate change. Therefore, taking the Chinese public as the research object, this paper discusses the impact of public awareness of climate policy on low-carbon travel. First, based on stimulus-organism response (SOR) theory, this paper constructs a theoretical model to study the impact of public perception of climate policy on low-carbon travel. Then, environmental emotion is used as a mediating variable in the model. Finally, 419 respondents were selected for a questionnaire survey to collect data. It is found that public awareness of climate policy affects low-carbon travel by triggering environmental emotions. Positive environmental emotions have a significant positive impact on low-carbon travel, while negative environmental emotions have a significant negative impact on low-carbon travel. In addition, positive environmental emotions have a greater impact on low-carbon travel than negative environmental emotions. Based on the above conclusions, this paper puts forward the following specific suggestions: in-depth publicity of climate policy, cultivation of positive environmental sentiment, strengthening the public's responsibility to respond to climate change concerns, etc. • The effect of climate policy cognition on low-carbon travel is explored. • Offers solutions by identifying the mediating role of environmental emotion. • Positive environmental emotion is more influential than negative environmental emotion on low-carbon travel. [ABSTRACT FROM AUTHOR]

This paper identifies the energy system benefits of transitioning district heating infrastructure from current 3rd generation district heating (3GDH) to 4th generation district heating (4GDH) with lower grid temperatures and more integration with other energy sectors. Previous papers have investigated the effect of going from 3GDH to 4GDH on a local perspective. In this paper it is investigated how this transition affects the energy system on a national level, where both the costs and energy effects are evaluated based on national hourly energy systems simulations including all energy sectors in a climate neutral energy system scenario. Moreover, the paper identifies the effects of different cooling solutions in datacentres. The analyses include effects on heat sources as well as the effect on the cost and losses in the district heating grid. This is done for the case of Denmark. In the case of Denmark, it is found that transitioning from 3GDH to 4GDH decreases the system cost by 220 M EUR/year, corresponding to 7 M EUR/TWh delivered heat at the end-user. Increasing the temperature outlet of datacentre waste heat has a value for the system as high as 52–59 M EUR/year, corresponding to 1.7–1.9 M EUR/TWh delivered heating at the end-user. • Evaluates the national energy system effects of 4th generation district heating. • The paper also evaluates the effects of different cooling solutions in datacentres. • The evaluation is done using a carbon neutral scenario for Denmark. • Going to 4th generation district heating reduces the system cost by 220 M EUR/year. • Higher temperature of waste heat from datacentres reduces the energy system cost. [ABSTRACT FROM AUTHOR]

As the massive carbon emissions from the power system, the shift of the power system to low-carbon becomes inevitable. In this context, this paper proposes a Stackelberg game approach to develop the operational strategy of energy hubs, which considers the reward and punishment ladder carbon trading mechanism and the coupling of electrothermal demand. To avoid the fixed carbon price in the past and the neglect of the incentive space for carbon trading, a ladder carbon trading mechanism of rewards and punishments is introduced to effectively depict carbon trading costs. The electrothermal coupling of the demand side is incorporated into the Stackelberg game model, and the flexible consumption model of users participating in the integrated demand response is established. The above model is solved by combining heuristic algorithm with solver CPLEX, which can solve the data privacy leakage problem of both parties. Simulation results show that the strategy can bring economic benefits to energy hub operators and users. Carbon emissions across the system were reduced by 14.4 %. Users with electric heating equipment can fully improve the electric load and heat load adjustment level, and improve their economic benefits by 2.4 % at the cost of a 3.2 % increase in carbon emissions. • Consider influence of demand-side electrothermal coupling on carbon emission. • Reward-punishment ladder carbon trading increases economic benefits by 16 %. • Using energy flexibly increases benefits by 2.4 % and carbon emissions by 3.2 %. • The proposed game model is more appropriate for future energy pricing strategies. • The solution method can better protect the data privacy of both parties. [ABSTRACT FROM AUTHOR]

Biomass pyrolysis is a promising method to produce renewable energy, which can contribute to the realization of carbon neutrality. However, high oxygen content and complex composition hinder the utilization of bio-oil produced by biomass pyrolysis. A new technology, two-step fast pyrolysis of torrefied biomass derived from corncobs and waste cooking oil under CO 2 atmosphere, was studied to produce hydrocarbons-rich bio-oil. Results showed that two-step pyrolysis was beneficial to the initial separation of hydrocarbons and oxygen-laden compounds. And the synergy between the torrefied corncobs and waste cooking oil occurred primarily in the second step of the two-step pyrolysis. Application of CO 2 in the first step significantly decreased the total peak area of condensable organic compounds, but increased the relative content of hydrocarbons. No matter what atmosphere was used in the first step, the relative content of hydrocarbons during the application of CO 2 in the second step was lower. Using a CO 2 atmosphere in the first step gave better results, while using N 2 in the second step tended to maximize the hydrocarbons content. Combined with CO 2 -assisted pyrolysis and stepwise pyrolysis, this paper provides a new idea for the thermal conversion of corncobs and waste cooking oil, to produce hydrocarbons. [Display omitted] • Two-step pyrolysis is conducive to hydrocarbon and oxygen-laden compound separation. • Synergy between torrefied corncobs and waste cooking oil occurred in second step. • CO 2 is suitable for the application in first step. • Relative content of hydrocarbons decreased with the use of CO 2 in second stage. • Two-step pyrolysis coupled with CO 2 atmosphere is better for hydrocarbon production. [ABSTRACT FROM AUTHOR]

With the development of low-carbon energy, the use of thermal and hydropower units for regulation in the power system dominated by new energy (PSDNE) is decreasing. Electric buses (EBs) are expected to become the primary dispatching objects in this context. Accurately evaluation EB's response capability (RC) is vital for the scheduling operation of the PSDNE. However, current evaluation methods for EB's RC are relatively crude, lacking detailed and quantifiable measures. This paper proposes a novel multi-dimensional evaluation method to provide the aforementioned RCs. The EB operational schedule revise model considering traffic and temperature is proposed to obtain more accurate EB charging load by revise arrival charging time and remaining battery energy. The proposed EB charging model considering carbon emissions contributes to revealing the impact of various charging modes, such as low-carbon and electricity price, on the Eb's RC. The EB multi-dimensional evaluation model is established to obtain quantified and detailed RCs to support the operation of NEDPS. These capabilities include fast response within various periods, sustained response over extended durations, and remaining RC after executing scheduling instructions. Finally, using the actual data from an EB station of a city in China, the effectiveness of the proposed evaluation model is verified. [Display omitted] • The impact mechanisms of traffic and temperature on the EB's RC are revealed. • The accuracy of the revised EB's operating schedule is greatly enhanced. • The impact mechanisms of carbon emissions reduction on the EB's RC are revealed. • The EB's RC under different charging modes is quantitatively evaluated. • The fast RC, sustained RC, and remaining RC of the EB are quantitatively evaluated. [ABSTRACT FROM AUTHOR]

Aviation carbon emissions are growing as the volume of aviation traffic continues to increase, both exacerbating global greenhouse gas emissions and increasing the resistance to green aviation development. To effectively promote aviation carbon abatement, this paper, based on the hybrid mechanism composed of carbon trading and taxation, a tripartite Itô stochastic evolutionary game model is first constructed. The complex game interactions among the administration, major airlines, and minor airlines are analyzed. Second, we use Gaussian white noise as the ambient uncertainty and apply stochastic Taylor expansion to find the numerical approximation solution. Finally, through numerical simulations, the decision-making behavior of stakeholders and their sensitivity to key influencing factors are illustrated. The study shows that different variables have differential effects on stakeholders' strategic choices in terms of convergence speed, change speed, and stability. Starting from three different regulatory paths, this study provides insights into the priority and direction of adjusting relevant variables, thereby offering guidance for policymakers and managers in effectively regulating aviation carbon abatement. [Display omitted] • A hybrid mechanism of carbon tax and carbon trading is designed. • Carbon abatement in aviation is studied using stochastic evolutionary games. • Simulations analyzed the sensitivity of stakeholders to key influencing factors. • Insights are given from three different regulatory paths. [ABSTRACT FROM AUTHOR]

Production of renewable C1 transport biofuels (such as biomethane and biomethanol) through the integration of anaerobic digestion (AD) with carbon capture, utilization and sequestration technologies may offer a solution to reduce greenhouse gas (GHG) emissions. This paper presented a detailed techno-economic and environmental assessment of four cases for biomethane or biomethanol production by incorporating AD, CO 2 utilization via biomethanation (CU), solid digestate pyrolysis (Py) and methanol synthesis (MeOH). The results reflected the current state of technologies and potential future scenarios within a mature market. Under optimistic scenarios (scaled-up systems and reduced hydrogen price of 1 €/kg), the minimum potential GHG abatement cost for the AD-Py-CU case was −111.1 €/t CO 2-eq when biomethane was sold at 1.03 €/Nm3 (a contract gas price in 2022), while the abatement cost rose to −58.2 €/t CO 2-eq when H 2 was purchased at 3.40 €/kg. When methanol was sold at 425 €/t (global weighted average value), the marginal abatement cost for the AD-Py-CU-MeOH (with H 2 at 1.0 €/kg) case was 136.5 €/t CO 2-eq , which is higher than current carbon credits at 33.5 €/t CO 2. This study suggests that biomethane produced by incorporating AD, CO 2 biomethanation and pyrolysis technologies may be economically and environmentally competitive over natural gas. [Display omitted] • Minimum selling prices of 0.50 €/Nm3 CH 4 were modelled with H 2 purchase of 1.0 €/kg. • Minimum selling prices of 661 €/t MeOH were modelled in the optimistic scenario. • The minimum marginal abatement cost for the CH 4 system was −114 €/t CO 2. • With H 2 purchase of 3.40 €/kg the marginal abatement cost of CH 4 rose to –62 €/t CO 2. • The marginal abatement cost of biomethanol is higher than proposed carbon credits. [ABSTRACT FROM AUTHOR]

China has set a goal of carbon neutrality by 2060 and is determined to increase wind and solar power to 1200 GW by 2030, even though it already has the world's largest installed capacity of renewables. However, the lack of flexibility in the power system will limit the development of a higher proportion of renewable energy. This paper evaluates the applicability of different types of flexible power sources in China for the first time. Above all, it describes the current situation of China's power industry and the necessity of increasing flexible power sources, establishes an evaluation system from the perspectives of benefit, opportunity, cost & risk, then determines 19 evaluation criteria. The BOCR-ANP-TOPSIS method was used to evaluate the system, where the ANP method determines the weights and the TOPSIS method ranks the alternatives. The result shows that pumped storage hydropower has the highest overall ranking, followed by the flexibility transformation of coal-fired power. Coupled with sensitivity and comparative analysis, valuable findings that will help future energy policymakers are reported. • Evaluating the applicability of different flexible power sources in China for the first time. • The identification of criteria for the selection of flexible power sources was given. • Making recommendations for China's flexible power source development policy. • The BOCR-ANP-TOPSIS method adopted can be extended to select flexible power sources in different regions meticulously. [ABSTRACT FROM AUTHOR]

In accordance with the Paris Agreement, many nations have set out a global framework to stabilise and prevent greenhouse gas (GHG) emissions to mitigate climate change. This study reviewed the literature on the GHG protection and control (GHGPC) impacts of overburden fractures in relation to coal mining. Different factors, such as geological conditions, mining conditions, and gas extraction methods, were compared because they influence GHGPC. Carbon emissions, coal mining safety, and environmental protection are crucial parameters. GHGPC can (1) improve the safety and efficiency of mining, (2) reduce GHG emissions, and (3) generate clean gas resources. During mining, cracks appear in overburden strata, causing GHG emissions. Various techniques, including scanning electron microscopy, nuclear magnetic resonance, two-dimensional and three-dimensional physical similarity simulations, permeability testing, and numerical simulations, have been adopted to determine the macroscopic and microscopic features of overburden fractures. Finally, the extraction method of GHG was optimised through field practice, namely, roadway, borehole, and pipe extraction, were analysed, and the comprehensive GHG extraction method was preferred to achieve superior management results. This paper reviewed studies that examine the development of fractures to elucidate the significance of GHGPC. Moreover, this article provides new insights into the achievement of the "dual carbon strategy" with particular reference to coal mining; it also summarises the holistic life cycle of gas management in terms of overburden activity, gas transport patterns, reservoir characteristics and typical technologies. It also summarises the holistic life span of GHGPC management in terms of overburden activity, GHG transport patterns, reservoir characteristics, and typical technologies. Finally, the authors discuss and conclude the article with proposed methods for future research directions. • The role of GHGPC in carbon neutrality was talked about from various aspects. • Technologies for GHG transport, extraction, and utilisation were elaborated. • GHG extraction technologies in coal mining were introduced. • New energy supply and the dual carbon strategy in coal mining were described. [ABSTRACT FROM AUTHOR]

Transferring energy-intensive industries to regions with abundant clean energy is crucial for achieving low-carbon transformation of energy-intensive sectors during carbon neutrality. By manually collecting the project data from energy-intensive enterprises in China, we construct a three-dimensional panel data with 1.86 million observations to empirically examines the impact of the carbon intensity constraint policy (CICP) on the transfer of high energy-intensive projects (HEP). Our findings indicate that the CICP accelerates the transfer of HEP. The transfer direction shows that the HEP transferred from the eastern region to the western region have increased, but the HEP transferred from the western region to the eastern region have not decreased. To explain the above phenomena, we further discuss the underlying mechanism from the perspective of energy structure and industrial agglomeration. From the standpoint of transfer-out regions, the higher the proportion of thermal power in the energy consumption structure, the more HEP will be transferred out. From the standpoint of transfer-in regions, the industrial agglomeration will attract the transfer of the HEP. However, we do not find evidence that wind power and photovoltaics can attract the HEP. This paper provides project-level empirical evidence for promoting the low-carbon transformation of energy-intensive industries. • The carbon intensity constraint accelerates the transfer of energy-intensive projects. • The dynamic effect shows a fluctuating and decreasing trend. • The transfer direction is the net transfer from the east to the west. • The more thermal power, the more energy-intensive projects will be transferred out. • We don't find the attraction of the clean energy for the energy-intensive projects. [ABSTRACT FROM AUTHOR]

Balancing the ecological and economic benefits of energy consumption is an essential requirement and a key part of achieving the task of high-quality economic development and the goal of carbon neutrality. This paper analyses the energy efficiency and spatial and temporal evolution characteristics of thirty Chinese provinces and cities from 2006 to 2019 based on the DSBM model. The results show that, firstly, environmental factors have a significant impact on the evaluation of energy efficiency, with the national energy efficiency showing phase fluctuations and a decreasing trend from the east to the center and then to the west during the sample period. Secondly, the country and the three major regions did not show a σ convergence. Thirdly, there is significant absolute and conditional convergence in overall energy efficiency after considering spatial spillover effects, and with a turning point. Fourthly, energy efficiency in the three major regions also shows a clubbing phenomenon, with different regions tending to their own steady state of energy efficiency. Finally, we put forward suggestions for improving energy efficiency. The results of the study help to understand the changing trends and influencing factors of inter-regional energy efficiency in China, which can provide a reference for achieving the transformation of energy structure and has important practical significance. [Display omitted] • The DSBM model to evaluate energy efficiency relaxes the assumptions of DEA models. • The DSBM model includes environmental and relaxation variables in EE assessment. • The spatio-temporal characteristic of EE is analyzed from multifaceted perspectives. • We analyze the club characteristic and key turning points of EE convergence in China. [ABSTRACT FROM AUTHOR]

The decoupling of CO 2 emissions from power generation is of great significance for China to accomplish the commitments of carbon peak and carbon neutral. However, the related studies in China's power sector are still limited. This paper aims to explore the decoupling relationship between CO 2 emissions and power generation of China's power sector as well as the driving factors of decoupling index at provincial level using Tapio model and LMDI method. The decoupling analysis shows that Heilongjiang, Beijing, Shanghai, Sichuan and Yunnan achieved decoupling and most provinces were in expansive coupling states from 2000 to 2019. The number of provinces in decoupling state during 2011–2015 was twenty-three and larger than periods of 2000–2005, 2006–2010 and 2016–2019. The decomposition analysis indicates that per capita GDP and population size were responsible for inhibiting the decoupling process for most provinces, while thermal power generation efficiency and electricity intensity promoted the decoupling. Specifically, coal-to-gas of Beijing, renewable energy utilization of Gansu and expansion in nuclear energy of Hainan contributed more to their decoupling. Besides, this paper also explores the regional agglomeration of decoupling index across provinces based on global and local Moran's I Index, demonstrating that the spatial autocorrelation was significantly positive during 2016–2019. • The decoupling index between CO 2 emissions and power generation was estimated. • The driving factors of decoupling index were studied based on LMDI method. • The spatial autocorrelation of decoupling indexes across provinces was explored. • The per capita GDP was the major factor inhibiting the decoupling process. • The thermal power generation efficiency was responsible for promoting the decoupling. [ABSTRACT FROM AUTHOR]

The realization of carbon neutral goal is inseparable from the development of new energy industry, and scientific and effective policy support can accelerate the progress of the goal. In this paper, the policy driven ability of China's photovoltaic industry in the background of carbon neutral is evaluated. Firstly, the evaluation system is established by the improved diamond model. Then, the policy evaluation standard is formulated according to the Interval Type-2 Fuzzy sets (IT2FS). Finally, the weight of each index is determined by using the fuzzy OWA operator weighting method (F-OWA). Then, the policy driving ability of China's photovoltaic industry is evaluated by fuzzy matter-element extension method (F-MEEM), and the effectiveness of the evaluation results is further verified by weight sensitivity analysis. According to the evaluation results, policy support plays an important role in the development of photovoltaic industry. This paper also gives policy suggestions for the development of China's photovoltaic industry under the background of carbon neutral from the macro, meso and micro perspectives. • China's PV industry evaluation system is established by the improved diamond model. •IT2FS and F-OWA are used to process indicators. •The policy driving ability of China's PV industry is evaluated by F-MEEM. •The effectiveness of the evaluation results is further verified by weight sensitivity analysis. •The results are analyzed in detail, and corresponding suggestions are put forward. [ABSTRACT FROM AUTHOR]

How to achieve the "double carbon" goal in energy systems has been the concern of governments. Integrated energy system (IES) is affected by climate change during his operation, in order to study the impact of climate change on IES and achieve the "double carbon" goal in energy systems, this paper proposes an integrated machine learning(IML) to forecast the long-term load, then investigates IES costs and carbon emissions in relation to climate, followed by the establishment of carbon peak energy system(CPES) and carbon neutral energy system(CNES), finally the honey badger algorithm is used to optimize the configuration of CPES and CNES. The results show that: IML can accurately make load forecasts. Under climate change, changes in load reduce the cost and carbon emissions of IES, and changes in equipment efficiency increase the cost and carbon emissions of IES. When both are considered, the cost and carbon emissions of IES increase by 1.18% and 0.92% per decade respectively. The costs of CPES and CNES increase by 0.93% and 1% respectively for every 10 years earlier than the year of achievement. To meet China's "double carbon" goal, CPES and CNES need to increase their costs by 1.97% and 2% respectively. • Integrated machine learning proposed for long-term load forecasting. • Studied the impact of system equipment efficiency and load with climate change. • Proposing carbon peaking energy system to achieve the carbon peak goal. • Proposed carbon-neutral energy system to achieve carbon neutrality goal. • The increased costs of achieving carbon peak and carbon neutral were studied. [ABSTRACT FROM AUTHOR]

To reduce carbon emissions and optimize energy utilization of integrated energy system (IES), an integrated electricity-heat-gas energy system containing coupled operation of oxy-fuel combustion capture and power to gas (OCC–P2G) and hydrogen-doped gas equipment is established in this paper. Firstly, the introduction of OCC technology transforms the thermal power unit into the OCC unit. The net output model of OCC unit and the equation of electric-carbon characteristic are established. Secondly, the two-stage refinement model of power to gas (P2G) and the model of hydrogen-doped gas equipment are constructed. Thirdly, considering the fairness principle of punishing positive carbon emissions and rewarding negative carbon emissions, a reward-penalty staircase carbon trading mechanism was constructed to constrain system carbon emissions. On this basis, an economic dispatch model of integrated energy system is established. The simulation results demonstrate that the ratio of wind abandonment is 0%, the actual carbon emission is only 35.08% of carbon quota, and the operation cost is only 237.1 thousand dollars. By setting multiple scenarios for comparative verification, the proposed strategy has lower economic cost and carbon emission. • The electric-carbon characteristic equation and net output power model of OCC unit are established. In addition, the electric-carbon characteristic of OCC unit is analyzed. • The coupled operation of OCC-P2G mode is proposed. The P2G process supplies high-purity oxygen for the OCC unit to broaden the oxygen source. The OCC unit provides the reaction feedstock for P2G device. • Considering the hydrogen-doped operation mode of gas turbine and gas boiler, the conversion efficiency hydrogen energy is improved. In addition, the mathematical model of hydrogen-doped operation of gas equipment is established. • Considering the fairness principle of carbon trading, the reward and punishment ladder-type carbon trading (RPLCT) mechanism is established. On this basis, a low-carbon optimal scheduling model of IES is proposed. [ABSTRACT FROM AUTHOR]

Decarbonization of building heating is the key to carbon neutrality. Heat pumps have great potential to replace non-renewable heating devices, thus creating economic and renewable heating systems. To overcome the application challenges of conventional heat pumps (HP), a novel dual-source heat pump (DSHP) heating system and corresponding model are proposed and validated in this paper. Simulated by the validated experiment-based model, the performance of the DSHP heating system is numerically investigated by comparing with different systems in various regions. The results show that the DSHP system has higher seasonal performance factors and near-zero defrosting costs when compared to the conventional HP heating system in different regions, resulting in 1.88%–21.53% reductions in annual heating bills and carbon emissions. Compared to the gas boiler heating system, the DSHP system can achieve 20.64%–54.36% of annual heating bill savings and 14.39%–86.09% of annual carbon reductions in selected regions. The investigation of heating characteristics and eco-economic performance of the DSHP system in different regions provided important guiding significance for the DSHP in global application, and thus contributes to achieving bill-saving and low-carbon heating and sustainable development. • A novel DSHP system is proposed for building heating and ventilation decarbonization. • Innovative heat recovery and defrosting achieve simple structure and high efficiency. • Experiment-based model of DSHP heating system is proposed and validated. • Its eco-economic performances are compared to the normal HP and gas boiler systems. • Case studies for application potential in various regions are conducted by comparison. [ABSTRACT FROM AUTHOR]

Banning gasoline vehicle sales policy (BGVSP) is considered a potentially important drivers for achieving carbon peak. This study, therefore, analyzed public support for such policies from the perspective of consumers. Using a grounded-theory approach, we developed a public-support model for BGVSP, on that basis, revealed the effects of the key elements and the theoretical logic. The results revealed: 1) Individual and psychological factors are important internal motivations, while the external driving factors include contextual factors and product factors. 2) The depth of individual perception is key to filling gaps in attitudes and behavior, and it plays an important role in improving public support. 3) The external contextual factors that affect consumer support mainly include external incentives, social influences, and urban contextual variables, which also play a moderating role in the integration model. The results show that the prohibition policy is easy to bring negative emotions, thereby causing public resistance, so the design of BGVSP should be based on the understanding of individual cognition, attitude and emotions. This paper constructs a model of the motivation of public support for China's localized BGVSP, and clarifies the core influencing factors and mechanisms, which provides fresh ideas for the realization of carbon peaking and carbon neutrality goals. • Banning gasoline vehicles increase the speed of carbon peaks in the transportation sector. • The public support for banning gasoline vehicle sales policy has been explored. • Developed a public support model with four core categories, namely, individual, psychological, contextual, and product. [ABSTRACT FROM AUTHOR]