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• Develop an hourly-resolution, multi-region model with total system cost optimized. • Energy storage technology can meet 85.8%-by-2050 renewable energy penetration. • UHVDC transmission technology is the most economical way for RES integration. • Optimal combination of UHVDC grid and ES can achieve 74.2% renewables penetration. • The cost-optimal operation strategy varies among six regions in planning period. High renewable energy penetration is an effective way to decarbonize the power system. However, many studies focus on the economics of integrating renewables at the generation-side rather than system-wide. This paper aims to explore the cost-optimal operation strategies of a renewable-dominant power system. Considering both cost reduction potential of energy storage technology and regional investment cost variance of ultra-high voltage direct current grids, an hourly-resolution, multi-region model with total system costs minimized is proposed. Moreover, energy storage-based, ultra-high voltage direct current-based, and mixed scenarios are taken into consideration to investigate the economics of high renewables penetration. The results show that energy storage technology can achieve maximum penetration of renewable energy at 85.8% while the total system cost is 11.8% higher than that of ultra-high voltage direct current transmission technology. Although ultra-high voltage direct current grid is the most economical option to integrate renewables, the penetration is 13 percentage points lower than that of energy storage technology. The combination of energy storage technology and ultra-high voltage direct current grid can achieve 74.2% renewable energy penetration, saving 9.4% of total system costs compared to that of energy storage technology only. The cost-optimal option for East and South China is to promote both energy storage and ultra-high voltage direct current technologies. Energy storage technology is preferred among North, Northwest and Northeast China, while ultra-high voltage direct current grid is the optimal option for Center China. [ABSTRACT FROM AUTHOR]

Biodiesel from non-grain feedstock has been considered as one of the proper substitutes for fossil fuels associated with a series of activities emerging in China in order to meet the resource shortage and develop the energy crops. This paper presents an ecological accounting framework based on embodied energy, emergy, and CO2 emission for the whole production chain of biodiesel made from Jatropha curcas L. (JCL) oil. The energy and materials invested in and CO2 emission from the whole process, including cropping, transportation, extraction, and production, are accounted and calculated. Also, EmCO2, the ratio of real CO2 released to the emergy-based sustainability indicator per joule biodiesel, is proposed in this paper to present a new goal function for low-carbon system optimization. Finally, the results are compared with those of the bioethanol (wheat) production in Henan Province, China, and bioethanol (corn) production in Italy in view of the indices of embodied energy, emergy and CO2 emissions and EmCO2. [Copyright &y& Elsevier]

With the global trend of clean and low-carbon energy transformation, China has put forward the 30·60 double carbon target. However, traditional energy still need to play a supporting role in the energy transition period. The purpose of this study is to optimize the dispatching order of thermal power resource, when clean renewable energy is given priority and fully dispatching, but still can not meet the energy demand of the whole society. Different from the traditional economic dispatching, the green thermal power dispatching evaluation mechanism proposed in this paper is oriented by cleanliness, supplemented by economy and reliability. This paper set up green power dispatching evaluation model through the comprehensive use of the Analytic Hierarchy Process, Entropy Weight Method and Grey Relation Analysis. And emergy method was used to solve the problem of environmental information quantification and evaluation. Finally, we established a set of green comprehensive energy efficiency evaluation system with 16 indicators. The results showed that the dispatch sequence has changed significantly under the new mechanism, which confirmed that the model has good effect and practical value for optimizing the cleaning dispatching of thermal power. [Display omitted] • Green energy dispatching is clean-oriented, supplemented by economy and reliability. • Quantified and evaluated environmental information using emergy analysis method. • Constructed a set of complete green energy efficiency evaluation index system. • Realized refined ranking different from the rough environmental constraints. • Thermal power dispatch sequence has changed significantly under the new mechanism. [ABSTRACT FROM AUTHOR]

• A chance-constrained co-optimization model for generation and reserve scheduling of cascade hydro-VRE hybrid systems. • Nonlinear dependence between generation efficiency and hydropower reserves is modeled. • Economic allocation of VRE reserve requirements among cascade hydropower stations. • A solution approach for chance constraints based on quantile regression theory. The rapid development of variable renewable energy (VRE), such as wind and solar energy, has stimulated the complementary operation of VRE with flexible cascade hydropower stations in China. Due to the uncertainties of VRE power generation and complex constraints of cascade hydropower stations, formulating reliable day-ahead generation and reserve scheduling plans is a real challenge in the actual operation stage of the cascade hydropower–VRE hybrid systems (CHVHS). In this paper, we propose a tractable chance-constrained co-optimization model for day-ahead generation and reserve scheduling of a CHVHES. First, compared with existing models, the relationship between the hydropower reserve capacities and water-electricity conversion efficiency is finely modeled. Accordingly, the economic allocation of total VRE reserve requirements among cascade hydropower stations is for the first time considered in our proposed model. This can save more water resources for cascade hydropower stations when compensating for VRE, further improving hydro–VRE complementary profits. Second, we propose a solution approach for chance constraints by incorporating the nonparametric probabilistic forecasting of VRE power based on quantile regression into the chance-constrained model, ensuring that the stochastic dependence between VRE power output and its point forecast can be effectively captured. Importantly, this solution approach does not require prior knowledge or any probability distribution assumptions of VRE power and does not introduce any additional computational burden. With the help of three-dimensional interpolation technology for nonlinear constraints, the proposed scheduling model is finally cast as a mixed-integer linear programming model that is computationally tractable. Numerical tests implemented on a real CHVHES located in Southwest China verify the effectiveness and advantages of the proposed methods. [ABSTRACT FROM AUTHOR]

• A wind power prediction method based on ensemble learning and hyper-parameters optimization is proposed. • A wind power sequence segmentation method based on the Swing Window is proposed. • The relationships mapping model between error sequence and NWP sequences are built. • A daily rolling error correction strategy is proposed to correct wind power prediction results. With a high proportion of renewable energy injected into the power grid, the accurate wind power prediction of wind farms is key to improving power quality and ensuring the stable operation of the power grid. In this paper, an ensemble learning prediction model considering the rolling error correction strategy used for short-term wind power prediction is proposed. Firstly, the ensemble learning prediction model integrating multiple Gradient Boosting Trees (GBDTs) based on Bayesian optimization is established, and the characteristics of prediction errors are analyzed. To further improve the prediction accuracy, a daily rolling error correction strategy based on the Swing Window segmentation method, Spearman correlation coefficient and Quantile Regression is established to obtain the optimal compensation amount. Finally, the corrected short-term wind power prediction results are obtained. The two-year dataset collected from a regional wind farm in China is used as the benchmark test. Different prediction models and error correction strategies are compared, and the effectiveness of the proposed method is comprehensively evaluated. The results from different seasons show that the proposed prediction method has good stability, and the proposed error correction strategy has good generalization ability. [ABSTRACT FROM AUTHOR]

Renewable energy consumption has a strong driving force for promoting energy conservation and emission reduction, and is a new way to achieve clean and low-carbon development. Based on this, this paper uses the data of renewable energy consumption, carbon productivity, GDP, population, energy efficiency and technological innovation of 30 provinces in China from 2011 to 2020, and empirically analyzes the impact of renewable energy consumption on carbon productivity in 30 provinces in China, using STIRPAT model, comprehensively considers spatial horizontally and temporal vertically dimension. The empirical results show that: (1) China's carbon productivity shows a significant spatial spillover effect, its impact can spill over to adjacent areas within 1000 km; (2) China's renewable energy power consumption plays a significant role in promoting the improvement of carbon productivity. (3) Renewable energy consumption in the western region plays the most important role in driving carbon productivity. Finally, according to the temporal and spatial relationship between renewable energy consumption and carbon productivity in different regions, we provide specific regional policy suggestions. • The STIRPAT model is employed to explore temporal and spatial impact, while it considers sub regions. • Spatialy, the impact can spill over to adjacent areas within 1000km. Temporally, the impact fluctuates and rises. • The positive role of renewable energy consumption is found in China's western region. [ABSTRACT FROM AUTHOR]

The Chinese government identifies the renewable energy sector as a core strategic industry. Since 2009, China is the country with the highest annual investment into renewable energy, predominantly wind and solar photovoltaic projects. Due to rapid cost decline, industrial transformation, and policy support, the relative share of solar project investment is growing at a disproportionate rate. However, there is no systematic analysis of how efficiently these investments are allocated; or the underlying risk and return characteristics. Based on structured interviews with 69 market participants, this paper identifies severe cash-flow uncertainty, unreliable supply chains and a weak regulatory environment as most prominent risk factors that currently inhibit sustainable and demand-driven market development. Expanding on the interview results, this study discusses the origins of risk in China and how the institutional response to investment risk currently fails to address the core problems. [ABSTRACT FROM AUTHOR]

Renewable energy has a critical role in limiting the greenhouse gas (GHG) emissions. This paper assesses the implication of aligning renewable energy deployment target with national emission reduction target for mitigation cost. The assessment methodology uses Asia-Pacific Integrated Assessment/computable general equilibrium (AIM/CGE) model to determine the mitigation cost in terms of GDP and welfare loss under alternative renewable targets in different climate-constrained scenarios. A range of country-specific emission constraints is taken to address the uncertainties related to global emission pathway and emission entitlement scheme. Comparative results show that China needs to increase its share of non-fossil fuel significantly in the primary energy mix to achieve the stringent emission reduction target compared to India. The mitigation cost in terms of economic and welfare loss can be reduced by increasing the penetration of the renewable energy to achieve the same emission reduction target. The modeling results show that coordinated national climate and renewable energy policies help to achieve the GHG emission reduction target in an efficient and cost-effective manner. [ABSTRACT FROM AUTHOR]

Over the recent decades, China’s building energy consumption has been growing rapidly. Also the fuel mix has been changing quickly with more natural gas & electricity and less coal being used. Meanwhile, the technologies used in building sector are improving in efficiency. In this paper, the impact of technical progress and the use of renewable energy in building sector are analyzed. The energy saving and emission reduction potential of building sector are also measured. China TIMES model is used to model the future energy consumption and carbon emissions in building sector. The modelling results indicate that building energy consumption is expected to grow to around 41.6EJ in the reference scenario in 2050. The energy saving potential in 2050 can be up to 4EJ due to the improvement of both building insulation (envelop) and energy use technologies. Renewable energy used in buildings can be a great contributor to the carbon mitigation in buildings. China’s building sector can reach a relatively low-carbon future with more low- and non-carbon fuels consumed. [ABSTRACT FROM AUTHOR]

The spatial distribution of biomass resources is not uniform. At present, the zoning of biomass energy development suitability is primarily based on resource potential, whereas energy demand is ignored as an important factor affecting the degree of local energy self-sufficiency. Under the constraints of high transportation costs, solar energy with low geographical constraints can be a supplementary energy source for biomass despite its instability. Based on the energy utilization potential of solar energy and biomass resources, this paper evaluates the energy surplus factor (ratio of renewable resource potential to energy demand) of each city in the study area, takes meeting the specific energy surplus factor as the construction prerequisites of biomass combined heat and power (CHP) plants, calculates the biomass resource utilization rate and energy surplus factor in the study area under different conditions, and provides zoning suggestions and data reference for the unified planning of biomass CHP plants. The minimum energy surplus factor that is suitable for the development of biomass energy is set as the construction threshold of biomass CHP plants (The construction threshold is the minimum condition for the construction of biomass CHP plants. Only areas where the energy surplus factor reaches the preset construction threshold are allowed to build biomass CHP plants). The results show that the construction threshold is negatively correlated with the utilization rate of biomass resources. When the construction threshold is less than 1.4, the utilization rate of biomass resources decreases rapidly with the increase of the construction threshold; when the construction threshold is greater than 1.4, the utilization rate of biomass resources decreases slowly and tends to be flat. It is suggested that biomass resources should be developed in different regions and in stages, and priority should be given to developing areas with an energy surplus factor greater than 1.4. Areas with an energy surplus factor of 0.3–1.4 are considered secondary development areas, and areas with an energy surplus factor of less than 0.3 are not recommended for development; these can meet 31% and 59% of the total energy demand and reduce 50319380 tons and 180524400 tons carbon emissions so that the limited construction cost can meet higher energy demand and biomass resource utilization. • Priority development areas are identified based on solar and biomass potential. • Energy surplus factor is calculated to determine the development suitability. • Strategies for zoning and phased planning of biomass resources are proposed. [ABSTRACT FROM AUTHOR]

• Integrating machine learning and vine-copula to catch the complex spatial correlations among the renewable resources. • Utilization of stochastic model predictive control to optimize the long-term hydro-wind-solar operation. • Potential assessment of hydropower to offset the effects of seasonal uncertainties and mismatch between renewable resources and requirements. It is popular to combine the hydropower plant with the wind and solar power plants to supply electricity, and the joint is termed as the hydro-wind-solar renewable energy supply system (RESS). The long-term optimal operation of the RESS is a challenging task, due to the nature of different spatial and temporal variabilities associated with renewable energy resources, and the significant operation uncertainties due to the changing natural environment. To address the task, the stochastic model predictive control (MPC), based on probabilistic forecasting and rolling stochastic optimization, is designed and implemented for the long-term operations of the RESSs in Yunnan province, China. The paper tests out the system efficiencies for different penetration levels of wind and solar power, and finds out that (1) the Long Short-Term Memory performs best among candidate point prediction algorithms; (2) the stochastic MPC considering the correlations among renewable resources helps the RESS operate with a higher efficiency; (3) the large-scale hydropower plant has great potential to offset the effects of seasonal uncertainties and demand-generation mismatch, but cannot completely avoid the electricity shortage enabled by unexpected scenarios of renewable resources. [ABSTRACT FROM AUTHOR]

A hybrid energy system including both off-site and distributed energy sources, energy conversion technologies and operation methods, is a necessary step on a transition path towards a sustainable energy system. The challenge is to identify such a combination of design options that result in minimum life cycle cost (LCC) and maximum exergy efficiency (EE) at each phase of the transition path. In this paper, a time-effective multi-objective optimization method based on genetic algorithm (GA), is proposed for the transition path problem. The proposed model makes use of a fitness function approach to reduce the model into one objective function and to reduce the computational time. In a case study, the model is applied to a potential net-zero exergy district (NZEXD) in Hangzhou, China. Here, three possible hybrid energy scenarios and three preference treatment strategies are analyzed. The study suggests that the proposed approach is workable for the identification of the most feasible options to be gradually integrated in an NZEXD in a multi-stage process. In the Hangzhou case, with the reduction of investments in distributed energy components and escalating market prices of fossil fuels, distributed energy system (DES) may have more feasibility in the near future. [ABSTRACT FROM AUTHOR]

• Inequality of renewable technology innovation is evaluated by Gini coefficients. • Contributors to renewable innovation inequality are decomposed by Shapley method. • Variables of regional attributes, policies and official characteristics are proposed. • Knowledge stock and R&D expenditure are the greatest contributors. • Energy-related experience and tenure of officials may be potential contributors. Regional inequality of technology innovation associated with renewables may lead to insufficient innovation growth over the long-term, which impedes the deployment of renewable energy and slows down low-carbon transition. This paper aims to explore the major contributors to regional inequality of technology innovation in renewable energy by taking China as a representative example. Three groups of variables including regional attributes, supporting policies, and local official characteristics are proposed as potential explanatory factors. A set of panel data covering both the photovoltaic and wind energy sectors in 31 Chinese provinces from 2008 to 2017 are collected for the empirical study. Gini coefficient is used to quantify the inequalities of renewable technology innovation, while Shapley decomposition method is applied to evaluate the contribution of each significant factors. The results show that the overall Gini coefficients of photovoltaic and wind technology innovation in China are 0.65 and 0.62, respectively, indicating medium-level regional technology innovation inequality in both sectors. Knowledge stock (46.44%), R&D expenditure (36.56%), green fixed industrial investment (13.53%), electricity consumption (1.33%), and the energy-related experience of local officials (0.05%) are significant contributors to regional inequality of photovoltaic innovation. Knowledge stock (45.20%), R&D expenditure (37.90%), electricity consumption (8.63%), feed-in tariffs (1.02%), and the tenure of local officials (0.18%) are significant contributors to regional inequality of wind innovation. Therefore, eliminating regional inequality of technology innovation in renewables should start with balancing regional R&D expenditure and knowledge stock. [ABSTRACT FROM AUTHOR]

• Techno-economic feasibility of the hybrid PV/Wind/Biomass system for sustainable rural electrification have been demonstrated under both off-grid and on-grid modes, via a case study of a village in West China. • Impacts of future development of the village and changes in government incentive policy have been analyzed by performing sensitivity analysis. • Flexibility of the proposed HRES has been demonstrated by comparing off-grid and on-grid modes of the hybrid system. Reliable and sustainable power supply for remote rural areas is of vital importance for development of these areas. In this paper, the techno-economic feasibility and flexibility of hybrid renewable energy systems are demonstrated under both off-grid and on-grid modes for rural electrification, where a case study of a village in West China is presented. According to simulation and optimization results as well as sensitivity analysis, the most cost-competitive configuration is found by Hybrid Optimization of Multiple Energy resources (HOMER). Comparison of the off-grid and on-grid modes of the hybrid system has been carried out. The results demonstrate that a hybrid renewable energy system which comprises solar, wind and biomass is reliable and cost-effective regarding sustainable rural electrification. Moreover, environmental and social benefits can also be acquired by this system. The high capability of the proposed flexible design is demonstrated over conditions for both off-grid and on-grid modes. [ABSTRACT FROM AUTHOR]

Abstract: Currently one of the most promising power solutions for remote rural areas and isolated islands which are far away from utility grid is the stand-alone solar photovoltaic (PV) renewable energy system or hybrid solar–wind power system. This paper presents the investigation results of a real remote solar PV project on an island in Hong Kong. The stand-alone PV system, rated at 19.8kWp, is established on a remote island for power generation to local residents. Power on this island was originally supplied by diesel generators and this new solar energy system has significantly reduced fuel costs and alleviated environmental pollution. The on-site entire system’s operating data was collected for one whole year in 2011, and the energy performance of the PV array, inverters, battery bank and the entire PV system were analyzed in terms of daily energy balance, normalized performance parameters and overall system energy utilization ratio. The results from this long term system monitoring and its evaluation enables a detailed inspection of system operating performance with respect to the technical issues, which provides a useful reference for future applications of solar photovoltaics in remote islands. [Copyright &y& Elsevier]

In recent years, China has successively issued relevant policies to support the development of distributed renewable energy sources such as dispersed wind power (DWP) and distributed photovoltaic (DPV). The capacity of DPV grows fast, but the progress of DWP deployment is limited. In this paper, the improved levelized cost of electricity (LCOE) model and the internal rate of return (IRR) are employed to evaluate the economics of DWP and DPV for case regions. We find that, under current market regime, the IRR of DWP in eastern and central regions is 8.81%–10.34% for the grid side, and which of DPV is 9.08%–12.8% for the user side. When the power market is restructured, the IRR of DWP for industrial and commercial user side increases to 12.73%–14.86%, higher than that the return of DPV. Policy implications on grid-connection, land expropriation, and financial support, planning and approval procedure are proposed to promote the development of DWP. Overall, this paper covers the research gap on the development of DWP in China with a technical/institutional economics perspective and a comparison with DPV. Furthermore, our efforts make a significant contribution to DWP policy by identifying the institutional factors that hinder the development of DWP. • Explore the technical & institutional factors around DWP deployment in China. • DWP and DPV gain comparable economic returns under current planning regime. • DWP can have better economic returns than DPV with electricity market reform. • Identify institutional factors that hinder DWP and propose policy implications. [ABSTRACT FROM AUTHOR]

• The data envelopment analysis is introduced to renewable energy development. • The method has two stages: comprehensive evaluation and structure optimization. • Indexes from different aspects are quantified via intuitionistic fuzzy numbers. • The comprehensive performances are determined based on the relative efficiencies. • The proportions of renewable energy are optimized based on the whole efficiency. Different kinds of renewable energy resources have developed rapidly. For renewable energy planning, it is meaningful to assess the comprehensive performances of different schemes and then to determine the optimal design of the energy structure. This paper presents a two-stage method for the comprehensive evaluation and structure optimization of renewable energy plans. First, in the evaluation stage, multiple indexes from different aspects are taken into consideration, of which each qualitative index will be converted quantitatively, using the intuitionistic fuzzy number to describe the fuzziness and ambiguity in a qualitative index. Then, the superefficiency data envelopment analysis model is used to determine the comprehensive performances of different plans based on the concept of relative efficiency. Next, in the optimization stage, an optimal model combining multiple renewable energy resources is established based on the relative efficiency results of the evaluation process. This model aims at the maximum efficiency as a whole and can be used to optimize the proportions of different renewable energy resources. Finally, a real case of renewable energy development from a province in China is given to demonstrate the feasibility and effectiveness of the proposed method in this paper. The results show that it can overcome the shortcomings of the traditional basic model, obtain more objective evaluation results and provide beneficial references for the strategy making of renewable energy development. [ABSTRACT FROM AUTHOR]

More and more attention has been given to the role of electric vehicles in reducing the economic cost and carbon emissions of the power system through the vehicle-to-grid (V2G) mode, as well as helping to integrate renewable energy power. The promotion of V2G mode needs to consider the effectiveness of policy costs, so it is urgent to estimate the potential benefits of V2G. In this paper, a multi-regional power dispatch and expansion model is constructed from the perspective of power system by taking China's plan to reach 1.2 billion kW of installed wind and photovoltaic power generation capacity in 2030 as an example, combining with the development planning of electric vehicles and power systems. The results show that by 2030, the implementation of unidirectional V2G and bidirectional V2G in China can reduce the total cost of power system by 2.02% and 2.08%, reduce the annual carbon emissions of the power system by 2.27% and 2.95%, and increase the total proportion of wind and photovoltaic power generation by 1.33% and 1.28% in the power mix. An increasing proportion of electric vehicles participate in V2G increases the proportion of new-installed wind generation and decreases that of photovoltaic power. Due to the high cost of battery degradation and the current power mix dominated by coal-fired generation, additional benefits of implementing bidirectional V2G over unidirectional V2G are limited. • V2G reduces the total power cost, carbon emissions, and renewables' curtailment. • Increasing the proportion of EVs participating in V2G improves potential benefits. • V2G changes the proportion of newly installed wind and solar power generation. • V2G shifts the electricity production from high-cost areas to low-cost areas. • Additional benefits of bidirectional V2G over unidirectional V2G are limited. [ABSTRACT FROM AUTHOR]

Abstract: Renewable energy is one of the possible solutions when addressing climate change. Today, large-scale renewable energy integration needs to include the experience to balance the discrepancy between electricity demand and supply. The electrification of transportation may have the potential to deal with this imbalance and to reduce its high dependence on oil production. For this reason, it is interesting to analyse the extent to which transport electrification can further the renewable energy integration. This paper quantifies this issue in Inner Mongolia, where the share of wind power in the electricity supply was 6.5% in 2009 and which has the plan to develop large-scale wind power. The results show that electric vehicles (EVs) have the ability to balance the electricity demand and supply and to further the wind power integration. In the best case, the energy system with EV can increase wind power integration by 8%. The application of EVs benefits from saving both energy system cost and fuel cost. However, the negative consequences of decreasing energy system efficiency and increasing the CO2 emission should be noted when applying the hydrogen fuel cell vehicle (HFCV). The results also indicate that developing renewable energy is crucial for transportation electrification. [Copyright &y& Elsevier]

Abstract: China has set ambitious goals to increase the use of renewable energy. Developing renewables in rural areas is also one of the most important energy strategies. This paper examines rural social acceptance of renewable energy deployment taking Shandong as a case study via a field questionnaire survey. Theory of planned behavior is adopted to establish an analytical framework, and a logit model is used to examine possible determinants of local social acceptance. The results show that rural residents are generally supportive renewable energy development given its positive impacts on environment. A stated willingness to pay more for renewable electricity is taken as a variable representing an individual’s behavioral intention. The probability of occurrence of positive intention is found to increase with household income, individual knowledge level and belief about costs of renewable energy use but decrease with individual age. Residents with higher level of income are more likely to be willing to pay more for green electricity, so are the younger people. Enhancive knowledge and understanding about renewable energy (for instance, the cost) would be conducive to win public acceptance of renewable energy deployment. [Copyright &y& Elsevier]

Abstract: The use of groundwater for cooling and heating purposes is of interest from both the economical and the ecological perspective. The groundwater heat pump (GWHP) system utilizes groundwater as alternative renewable and clean energy source for space heating and/or cooling, withdraws water from a production well, passes it through a heat exchanger and discharges the water into an injection well. By utilizing the relatively stable temperature of groundwater, GWHP system can achieve a higher coefficient of performance. Due to the utilization of groundwater stored in the aquifer, the assessment of the hydraulic capacity of the aquifer based on numerical groundwater models is always needed for the optimum design and the efficient performance of GWHP. In this paper, numerical methods of underground heat-water transfer, energy balance method and thermal storage method were presented to calculate the capacity of unit area of shallow groundwater aquifer. The model results indicate that the numerical method, which is based on performance efficiency of GWHP, represents the behaviour of groundwater pumping/recharging processes, and serves better than energy balance method and thermal storage method, in addition it has been proven itself that this method has the advantages of energy saving and environmental protection. The calculated capacity is positively related to aquifer thickness. It is found that it is easy for ground water recharge in alluvial and pluvial fan located at the piedmont, while the calculated capacity is relatively smaller compared with that of south-east plain where it is not easy for groundwater recharge. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to investigate the reasons for ever growing energy consumption in buildings and to give enhanced supervision strategies for reduction of building energy consumption compared to regular ones. A case study of Ningbo city was used to make a detail analysis. Several factors were determined as the reasons for ever growing building energy consumption including climate change, household electricity load increase, the growth of real estate, fast-growing household electrical appliances, high energy consumption in existing buildings, changes in industrial structure and the lack of enhanced government supervision. Then the discussion of suitable countermeasures shows that only enhanced supervision strategies are currently applicable. Finally, it is concluded that enhanced government supervision strategies, including the establishment of a strict control system for new built buildings through information integration and encryption, establishing an energy efficiency supervision system of large-scale public building and a carrot-and-stick approach with added expert checklist for the building application of renewable energy, showed great advantages in promoting building energy efficiency in Ningbo, compared with other cities. These supervision strategies are applicable in other cities as they are in the similar situations in the enforcement of building energy efficiency. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to identify the relations between transportation energy consumption and its impacted factors. We first analyze the current status of transportation energy consumption in China. Then, the logarithmic mean Divisia index (LMDI) technique is used to find the nature of the factors those influence the changes in transportation energy consumption. We find that: (1) In 2006, the transportation energy consumption increased by 7.63 times against that in 1980. (2) Up to 2006, the oil consumed by transportation accounted for 49.6% of that in the whole country, which almost equaled to the net oil import. (3) In the light of the increasing energy consumption intensity, the energy-utilization effectiveness of transportation sector has been declining gradually. (4) The transportation activity effect is the most important contributor to increase energy consumption in the transportation sector and the energy intensity effect plays the dominant role in decreasing energy consumption. [Copyright &y& Elsevier]

Abstract: Along with high-speed economic development and increasing energy consumption, the Chinese Government faces a growing pressure to maintain the balance between energy supply and demand. In 2009, China has become both the largest energy consumer and CO2 emitting country in the world. In this case, the inappropriate energy consumption structure should be changed. As an alternative, a suitable infrastructure for the implementation of renewable energy may serve as a long-term sustainable solution. The perspective of a 100% renewable energy system has been analyzed and discussed in some countries previously. In this process, assessment of domestic renewable energy sources is the first step. Then appropriate methodologies are needed to perform energy system analyses involving the integration of more sustainable strategies. Denmark may serve as an example of how sustainable strategies can be implemented. The Danish system has demonstrated the possibility of converting into a 100% renewable energy system. This paper discusses the perspective of renewable energy in China firstly, and then analyses whether it is suitable to adopt similar methodologies applied in other countries as China approaches a renewable energy system. The conclusion is that China’s domestic renewable energy sources are abundant and show the possibility to cover future energy demand; the methodologies used to analyse a 100% renewable energy system are applicable in China. Therefore, proposing an analysis of a 100% renewable energy system in China is not unreasonable. [ABSTRACT FROM AUTHOR]

Abstract: To meet the demand of its fast growing economy, China has become already the second largest buyer of crude oil. China is facing critical problems of energy shortage and environment deterioration. Rational and efficient energy use and environment protection are both getting more attention in China. Biomass energy is renewable energy made from biological sources. China''s biomass resources are abundant, which could provide energy for future social and economic development. However technologies for biomass resource conversion in China are still just beginning. In this paper, current biomass resource distribution and technologies of biomass energy, including power generation, biofuel production and biomass-based chemical production are reviewed. [Copyright &y& Elsevier]

• An optimal configuration method of concentrating solar power in power systems. • A data-driven scenario generation method to describe the uncertainty in power systems. • The benefits of concentrating solar power are comprehensively considered. • Sensitivity factors affecting the configuration results are analyzed in the case study. The proportion of renewable energy sources and the flexibility demands of the power grid have increased simultaneously, which has caused difficulties in renewable energy consumption and the secure operation of power systems. Concentrating solar power (CSP) can provide additional flexibility for power systems and change the uncontrollable characteristics of variable renewable energy generation. Due to the high construction cost, it is necessary to fully evaluate the configurational scheme of CSP. In this paper, we propose an optimal configuration method for CSP in multienergy power systems to fully utilize the CSP benefits. We first improve the variational autoencoder (VAE) to describe the uncertainty in power systems and generate scenarios for the configuration model. The model consists of two stages: planning and operation. The planning model determines the configuration capacity of each component of the CSP station. The operation model considers the day-ahead and real-time periods to analyze the operational cost of the power systems with CSP. By means of linearized methods, the configuration model is treated as a mixed integer linear programming (MILP) formulation to obtain a rapid solution. A case study is conducted based on the power source data of a province in northwestern China. The simulation results show that flexibility values makes CSP more competitive in the configuration process, and the configuration results are significantly affected by the coordination with other power sources. We use sensitivity analysis with different situations to explore the development prospects of CSP. [ABSTRACT FROM AUTHOR]

• The replacing of a coal-fired boiler by a GWHP system is investigated. • The operation of each system has been monitored over one-year period. • The boiler has lower investments and covers lower thermal load than the GWHP. • GWHP shows higher economic performance considering Average Energy Price. • GWHP system may be cost effective over traditional boilers for applications. Currently in China, the replacement of coal-fired boilers by clean and renewable energy sources is considered as an essential measure to alleviate air pollution. This paper investigates the thermo-economic performance of replacing a coal-fired boiler by a Groundwater Heat Pump (GWHP) system for a greenhouse, where the GWHP system was constructed to reduce emission and also to provide cooling. The operation of this system has been monitored over a one–year period. The results show that the thermal efficiency factor of the boiler varies in the range of 0.53–0.68 and the Coefficient of Performance (COP) of the GWHP system averages at 4.1 for cooling and at 3.3 for heating. Although the boiler has both lower capital costs and lower operating costs, the analysis of Average Energy Price (AEP) shows that the GWHP system has a higher economic performance, since it has a lower AEP of 0.040 USD /kWh in heating and 0.023 USD/kWh in cooling over an expecting lifetime of 20 years, in comparison to the boiler at 0.052 USD/kWh over a lifetime of 10 years. This indicates that GWHP system may be considered as an alternative over traditional boilers in terms of thermo-economic performance for applications in other places of the world with similar climate condition. [ABSTRACT FROM AUTHOR]

Following India's efforts to mitigate the emission of greenhouse gases, there has been a transition from fossil fuels to clean energy sources, such as solar and wind, in the energy portfolio. The renewable energy sector is widely acknowledged as a fertile ground for employment creation, as it is labour-intensive. Against this backdrop, the main objective of this paper is to provide an empirical explanation of how the growth of renewable energy sources, particularly solar photovoltaic (PV) technology, affects employment creation in India. The findings reveal that, despite a substantial investment in India's solar PV technology, the number of jobs created by the sector declined marginally from 164000 in 2017–114000 in 2018. India's estimated employment elasticity is just 0.004, implying that the level of employment does not show a significant positive response to changes in installed capacity. Almost 60 per cent of the global solar PV workforce is in China, which has become the leading country both in terms of installed capacity of global solar PV technology and manufacturing of solar PV cells and modules. The wide disparity in solar PV employment between India and China is explained by the former's excessive dependence on China for solar PV cells. Alongside climate conservation, India should, therefore, place more emphasis on revitalising the domestic solar manufacturing industry to bring about efficient use of the nation's untapped resources. [ABSTRACT FROM AUTHOR]

• A modified dynamic recursive CGE model is constructed. • Renewable energy growth is considerable only if ETS revenue is used. • Broader renewable energy subsidies are better than ones with narrow scope. • A small part of ETS revenue should be used to subsidize residents for social stability. Emission Trading Scheme (ETS) and renewable energy generation are emission reduction methods in most countries in the world. However, few studies have focused on the impact of ETS on renewable energy. The question is, can carbon trading promote renewable energy generation? This paper first analyzes different distribution strategies of ETS revenue by applying dynamic recursive computable general equilibrium model with multi-sectors. Practical scenarios and better options of distribution of ETS revenue by a comprehensive evaluation based on entropy weight method are proposed. The results show that ETS with no subsidy to renewable will reduce the demand for energy, increase the cost of renewable energy sources and decrease the generation. ETS will be the spring of renewable energy generation when most of the revenue is used for all kinds of renewable energy sources, instead of some of them. The growth of renewable energy generation is also substantial. It is necessary that a small portion of ETS revenue should be used to subsidize residents to reduce the gap between the rich and the poor. If this income is used for government investment and consumption, it will also help to mitigate economic losses, which is caused by the direction of investment by the Chinese government. [ABSTRACT FROM AUTHOR]

• Optimal configuration of the two representative district MESs in southern and northern China. • Up to 80% of CO 2 can be reduced and more than 40% renewable penetration can be achieved by the MES. • The average cost of reducing CO 2 rises from 491 CNY/tCO 2 to 880 CNY/tCO 2 for the Tongli system. • The cost of reducing CO 2 is higher in southern China than in northern China under the same target level. Multiple energy systems (MES) can exploit synergies among different energy sectors to optimize overall efficiency. They can accommodate renewable energy sources and reduce carbon emissions more economically than in systems where each energy sector is planned and operated separately. This paper describes the optimal planning of two real-world district MESs in China: Tongli new energy town and Tongzhou subsidiary administrative center. In addition to the conventional economy objective, two kinds of low-carbon targets, including the carbon emission target and renewable penetration target, are taken into account. The results show that investment decisions on coal-fired units, combined heat and power plants and renewable energy sources are significantly influenced by the choices of different targets. Reducing carbon emissions and increasing renewable energy integration generally work in tandem, but result in a higher planning cost. The average cost of reducing carbon emissions by 40% is 528 CNY/tCO 2 in Tongli and 327 CNY/tCO 2 in Tongzhou. Meanwhile, the average cost of achieving a 25% penetration of renewable energy is 468 CNY/MWh in Tongli and 363 CNY/MWh in Tongzhou. As expected, the cost of carbon reduction and renewable energy integration gradually rises as the targets tighten. Only a small fraction of the available renewable energy is curtailed (2.9% in Tongli and 8.3% in Tongzhou) even when the renewable penetration reaches 40% in both two systems. Finally, a sensitivity analysis illustrates the effect of planning parameters, including the carbon price, the capital cost of energy components and the fuel prices, on the planning results. [ABSTRACT FROM AUTHOR]

• China's Nationally Determined Contributions do not comply with the Paris Agreement. • Overall coal usage needs to decrease by 60% (2 °C) or even 100% (1.5 °C) by 2050. • 100% Renewable energies are cost-efficient to decarbonize the electricity sector. • Sector coupling increases the electricity demand by 100% (2 °C) to 400% (1.5 °C). • Incentives for local actors are needed for a sustainable low-carbon transformation. Growing prosperity among its population and an inherent increasing demand for energy complicate China's target of combating climate change, while maintaining its economic growth. This paper, therefore, describes three potential decarbonization pathways to analyze different effects for the electricity, transport, heating, and industrial sectors until 2050. Using an enhanced version of the multi-sectoral, open-source Global Energy System Model, enables us to assess the impact of different CO 2 budgets on the upcoming energy system transformation. A detailed provincial resolution allows for the implementation of regional characteristics and disparities within China. Conclusively, we complement the model-based analysis with a quantitative assessment of current barriers for the needed transformation. Results indicate that overall energy system CO 2 emissions and in particular coal usage have to be reduced drastically to meet (inter-) national climate targets. Specifically, coal consumption has to decrease by around 60% in 2050 compared to 2015. The current Nationally Determined Contributions proposed by the Chinese government of peaking emissions in 2030 are, therefore, not sufficient to comply with a global CO 2 budget in line with the Paris Agreement. Renewable energies, in particular photovoltaics and onshore wind, profit from decreasing costs and can provide a more sustainable and cheaper energy source. Furthermore, increased stakeholder interactions and incentives are needed to mitigate the resistance of local actors against a low-carbon transformation. [ABSTRACT FROM AUTHOR]

Biomass power is one of the most important renewable energy sources in China. In order to provide a reference for China's biomass power planning, this paper builds a power sector-planning model using the Long-range Energy Alternatives Planning System (LEAP). The results show that in the base scenario, the installed capacity of agricultural and forestry residues, municipal solid waste and biogas will increase to 22350 MW, 21150 MW, and 4900 MW, respectively by 2030. From the point of view of total volume, biomass supply is not a constraining factor for biomass power source. However, there are some social and economic factors that impede the development of the biomass power industry, some of which may not be addressed in the short term. Therefore, the development of the biomass power industry in China is a long-term process. Some policy suggestions were proposed, including reasonable planning and more subsidies for biomass supply value chain. • An optimal power-planning model focused on bio-energy in China was developed. • Agricultural and forestry power, waste power and biogas power were all analyzed. • Social and economic factors that impede biomass power were investigated. [ABSTRACT FROM AUTHOR]