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A reasonable allocation of production schedules and savings in overall electricity costs are crucial for large manufacturing conglomerates. In this study, we develop an optimization model of off-site industrial production scheduling to address the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's power supply, and the difficulty in promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and variations in electricity prices in different places to optimize the scheduling of industrial production in various locations. The model is embedded with two sub-models, i.e., an electricity price prediction model and a distributed photovoltaic power cost model to complete the model parameters, in which the electricity price prediction model utilizes a Long Short-Term Memory (LSTM) neural network. Then, the particle swarm optimization algorithm is used to solve the optimization model. Finally, the production data of two off-site pharmaceutical factories belonging to the same large group of enterprises are substituted into the model for example analysis, and it is concluded that the optimization model can significantly reduce the electricity consumption costs of the enterprises by about 7.9%. This verifies the effectiveness of the optimization model established in this paper in reducing the cost of electricity consumption on the demand side. [ABSTRACT FROM AUTHOR]

The demand for the power grid system's capacity to undergo peak-shaving is increasing as the proportion of renewable energy rises. In China, nuclear power units usually only provide a base load operation in the view of safety and economic considerations, but they do not provide load adjustment services, which undoubtedly increases the pressure of grid load adjustment. In this paper, a novel flexibility load adjustment strategy of the CHP nuclear unit is studied, which is achieved by introducing the thermal storage tank (TST) into the Rankine cycle without changing the output of the nuclear reactor. The AP1000 pressurized water reactor nuclear power unit for combined heat and power is taken as an example, and the thermodynamic model is established through the water vapor equation. Furthermore, the reference system is simulated for the goal of minimizing the imbalance between power supply and demand, and the flexibility–environment–economy benefits are evaluated. The results show that the heat storage/release of the TST may achieve power output flexible adjustment of the nuclear unit, and the power imbalance of the reference energy system is reduced from 1107.99 MWh to 457.24 MWh, a reduction of 58.73%. The introduction of a 600 MWh TST can enable the reference unit to contribute 335 MWh of peak electricity within the reference day. From the perspective of replacing the power generation output increment of coal-fired power units with equal amounts, it can achieve a reduction of 106.09 tons of coal consumption in the case day, which means that 277.73 tons of CO2 emissions can be reduced. The profit of the reference unit can be improved by CHY 70,125 via participating in load adjustment in the case day if following the time-of-use electricity price. [ABSTRACT FROM AUTHOR]

The large-scale centralized development of wind and PV power resources is the key to China's dual carbon targets and clean energy transition. The vast desert–Gobi–wilderness areas in northern and western China will be the best choice for renewable energy development under multiple considerations of resources endowment, land use constraints, technical conditions, and economic level. It is urgent to carry out a quantitative wind and PV resource assessment study in desert–Gobi–wilderness areas. This paper proposed a multi-dimensional assessment method considering the influence of the power grid and transportation infrastructure distributions, which includes three research levels, namely, the technical installed capacity, the development potential, and the development cost. Nine main desert–Gobi–wilderness areas were assessed. The wind and PV technical installed capacities were 0.6 TW and 10.7 TW, and the total development potentials were over 0.12 TW and 1.2 TW, with the full load hours of 2513 and 1759 and the average development costs of 0.28 CNY/kWh and 0.20 CNY/kWh. Finally, this paper proposed the meteorological–electrical division distribution. A case study in the Kubuqi and Qaidam Deserts was carried out on wind–wind and wind–PV collaborative development across different meteorological–electrical divisions, which can reduce by 58% the long-term energy storage capacity and decrease the total system LCOE from 0.488 CNY/kWh to 0.445 CNY/kWh. [ABSTRACT FROM AUTHOR]

Solar hydrogen production technology is a key technology for building a clean, low-carbon, safe, and efficient energy system. At present, the intermittency and volatility of renewable energy have caused a lot of "wind and light". By combining renewable energy with electrolytic water technology to produce high-purity hydrogen and oxygen, which can be converted into electricity, the utilization rate of renewable energy can be effectively improved, while helping to improve the solar hydrogen production system. This paper summarizes and analyzes the research status and development direction of solar hydrogen production technology from three aspects. Energy supply mode: the role of solar PV systems and PT systems in this technology is analyzed. System control: the key technology and system structure of different types of electrolytic cells are introduced in detail. System economy: the economy and improvement measures of electrolytic cells are analyzed from the perspectives of cost, consumption, efficiency, and durability. Finally, the development prospects of solar hydrogen production systems in China are summarized and anticipated. This article reviews the current research status of photovoltaic-photothermal coupled electrolysis cell systems, fills the current research gap, and provides theoretical reference for the further development of solar hydrogen production systems. [ABSTRACT FROM AUTHOR]

The serious problem of wind power curtailment in northern China has created a pressing need to enhance the peak-shaving ability of the power system. As the main source of power supply in northern China, combined heat and power (CHP) units have significant potential for peak-shaving. Currently, the Chinese government encourages CHP plants to increase their peak-shaving capacity by installing power-to-heat (P2H) equipment. In addition, the government has implemented auxiliary service market policies to encourage CHP plants to provide peak-shaving services. In order to maximize economic benefits for CHP plants, this paper proposes an optimal configuration method of P2H equipment with the static payback time (SPT) as the objective function. Cost and income models of installing the P2H equipment are constructed by taking into account the auxiliary service market policies. The peak-shaving income model of the CHP plant is derived emphatically as a key part of the proposed method. Finally, the district heating region in Jilin province is used as a case study example. The results show that adding the P2H equipment is significantly effective in improving the peak-shaving ability of CHP units, and investing in heat pumps is more cost-effective than electric boilers. The proposed method can be applied to other northern regions relying on CHP units for central heating, providing a valuable solution to the problem of wind power curtailment in these regions. [ABSTRACT FROM AUTHOR]

The disordered access of massively distributed energy resources (DERs) brings great challenges to the operation stability of the power grid. This paper puts forward the concept of a cluster, which gathers DERs in large quantities, small capacities, dispersion and disorder to form a large, centralized and orderly whole, namely cluster, with certain incentive measures. In this paper, a multi-timescale optimization method of day-ahead planning and intra-day rolling optimization is proposed according to the characteristics of aggregated clusters and the requirements of China's power grid architecture. Specifically, the day ahead model is proposed in two steps: the first step is to establish an optimization model with the goal of optimal fitting the target load curve and maximizing the utilization of DERs; The second step is to establish a potential game model considering the reasonable distribution of cluster benefits. Taking the minimum percentage of output correction of each cluster as the objective, considering the deviation of load forecasting and the deviation of day ahead instruction execution, an intra-day rolling optimization model is established. Finally, the application scenario of cluster participation in power grid auxiliary peak shaving is simulated and verified. The simulation results show that the cluster collaborative optimization method proposed in this paper can effectively reduce the load peak valley difference and maximize the use of cluster resources. The optimization tasks can be reasonably allocated while ensuring the stable and reliable operation of the power grid. [ABSTRACT FROM AUTHOR]

With the increasing severity of climate change, the power industry, as one of the main sources of carbon emissions, is playing an extremely important role in the process of low-carbon energy transformation. The purpose of this paper is to try to find a general method to solve the optimal path for the low-carbon evolution of the power supply structure so as to meet the challenges faced by the low-carbon transformation of the power industry in the future. This paper first uses the capacity coefficient index (CCI) to represent the power generation ability of different technologies and proposes a forecasting method for the CCI of renewable energy generation. In this paper, a two-layer optimization model considering multiple constraints is established and solved using the MPC method. The results show that China's installed capacity of renewable power could account for more than 50% in 2030, while the carbon emissions will decrease after reaching a peak in 2023. On the premise of ensuring sufficient reserve adjustment capacity of thermal power units, increasing the proportion of renewable energy generation is an important way to realize emission reduction in the power industry. [ABSTRACT FROM AUTHOR]

China and Russia have different interests in the Arctic but are forced to look for possible ways of cooperation in energy projects in the current external conditions. This changes the priorities of both countries and, accordingly, transforms the risks. Objectives of the research: to build an algorithm for identifying anthropogenic environmental risks in the context of two major players economic activities in the Arctic region: the Russian Federation and China. In the paper, we formulated an algorithm of environmental risk identification. We identified environmental hazards from the main parameter—the type of economic activity for the extraction of energy resources, premises, and factors for the occurrence of environmental hazards and compiled criteria for risk selection. Methods used: complex analysis (mixed method research): empirical and comparative methods, methods of expert assessments, the method of inductive statistics (inferential statistics) to compare the perception of risk at the level of different groups. Results: the algorithm has been formed for determining risks in the changed external conditions. Major anthropogenic environmental risks are identified from the perspective of the main players in the Arctic—Russia and China, which can help to make the necessary decisions on time and partially prevent environmental degradation. This makes it possible to identify the risks associated with conducting economic activities for the extraction of energy resources in the Arctic region. Therefore, this study contributes to a more accurate identification of anthropogenic environmental risks in the Arctic region. [ABSTRACT FROM AUTHOR]

Distributed energy resources aggregators (DERAs) are permitted to participate in regional wholesale markets in many counties. At present, new market players such as aggregators participate in China's power market transactions. However, studies related to market trading strategy have mostly focused on centralized wind power and PV generation units. Few studies have been conducted on the decision-making strategies for DERAs in China's power market. This paper proposes an auxiliary decision-making model for distributed energy systems to participate in the day-ahead market with more reasonable trading strategies. Firstly, the Gaussian mixture model (GMM) is used to deal with the uncertainties of wind power and photovoltaic (PV) output in the distributed energy system. Secondly, the information gap decision theory (IGDT) is used to deal with the uncertainty of price fluctuations in the spot electricity market. Thirdly, according to the different risk preferences of the DERAs facing market price fluctuation, the robust decision model and opportunity decision-making model in the day-ahead market are constructed, respectively. Finally, to deal with the irrational behavior of the DERAs' perception of "gain" and "loss" with market risks in China's two-tier market environment, the prospect theory and the marine predator's algorithm (MPA) are employed to obtain a day-ahead trading decision scheme for DERA. The analyses show that RDES with robust preference can withstand greater price volatility in the day-ahead market; they will reduce the bidding expectations and increase the system operating cost to improve the achievability of the expected revenue. However, DERAs under the opportunity strategy is more inclined to sell electricity to the market and offset system operating costs with revenue. The proposed model can provide strategic reference for DERAs with different risk preferences to bid in day-ahead market and can improve the level of aggregators' participation in electricity trading. [ABSTRACT FROM AUTHOR]

The global industrial chain and energy supply chain are being reconfigured at an accelerated pace, and the uncertainty of China's energy supply security is growing significantly. Empowering energy supply chains through the digital economy ( d i e c ) has a positive effect on accelerating the transformation of China's energy supply structure. This paper discusses the effect and mechanisms of the digital economy on energy supply chain efficiency ( e s c e ). Specifically, based on the panel data of 112 energy enterprises in China from 2011 to 2019, energy supply chain efficiency and digital economy at the enterprise level were evaluated through three-stage DEA and content analysis, respectively. A two-way fixed effects model and mediation effect mode were adopted to investigate the nexus of d i e c and e s c e . The results show that the digital economy improves energy supply chain efficiency, and the conclusion holds water even after a series of robustness tests and endogenous treatment. Meanwhile, its promotion effect is more significant among large enterprises, non-state enterprises and enterprises in high market-oriented regions. The main impact mechanisms are regional industrial agglomeration and technological innovation of enterprises. Based on the above conclusions, it is suggested to take advantage of the industrial aggregation effect and technological innovation effect of the digital economy to further improve the efficiency of the energy supply chain for the purpose of maintaining energy supply security. [ABSTRACT FROM AUTHOR]

The introduction of the new round of electricity reform policies has made the electricity sales companies' trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China's current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market. [ABSTRACT FROM AUTHOR]

Frequency stability is an important factor for the safety and stability of the power system operation. In a traditional power system, the operation stability is ensured by the inertia response, primary frequency modulation, and secondary frequency modulation. In recent years, in order to achieve the goal of carbon neutralization and carbon peaking, China has made great efforts in new energy development. With large-scale new energy connected to the power grid, the proportion of traditional conventional synchronous units has gradually declined. At the same time, a large number of power electronic devices have been used in the power grid, which led to the capability decline of the inertia response and primary frequency modulation. For example, the East China Power Grid has experienced a sharp frequency drop in such an environment. In order to solve the above problems, the operation principle and control mode of various new energy resources are analyzed in this paper. Moreover, the process and principle of power grid frequency response are studied and the evaluation index of frequency response capability is proposed. The research results can quantitatively evaluate the system inertia response and primary frequency modulation level and provides a judgment tool for dispatching operators and system planners. [ABSTRACT FROM AUTHOR]

Hydrogen energy leads us in an important direction in the development of clean energy, and the comprehensive utilization of hydrogen energy is crucial for the low-carbon transformation of the power sector. In this paper, the demand for hydrogen energy in various fields is predicted based on the support vector regression algorithm, which can be converted into an equivalent electrical load when it is all produced from water electrolysis. Then, the investment costs of power generators and hydrogen energy equipment are forecast considering uncertainty. Furthermore, a planning model is established with the forecast data, initial installed capacity and targets for carbon emission reduction as inputs, and the installed capacity as well as share of various power supply and annual carbon emissions as outputs. Taking Gansu Province of China as an example, the changes of power supply structure and carbon emissions under different scenarios are analysed. It can be found that hydrogen production through water electrolysis powered by renewable energy can reduce carbon emissions but will increase the demand for renewable energy generators. Appropriate planning of hydrogen storage can reduce the overall investment cost and promote a low carbon transition of the power system. [ABSTRACT FROM AUTHOR]

The variability and inhomogeneity of solar energy limits the development of solar heating systems (SHS) in many fields. In order to improve the utilization efficiency of SHS, this paper takes three typical cities (Xi'an, Dunhuang, Lhasa) as the research object, studies the operation state of SHS in student dormitory buildings, and puts forward a corresponding optimization strategy. The research shows that the reduction of water supply temperature will improve the operation efficiency and energy saving effect of a spontaneous combustion heat pump and that there is an optimal volume of heat storage water tank (HSWT), which can make the energy saving effect of SHS run better. The optimization of the SHS shows the water supply temperature is 35 °C, and the optimal volume of HSWT is 15 m3 in the "Resource-general area (Ⅲ)" represented by Xi'an, 25 m3 in the "Resource-rich area (Ⅱ)" represented by Dunhuang, and 40 m3 in the "Resource-richer area (Ⅰ)" represented by Lhasa. With the increase in the abundance of solar energy resources in the region, the optimal volume of HSWT also increases. Meanwhile, the solar energy contribution rate of the three regions in descending order is 61.3% (Lhasa), 32.8% (Dunhuang), and 25.9% (Xi'an). After optimization, the contribution of SHS increased by about 5%. The research results will help improve the efficiency of SHS in cold areas of China and make the system more efficient and energy efficient during operation. [ABSTRACT FROM AUTHOR]

LVDC buildings use a low-voltage direct current (LVDC) distribution system for energy transmission and integrate photovoltaic (PV), battery energy storage (BES) and the utility grid as building energy resources. This technology can reduce energy loss in conversion to a certain extent and increase renewable energy compared with traditional AC distribution systems. Under the national goal of carbon peaking and carbon neutrality, LVDC buildings have been proven to be a new approach to energy conservation and emission reductions, and have been applied in engineering in China. However, the construction methods and integrated technologies of those projects are not clear, and technical barriers and policy constraints for the engineering application of LVDC buildings are not systematically discussed yet. This paper presents the latest study of LVDC building engineering applications the advantages and drawbacks of LVDC development in China. First, relevant policies and standards which support the development of LVDC building industries are summarized. More than 60 practical LVDC projects are investigated, and the application characteristics and the technology status of building types, and their capacity and design methods, etc., are analyzed. The attitudes of stakeholders toward LVDC buildings are surveyed to determine the policy direction according to the demands of this technology, with reference to building practitioners who intend to engage in LVDC projects. [ABSTRACT FROM AUTHOR]

Carbon neutrality is one of the most important goals for the Chinese government to mitigate climate change. Coal has long been China's dominant energy source and accounts for more than 70–80% of its carbon emissions. Reducing the share of coal power supply and increasing carbon capture, utilization, and storage (CCUS) in coal power plants are the two primary efforts to reduce carbon emissions in China. However, even as energy and water consumed in CCUS are offset by reduced energy consumption from green energy transitions, there may be tradeoffs from the carbon–energy–water (CEW) nexus perspective. This paper developed a metric and tool known as the "Assessment Tool for Portfolios of Coal power production under Carbon neutral goals" (ATPCC) to evaluate the tradeoffs in China's coal power industry from both the CEW nexus and financial profits perspectives. While most CEW nexus frameworks and practical tools focus on the CEW nexus perturbation from either an external factor or one sector from CEW, ATPCC considers the coupling effect from C(Carbon) and E(Energy) in the CEW nexus when integrating two main carbon mitigation policies. ATPCC also provides an essential systematic life cycle CEW nexus assessment tool for China's coal power industry under carbon-neutral constraints. By applying ATPCC across different Chinese coal industry development portfolios, we illustrated potential strategies to reach a zero-emission electricity industry fueled by coal. When considering the sustainability of China's coal industry in the future, we further demonstrate that reduced water and energy consumption results from the energy transition are not enough to offset the extra water and energy consumption in the rapid adoption of CCUS efforts. However, we acknowledge that the increased energy and water consumption is not a direct correlation to CCUS application growth nor a direct negative correlation to carbon emissions. The dual effort to implement CCUS and reduce electricity generation from coal needs a thorough understanding and concise strategy. We found that economic loss resulting from coal reduction can be compensated by the carbon market. Carbon trading has the potential to be the dominant profit-making source for China's coal power industry. Additionally, the financial profits in China's coal power industry are not negatively correlated to carbon emissions. Balance between the carbon market and the coal industry would lead to more economic revenues. The scenario with the most rapid reduction in coal power production combined with CCUS would be more sustainable from the CEW nexus perspective. However, when economic revenues are considered, the scenario with a moderately paced energy transition and CCUS effort would be more sustainable. Nevertheless, the ATPCC allows one to customize coal production scenarios according to the desired electricity production and emission reduction, thus making it appropriate not only for use in China but also in other coal-powered regions that face high-energy demands and carbon neutrality goals. [ABSTRACT FROM AUTHOR]

The low-carbon transformation of the power industry is of great significance to realize the carbon peak in advance. However, almost a third of China's CO2 emissions came from the power sector in 2019. This paper aimed to identify the key drivers of CO2 emissions in China's power industry with the consideration of spatial autocorrelation. The spatial Durbin model and relative importance analysis were combined based on Chinese provincial data from 2003 to 2019. This combination demonstrated that GDP, the power supply structure and energy intensity are the key drivers of CO2 emissions in China's power industry. The self-supply ratio of electricity and the spatial spillover effect have a slight effect on increasing CO2 emissions. The energy demand structure and CO2 emission intensity of thermal power have a positive effect, although it is the lowest. Second, the positive impact of GDP on CO2 emissions is decreasing, but that of the power supply structure and energy intensity is increasing. Third, the energy demand of the industrial and residential sectors has a greater impact on CO2 emissions than that of construction and transportation. For achieving the CO2 emission peak in advance, governments should give priority to developing renewable power and regional electricity trade rather than upgrading thermal power generation. They should also focus on promoting energy-saving technology, especially tapping the energy-saving potential of the industry and resident sectors. [ABSTRACT FROM AUTHOR]

A novel pumped hydro combined with compressed air energy storage (PHCA) system is proposed in this paper to resolve the problems of bulk energy storage in the wind power generation industry over an area in China, which is characterised by drought and water shortages. Thermodynamic analysis of the energy storage system, which focuses on the pre-set pressure, storage volume capacity, water air volume ratio, pump performance, and water turbine performance of the storage system, is also presented. This paper discovers how such parameters affect the performance of the whole system. The ideal performance of this novel system has the following advantages: a simple, highly effective and low cost structure, which is comparable to the efficiency of a traditional pumped hydro storage system. Research results show a great solution to the current storage constraints encountered in the development of the wind power industry in China, which have been widely recognised as a bottleneck in the wind energy storage industry. [ABSTRACT FROM AUTHOR]

Electricity consumption is often the hotspot of life cycle assessment (LCA) of products, industrial activities, or services. The objective of this paper is to provide a consistent, scientific, region-specific electricity-supply-based inventory of electricity generation technology for national and regional power grids. Marginal electricity generation technology is pivotal in assessing impacts related to additional consumption of electricity. China covers a large geographical area with regional supply grids; these are arguably equally or less integrated. Meanwhile, it is also a country with internal imbalances in regional energy supply and demand. Therefore, we suggest an approach to achieve a geographical subdivision of the Chinese electricity grid, corresponding to the interprovincial regional power grids, namely the North, the Northeast, the East, the Central, the Northwest, and the Southwest China Grids, and the China Southern Power Grid. The approach combines information from the Chinese national plans on for capacity changes in both production and distribution grids, and knowledge of resource availability. The results show that nationally, marginal technology is coal-fired electricity generation, which is the same scenario in the North and Northwest China Grid. In the Northeast, East, and Central China Grid, nuclear power gradually replaces coal-fired electricity and becomes the marginal technology. In the Southwest China Grid and the China Southern Power Grid, the marginal electricity is hydropower towards 2030. [ABSTRACT FROM AUTHOR]

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified. [ABSTRACT FROM AUTHOR]

In China, with the increasing permeability of wind power, the power supply capacity is enough overall, but has shortage in partial-time. During peak hours, the capability of wind power consumption is poor and the power balance becomes more difficult. In order to maximize the utilization of wind power, the net loads are chosen as the response objectives, which contain significant uncertainties and have no probabilistic distribution characteristics. Under the traditional day-ahead power dispatch mode with fixed length time intervals and in the regions with insufficient hydroelectricity, the thermal generators take charge of the peak-load shaving. The frequent adjustments of thermal power output affect the system operation safety, economic benefits, and environmental benefits. Thus, a time-interval-varying optimal power dispatch strategy based on net load time-series characteristics is proposed in this paper. The net loads respond differently to intervals. The length of each time interval is determined based on the net load time-series characteristics analyzed by random matrix theory. The dispatch mode in each time interval is determined according to the characteristic quantification index calculated by the empirical modal decomposition and sample entropy. The proposed strategy and method can extend the continuous and stable operation time of the thermal generators, reduce the coal consumption caused by the ramping operation, and improve the safety, stability, and economy of the system. Furthermore, the proposed dispatch mode is environmentally friendly with reduced environmental cost and increased carbon credits. An actual provincial power grid in northeast China is taken as the example to verify the rationality and effectiveness of the proposed method and strategy. [ABSTRACT FROM AUTHOR]

In order to implement the national need for the optimal allocation of power resources, power load forecasting, as an important research topic, has important theoretical and practical significance. The purpose of this study is to construct a prediction model considering climate factors based on a large amount of historical data, and to prove that the prediction accuracy is related to both climate factors and load regularity. The results of load forecasting are affected by many climate factors, so firstly the climate variables affecting load forecasting are screened. Secondly, a load prediction model based on the IPSO-Elman network learning algorithm is constructed by taking the difference between the predicted value of the neural network and the actual value as the fitness function of particle swarm optimization. In view of the great influence of weights and thresholds on the prediction accuracy of the Elman neural network, the particle swarm optimization algorithm (PSO) is used to optimize parameters in order to improve the prediction accuracy of ELMAN neural network. Thirdly, prediction with and without climate factors is compared and analyzed, and the prediction accuracy of the model compared by using cosine distance and various error indicators. Finally, the stability discriminant index of historical load regularity is introduced to prove that the accuracy of the prediction model is related to the regularity of historical load in the forecast area. The prediction method proposed in this paper can provide reference for power system scheduling. [ABSTRACT FROM AUTHOR]

This paper analyzes the macro-economic impact of controlling fossil energy consumption in China by using a social accounting matrix framework. The empirical results show that, first, restricting the exploitation of fossil energy resources will lead to a decline in the output of other production activities, thereby reducing the factor income and the living standards of residents. Second, improving energy efficiency can promote increased output in other production sectors, and raise factor returns and residents' living standards. Third, raising the price of energy products will result in higher costs of the entire society. The stronger the dependence on the energy sector, the greater the increase in the industrial cost. Therefore, the government should increase investment in energy efficiency, keep to energy intensity constraints, restrict the extraction amount of energy resources, and reasonably control energy prices based on market environmental factors. [ABSTRACT FROM AUTHOR]

With the rapid progress of socio-economic development and urbanization in China, a wide variety of literature has focused on the phenomenon of energy-consumption disparity, which in turn could be related to numerous fundamental energy dilemmas that China must deal with now or soon, including energy use inefficiency, regional energy shortage, insufficient use of green energy, etc. However, in most cases, only a tendency scenario is discussed, while identifying which factors are more likely to affect the improvement of energy supply/use has not yet been fully explored. Therefore, this paper attempts to explore differences in energy consumption in specific, household-level aspects. Based on the information provided by Chinese General Social Survey (CGSS2015), the Gini coefficient and the Lorentz asymmetry coefficient are used to measure the difference among various categories of energy type and end use within and between different geographical sub-groups. The findings show that: (1) household energy-consumption behaviors exhibit a complicated effect on the overall level of energy-consumption difference; (2) from the supply side, energy users show the most significant difference in biomass energy consumption, while from the demand side, the contribution of space heating to the difference in total energy consumption is the highest; (3) a great urban–rural difference in energy consumption is generally observed with its difference within rural areas being much greater than in urban areas; (4) the eastern, middle and western regions weight differently in explaining the overall difference of energy consumption. These findings provide meaningful materials and references for policymakers in China to understand the overall situation of individual energy consumption to a great extent, and to locate key points to reform the current energy policy framework. [ABSTRACT FROM AUTHOR]

The concept of the smart grid has been gaining more and more attention worldwide since it was proposed by the U.S. Electric Power Research Institute in 2001. Recently, it has been propelled again by the promotion of low carbon economies in developing countries. To satisfy the exponential increase in electricity demand and alleviate environmental degradation caused by fossil fuel-based power generation, China has made great efforts in constructing a smart grid as a substitution of traditional energyintensive power grid. In the 12th Five-Year Plan in particular, it was stated that emphasis should be placed on the development of renewable energy and smart grids. The objective of this paper is to provide an insight into the current research on smart grids, and shed light on the development of smart grids in China, based on the analysis of which, the obstacles and barriers in the development process are identified. Finally, policy prospects on the construction of smart grids in China are proposed from the aspects of technology, administration and management. [ABSTRACT FROM AUTHOR]

The new energy industry (NEI) is key to achieving a clean and low-carbon economy. Improving its technical efficiency, a factor reflecting the ability of an enterprise or industry to produce maximum economic outputs from a given set of inputs and production technologies, is vital for the healthy development of the NEI. Nevertheless, due to the fragmentation of industry data, it is still difficult to accurately measure the technical efficiency of China's NEI and understand the driving factors behind it. Based on the panel data derived from 17,457 observations on new energy enterprises in 29 Chinese provinces during 1998 and 2013 (latest data available), this paper uses data envelopment analysis (DEA) and geographically and temporally weighted regression (GTWR) for the first time to investigate the spatiotemporal characteristics and driving factors of the technical efficiency of China's NEI. The results show that the technical efficiency of China's NEI was relatively low and increased modestly from 0.44 in 1998 to 0.52 in 2013. Exploring the reasons from the perspective of spatiotemporal heterogeneity, we find that enterprise scale and technological progress are the major driving factors for increasing NEI's technical efficiency. However, the role of economic development in improving efficiency has gradually disappeared. Moreover, the negative effect of state-owned enterprises on efficiency becomes increasingly obvious. The effect of new energy resources is negligible. Our main contribution is the technical efficiency of China's NEI which is measured at the provincial level and its main driving factors are explored by considering spatiotemporal heterogeneity. Accordingly, we put forward some specific recommendations to improve the technical efficiency of China's NEI. [ABSTRACT FROM AUTHOR]

Offshore wind is considered a crucial part in the future energy supply. However, influenced by weather conditions, the maintenance of offshore wind turbine system (OWTs) equipment is challenged by poor accessibility and serious failure consequences. It is necessary to study the optimized strategy of comprehensive maintenance for offshore wind farms, with consideration of the influences of incomplete equipment maintenance, weather accessibility and economic relevance. In this paper, a Monte Carlo algorithm-improved factor is presented to simulate the imperfect preventive maintenance activity, and waiting windows were created to study the accessibility of weather conditions. Based on a rolling horizon approach, an opportunity group maintenance model of an offshore wind farm was proposed. The maintenance correlations between systems and between equipment as well as breakdown losses, maintenance uncertainty, and weather conditions were taken into account in the model, thus realizing coordination of maintenance activities of different systems and different equipment. The proposed model was applied to calculate the maintenance cost of the Dafengtian Offshore Wind Farm in China. Results proved that the proposed model could realize long-term dynamic optimization of offshore wind farm maintenance activities, increase the total availability of the wind power system and reduce total maintenance costs. [ABSTRACT FROM AUTHOR]

The undersupplies of feedstock and high costs have hindered the development of China's biomass power generation. In this paper, the noncooperative game, farmer–broker cooperative game, and broker–biomass power plant cooperative game, under government incentives, are constructed and analyzed. The optimal decision strategies and profits for these three cases are obtained, while numerical examples and sensitivity analysis are conducted, aiming at illustrating some specific features of the games. It is shown that the government plays a critical role in the development of utilizing agribiomass for power generation and can work better in cooperative games. In addition, both agribiomass supply quantity and profits of supply chain members are higher in cooperative than in noncooperative game. Meanwhile, farmers can get the maximum profit in the broker–biomass power plant cooperative game, while biomass power plant makes the maximum profit in the farmer–broker cooperative game. To guide the healthy development of the industry, there is an urgent need for further exploration of the biomass supply chain management and coordination issue. Specifically, the cooperative game for establishing optimal feedstock price subsidy policy will be done by way of adjusting government incentives and alliance profit distribution. [ABSTRACT FROM AUTHOR]

This study aims to find the relationship between energy resource dependence and economic growth in consideration of interprovincial heterogeneity. This paper first uses panel data from 14 provinces with rich energy resources in China between 2001 and 2016 as a whole to test the energy resource curse hypothesis. It finds that there is no obvious resource curse from a general perspective. It further makes time prediction and transmission channel analysis based on regressions of each province and classifies them into four groups according to the different degrees of the resource curse. It shows the different roles of resource dependencies in different groups. Twelve provinces are subject to different degrees of the resource curse, among which, six provinces would eventually experience negative economic growth if they increase the degree of resource dependence. Next, this study discusses the mechanism of one particular group, "invisible energy resource curse", which is when energy resources directly promote but indirectly hinder economic growth. Finally, based on the results, the present study offers policy suggestions according to provinces' heterogeneous curse levels. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei region has abundant biomass resources, which are difficult to collect and thus are underutilized. However, the potential estimation of biomass energy can result in a comprehensive understanding of bioenergy resources in order to establish a technology roadmap for the region's bioenergy development. Therefore, it is essential to estimate the potential of Beijing-Tianjin-Hebei biomass resources and bioenergy utilization. In this paper, the amount of main biomass resources for possible energy use and bioenergy utilization are calculated based on a statistical data estimation method for crop residues; human, poultry, and livestock manure; and municipal solid wastes. On the basis of biomass resources and bioenergy utilization potential, the technology roadmap is established. The results show that the amount for available biomass energy use is unevenly distributed in the Beijing-Tianjin-Hebei region, and the largest amount of resources is crop residues (36.52 million tons or 18.26 million tons coal equivalent). The biogas from human, poultry, and livestock manure and densified solids from crop residue technology roadmap is suitable for the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Power quality is one of many issues affecting the traction power supply system. Prominent among the causes of poor power quality is voltage low-frequency oscillation (VLFO). In this paper, a fuzzy-based PI (FPI) controller to optimize the performance of the traction line-side converter (TLSC) and suppress the effect of VLFO is proposed. Firstly, the mathematical model of China's railway high-speed five single-phase TLSC is developed, and then the FPI control unit is designed based on specific requirements. The fuzzy antecedent and consequence rules were generated based on the expert and previous knowledge of TLSC operation. An offline simulation of the proposed control scheme under different loads and parameters is conducted to verify the designed. To validate the model, the traction power supply system (TPS) is built on the field-programmable gate array (FPGA) real-time digital simulator (FPGA-RTDS), while the FPI control algorithm is load on modeling tech rapid control prototyping (RCP) real-time digital controller (RTDC). Hardware-in-the-loop (HIL), and offline simulation studies between current decoupling (PI) control, sliding mode control (SMC), and the proposed control method confirms in addition to excellent dynamic performance; the proposed method can successfully suppress the effect of VLFO. [ABSTRACT FROM AUTHOR]