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      • WANG Ke, WU Feng, CAO Ruolin, YAO Jianguo, HUANG Qifeng, LI Yaping

        Available online:June 19, 2024  DOI: 10.7500/AEPS20231030001

        Abstract:Studying demand response (DR) behavior in the market environment and exploring the real motivations and characteristics of demand-side flexible resources participating in the market is conducive to promote the participation of load-side flexible resources in the operation of the power grid, correcting and optimizing the electricity market mechanism, and enhancing the flexible regulation capabilities of the new power system. Firstly, the research on DR behavior characteristics and models in the market environment is reviewed and summarized. The diversified market environments for DR resource participation is sorted out from the perspectives of mature electricity markets in Europe and United States and the construction of electricity markets in China. Secondly, the response behavior characteristics of demand-side flexible resources in the market environment are analyzed from 6 perspectives of preference diversity, utility optimization, behavioral correlation, behavioral game, price elasticity, and response uncertainty. Next, combining principles from behavioral economics, a universial mathematical model of DR behavior is constructed, organizing the market response behavior modeling methods adapted to different behavioral characteristics from the perspectives of response mechanisms and data-driven approaches, and conducting adaptability analysis. Finally, future research directions are expected from the perspectives of social impact, insufficient information, user limited rationality, optimal decision-making in multiple markets, and comprehensive DR

      • LIU Qinyi, HUANG Weihuang, GUO Zhu, ZHU Hongxi, LIU Fei

        Available online:June 19, 2024  DOI: 10.7500/AEPS20231005002

        Abstract:Due to the mismatch of the line impedance of each converter, it is difficult to realize the accurate reactive power sharing for multiple parallel grid-forming converters under the traditional droop control strategy. In order to improve the reactive power sharing accuracy, this paper analyzes the power sharing mechanism of the parallel converters and proposes an adaptive virtual impedance design method that combines the reactive power sharing error and the output voltage of the converter. Under the operation condition where the actual line impedance is unknown and there is no interconnection communication between distributed units, the reactive power sharing strategy based on the proposed method can achieve high reactive power sharing accuracy. It also improves the contradiction between the reactive power sharing accuracy and the output voltage drop that exists when the virtual impedance is introduced. And the circulating current between converters is suppressed. In addition, the small-signal stability analysis of the converter is performed to rationally design the control parameters. The hardware-in-loop simulation results verify the effectiveness of the proposed control strategy.

      • WU Yufeng, LIU Dong, LIAO Wang, WEI Xu, CHEN Guanhong, CHEN Fei

        Available online:June 18, 2024  DOI: 10.7500/AEPS20231007001

        Abstract:With the development of active distribution networks, the impact of communication conditions on voltage control becomes more significant. The interruption in communication between the main station and PV inverters hinders the adjustment of reactive power, resulting in voltage violations in the distribution network. This paper proposes a hierarchically-coordinated voltage control method for active distribution network considering the communication conditions. This paper models the cyber side of the distribution network to describe the information interaction of the control process. The proposed method achieves effective adjustment of reactive power output for each inverter under different communication conditions by the cooperation of the central and local hierarchies. The central hierarchy establishes the droop output constraint for inverters under communication conditions, the power flow constraint of distribution networks, and the multi-objective function covering both network loss and voltage deviation. Subsequently, the central hierarchy solves the linear optimization problem. The local hierarchy selects droop parameters based on inverter communication conditions. These parameters are either optimized centrally or preset in advance. By analyzing the simulation result for IEEE 118 system, effectiveness of the proposed method is verified. The proposed method can ensure that the voltage of the distribution network remains within the normal range during communication interruptions, while achieving global optimization of network loss and voltage distribution

      • CHEN Tingwei, ZENG Jun, ZHANG Xuan, Zhao Ziyu, HUANG Xiangmin, LIU Junfeng

        Available online:June 18, 2024  DOI: 10.7500/AEPS20231016004

        Abstract:The stable operation of the power grid with large-scale distributed renewable energy is an important research direction for optimizing the operation of the power grid under the new situation of low-carbon transformation. In response to the multi-agent characteristics and randomness issues brought about by the participation of the clusters for distributed renewable energy aggregation in optimizing power grid operation, an optimization method for cluster-grid cooperative interaction for large-scale distributed renewable energy integration is proposed. First, by constructing a high-dimensional inscribed rectangle in the constraint space of flexible resources, an adjustable power domain is formed to represent the flexible adjustment range, by constructing a flexible constraint of adjustable power domain to fully cover the fluctuation range of renewable energy clusters, the optimization results are feasible in all scenarios within the random fluctuation range of renewable energy clusters. Then, based on the self-interested and autonomous characteristics of multi-agents in power grid operation, an optimization model of potential game cluster-grid cooperative interaction is constructed to meet the requirements of parallel optimization for homogeneous individuals and serial optimization for non-homogeneous individuals. A distributed optimization method and process suitable for the model are proposed. Finally, simulation examples show that the proposed method effectively achieves multi-agent collaborative interaction optimization and ensures the feasibility of the optimization results in all scenarios.

      • HUANG Lingling, SHI Xiaohua, FU Yang, LIU Yang, YING Feixiang

        Available online:June 14, 2024  DOI: 10.7500/AEPS20231101006

        Abstract:Graph convolution networks (GCNs) possess strong data correlation mining capabilities and have gained significant attention in the field of wind power prediction in recent years. However, traditional ultra-short-term wind power prediction based on GCN model is difficult to deal with the dual-mode problem of the two core factors (wind speed and unit state information) that affect wind power simultaneously. Based on this, an ultra-short-term power prediction for offshore wind farms based on dual channel graph convolution network (DCGCN) model is proposed. Firstly, a unit state index model based on the theoretical power curve is established to quantitatively characterize the impact of unit state changes on its power generation capacity. Secondly, the graph topology of the offshore wind farm is constructed, and the correlation relationship model between the wind speed captured by each unit of the wind farm and the unit state information is established based on the wind speed and state adjacency matrices. Finally, an ultra-short-term power prediction method of wind farm based on DCGCN is established.Case study results indicate that the proposed model is helpful to improve the training efficiency and prediction accuracy of the wind farm power prediction model.This work is supported byFoundation supported by National Natural Science Foundation of China (No. 52177097) and Scientific Research and Innovation Plan Program of Shanghai Education Commission (No. 2021-01-07-00-07-E00122).

      • JIANG Xinyue, ZHANG Si, WANG Yunchu, XU Lizhong, YANG Li, LIN Zhenzhi

        Available online:June 14, 2024  DOI: 10.7500/AEPS20231205002

        Abstract:With the continuous advancement of the integration of high proportion of renewable energy and national “dual carbon” goal, the advantages of flexible operation, rapid start-up and shutdown, and low-carbon emission intensity of gas units have attracted more attention. However, even considering the demand of natural gas for off-contract and peak power generation, the relatively fixed or even tight daily gas supply is still difficult to cope with the change of natural gas demand under different meteorological conditions, which directly affects the economy and reliability of the new power system. Based on this, a gas-electricity coordinated optimal dispatch strategy considering the flexible natural gas supply constraint is proposed. Firstly, the flexible natural gas supply mechanism of multi-day overall allocation and natural gas consumption assessment under limited supply is designed. Secondly, a dispatch risk assessment method considering the uncertainty of wind and photovoltaic power and the transmission of price fluctuations in the gas-electricity market is proposed. Then, the multi-day optimal dispatch model of the system is constructed with the objective of minimizing the system operation cost and risk cost. Finally, a modified power system with natural gas supply in a province in China is taken as an example to verify the validity of the constructed model. The case analysis results show that the multi-day dispatch combined with the flexible natural gas supply mechanism can realize the flexible allocation of the gas generation between the daily load demand and the wind/photovoltaic power output.

      • YANG Fan, CAO Jiuzhou, YE Lingyue, LI Dongdong, LIN Shunfu, ZHAO Yao, SHEN Yunwei

        Available online:June 14, 2024  DOI: 10.7500/AEPS20231220005

        Abstract:Due to the varying costs of distributed generators in the AC/DC hybrid microgrids, it is easy to cause higher system costs with the droop control that distributes power according to the capacity ratio. A droop control based on incremental costs is proposed to address this issue. To further eliminate the impact of mismatched line impedances on power distribution accuracy and fully consider the economic operation of the microgrid, this paper proposes a hierarchical-distributed control strategy based on the consensus algorithm. This control strategy is divided into subnetwork-level control and system-level economic control. The subnetwork-level control introduces frequency/voltage secondary control term and cost secondary control term in the incremental cost-based droop control to restore the AC frequency and DC voltage, and realizes the economic power distribution of distributed generators among the subnetworks at the same time. In the system-level economic control, “relative frequency index” and “relative voltage index” are introduced to construct the local control strategy of the bidirectional interconnected converter. The power secondary control term based on the consistency algorithm is further introduced to realize the incremental cost of each distributed generator to be consistent, so as to achieve the global optimal economic operation of the system. Finally, the simulation of the AC/DC hybrid microgrid model is carried out to verify the effectiveness of the proposed control strategy.

      • YANG Chen, XIE Yeyuan, DUAN Jun, WANG yu, REN Tieqiang, ZHANG Junjun

        Available online:June 14, 2024  DOI: 10.7500/AEPS20230719001

        Abstract:Modular multilevel matrix converter (M3C) is currently the main power electronic equipment used for frequency conversion in flexible low-frequency transmission systems. M3C contains 9 bridge legs and is widely used in high-voltage and high-power situations with a large number of series modules, which poses special testing requirements for the production of its equipment sub-modules. On the basis of analyzing the steady-state voltage and current of M3C bridge legs, a drag operation test system is designed for several series bridge-leg submodules (valve sections), which can perform equivalent power operation tests to assist in the production and factory testing of M3C equipment. A control strategy for the push-push test system is proposed, and a valve section push-push test system consisting of two sets of four series sub-modules is constructed and verified through relevant experiments. The experimental results show that the proposed test system can meet the equivalent power operation test of M3C bridge arm series submodules, and does not require high power consumption from the power source.

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      Volume 48,2024 Issue 11

      • GUAN Li, CHANG Jiang, SUN Dayan, WANG Delin, HUANG Guodong, ZHANG Ruiwen, ZHAO Tianhui

        2024,48(11):2-10, DOI: 10.7500/AEPS20230728012

        Abstract:The inter-provincial electricity spot market has been continuously operating for more than two years. Based on the implementation of inter-provincial medium- and long-term transactions, it has achieved market-oriented electricity surplus and shortage mutual assistance and large-scale optimal allocation of resources. The practice shows that the inter-provincial electricity spot market has played an important role in improving the supply capacity of the whole power grid and promoting the consumption of clean energy. Firstly, this paper describes the trial operation and effectiveness of the inter-provincial electricity spot market since 2022. Secondly, the mechanism of inter-provincial electricity spot trading is analyzed from the market framework, the clearing mechanism, and the declaring mechanism. Finally, based on the current situation of inter-provincial electricity spot market construction, the future development directions are prospected.

      • ZHANG Hengji, WANG Haining, YUAN Mingzhu, YIN Xuan

        2024,48(11):11-23, DOI: 10.7500/AEPS20230314005

        Abstract:The medium- and long-term electricity market in China has achieved good results after years of construction. But with the construction of new power systems, the overall market structure has changed, and medium- and long-term trading faces new challenges in achieving market connection and integration, supporting the entry into the market and consumption of renewable energy. This paper first outlines the key points for the construction of the medium- and long-term market at the current stage. Then, a review and commentary of the current medium- and long-term market trading mechanisms are conducted from four aspects: differences in trading rules, connection with the spot market, coordination between the two markets, and operation of the green electricity market. Finally, suggestions are proposed for the construction direction of the future medium- and long-term market from the perspective of market unity and green development.

      • JING Zhaoxia, LI Yupeng, ZHAO Yuxuan, LIU Zhaoxi

        2024,48(11):24-36, DOI: 10.7500/AEPS20231030008

        Abstract:In the context of the low-carbon transformation of the energy system, the operation of electricity markets in various countries faces multiple policy boundaries. To solve the problem of how governments should intervene in markets to achieve multiple objectives, further research on hybrid electricity markets is conducted based on the two-stage market competition theory, combined with the driving relationship between government and market in the electricity market system. First, the equilibrium principles and challenges of traditional electricity markets are deeply analyzed, and the reasons for government intervention in electricity markets are classified and discussed, including externalities, imperfection in the market system, imperfection in market mechanisms, and imperfection in market competition. Then, the significance and challenges of the basic structure of hybrid electricity markets based on the two-stage market competition theory are discussed. On this basis, a two-dimensional four-module hybrid electricity market extension structure is proposed, which includes short-term and long-term, market and government. And the key steps and contents of its design are analyzed. Finally, the design of government intervention methods in hybrid electricity markets is discussed based on the problems existing in China’s electricity market construction.

      • XU Qifeng, PAN Weiwei, QIAO Songbo, LI Zhiyi, LUO Renjie

        2024,48(11):37-45, DOI: 10.7500/AEPS20230228004

        Abstract:The launch of national green electricity trading provides a sufficient market-based approach for the realization of the environmental value of green electricity under the background of low-carbon transformation in the power system. With the large-scale permeation of various trading entities and the diversification of green electricity demand on the user side, the current green electricity trading mechanism needs further research to improve flexibility and credibility of certification. It is urgent to optimize the mechanism design to meet the requirements of refined transaction involving massive entities and the reasonable value distribution. Thus, a dual-account mechanism for green electricity trading based on the blockchain technology is proposed in this paper. First, the dual-account management mechanism consisting of the trading account and consumption account is set up,where the circulation of green property and the generation of consumption certificates are recorded separately. Combining with the circulation of green properties, the transaction mode of “coordination of certification and electricity” is designed, which aims to achieve effective connection between green electricity trading and green certificate trading. Finally, the rule contract writing, post-verification design of each transaction process, and block storage design of consumption certificate are carried out for green electricity trading from the perspective of blockchain technology. Trading entities are evaluated by using the historical performance rate to reduce the risk of market operation. The case experiment shows that the mechanism can effectively improve the flexibility and credibility of green electricity trading and alleviate the pressure of renewable energy subsidies to a certain extent.

      • ZHANG Xian, SHI Zhuyu, CHANG Xin, WANG Dong, LI Da, CHEN Chunyi

        2024,48(11):46-54, DOI: 10.7500/AEPS20231016002

        Abstract:The evaluation and certification of green electricity consumption are critical in the construction of the green electricity market. Currently, there is a lack of effective technical verification methods for evaluating and certifying green electricity consumption. Moreover, the evaluation process faces technical challenges regarding privacy protection of green electricity consumption data. An evaluation and certification model of green electricity consumption based on privacy computing is proposed. First, a novel homomorphic encryption method is devised to support the privacy protection of multiple parties involved in evaluation of green electricity consumption. In contrast to traditional homomorphic encryption algorithms, this method demonstrates higher efficiency in the encryption and decryption processes, and the procedure of encryption and decryption can be segmented while maintaining full homomorphism. Then, a collaborative privacy computing model of homomorphic encryption and trusted execution environment (TEE) is proposed to solve the problem that the traditional homomorphic encryption algorithm can not support the nonlinear operation in ciphertext, and the calculation and storage cost are high. Finally, based on the verifiability mechanism of the computing process of TEE and the tamper-proof characteristics of blockchain certificate data, a reliability assurance mechanism of green electricity consumption evaluation results is established. Theoretical and experimental results demonstrate that the proposed scheme can efficiently compute the evaluation data involving privacy protection for green electricity consumption, which takes approximately 0.114 seconds to complete the green electricity consumption evaluation of privacy protection for 10 000 consumers.

      • GUO Weijia, LIU Dunnan, XIE Kai, LI Zhu, LI Genzhu, SUN Tian

        2024,48(11):55-63, DOI: 10.7500/AEPS20240408001

        Abstract:With the integration of large-scale renewable energy, the secure power-supply ensurance situation of power grids has become increasingly severe. Under this background, a joint clearing mechanism for electric power energy and balance regulation service is established with consideration of the external security costs of renewable energy. The electric power energy costs and the balance regulation service costs are coupled and superposed,and through the joint clearing, the balance regulation service is organized in a market-oriented manner to reflect the energy value and the security value of electric power energy at a reasonable price, so as to give a clear price signal to facilitate the sharing of balance responsibilities. Finally, through the case analysis, it is verified that the proposed operation mechanism has the significant advantages in terms of economy and robustness.

      • QU Ying, XIAO Yunpeng, ZHANG Chen, WANG Xiuli

        2024,48(11):64-76, DOI: 10.7500/AEPS20230206005

        Abstract:The increase in the proportion of renewable energy has led to a significant increase in the requirement for flexible regulation resources in the power system. However, the traditional capacity market only aims to guarantee the system adequacy during the peak load period. There may still be a shortage of power supply due to insufficient flexible regulation capacity. Therefore, this paper proposes a robust optimal clearing model and a pricing method for the capacity market that considers the flexible regulation requirement. The settlement rules for different resource types are provided. And it is verified that the proposed capacity market pricing mechanism can satisfy the properties of social efficiency, balance of payments, individual rationality, and incentive compatibility. Finally, the IEEE 118-bus system is used for the case study. The results show that the proposed capacity market mechanism can simultaneously guarantee the adequacy of the system to cope with peak load and flexible regulation requirement, reasonably describe the capacity value of flexible regulation resources, and effectively distinguish between the effective capacity contribution of different types of resources and the responsibility of causing flexible regulation requirement, which helps to guide renewable energy units to suppress their output uncertainty fluctuations and incentivize flexible resources to provide capacity to meet system flexible regulation requirement.

      • HUANG Haitao, JIA Xiufeng, CHENG Kai, XU Jiadan

        2024,48(11):77-87, DOI: 10.7500/AEPS20231008009

        Abstract:In order to adapt to the new trend of capacity resource diversification and the new requirements of investment incentive in the new power system, aiming at the construction problem of sufficiency guarantee mechanism for generation capacity in China, the capacity subsidy electricity price mechanism and capacity evaluation method are constructed with consideration of diversified source, storage and load resources. First, based on the theory of marginal generation cost, the “lack of money” problem in the pure electric energy market and the principle of capacity pricing are revealed, the method of setting capacity subsidy electricity price is put forward, and the capacity adjustment coefficient is introduced to effectively stimulate investment. Then, combined with the different characteristics of source, storage and load resources, the peak load capacity support is provided for the system, the active power output and scheduling models of wind, solar and water renewable power sources and new load storage entities are established, and the two-state method is integrated to construct various component models. The reliability evaluation method of sufficient capacity of diversified resources is established by using the sequential Monte Carlo simulation. On this basis, a practical evaluation method for classification differences is proposed, which overcomes the defects of traditional evaluation methods of wind,solar,energy storage and load, scientifically reflects the actual contribution of various resources to capacity support, and takes into account the simplicity and transparency of calculation. Finally, the case verification shows that the mechanism can realize fair compensation, provide scientific power generation investment signal, and ensure cost recovery, sufficient generation capacity and stable electricity price. The practical evaluation method better balances the relationship between evaluation accuracy and policy implementation.

      • ZHANG Hongji, DING Tao, HUANG Yuhan, XIE Liushuangfei, HE Yuankang, SUN Xiaoqiang

        2024,48(11):88-99, DOI: 10.7500/AEPS20231022001

        Abstract:Pumped storage power stations, as effective flexibility resources for power systems, will become crucial in ensuring the safe and stable operation of new power systems. The formulation of reasonable schemes for recovering the fixed costs of construction of pumped storage power stations is a key issue in supporting system operation and stimulating investment. In the context of marketization operations for pumped storage power stations, this paper constructs a capacity charge pricing model that sequentially integrates the pumped storage power stations into the spot and ancillary service markets, achieving regular recalibration of the unallocated costs of pumped storage power stations with the objective of revenue and expenditure balance during the operation period. Meanwhile, considering the potential entities for allocating the capacity charges of pumped storage power stations, a utility-proportional Vickrey-Clarke-Groves (VCG) mechanism is proposed to allocate costs of the capacity charges of pumped storage power stations, quantify the substitutive benefits of allocation entities on both the source and load sides, and proportionally allocate the capacity charges. Effectiveness of the proposed method is validated through simulation analysis of actual system cases.

      • CHEN Dapeng, LIU Qing

        2024,48(11):100-110, DOI: 10.7500/AEPS20230908004

        Abstract:The development experience of the European unified electricity market can provide significant inspiration for the construction of the Chinese electricity market. The day-ahead electricity market is the basic link and essential component of the European unified electricity market. Firstly, the basic situation of the European day-ahead electricity market is sorted out, the concept of main market orders is introduced, and the characteristics and applications of market orders are further summarized and compared. Secondly, the basic model for European day-ahead electricity market clearing is built, the main process of the solution algorithm is given, and its basic principle is analyzed. At the same time, the case analysis and application expansion are carried out. Finally, combined with the research focus on the European day-ahead electricity market, the future development trends are analyzed, and the enlightenment and suggestions for the construction of the Chinese electricity market are summarized and proposed.

      • ZHANG Runfan, LING Xiaobo, REN Xinyi, BIE Zhaohong, FENG Kai, ZENG Dan

        2024,48(11):111-121, DOI: 10.7500/AEPS20230415002

        Abstract:Under the continuous increase in the proportion of renewable energy, the inter-provincial consumption demand has been steadily rising. Establishing an inter-provincial electricity market that meets the overall resource optimization operation is crucial to promoting market efficiency. A bi-level clearing model of the inter- and intra-provincial electricity spot markets is established based on the time-coupling relationship of multiple block orders and hourly orders. Firstly, a mixed-integer linear programming model is constructed, encompassing multiple orders including ordinary hourly orders, flexible hourly orders, conventional block orders, removable block orders, and extended linked block orders. Secondly, to address the challenge of clearing difficulty arising from the complexity of inter-temporal coupling in block orders and the large number of inter-provincial market entities, a screening mechanism for the entities participating in inter-provincial market is proposed, which is based on the intra-provincial clearing results. Furthermore, the inter-provincial market clearing based on the selected entities from each province is realized, and the final winning bid result is formed by integrating the inter- and intra-provincial clearing results. Finally, the rationality and effectiveness of the model are verified through a case of IEEE RTS-96 system interconnected in multiple regions. The results indicate that, compared with individual provincial clearing, the bi-level clearing of the inter- and intra-provincial markets can enhance the overall social welfare. The proposed method can not only improve the solving efficiency, but also approach the global optimal solution to the inter-provincial overall clearing, thereby maximizing the social welfare.

      • BAI Qingli, ZHAO Zhipeng, JIN Xiaoyu, CHENG Chuntian, DENG Zhihao, JIA Zebin

        2024,48(11):122-133, DOI: 10.7500/AEPS20230118004

        Abstract:It is a general trend for renewable energy represented by wind power to participate in the electricity spot market, but the uncertainty of wind power output makes its market competitiveness weak, while the uncertainty of electricity price further increases the revenue risk it bears. Combining hydropower with flexible regulation capabilities is an effective solution, and formulating bidding strategies that align with the risk willingness of decision-makers is a key issue that needs to be solved urgently. Therefore, from the perspective of price takers, a bidding model of hydropower combined with wind power participating in the electricity spot market is proposed. In the model, a typical scenario set after Cartesian product combination is used to describe multiple uncertainties such as wind power output and market price, the conditional value at risk (CVaR) is used to measure the market risk caused by uncertainties, and the risk factor is included in the decision-making process as the risk preference of the decision-makers. The nonlinear function in the model is solved by introducing 0/1 integer variables and transforming it into a mixed-integer linear programming (MILP) model. The effectiveness of the model is validated against the background of a cascade hydropower station and a wind farm in a certain province in Southwestern China, and the impact of risk preference on bidding decisions is further analyzed.

      • ZHANG Shuailong, ZHENG Kedi, LIU Xue, CHENG Lanfen, TANG Chong, CHEN Qixin

        2024,48(11):134-142, DOI: 10.7500/AEPS20230804004

        Abstract:Offshore wind power will become an important technological option for China to achieve carbon emission peak and carbon neutrality due to its more utilization hours for electric power generation. However, with the continuous increase in the offshore wind power installed capacity, its intermittency and fluctuation will have a significant impact on the security and stability of power systems, as well as the economic operation of electricity markets. To characterize the correlation between wind speeds at different station sites, the vine copula theory is used for offshore wind power modeling and a joint distribution model is constructed for multiple wind farms by using the C-vine copula function. On this basis, a method is proposed for constructing the typical congestion scenarios in the electricity market based on the consensus clustering. Numerical simulation calculations are conducted with the simplified power grid architecture data of Guangdong province, China to empirically analyze the changes in key indicators such as generation structure of the power system, carbon emissions, and market electricity prices before and after the large-scale grid-integration of offshore wind power.

      • ZHANG Huaiyu, XIA Qing, ZHANG Bingjin, TAN Zhenfei, DONG Cheng, SUN Yujun, LAI Xiaowen

        2024,48(11):143-152, DOI: 10.7500/AEPS20230129003

        Abstract:With the advancement of electricity market reform, all provincial markets in East China region have been in the trial operation stage. In order to balance the smooth operation of the electricity spot market and the safe operation of regional power grid, it is urgent to study a more efficient region-province cooperative operation mechanism. First, the challenges and thoughts for the improvement of region-province scheduling cooperative mode under the background of electricity spot market are analyzed. Then, the feasible region models of the regional power grid scheduling and provincial and municipal scheduling are constructed, and the method for dimensionality reduction and linearization of the feasible region model is proposed. On this basis, a region-province cooperative and optimized operation mechanism based on the scheduling feasible region is proposed, which focuses on exploring the business process of region-province two-level cooperative operation and the calculation method of provincial and municipal feasible regions. Finally, the effectiveness of the scheduling feasible region model and the two-level market cooperative operation mechanism is verified through the analysis of regional power grid cases.

      • LIU Shiqi, LOU Nan, ZHANG Hongxuan, WANG Ke, FAN Zhantao, YANG Lin

        2024,48(11):153-161, DOI: 10.7500/AEPS20231115001

        Abstract:With the continuous promotion of the construction of the China southern regional electricity market, there have been cases of cross-section overlimit due to the dispatch of unit frequency regulation capacity during the trial operation of power regulation in the regional electricity spot market. In order to improve the efficiency of security verification and achieve the effective integration of the frequency regulation security verification process with the electricity spot market, a real-time security verification optimization strategy for the whole process of the frequency regulation auxiliary service market is proposed. A refined cross-section classification strategy suitable for regional power grids is optimized and designed to quickly screen the closed and connected sections of frequency regulation units to improve the security verification efficiency. For different types of cross-sections, typical scenarios for the dispatch of frequency regulation capacity considering third-party independent energy storage and adjustable loads are designed. Random automatic generation control (AGC) instructions are then transformed into deterministic scenarios for the dispatch of frequency regulation capacity. On this basis, two connection paths between the frequency regulation security verification and the electricity spot market are proposed to meet the different needs of different stages in regional electricity spot market construction. Finally, the accuracy and effectiveness of the proposed method are verified based on the actual operation of the frequency regulation market in southern China.

      • >Basic Research
      • LI Yizhe, WANG Dan, LI Jiaxi, JIA Hongjie, ZHOU Tianshuo, LIU Jiawei

        2024,48(11):162-172, DOI: 10.7500/AEPS20230813002

        Abstract:The entropy state mechanism and analysis method of the integrated energy system (IES) provides a new theoretical basis for the analysis of IES energy quality for renewable energy integration. For different energy system scales and scenarios, how to systematically solve the entropy state distribution of large-scale energy systems is one of the basic problems that need to be solved urgently in subsequent system planning, operation, and energy management and control. On the basis of IES entropy state theory, the calculation system and ideas of the system entropy state distribution are further sorted out. According to the needs of solving the entropy increase flow, some key calculation matrices and calculation column vectors are defined. Then, combined with the definition of IES exergy flow model and entropy state network, considering the entropy increase flow conversion and distribution mechanism of energy hub (energy station), the IES entropy state calculation models based on sequential solution and simultaneous solution are established. The correctness and effectiveness of the two calculation models are verified by cases, and the similarities, differences and applicability of the two calculation methods are discussed.

      • YIN Chenxu, SUN Yonghui, XIE Dongliang, ZHANG Zhaoqing, ZHOU Wei, MENG Yunfan

        2024,48(11):173-183, DOI: 10.7500/AEPS20231204009

        Abstract:Considering the subjectivity in multi-objective optimization for existing integrated energy systems, this paper proposes a multi-objective cooperative optimization method of single entity based on the non-cooperative game theory. First, an integrated electricity-gas system model coupling the distribution network, gas distribution network, and energy station is established. To make the optimization dispatch results closer to reality, a compressor model with variable compression ratio is employed in the model of gas distribution network. Its nonlinear consumption characteristic is considered. Then, based on the non-cooperative game theory, the economic objective and environmental objective of the energy station with a single stakeholder are treated as completely equal and rational virtual gamers. The strategy space is composed of the constraints of various devices in the system. Moreover, to ensure the existence of Nash equilibrium solutions in the game model, auxiliary variables and constraints are used to transform the payoff functions (objective functions) into pseudo-convex and differentiable functions. The method of convex relaxation is applied to handle non-convex and nonlinear constraints in the model, and a non-linear iterative strategy is proposed to accelerate the relaxation tightening process. In order to facilitate the solving of Nash equilibrium, the Nikaido-Isoda function is used to reformulate the payoff function, transforming the original model into a global optimization problem. Finally, the validity of the proposed method is verified by cases.

      • SONG Yuhang, CHEN Yufan, WEI Yanling, GAO Shan

        2024,48(11):184-196, DOI: 10.7500/AEPS20230621004

        Abstract:An environmental modeling method suitable for reinforcement learning is proposed for the charging path planning problem of electric vehicles. Based on the actual situation of urban road network and geographical distribution of charging stations, this method divides the basic driving path of electric vehicles into three segments for representation. Based on the three-segment expression method, the design scheme of state space, action space, state transition, and reward function is proposed. The charging path planning is modeled as a Markov decision process, and solved by the Q learning method and the deep Q network (DQN) method. The experimental results show that the design scheme of the reinforcement learning environment based on the three-segment expression method is solvable and portable. It takes into account the realistic scenarios such as the deceleration and turning of electric vehicles in the process of driving from the road to the charging station, and simplifies the charging action into a driving direction choice, which improves the efficiency of the reinforcement learning algorithm based on Q learning and DQN.

      • WANG Yaojian, GU Jie, WEN Honglin, JIN Zhijian

        2024,48(11):197-207, DOI: 10.7500/AEPS20230420001

        Abstract:Predicting the wind power output in the next few hours is crucial for the safe and economic operation of the power system as well as the participation of wind power in the electricity market. Due to the strong randomness and non-stationarity of the wind power sequence, it is necessary to characterize and model its uncertainty. Moreover, factors such as equipment aging, blade contamination, and changes in the wind farm environment can affect the output characteristics of wind turbines, thereby making the parameters of the wind power prediction model time-varying and increasing the difficulty of wind power prediction. This paper proposes a short-term wind power probability prediction method based on online Gaussian process. First, the Gaussian process regression model is used to model the wind power prediction problem. Then, the complexity of Gaussian process calculation is reduced by combining structured kernel interpolation with the Woodbury identity, which enables fast Gaussian process solving. Finally, the method of block caching and updating is adopted to realize the real-time online updating of parameters and hyperparameters for Gaussian process model. The wind power generation data released by the 2014 Global Energy Forecasting Competition is used to validate the proposed algorithm. The results show that the proposed algorithm has good prediction performance and adaptability to effectively deal with the problem of time-varying model parameters.