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最新刊期
卷 50 ， 期 9 ， 2026
- 摘要：In the context of the energy transition, resolving the “energy trilemma”, i.e. balancing security and reliability, economic efficiency, and green low-carbon development, has become the core challenge in the evolution of power systems. To address this, based on an analysis of the adaptability dilemmas within the classic electricity market paradigm, this paper proposes a novel electricity market paradigm centered on a market-based regulation responsibility system. By clearly defining property rights for system balancing services and introducing standardized “substitute power products” as trading carriers, this paradigm reshapes market entities into self-scheduling units that trade autonomously around regulation responsibility curves. Furthermore, leveraging the concept of multi-time scale self-similarity, it establishes a collaborative mechanism between the “substitution market” and the “regulation market”. This incentivizes market entities to optimize the allocation and utilization of regulation resources through full competition, thereby transforming system security from “external planning” reliant on dispatch instructions into “endogenous security” driven by the profit motives of micro-entities. This mechanism will effectively activate dispersed flexibility resources society-wide and significantly lower the system marginal accommodation costs through market competition, providing an implementation path that is both institutionally feasible and technically operable to construct a new power market capable of endogenously and synergistically achieving security, economic efficiency, and green development.关键词：energy trilemma;security;reliability;regulation responsibility;substitute power product;electricity market1|1|0更新时间：2026-08-21
- 摘要：With the deepening advancement of energy transition, the integration of a high proportion of renewable energy has posed unprecedented challenges to the balance of power systems. This paper systematically reviews the evolution of power system balancing mechanisms from traditional planned dispatch to market-oriented transition. It conducts an in-depth analysis of the mechanism, applicable conditions, and evolutionary logic of three typical models: the centralized optimization model based on locational marginal pricing represented by North America, the decentralized decision-making model based on balancing responsible parties represented by Europe, and the real-time response model based on a single energy-only market represented by Australia. On this basis, in view of the characteristics of China's power system development, a hierarchically coordinated market-oriented balancing mechanism is proposed from four aspects: inter-provincial and regional coordination, integration of administrative planning and market mechanisms, multi-timescale optimal design, and balancing responsibility sharing. Corresponding recommendations are also put forward for the implementation path of the market-oriented balancing mechanism.关键词：power system;renewable energy;balancing mechanism;electricity market;ancillary service;flexibility resource1|1|0更新时间：2026-08-21
- 摘要：Capacity adequacy of power system is crucial for ensuring power system security and stability, as well as the stable operation of electricity markets. At present, China is in an accelerated transition phase of building a new power system, facing the dual challenges of coordinating energy structure adjustment and advancing market-based reform. The current energy-centric market system lacks market-based mechanisms to incentivize long-term system adequacy, which hinders the achievement of power and energy balance across multiple time scales in electricity markets. Accordingly, this paper first proposes a renewed connotation of capacity adequacy based on the operation characteristics of the new power system. Next, it reviews current practices of capacity adequacy mechanisms both domestically and internationally and analyzes the applicability of different mechanisms under evolving power system conditions. On this basis, a fundamental framework for establishing capacity adequacy mechanisms is proposed. Finally, it provides recommendations for developing capacity adequacy mechanisms tailored to the new power system, covering aspects such as mode selection, development pathways, and key issues in implementation.关键词：new power system;electricity market;capacity adequacy;renewable energy;capacity market2|6|0更新时间：2026-08-21
- 摘要：Formulating an emergency supply guarantee mechanism adapted to new power systems is an important measure to enhance the safe and reliable supply capability of electricity in the context of frequent risk triggers. As the electricity market system and its functions continue to improve, it is necessary to re-evaluate their supporting role in emergency supply guarantee. From the perspective of cyber-physical-social system in energy (CPSSE), this paper analyzes the positioning of the electric energy and reserve markets within the emergency supply guarantee framework, the core role of market regulation, and the shortcomings of existing market supervision mechanisms. A hybrid simulation environment for day-ahead to real-time electricity energy and reserve markets is constructed, demonstrating the necessity of implementing coordinated supervision. Based on this, a coordinated regulation framework for electric energy and reserve markets is established, incorporating categorized supervision and equivalent coordination, and a closed-loop feedback-based decision-making mechanism for coordinated supervision is designed. Through multi-scenario hybrid simulations with and without the coordinated supervision mechanism, it is verified that the proposed equivalent coordination scheme can reduce system costs while adhering to given operational boundaries, thereby supporting emergency supply guarantee requirements. Finally, it is proposed that, through comparative analysis between simulation trajectories and actual system trajectories, continuous iteration of model falsification and mechanism verification can be carried out, thereby achieving adaptive supervision control in real-world markets.关键词：emergency supply guarantee;electric energy market;electricity market;reserve market;coordinated supervision;cyber-physical-social system in energy (CPSSE)3|1|0更新时间：2026-08-21
- 摘要：With the development of the new power system, the large-scale integration of renewable energy has imposed higher requirements on the regulation capability of the power system. To enhance the regulation capability of the new power system, it is necessary to establish a regulatory capacity market. First, this paper demonstrates the necessity and core value of the regulatory capacity market. Then, a framework for building the regulatory capacity market is proposed, including the market framework with the dimensions of object structure, temporal structure, spatial structure, and participant structure, as well as key mechanisms such as pricing and management mechanisms. Finally, in view of the technical challenges in market clearing for the regulatory capacity market, a clearing technique based on long-term production simulation is proposed to determine clearing results. The feasibility and effectiveness of the designed regulatory capacity market are verified through a series of scenario calculations constructed based on data from the North China. The results show that the regulatory capacity market can optimize the allocation of regulatory resources according to system demands, reasonably clear various regulatory resources, effectively enhance the renewable energy accommodation rate, ensure the economic and efficient operation of the power system, while simultaneously providing stable revenue expectations for regulatory resources.关键词：new power system;renewable energy;electricity market;capacity market;regulation capability;market clearing2|1|0更新时间：2026-08-21
- 摘要：A rational pricing mechanism is the basis for the effective operation of electricity markets, with the participation rationality being a basic requirement for mechanism design. For the three-part bidding mechanism designed to facilitate the participation of resources with start-up and no-load costs, as well as intertemporal constraints such as coal-fired and gas-fired power plants in the market, the locational marginal pricing approach based directly on Lagrange multipliers is no longer applicable. Internationally, this issue is typically addressed through full-cost compensation mechanisms. However, in China, considering the coupling relationship between spot markets and medium- and long-term markets, partial compensation mechanisms are mostly adopted. To investigate the impact of partial compensation mechanisms on the strategic behavior of market participants, a multi-agent simulation framework based on deep reinforcement learning is constructed to precisely characterize the three-part bidding strategies of generating units, thereby enabling the quantitative revelation of the strategic behavior characteristics of market participants and their risk transmission pathways, as well as validating the effectiveness of market mechanism design. Based on this framework, simulation analyses are conducted for typical compensation mechanisms, including no compensation, start-up cost compensation only, time-of-use compensation, and full-cost compensation. The results indicate that under locational marginal pricing mechanisms, inadequate compensation tends to induce the strategic price increase among generating units to avoid losses, thereby increasing the market electricity prices and reducing social welfare, further affecting the power balance of the power system. In contrast, a full-cost compensation mechanism helps safeguard the revenues of power producers, lower electricity prices, and incentivize the provision of regulation capabilities.关键词：electricity market;three-part bidding;full-cost compensation mechanism;locational marginal pricing;participation constraint;multi-agent simulation;deep reinforcement learning4|1|0更新时间：2026-08-21
- 摘要：To ensure the frequency security of power systems with a high proportion of renewable energy, it is necessary to establish reasonable market mechanisms to obtain the ancillary services of inertia and primary frequency regulation from the resources such as conventional units and grid-forming energy storage. In this paper,the basic requirements for ancillary market design of inertia and primary frequency regulation are analyzed. First,based on the “dependency coupling characteristics” of power generation and inertia of conventional units, the inertia offer and compensation mechanism based on the minimum generation power offer is designed. Then, a multi-stage sequential clearing mechanism is constructed by embedding the frequency security check phase and ancillary market clearing phase of inertia and primary frequency regulation based on the capacity shortage procurement.These phases are between the pre-clearing phase and the formal clearing phase of spot electricity energy market, and the clearing model is given. Furthermore, the ancillary service costs of inertia and primary frequency regulation are decomposed into two cost parts shared by consumers and renewable energy, and the calculation method is given. Finally, the simulation is conducted on the modified IEEE 39-bus system case, and the effectiveness of the proposed market clearing and cost allocation mechanisms is verified.关键词：frequency security;inertia;primary frequency regulation;ancillary service;spot electricity energy market;market clearing;grid-forming energy storage;cost allocation1|1|0更新时间：2026-08-21
- 摘要：Price-based demand response (PBDR) can enable flexibility demand-side resources (DSFRs) to provide regulation capability for power systems, and its regulation effects are directly related to the regulation willingness of each resource entity. However, this regulation willingness has the characteristic of being difficult to directly obtain. To address this, a parameterized estimation method of the regulation willingness based on the inversion of historical energy consumption data is proposed from a non-cooperative game equilibrium perspective. First, a parameterized decision model for the price response of individual DSFR is developed, and based on this, a non-cooperative game problem is constructed for large-scale DSFRs to participate in PBDR. Second, by adopting the variational inequalities and strong duality of linear programming, a non-cooperative game equilibrium problem for demand response is then reformulated as an equivalent equilibrium condition consisting of a set of linear inequalities. Based on this, integrating the construction form of prior information for the regulation willingness function, the inverse variational inequalities driven by historical energy consumption data are constructed to achieve the parameterized estimation of regulation willingness for DSFRs in PBDR, and its computational efficiency is analyzed. Additionally, a generalization error evaluation metric for regulation willingness estimation is defined, and its upper bound of generalization error is derived using uncertain convex programming theory. The generalization ability of the proposed parameterized estimation method for regulation willingness is analyzed theoretically. Finally, through case analyses, the accuracy of the proposed parameterized estimation method for regulation willingness is validated, and the role of the accuracy of prior information in the regulation willingness estimation is explored.关键词：parameterized estimation;demand response;flexibility resource;regulation willingness;game;equilibrium analysis;variational inequality;inverse optimization4|1|0更新时间：2026-08-21
- 摘要：As a key flexibility resource on the load side, the regulation capability of electric vehicles (EVs) is not only related to physical operation constraints but also to their business modes participating in the electricity market. To fully exploit the flexibility regulation potential of EVs, this paper first models the regulation capabilities of EV clusters under various business modes. Then, a multi-market for electric energy-frequency regulation-reserve-retail, involving a day-ahead and real-time two-stage bi-level optimization model is established to optimize the trading decision behaviors of EV clusters. Finally, case studies are conducted on the IEEE 30-bus system to validate the regulation capabilities of EV clusters under four typical business modes: self-charging with battery ownership, station-controlled charging with battery ownership, station-controlled battery swapping with leasing and recycling, and self-charging with leasing and recycling. The results show that the station-controlled swapping-leasing mode achieves the highest adjustable capability due to its deep regulation advantages, maximizing revenue. Additionally, EV cluster trading strategies tailored to various business modes are proposed.关键词：electric vehicle (EV);flexibility resource;business mode;electricity market;joint clearing;trading decision1|1|0更新时间：2026-08-21
- 摘要：On the background of the development of new power systems, it is of great significance for electric vehicles (EVs) to participate in system regulation as flexibility load-storage resources through the electricity market. Some cities in China have carried out small-scale operations for EVs to participate in the transaction of diversified electricity markets through charging and discharging stations. However, there are still some problems, such as the inaccurate calculation method of the value generated by stations participating in the market and the lack of market participation recommendation schemes. To this end, this paper proposes a method for estimating the differentiated profit potential of EV charging and discharging stations participating in the diversified electricity market and matching the optimal market. Firstly, a differentiated value evaluation framework for EV charging and discharging stations participating in diversified electricity markets is designed, and the whole process of data reconstruction, future profit estimation, and optimal market matching is described in detail. Secondly, an efficient quantitative method for the adjustable capability of charging and discharging stations is proposed to realize the transformation from scattered user charging records to the overall adjustable range of the station. Through the calculation and deduction of the maximum profit of the diversified electricity market, the historical value data set of the station participating in the diversified electricity market is constructed. Thirdly, a cross-period sparse prediction model based on multi-scale mixing and the bidirectional long short-term memory network is proposed to accurately estimate the future profits of stations participating in multiple markets. A mixed clustering algorithm based on future profit data is further proposed to achieve the optimal matching between the station and the electricity market by extracting future profit characteristics. Finally, based on the charging order data of a city in Shandong Province of China, the effectiveness of the proposed method is verified. The results show that the proposed method can provide a basis for station operators to participate in market decision-making.关键词：electric vehicle (EV);charging and discharging stations;electricity market;adjustable capability;profit potential;market matching;mixed clustering3|1|0更新时间：2026-08-21
- 摘要：To address the difficulty for building aggregators in formulating bidding strategies in highly uncertain and competitive market environment, a quantity-and-price bidding strategy based on Bayesian network agent is proposed for building aggregators participating in the day-ahead demand response electricity market, so as to effectively increase the number of winning bids and improve their economic benefits. First, a day-ahead demand response electricity market clearing model is constructed using the quantity-and-price method and the system marginal price mechanism. Then, considering the cost quantity-price curve of adjustable resources dispatched by building aggregators, a decision-making model for their quantity-and-price is designed, and conditional value-at-risk is introduced to measure the market risk, ensuring their reliable profits. Furthermore, to solve the difficulty in obtaining the optimal quantity-price combination, a quantity-and-price strategy based on time-series generative adversarial network-Bayesian network-deep deterministic policy gradient is proposed to efficiently generate the optimal quantity-price combination. Finally, case studies based on demand response market data from ISO New England show that the proposed strategy can significantly improve the economic profits of building aggregators and effectively avoid market risks.关键词：building aggregator;demand response;time-series generative adversarial network;Bayesian network;deep deterministic policy gradient;quantity-and-price strategy1|1|0更新时间：2026-08-21
- 摘要：With the gradual application scope expansion of the medium- and long-term centralized bidding transactions, in order to achieve the cross-regional resource bidding on the same platform, fully utilize the transmission capability of cross-provincial channels, and achieve the global optimization allocation of power generation resources under the maximization of the entire social welfare, research on the integrated clearing method for the inter-provincial and intra-provincial two-level market is carried out for the medium- and long-term centralized bidding transaction mode. First, based on the comparative analysis of the operation mechanisms for current inter-provincial and intra-provincial medium- and long-term centralized bidding transactions, a two-level market integrated clearing mechanism is designed under the medium- and long-term centralized bidding transaction mode. Then, aiming at the maximization of overall social welfare, the optimization model and the pricing method for the integrated clearing are proposed considering all path combinations for the inter-provincial and intra-provincial medium- and long-term centralized bidding transactions. Finally, the effectiveness of the proposed method is verified by adopting the simulation case of the typical provinces with detailed designs, and the mechanism suggestions are proposed based on the simulation results. The simulation results indicate that the proposed integrated clearing method realizes the synchronous clearing of cross-regional, intra-regional and intra-provincial transactions under the medium- and long-term centralized bidding transaction mode through a single optimization. Also, the proposed method enhances the coordinated operation efficiency of two-level medium- and long-term market and ensures the competition fairness among market entities.关键词：electricity market;centralized bidding transaction;integrated clearing;clearing mechanism;clearing method;pricing method1|3|0更新时间：2026-08-21
- 摘要：With the advancement of the carbon emission peak and carbon neutrality strategy and the increasing penetration of renewable energy, Guangdong electricity market of China faces new challenges and urgently requires the establishment of market mechanisms adapted to the new power system. First, to address the problems of limited variety and low trading frequency in medium- and long-term markets, as well as imperfect pricing and bidding mechanisms in the spot market, a basic framework of the “multi-time scale medium- and long-term + bilateral spot” market mechanism for the new power system is proposed. Second, based on this framework, a comprehensive market trading system is proposed for renewable energy. This system is designed to realize the dual value of its electric energy and environmental attributes, and consists of both electricity and green power trading products. Finally, on this basis, considering the characteristics of different flexibility resources a trading mechanism is further designed for new energy storage, pumped storage, and virtual power plants to meet the trading demands of these new entities. Practical application in Guangdong electricity market shows that the proposed market mechanism adapted to the new power system facilitates the smooth market entry of new entities, effectively contributing to the green energy transition and enhancing the flexibility of the power system.关键词：new power system;electricity market;spot market;market mechanism;renewable energy;flexibility resource2|2|0更新时间：2026-08-21
- 摘要：The Gansu Provincial power grid in China serves as a representative sending-end grid, characterized by a high penetration of renewable energy. In response to the current development realities of the power grid and renewable energy in Gansu Province,China, as well as the operation challenges it faces, this paper proposes a “one-core, five-dimensional” provincial electricity market system. This system focuses on serving the construction of a new power system, followed by multi-time scale trading mechanisms, multi-spatial-dimension clearing processes, multi-resources optimization and allocation, multi-trading product coverage, and multi-value incentive manifestation. Subsequently, the trading mechanisms of the Gansu Provincial electricity market are rigorously analyzed, and the market operation performance and key achievements are presented. Finally, the forward-looking insights into the construction of Gansu Provincial electricity market system are provided.关键词：renewable;electricity market;spot market;new power system;electricity market system1|1|0更新时间：2026-08-21
Market\-based Power Balancing Mechanisms and Methods for New Power System
- 摘要：Exploiting the regulation potential of massive electric vehicles (EVs) within distribution networks is one of the critical solutions to addressing the challenges arising from the integration of high proportions of renewable energy into power systems. However, effectively aggregating heterogeneous EVs in distribution networks and accurately quantifying the regulation capability remain key technical challenges for enabling coordinated scheduling between transmission and distribution networks in current research. Therefore, a hierarchical coordinated optimal scheduling method of transmission-distribution networks and EV aggregators (EVAs) based on feasible region aggregation and projection is proposed. Through the feasible region aggregation and projection method, the inter-layer information transmission is achieved, and the efficient scheduling is realized by integrating a hierarchical coordinated optimal model. First, considering the diverse charging regulation modes of EV users, convex polytopes are utilized to characterize the power feasible region of individual EV under various charging regulation modes, and an inner approximation aggregation method for EV power feasible regions based on convex polytope affine transformation is proposed. Then, a projection method for operation feasible region of distribution networks based on boundary shrinking is proposed to quantify and evaluate the regulatable range of interactive power between each distribution network and transmission network. Subsequently, a hierarchical coordinated optimal scheduling model of transmission-distribution networks and EVAs is established based on feasible region aggregation and projection. Finally, a transmission-distribution system case is employed for simulation verification. The results demonstrate that the proposed method enables more comprehensive utilization of EV regulation potential, alleviates generator ramping requirements, mitigates photovoltaic output fluctuations, and reduces overall system operation costs.关键词：transmission network;distribution network;coordinated optimal scheduling;electric vehicle;regulation capability;feasible region projection1|1|0更新时间：2026-08-21
- 摘要：Active distribution network (ADN) is a crucial link for ensuring customer power supply and renewable energy accommodation. However, the stochastic nature and prediction uncertainty of renewable energy create a trilemma among local accommodation, power supply security, and economic efficiency in ADN. Based on this, this paper proposes the data-driven distributionally robust optimization (DRO) and operation method for ADN based on Kolmogorov-Arnold network (KAN). First, KAN with multi-feature inputs is used to perform temporal prediction of photovoltaic power and load. Then, based on rolling prediction from the trained KAN prediction model, prediction errors are generated and the data-driven DRO ambiguity set is constructed to reflect the error characteristics of the prediction model. Finally, this paper formulates the data-driven DRO and operation model for ADNs based on KANs. The Kullback-Leibler (KL) divergence-based data-driven DRO method is transformed into an exponential-cone programming model that requires no dualization of the original optimization problem and is easy to trace. It is proven that the transformed model, featuring an exponential-cone objective and second-order cone constraints, satisfies joint convexity. Case studies on the modified IEEE 33-bus and IEEE 69-bus ADNs compare Moment-based and Wasserstein-distance-based DRO methods with the proposed method. It also validates that the data-driven DRO method based on KANs for ADN can effectively reconcile conflicts in total operation costs and reduce the impact of prediction errors on ADN operation.关键词：active distribution network (ADN);renewable energy;distributed photovoltaics;Kolmogorov-Arnold network (KAN);data-driven;distributionally robust optimization (DRO)1|1|0更新时间：2026-08-21
- 摘要：The intermittency and volatility of massive distributed photovoltaic (PV) output introduce strong uncertainty into distribution network power flows, making frequent voltage violations and increased operation network losses increasingly prominent issues. To address this, this paper proposes a hybrid data-knowledge-driven voltage/VAR optimization (VVO) strategy for distribution networks with high penetration of distributed PV. First, to tackle the strong uncertainty and high dynamic characteristics of distribution network power flow states, an improved distributed soft actor-critic (DSAC) algorithm is proposed. By directly learning the distribution function of state-action returns, it explores the uncertainty of cumulative discounted returns, mitigating the overestimation problem of state-action values and significantly enhancing the performance of the VVO strategy. Second, to resolve the issue of frequent voltage constraint violations, an expert knowledge safety layer based on the DistFlow equations is embedded into the data-driven VVO process. By projecting and correcting the actions output by the DSAC agent through physical knowledge, a deep integration of data learning and knowledge constraints is achieved, improving the feasibility and safety of the strategy. Subsequently, a data augmentation model based on the multivariate conditional t-distribution Copula is proposed. By generating high-quality and diverse training data, it significantly enhances the generalization capability and robustness of the DSAC strategy in complex operation scenarios. Finally, the effectiveness of the proposed strategy is validated by the simulation results on the IEEE 34-bus and IEEE 118-bus systems.关键词：distribution network;voltage/VAR optimization;high penetration of photovoltaic;hybrid data-knowledge-driven;deep reinforcement learning1|1|0更新时间：2026-08-21
- 摘要：In a weak grid, grid-following converters are prone to oscillation instability due to the interaction between the phase-locked loop (PLL) and the grid impedance. However, the DC voltage synchronization control method in the grid-forming technology can achieve autonomous synchronization by utilizing DC dynamics to emulate generator power angle characteristics, offering enhanced stability. By comparing the generator rotor motion equation with the DC voltage synchronization control structure, this paper proposes an adaptive control strategy for the grid-following converter in a weak grid, considering DC synchronization characteristics. This strategy introduces the DC dynamic deviation into the PLL synchronization link and employs weight coefficient allocation to achieve coordinated integration of both methods, enabling the converter to possess the stability advantages of the grid-forming control in weak grids. On this basis, the weight coefficients are designed according to system damping characteristics, and their correlation with the grid impedance is revealed. Further, the adaptive parameter adjustment is realized by integrating the online impedance identification technology. The sequence impedance model analysis shows that the proposed strategy can effectively suppress the sub-synchronous oscillation of grid-following converters in weak grids. Finally, the effectiveness of the proposed method is verified through experiments.关键词：weak grid;grid-following converter;DC synchronization characteristic;phase-locked loop;adaptive control;sub-synchronous oscillation;sequence impedance model2|1|0更新时间：2026-08-21
- 摘要：In the scenario of parallel compensation, large-scale wind power grid-connected systems are prone to high-frequency oscillation under the influence of source and grid interaction. The actual impedance network of the power system is complex and the operation conditions are diverse, which limits the applicability of traditional high-frequency oscillation suppression strategies. Therefore, a bi-directional suppression strategy of high-frequency oscillations for a doubly-fed induction generator (DFIG) grid-connected system based on stator voltage feedforward compensation is proposed. Firstly, by constructing an impedance model of the DFIG grid-connected system, the mechanism of high-frequency oscillation is analyzed. Then, the grey relational analysis method is introduced to quantify the dominant factors affecting high-frequency oscillations on both sides of the source and grid. Furthermore, based on the quantified dominant factors, the control loops of the inverters on both sides of the source and grid are reconstructed, and the output impedance of the reshaped inverters is represented in the form of equivalent coefficients. A bi-directional suppression strategy of high-frequency oscillation for the DFIG grid-connected system based on stator voltage feedforward compensation is proposed, effectively improving the output impedance characteristics of the DFIG. Finally, a multi-DFIG grid-connected system and an actual power system model in western China are built in RTLAB-OP5600 for simulation, verifying the accuracy and applicability of the proposed high-frequency oscillation suppression strategy.关键词：wind power grid-connected system;high-frequency oscillation;doubly-fed induction generator (DFIG);virtual impedance0|1|0更新时间：2026-08-21
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