Aug 2026· Frontiers in Energy Research· Vol 14· 0 citations· 30 references
Abstract
With the urgent need to achieve carbon neutrality goals and the rapid development of distributed energy resources, traditional electricity markets face challenges in effectively integrating environmental and economic values, lacking unified mechanisms to simultaneously clear energy and environmental transactions. This study proposes an energy credits–electricity joint trading mechanism for virtual power plants that achieves co-equilibrium through explicit coupling between energy and environmental value markets. First, a multi-dimensional energy credit quantification model is established, integrating energy type, time period, trading volume, and behavioral characteristics to differentiate environmental contributions. An optional reputation assessment enhancement covering prediction accuracy, fulfillment reliability, response timeliness, trading frequency, and anomaly behavior can be integrated for virtual power plant (VPP) operators requiring behavioral differentiation. Second, a unified joint clearing model is constructed that co-optimizes energy and credit trading, employing the alternating direction method of multipliers (ADMM) to decompose large-scale optimization problems into parallelizable prosumer and market coordination subproblems. Simulation results across single-day, multi-day (5-day cycle), and seasonal scenarios demonstrate that the mechanism successfully distinguishes prosumer performance: renewable energy prosumers accumulate substantial positive credits (136.2 credits over 5 days), while fossil fuel users incur credit deficits (−25.1 credits single-day), achieving system-level carbon credit balance over multi-day settlement cycles. The proposed mechanism effectively realizes the principle of “green contributors benefit, polluters pay” and provides a practical pathway for integrating environmental value in electricity markets.
With the increasing penetration of renewable energy sources, active distribution networks face significant challenges in voltage regulation and carbon emission mitigation. Energy storage systems (ESS) provide a flexible solution, yet their economic viability is heavily influenced by emerging market mechanisms such as Carbon Trading and Green Certificate Trading. This paper proposes a dynamic optimization framework for ESS configuration. Firstly, a cooperative differential game model aiming for social welfare maximization is established between the Distribution Network Operator (DNO) and independent Energy Storage Operators (ESO), where the state-of-charge (SoC) and cumulative carbon intensity are modeled by analogizing epidemiological dynamics. Subsequently, Pontryagin’s Maximum Principle (PMP) is employed to derive the theoretical feedback Nash equilibrium and optimal trajectories. To address the model dependency and computational complexity of analytical methods in high-dimensional network environments, a data-driven solution framework based on Proximal Policy Optimization (PPO) is further proposed. By reconstructing the continuous-time game into a Markov Decision Process (MDP), the PPO agent achieves adaptive scheduling through autonomous interaction with the market environment.
Wen-Bin Hei, Qixin Zhao, Yue Zhang et al.· Journal of Physics, Conferen...· 0 citations
Under the background of energy transition and "dual carbon" goals in China, distributed new energy (DNE) and energy storage equipment's installed capacity has increased exponentially. As an efficient distributed resource management system, the virtual power plant has also garnered significant attention from domestic scholars and institutions. Extensive research has been conducted on a series of trading strategies for virtual power plants participating in the electricity spot market. With the expanding scale of virtual power plants involved in market-based trading, the operational evaluation of virtual power plants is set to become a key focus of attention. This paper proposes an operational optimization model aimed at enhancing the participation of generation-type virtual power plants with energy storage in the spot market and reducing prediction deviations. The model considers factors such as penalties for predicted power deviations, historical positive and negative power deviation of generation aggregation units, and energy storage charging and discharging efficiency. The paper analyzes and discusses the impacts under different evaluation intensities. When the system evaluation threshold is lowered and the unit deviation penalty coefficient is increased, the model effectively reduces assessment costs and improves the daily operational benefits in scenarios involving distributed virtual power plants with energy storage.
Kaiqing Liang, Xuebo Qiao, Xiangyang Su et al.· 2026 5th International Confe...· 0 citations
To alleviate renewable energy curtailment and the high operating costs arising from the temporal and spatial mismatch of distributed generation, this paper develops a cross-park dispatch optimization approach for power systems under the joint participation of carbon trading and green certificate trading (GCT). The proposed approach aims to improve system flexibility and economic performance in coordinated multi-park operation. Specifically, adjustable resources in different parks are dispatched in a coordinated manner, and the total comprehensive operating cost is taken as the optimization objective. In addition, the Alternating Direction Method of Multipliers (ADMM) is adopted to determine inter-park electricity trading prices and exchanged power in a distributed framework. Furthermore, an asymmetric bargaining model is introduced to distribute the cooperative benefits, ensuring a balance between fairness and incentive compatibility. Simulation results demonstrate that inter-park electricity interaction reduces generation costs by 5.29%. The integration of carbon and green certificate trading further reduces costs by 7.4%. After asymmetric bargaining-based benefit allocation, the operating costs of parks with higher contributions decrease by up to 10.34%. The results conclude that the proposed strategy effectively leverages the complementary advantages of multi-park resources and optimizes the synergy between carbon markets, green certificate markets, and physical dispatch.
Chunxian Feng, Yifeng Wang, Wenxue Wang et al.· Energies· 0 citations
To address the challenges of absorption difficulty and insufficient economy caused by the grid connection of high-proportion renewable energy, this paper constructs a non-cooperative asymmetric game model between a wind-PV-thermal integrated energy system and external independent power generation units participating in the spot and frequency regulation coordinated market under the framework of Liaoning Province’s frequency regulation market rules. Taking the profit maximization of each participant as the core objective, a joint clearing model that incorporates the costs, compensations, and constraints of both the spot and regulation service markets are established, and the Nash equilibrium is solved through the application of the strategy iteration algorithm. Case studies verify that through internal resource coordination, the integrated energy collaborative system significantly reduces marginal costs and frequency regulation quotes, effectively improves its own market revenue while promoting renewable energy absorption, providing an economical and reliable operation support for the new power system.
Qi-Qi Zhai, Guoliang Bian· Strategic Planning for Energ...· 0 citations
Peer-to-Peer (P2P) energy trading has emerged as a transformative approach for creating decentralized energy markets, empowering prosumers to actively participate in energy generation and consumption. This paper presents a novel P2P energy market framework that incorporates the technical constraints of physical electricity networks to design a more economically efficient market. By allocating power losses and transaction fees, the proposed model ensures fairness and transparency in energy transactions. Additionally, the market allows consumers to trade with the main grid to meet their energy needs and integrates Demand Response (DR) programs to balance supply and demand during periods of local generation shortages. To evaluate the proposed model, an Alternating Direction Method of Multiplier (ADMM) is employed for market clearing, ensuring scalability and efficiency. Numerical simulations were conducted on a standard IEEE 13-node test feeder demonstrate the feasibility and effectiveness of the proposed framework, highlighting its potential to enhance sustainability and grid resilience in decentralized energy systems.
Tran-Thanh Son, N. Anh, Ta-Xuan Hung et al.· E3S Web of Conferences· 0 citations
Decentralized energy communities (DECs) allow households, prosumers, and small generators to trade electricity locally, improving grid flexibility and supporting renewable integration. However, local market designs often face a trade-off between efficiency and fairness. Efficiency-oriented settlement rules can produce payment outcomes that are perceived as unfair, while strongly redistribution-based approaches may weaken incentives and reduce operational performance. This paper proposes a hybrid Vickrey-Clarke-Groves (VCG)-Shapley payment framework designed to balance an efficiency-oriented VCG settlement baseline, contribution-based fairness, and settlement stability. The VCG mechanism forms the efficiency-oriented settlement base, and a Shapley-inspired redistribution layer incentivizes meaningful community contributions beyond net energy supply. We develop a 14-factor contribution score to operationalize this approach, covering reliability, flexibility, self-consumption, demand response, renewable integration, transparency, and other supportive behaviors. Scores are evaluated every 30 minutes using time-varying weights to reflect the changing system conditions. A 24-hour simulation with generators, prosumers, and consumers compares the VCG-only settlement, the score-based redistribution, a convex combination payment and the proposed hybrid mechanism. The results show that the hybrid method produces the lowest SD and MAD-based payment dispersion among the evaluated post-VCG alternatives, preserves the VCG settlement anchor, and satisfies interval-level budget balance.
Kaung Si Thu, Pikkanate Angaphiwatchawal, S. Chaitusaney· IEEE Access· 0 citations
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