Dual-Objective Optimization for Independent Energy Storage in Electricity Markets Based on Source-Load Fluctuation Quantification
Cui Yang1, Cheng Dingran1, Fu Guobin2, Xu Yang1, Wang Yijian3
1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China; 2. State Grid Qinghai Electric Power Research Institute Xining 810008 China; 3. School of Electrical Engineering Shanghai Jiao Tong University 200240 Shanghai China
Abstract：Large-scale renewable energy integration has significantly increased source-load fluctuation differences in power systems, elevating the difficulty of power and energy balance regulation. This transformation highlights the crucial role of energy storage in system flexibility regulation. However, existing energy storage pricing mechanisms fail to ensure reasonable returns, constraining both the full utilization of storage regulation potential and industrial-scale development. Consequently, establishing rational pricing mechanisms has become critical for the evolving power system landscape. This paper proposes a dynamic pricing mechanism based on source-load fluctuation quantification from the grid-side perspective, targeting flexibility resources represented by independent energy storage. The proposed approach aims to address the fundamental challenge of creating market incentives that effectively guide storage participation while maintaining system stability and economic viability. The methodology consists of three integrated components. First, the inertia within (IW) clustering analysis method is employed to partition the total source-load fluctuation intervals. Through systematic analysis of clustering metrics, optimal interval divisions are determined, establishing a comprehensive source-load fluctuation state matrix. This matrix construction process involves creating full-scenario state combinations through Cartesian products and implementing fuzzy logic-based valuation to achieve precise quantification of fluctuation differences. The approach introduces the concept of minimum energy blocks to represent the fundamental energy units for state transitions, providing a quantitative foundation for storage capacity configuration and operational decisions. Second, a mapping relationship between source-load fluctuation states and electricity price intervals is established. Based on market-oriented principles, the mechanism transforms quantified fluctuation differences into dynamic price signals that reflect real-time system regulation needs. This design creates a medium and long-term time-of-use dynamic pricing mechanism specifically oriented toward independent energy storage, replacing traditional fixed price structures with adaptive pricing that responds to system conditions. The price intervals dynamically adjust based on source-load matching states, providing higher incentives when system regulation needs are greater and moderate prices during balanced conditions. Third, a verification framework based on dynamic programming is constructed to validate the proposed pricing mechanism. This framework simulates energy storage response behavior under dynamic price guidance through multi-stage optimization modeling. A relative achievement rate evaluation system is introduced to verify the synergistic effects between storage economics and source-load matching degree. The framework establishes separate optimization baselines for matching degree maximization and profit maximization, then evaluates the collaborative optimization performance through normalized metrics, enabling comprehensive assessment of the mechanism's effectiveness. Case study analysis demonstrates that compared to fixed price interval mechanisms, the proposed dynamic price interval mechanism achieves significant improvements in both source-load matching degree and storage revenue when guiding independent energy storage market participation. Under unified configuration scenarios, the collaborative optimization strategy simultaneously achieves a 95.40% relative achievement rate for optimal matching degree and a 91.08% relative achievement rate for optimal revenue. The mechanism effectively reduces system renewable curtailment while maintaining reasonable storage utilization rates across different operational scenarios. The results prove the feasibility and effectiveness of the dynamic price interval mechanism in guiding independent energy storage participation in electricity markets. This research provides a viable pathway for independent energy storage participation in medium and long-term electricity markets, contributing to the sustainable development of new power systems characterized by high renewable energy penetration and enhanced flexibility requirements.
崔杨, 程丁然, 傅国斌, 徐扬, 王议坚. 基于源-荷波动量化构建电价区间引导独立储能参与电力市场的协同优化方法[J]. 电工技术学报, 2026, 41(11): 3755-3771.
Cui Yang, Cheng Dingran, Fu Guobin, Xu Yang, Wang Yijian. Dual-Objective Optimization for Independent Energy Storage in Electricity Markets Based on Source-Load Fluctuation Quantification. Transactions of China Electrotechnical Society, 2026, 41(11): 3755-3771.
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2026, Vol. 41 
