水风光联合参与多地区现货市场竞标策略优化及调度方法
By generating typical scenarios and constructing a multi-leader, multi-follower game model, the bidding strategy of hydro-wind-solar systems is optimized, solving the internal game and cross-market strategy problems in multi-regional spot markets. This achieves economic optimization and interest coordination for hydro-wind-solar systems and enhances the market competitiveness of clean energy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUAZHONG UNIV OF SCI & TECH
- Filing Date
- 2026-03-05
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient to achieve technically feasible, economically optimal, and interest-coordinated bidding strategies for hydro-wind-solar systems in multi-regional spot markets. They also fail to simultaneously address the comprehensive optimization issues related to multi-stakeholder game behavior within the system, cascade hydro-electric coupling constraints, and cross-market strategies.
Typical scenarios are generated using Latin hypercube sampling and K-means clustering algorithm. A two-layer model for optimizing bidding in multi-regional spot markets based on multi-leader, multi-follower Stackelberg game is constructed. The bidding strategy is optimized by distributed iterative solution algorithm and damping update method. Combined with cascade hydraulic-electric coupling constraints, the bidding and scheduling of the water-wind-solar system are optimized.
It maximizes the overall benefits and minimizes the risks of hydro-wind-solar systems in spot markets across multiple regions, improves the market-based consumption and optimal allocation of clean energy, and enhances the scientific nature and numerical stability of decision-making.
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Figure CN121787673B_ABST