Multi-objective Optimization for Peak Shaving of Wind-solar-cascade Hybrid Pumped Storage System Accounting for Green Electricity Trading

CHEN Zhiliang; WEI Miao; HU Xinyuan; YANG Yongbo; MA Zhijun; MA Zhongkun

doi:10.13296/j.1001-1609.hva.2025.11.006

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Multi-objective Optimization for Peak Shaving of Wind-solar-cascade Hybrid Pumped Storage System Accounting for Green Electricity Trading

Power Grid Regulation and Control Strategy | 更新时间：2025-11-04

- Multi-objective Optimization for Peak Shaving of Wind-solar-cascade Hybrid Pumped Storage System Accounting for Green Electricity Trading
- High Voltage Apparatus Vol. 61, Issue 11, Pages: 58-70(2025)
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- DOI：10.13296/j.1001-1609.hva.2025.11.006
  CLC：
- Received：22 May 2025，
  
  Revised：2025-07-28，
  
  Published：16 November 2025
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CHEN Zhiliang, WEI Miao, HU Xinyuan, et al. Multi-objective Optimization for Peak Shaving of Wind-solar-cascade Hybrid Pumped Storage System Accounting for Green Electricity Trading[J]. High voltage apparatus, 2025, 61(11): 58-70.
DOI：

CHEN Zhiliang, WEI Miao, HU Xinyuan, et al. Multi-objective Optimization for Peak Shaving of Wind-solar-cascade Hybrid Pumped Storage System Accounting for Green Electricity Trading[J]. High voltage apparatus, 2025, 61(11): 58-70. DOI： 10.13296/j.1001-1609.hva.2025.11.006.

摘要

针对水电机组传统调节模式出力透支与调节灵活性不足的问题，文中提出了计及绿电交易的风光—梯级混合式抽水蓄能调峰多目标优化控制方法。通过拉丁超立方采样和迭代自组织聚类算法生成风光出力典型场景集，综合考虑风光出力预测准确度、碳减排价值、环境效益及市场供需多种因素，建立了绿电价格动态测算模型。通过将部分传统水电机组改造为抽水蓄能机组，构建风光—梯级混合式抽水蓄能联合系统，解决常规水电调峰功能单一的问题。以剩余负荷峰谷差最小和绿电收益最大为目标，建立计及绿电交易的风光—梯级混合式抽水蓄能调峰多目标优化模型，对比分析了不同改造方案的调峰效果。算例结果表明：采用多水电站改造方案优化后的剩余负荷峰谷差降低了61.6%，绿电收益达786.63万元，光伏利用率提升至99.49%，为新型电力系统低碳化与灵活性提升提供了理论依据与实践路径。

Abstract

In view of the issues of output overcommitment and insufficient regulation flexibility in traditional operation modes of hydropower units，in this paper a multi-objective optimal control method for peak shaving considering green electricity trading in a wind-solar-cascade hybrid pumped storage system is propsoed. The typical scenarios for wind and solar power output are generated by using Latin hypercube sampling and an iterative self-organizing clustering algorithm. A dynamic pricing model for green electricity with such comprehensive consideration factors as the prediction accuracy of wind and solar power output，carbon reduction value，environmental benefits，and market supply and demand is set up. By converting some conventional hydropower units into pumped storage units，a wind-solar-cascade hybrid pumped storage integrated system is constructed，overcoming the limitation of singlefunction peak shaving in conventional hydropower. Moreover，a multi-objective optimization model for peak shaving considering green electricity trading with the minimization of the residual load peak-valley difference and the maximization of green electricity revenue as objectives is set up. The peak-shaving effects of different retrofitting schemes are comparatively analyzed. The example calculation shows that the residual load peak-valley difference after the adoption of the multi-hydropower-station retrofitting scheme is reduced by 61.6%，green electricity revenue is up to 7.866 3 million yuan，and photovoltaic utilization rate is increased to 99.49%，which can provide a theoretical basis and practical pathway for enhancing the low-carbon transition and flexibility of the new power system.

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