| 葛毅,王鹏,李泽森,龚国仙,李冰洁,黄明宇.区域电力系统储能容量多目标分布鲁棒规划[J].电力需求侧管理,2026,28(4):30-36 |
| 区域电力系统储能容量多目标分布鲁棒规划 |
| Multi-objective distributionally robust planning of energy storage for power systems |
| 投稿时间：2026-03-01 修订日期：2026-05-05 |
| DOI：10.3969/j.issn.1009-1831.2026.04.005 |
| 中文关键词: 电力系统规划 频率安全 多目标规划 约束线性化 分布鲁棒优化 帕累托解集 |
| 英文关键词: power system planning frequency security multi-objective optimization constraints linearization distributionally robust optimization pareto solution set |
| 基金项目:国网江苏省电力有限公司科技项目(J2024156) |
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| 中文摘要: |
| 随着可再生能源高比例并网,电力系统短时功率不平衡加剧,频率安全面临挑战。配置储能成为应对该挑战的关键手段。现有考虑频率安全的储能规划方法在推导频率安全约束时通常预设功率波动,导致结果保守,且非线性频率约束在不确定性下求解复杂。为此,提出一种多目标分布鲁棒储能容量规划方法。该方法通过聚类生成典型日场景,采用场景枚举法将非线性频率安全约束转化为混合整数规划形式,并基于分布鲁棒优化应对功率不确定性。通过算例给出了频率安全在不同置信水平下的帕累托解集,并进一步分析了频率安全约束及绿色目标权重等关键因素对储能配置的影响。结果表明,所提方法能有效协同经济、绿色与安全目标,为区域电力系统储能规划提供决策支持。 |
| 英文摘要: |
| With the high penetration of renewable energy integrated into the grid, short-term power imbalances in power systems intensify, posing challenges to frequency security. Deploying energy storage is regarded as a critical means to address this challenge. In existing energy storage planning methods that consider frequency security, power fluctuations are usually presupposed when deriving frequency security constraints, leading to overly conservative results; moreover, the nonlinear frequency constraints become computationally complex under uncertainty. To this end, a multi-objective distributionally robust energy storage capacity planning method is proposed. Typical daily scenarios are generated through clustering, the nonlinear frequency security constraints are transformed into a mixed-integer programming formulation via scenario enumeration, and distributionally robust optimization is employed to handle power uncertainty. Pareto solution sets with frequency security satisfied at different confidence levels are provided through case studies, and the impacts of key factors such as frequency security constraints and green objective weights on energy storage configuration are further analyzed. It is demonstrated that the proposed method can effectively coordinate economic, green, and security objectives, offering decision support for energy storage planning in regional power systems. |
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