Multi-objective Distributionally Robust Optimal Allocation for Supply-reliable Wind-storage Microgrids Considering Topological Structure Selection

ZHANG Haoze; WANG Lei

doi:10.19725/j.cnki.1007-2322.2024.0154

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Multi-objective Distributionally Robust Optimal Allocation for Supply-reliable Wind-storage Microgrids Considering Topological Structure Selection

更新时间：2026-10-19

- Multi-objective Distributionally Robust Optimal Allocation for Supply-reliable Wind-storage Microgrids Considering Topological Structure Selection
- Vol. 43, Issue 5, Pages: 821-832(2026)
- 作者机构：
  
  上海电力大学电气工程学院, 上海市杨浦区,200090
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2024.0154
  CLC： 5
- Published：2026
- 稿件说明：
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ZHANG Haoze, WANG Lei. Multi-objective Distributionally Robust Optimal Allocation for Supply-reliable Wind-storage Microgrids Considering Topological Structure Selection[J]. 2026, 43(5): 821-832.
DOI：

ZHANG Haoze, WANG Lei. Multi-objective Distributionally Robust Optimal Allocation for Supply-reliable Wind-storage Microgrids Considering Topological Structure Selection[J]. 2026, 43(5): 821-832. DOI： 10.19725/j.cnki.1007-2322.2024.0154.

摘要

针对现有配置方法下微网可靠性不足和风电不确定性的问题，提出考虑拓扑结构选择和分布鲁棒机会约束的保供电型风储微网多目标配置方法。首先，建立以微电网故障率、净等年成本和功率损耗为目标的保供电型风储微网优化配置模型，实现微网系统在可靠性、经济性和节能三方面的最优表现。其次，考虑到拓扑结构对于确保微网的可靠性至关重要，在上述优化模型中引入结构变量来提高微网可靠性。然后，采用分布鲁棒机会约束(distributionally robust chance constraint，DRCC)处理风电不确定性问题，构建基于Wasserstein距离的DRCC模型，再利用CvaR-Slim凸近似原理将所构建的DRCC模型线性化。最后，以某高层商业办公楼为算例，通过将NSGA Ⅱ算法和多属性模糊决策(multi-attribute fuzzy decision-making，MAFDM)算法结合来求解优化模型，并将所得结果与其他常规方案进行对比分析，验证所提微网优化配置方法的有效性。

Abstract

To address the issues of the insufficiency in reliability and uncertainty in wind power under existing configuration methods

a multi-objective configuration method for power supply assurance wind-storage microgrids is proposed. The proposed method accounts for topological structure selection and distributionally robust chance constraint (DRCC). First

an optimal configuration model for power supply assurance wind-storage microgrids with the target of microgrid failure rate

net equal annual cost

and power loss is established

aiming to achieve the optimal performance of the microgrid system in reliability

economy and energy saving. Secondly

given the significant impact of the topological structure on microgrid reliability

structural variables are introduced into the aforementioned optimization model to improve the reliability and configuration flexibility of the microgrid. Subsequently

a DRCC model based on Wasserstein distance is constructed to address the uncertainty of wind power. The DRCC model is linearized using the CVaR-Slim convex approximation approach. Finally

taking a high-rise commercial office building as an example

the NSGA-Ⅱ algorithm is combined with multi-attribute fuzzy decision-making (MAFDM) algorithm to solve the optimization model. The comparative analysis of the optimization results verifies the effectiveness of the proposed microgrid optimal configuration method.

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references

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