基于ADMM机会约束的光-储微网分布式优化运行

Distributed Optimization Operation of Optical Storage Microgrid Based on ADMM Chance Constraint

中文关键词: 光-储微网  源荷不确定性  ADMM机会约束  优化运行

英文关键词: Optical storage microgrid  Source-Load Uncer-tainty  ADMM chance constrianed  Optimal operation

中文摘要:

      当前光-储微网优化研究多采用确定性模型或鲁棒优化方法，前者忽略不确定性风险，后者因保守性牺牲经济性。针对这一问题，本文提出一种基于机会约束的分布式优化运行模型，以平衡经济性与运行风险。首先，通过数据拟合构建光伏发电功率和负荷预测误差的概率分布模型，量化不确定性影响；其次，基于机会约束理论建立概率功率平衡约束，将风险控制转化为置信水平调控问题；最后，设计自适应参数的交替方向乘子法（ADMM），实现分布式高效求解，并保护各参与方数据隐私。研究结果表明：通过调整置信水平，该模型可在风险与经济性间灵活权衡，当置信水平从85%提升至100%时，系统运行风险降低100%，同时总收益减少9.8%。相较于传统方法，所提模型在保障可靠性的同时，显著提升了优化结果的合理性。

英文摘要:

      The current research on optimization of photovolta-ic-storage microgrids mostly employs deterministic mod-els or robust optimization methods. The former ignores uncertainty risks, while the latter sacrifices economic performance due to its conservatism. To address this issue, this paper proposes a distributed optimization operation model based on chance constraints to balance economic efficiency and operational risk. First, a probability dis-tribution model for photovoltaic power generation and load forecasting errors is constructed through data fitting to quantify the impact of uncertainty. Then, a probabilistic power balance constraint is established based on chance constraint theory, transforming risk control into a confi-dence level adjustment problem. Finally, an alternating direction method of multipliers (ADMM) with adaptive parameters is designed to achieve efficient distributed solving while protecting the data privacy of all partici-pants. The results show that by adjusting the confidence level, this model can flexibly balance risk and economic efficiency—when the confidence level is increased from 85% to 100%, the system operation risk is reduced by 100%, while the total revenue decreases by 9.8%. Com-pared to traditional methods, the proposed model signif-icantly improves the rationality of the optimization results while ensuring reliability.