计及鲁棒预算调节的配电网分布式光伏承载力区间评估

Assessment of the Carrying Capacity Range of Distributed Photovoltaics in Distribution Networks Considering Robust Budget Adjustment

中文关键词:分布式光伏  双层鲁棒优化模型  区间评估  分布式光伏功率随机性  灵活资源调度不确定性

keywords:distributed photovoltaic （DPV）  bi-level robust optimization model  range assessment  randomness of DPV power  uncertainty of flexible resource scheduling

中文摘要:针对传统评估方法通过优化模型或数值仿真得到一系列数值点，准确性易受不确定性因素的影响的问题，提出计及鲁棒预算调节的（distributed photovoltaic，DPV）最大承载力区间评估方法，以提高评估结果的适应性和实用性。DPV承载力区间由乐观上界和悲观下界构成（乐观上界由计及多种运行约束的确定性模型刻画；悲观下界由含鲁棒预算调节约束的双层鲁棒模型进行描述，鲁棒预算调节约束用于融合不确定性因素）。双层鲁棒模型被等价重构为单层混合整数线性规划模型进行求解。135节点配电系统的仿真结果表明，所提方法能够在有效计及DPV功率波动随机性和灵活资源调度不确定性的同时，得到适用性强的DPV最大承载能力区间，从而验证了所提方法的有效性。

Abstract:Accurately assessing the maximum carrying capacity of Distributed Photovoltaic （DPV） systems is essential for enabling distribution networks to integrate DPV more effectively. However，traditional assessment methods，which rely on optimization models or numerical simulations to obtain a series of numerical points，are often susceptible to the influence of uncertainties. To address this，this paper proposes a DPV maximum carrying capacity range assessment method that incorporates robust budget adjustment，thereby enhancing the adaptability and practicality of the assessment results. The DPV carrying capacity range consists of an optimistic upper bound and a pessimistic lower bound. The optimistic upper bound is characterized by a deterministic model that accounts for various operational constraints，while the pessimistic lower bound is described by a bi-level robust model with robust budget adjustment constraints to integrate uncertainties. The bi-level robust model is equivalently reformulated into a single-level mixed-integer linear programming （MILP） model for solution. Finally，simulation results on a 135-bus distribution system validate the effectiveness of the proposed method. The proposed approach can effectively account for the stochastic nature of DPV power fluctuations and the uncertainties in flexible resource scheduling，while providing a robust and practical DPV maximum carrying capacity range.