Model and observation of the feasible region for PV integration capacity considering Wasserstein-distance-based distributionally robust chance constraints

Abstract

The increasing integration scale of photovoltaic (PV) systems brings enormous challenges on distribution networks (DNs). To provide an explicit boundary of feasible PV integration capacity (PVIC) associated with each integration location, this paper proposes a novel depiction of PV hosting capability, which is the feasible region for PVIC in high-dimensional space. Next, a multi-objective optimization model based on information gap decision theory (IGDT) is proposed to observe the feasible region, where active distribution network management (ADNM) schemes with a limited budget are deployed to improve PV hosting capability. The impact of PV output uncertainty on security constraints is addressed by data-driven Wasserstein-distance-based distributionally robust chance constraints (WDRCCs). Finally, a systematic procedure is developed to solve the proposed model. Note that the exact power flow model associated with a new equivalent WDRCC reformulation method is deployed so as to guarantee the accuracy of the assessment. The effectiveness, solution accuracy, computational efficiency, and scalability of the proposed model and method are verified with the 4-bus system, the IEEE 33-bus system, and the IEEE 123-bus system. The output of the common method based on the linearized power flow deviates by more than 10% from the output of the proposed method based on the exact power flow in the 33-bus system. Each multi-location PV integration request is feasible as its locations and capacities belong to the proposed region. It implies that this region can provide guidance for PV allocation.