Optimal Dispatch of Active Distribution Network for Solar Power Accommodation Based on Conditional Value at Risk

Abstract

Nowadays, with the worldwide attention on renewable energy, the grid-connected photovoltaic (PV) equipment is playing a significant role in the active distribution network (ADN). This paper proposes a novel day-ahead optimal dispatch model for ADN based on the conditional value at risk (CVaR) to promote solar power accommodation. Firstly, the uncertainties of PV output and load are modeled by the generated typical scenarios based on historic data and K-means clustering and can be embedded in the discretized and linearized CVaR model. Then, the optimal dispatch model aimed to maximize solar power accommodation is established. Active management (AM) includes the on-load tap changer, capacitor bank, battery energy storage, and load curtailment. Constraints mainly involve power flow, nodal voltage, branch power load, and the limits of AM. The problem is finally transferred into a mixed-integer second-order cone programming one, which can be solved by the commercial solver Gurobi directly based on the branch-and-bound method. Case studies based on a modified IEEE 33-bus system illustrate the feasibility and validity of the proposed method.