Resiliency-Constrained Placement and Sizing of Virtual Power Plants in the Distribution Network Considering Extreme Weather Events

Abstract

Abstract The placement and scale of virtual power plants (VPPs) in distribution networks are the only topics covered in this article that pertain to the resilience of the grid to severe weather. This problem is framed as a two-objective optimization, where the predicted energy that the network would not deliver in the case of an earthquake or flood, and the annual planning cost of the VPP, are the two objective functions to be reduced. The constraints include the formula for VPP planning, limitations on network operation and resilience, and equations for AC power flow. Uncertainties about demand, renewable power, energy prices, and the supply of network hardware and VPP components are all taken into account in stochastic programming. The proposed technique achieves a single-objective formulation in the subsequent stage by the use of a Pareto optimization strategy based on the ε-constraint method. This article uses a solver based on a hybrid of Crow search algorithm (CSA) and sine cosine algorithm (SCA) to achieve the trustworthy optimal solution with lowest dispersion in the final response. In order to tackle the problem, the proposed system looks at how the VPP affects network resilience, scales it, and combines it with the hybrid evolutionary algorithm. In the end, the numerical findings verify that the optimal placement and dimensions of VPPs help to improve the operational, financial, and resilience status of the distribution network by applying the proposed problem to a 69-bus distribution network.