Equilibrium Optimizer-Based Approach of PV Generation Planning in a Distribution System for Maximizing Hosting Capacity

Abstract

This paper presents an Equilibrium Optimizer (EO)-based method that simultaneously determines locations and sizes of multiple photovoltaic (PV) units for maximizing a distribution system's PV hosting capacity (PVHC). The proposed method avoids various search-space restrictions seen in recent literature. The constraints in this paper are separated into two types based on the necessity of power flow analysis. The proposed method is implemented through co-simulation between MATLAB and OpenDSS. PV output and load demand variation is considered through a 24-hour profile representing a season. Smart inverter is considered through the PV inverter volt-var control (VVC) scheme. The proposed method is tested on the IEEE 123-bus benchmark system. Four test cases are considered to determine the impact of reverse power flow (RPF) limit and the impact of VVC toward the optimal PV planning. The results show that EO produces superior results compared to Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Coyote Optimization Algorithm (COA).

Enhancing PV distributed generator planning in medium‐voltage DC distribution networks: A multi‐design techno‐economic analysis with load demand response

“…Recently, there are several current EOA implementations available in power system engineering topics for optimal allocation of multiple DG units and network reconfiguration [27], optimal allocation of PV sources and battery energy storage [28], optimal allocation of PVDG units for maximizing a PV hosting capacity [29], optimal allocation of optimal wind turbines (WT) generators [30], and optimal allocation of hybrid WT generators and energy storages [31], and distributed thyristor-controlled series compensator planning [32]. Applied EOA technique for the solar PV modules parameters extraction [33,34], energy management in a hybrid electric vehicle [35], load frequency control problem of power system [36], optimal automatic voltage regulator system [37], solving the reactive power dispatch problem [38], and solving the issue of optimal power flow [39,40].…”

Optimal Allocation of Photovoltaic-Green Distributed Generation for Maximizing the Performance of Electrical Distribution Networks

“…Hence, designers of distribution networks (DNs) must consider incorporating this vital technological necessity. Improper location, excessive quantity, or inadequate sizing of GDG installations may lead to an increase in power loss, voltage drop, and an overall unstable power system [4]. Although there are many optimization techniques, the choice between them depends on the specific requirements, objectives, and characteristics of the problem, as well as considerations such as optimization complexity, decision criteria of quantifiability, computational resources, and user expertise [5,6].…”