Performance comparison of optimum power flow based on the sequential second‐order cone programming in unbalanced low voltage distribution networks with distributed generators

Abstract

A solution technique using sequential second-order cone programming to solve the optimum power flow problem in low voltage (LV) distribution networks with distributed generation is developed. A novel bound tightening method is suggested to get exact solutions with few iterations. A novel approximation method is suggested to increase exactness by approximating phase angle dependent components. The performance of the suggested solution method is compared with linear programming, genetic algorithm, particle swarm, sequential quadratic programming with multiple start points, and global search-based optimization methods. The exactness of the generated solutions is validated after comparison with a load flow. The proposed algorithm provides better performance in optimality, execution time, and exactness compared to other methods.distributed generation, optimum power flow, power distribution system, second-order cone programming | INTRODUCTIONOptimum power flow (OPF) is used as a tool to optimally control controllable devices such as smart inverters, batteries, tap changing transformers, and static var compensators in LV networks. OPF for transmission networks is widely discussed in the literature, and they are used in day-to-day operations in transmission system control centers. 1,2 With the increased penetration of renewable energy in low voltage distribution systems, the use of OPF for controlling power