Optimal Sizing and Placement of Solar Cell Distributed Generator Suitable for Integrated Power System Environment

Abstract

A novel fuzzified Clustered Gravitational Search Algorithm (CGSA) has been employed for solving multi-objective problem formulated for solar based distributed generation. Optimal sizing and placement of solar distributed generation is considered. High solar penetration can lead to high-risk level in power system reliability. In order to maintain the system reliability, solar power dispatch is usually restricted based on the reliability level of the system. Two conflicting objective functions such as power loss and reliability level of the system are also considered for solving optimal placement of solar distributed generation (SDG). Binary coded CGSA is employed for solving optimal placement of SDG and sizing is determined using real coded CGSA. The fuzzy membership function for each objective is designed and multi-objective optimal placement problem has been presented. The proposed method is validated on IEEE standard 69-bus radial distribution networks. The efficiency of the proposed optimization technique is validated by comparing the results with other results available in the existing articles.

Optimal PMU Placement for Türkiye 400 kV Interconnected Power System Observability with Dragonfly Algorithm

“…PMU measurements have become important in power systems due to the benefits they provide in studies to reduce risks against cyber-attacks, Volt-VAr control, which is expressed as reactive power control, and transmission network state estimation studies [2][3][4][5]. They have done different studies using power systems and IEEE bus systems [6][7][8][9]. They applied state estimation for different power systems with synchronized phasor measurements provided using PMU [10].…”