International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1057 Performance Improvement of the Distribution Systems using Meta-Heuristic Algorithm Controlled PV System Dr.Eng. Elham Mohamed Darwish 1 , Prof.Dr. Hany M. Hasanien 2 , Ahmed Atallah 3 , Soliman M. El-Debeiky 4 1 South Cairo Electricity and distribution Company, Cairo, Egypt 2,3.4 Electrical and Machines. Department-Faculty of Engineering Ain Shams University, Cairo, Egypt ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - The voltage profile of distribution grids with distributed generation (DG) is affected significantly due to the high penetration of the DG units. This paper focuses on enhancing the performance of the Photovoltaic (PV) system plants in the Egyptian distribution networks. The PV arrays are connected to the distribution grid via a three-phase inverter and a three-phase step up transformer. The PV inverter is fully controlled by the proportional plus integral (PI) controller through a cascade control scheme. The salient feature of this threshing is the design of the PI controller using the novel whale optimization algorithm (WOA). The effectiveness of the suggested controller is compared with that by using the genetic algorithm under uneven operating conditions. The WOA is coded using MatlaB software. The validity of the suggested paragon is verified extensively using the simulation results, which are carried out using Mat laB/Simulink Key Words: Genetic Algorithms, Response Surface Methodology, PV Systems Distribution System, Voltage Profile, Voltage Drop, P-V and V-I characteristics, Proportional Plus Integral Controller. Introduction 1. INTRODUCTION The PV systems are considered one of the most promising renewable energy systems, so the PV systems received great efforts worldwide in the last decades. This is due to many reasons just like that as, the trend to obtain a clean energy, the environmental concern, the increase in fuel prices, the possibility of fossil fuel depletion and reduction of the PV components cost [1,2]. The high level of penetration of the PV system into the power grid causes several problems which should be addressed, studied and investigated. The voltage drop (VD) of the distribution grid is considered to be solved using the installation of PV systems and it represents significant challenge. This study focuses on improving the voltage profile in three-phase distribution systems using advanced controlled PV systems, compared to the other current systems. In this respect, many studies evolutionary and swarm intelligence optimization techniques have been utilized to solve this problem such as genetic algorithms (GA) [3], [4], differential evolution (DE) [5], particle swarm optimization (PSO) [6], simulated annealing (SA) algorithm [7], bacterial foraging (BF) algorithm [8], harmony search algorithm (HSA) [9], artificial bee colony (ABC) algorithm [10], and Shuffled Frogs Leaping Algorithm (SFLA) [11]. The significant development of the meta-heuristic optimization techniques represents the impetus for using the WOA approach to improve the voltage to end grid where voltage drops reach unacceptable values. Meta-heuristic optimization algorithms are becoming more popularity in engineering applications because they: (i) rely on rather simple concepts and are easy to implement; (ii) do not need gradient information; (iii) can bypass local optima; (iv) can be used in a wide extent of problems covering uneven disciplines. The strength point of these a venues is that the best individuals are always combined together to form the next generation of individuals. This allows the population to be optimized over the destination of generations. This gives the premier motivation to the authors to solve this problem using a new methodology. A novel meta-heuristic algorithm called WOA is applied to optimally design, the PI controlled PV system to improve the voltage profile in the Egyptian distribution network. The WOA is a novel meta-heuristic algorithm, which inspired by the behaviour of the hump back whale. It is invented by Seyedali Mirjalili. Population-based meta-heuristic optimization algorithms share a commonest feature regardless of their nature. The search process is divided into two phases: exploration and exploitation [12, 13, and 14]. The optimizer must include operators to globally explore the search space: in this phase, movements (i.e. perturbation of design variants) should be randomized as most as sustainable. The exploitation phase follows the exploration phase and can be definable as the process of investigating in detail the promising area(s) of the search space. Exploitation hence pertains to the local search capability in the promising regions of design space found in the exploration phase. Finding a proper balance between exploration and exploitation is the most challenging task in the development of any meta- heuristic algorithm due to the stochastic nature of the optimization process The WOA is applied successfully to solve the optimization problems in many engineering studies. The proposed WOA is