Efficient Optimization Algorithm for Dwindling Payment and Power Management

Abstract

In this current era, rising demand ultimately leads to the scarcity of source in terms of power. To fulfill this inadequacy and because of the availability and easy conversion of electrical energy, hybrid energy system is the best choice for non renewable energy source replacement, which dominates the demand of reliable power. In this paper, we have proposed and analyzed the optimal capacity of the Photovoltaic and Wind as a hybrid system, standing as a foremost motivating force for the public improvement. To provide uninterrupted supply, storage device is used along with the integrated sources. The key pioneering part of this research paper is the performance of the projected system for cost optimization, which is realized by running the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms. The result is the baseline system cost necessary to meet the load requirements. The above stated process is implemented using MATLAB. The motivation of choosing these algorithms is because of swift convergence in real time power management. Performance parameter Total Harmonic Distortion (THD) is also calculated for the proposed system.