Economic analysis of an intelligent optimization based hybrid renewable energy system

Abstract

In response to a growing population, rising oil prices, depletion of newlinefossil fuels, and a growing demand for energy, renewable energy has become a newlineviable alternative to conventional energy. A renewable energy source (RES) newlinehas several advantages similar to conventional energy sources, including newlinepollution-free, cost-effective, environmentally friendly, and more sustainable. newlineAlthough these energy sources have numerous advantages, they also have some newlinedrawbacks, such as high production costs and a long energy production cycle. newlineHybrid Renewable Energy Systems (HRES) are a solution which combines newlinerenewable energy with conventional energy sources to form a viable solution. newlineHybrid Energy Systems (HES) are difficult to size optimally to satisfy customer newlinepower demand and meet reliability requirements. Availability of generated newlinepower and the cost of equipment are two fundamental constraints preventing newlinewidespread adoption. It is essential to design these hybrid renewable energy newlinesystems to fulfill all load requirements while requiring the least amount of newlineinvestment and running expenses as possible. This research presents a newlineproductive approach to the economic management of smart grid-connected newlinesystems, which addresses the aforementioned issues. newlineAn optimization based cost analysis method is presented to minimize newlinethe cost function while providing the energy demand. Fuzzy rule based Particle newlineSwarm Optimization (F-PSO) based cost analysis of hybrid renewable energy newlinesystem is proposed. The advantages of hybrid systems over single energy newlinesystems include low pollution, high load factor, and high efficacy. Providing newlineenvironmental benefits, reliability, and cost-effectiveness are all advantages of newlinehybrid renewable energy systems newline