A PSO-Based Multi-objective Optimization to Satisfy the Electrical Energy Demand Through Renewable Energy Integration: A Case Study

Abstract

In the pathway of sustainable development, the energy consumption achieves crest and becomes a global issue. Several countries are trying to tackle this problem of increase in demand of energy and limited reserves of fossil fuel-based resources. Also, the energy consumption giving rise to the environmental issues is another big concern. Researchers, all over the globe, are very keen about this problem and suggesting solutions in the form of energy efficiency, conservation and renewable energy technology. Nowadays, larger penetration of renewable energy resources in grid is getting much more lead and importance. This paper reveals a particle swarm optimization (PSO) technique in Microsoft XL optimizer and is utilized to satisfy the electrical demand for the case study of Kolhapur in Maharashtra state in India. The 40% of total electrical the demand is tried to satisfy due to lack of supportive grid capability to accommodate the renewable electricity more than this. Solar PV, wind energy and small hydropower resources are utilized to satisfy the electrical demand. An optimization problem based on multi-objective is formulated for the integrated combination of resources to satisfy the average single-day electrical demand of first of each month for the whole year. Mainly, cost and CO2 emission reduction are the objectives considered to solve the constant optimization problem.