A NOVEL DESIGN AND OPTIMIZED MODEL OF A NANO GRID FOR ENERGY AND ECONOMIC MANAGEMENT USING NATURE INSPIRED ALGORITHM

Abstract

In today’s environment, small energy systems such as Nano grids play significant role in enhancement of grid modelling with smart grids and microgrids. The main concern is optimal output in energy and economic performance in order to reduce operating costs and increase system efficiency. This paper proposes and shows a novel nano grid paradigm to integrate state-of-the-art materials for energy storage and renewable generation. Further, an advanced hybrid Differential Evolution–Salp Swarm Algorithm (DE-SSA) is employed for multi-objective energy-economic management, combining the global search capabilities of DE with the efficient local exploitation of SSA. Simulation results that demonstrate higher system reliability, lower operating costs, and increased energy usage as compared to conventional and single-algorithm approaches demonstrate the promise of DE-SSA for nanogrid management