Renewable energy management using improved ABC algorithm for residential community

Abstract

Smart grid have acquired centre of attraction in today’s scenario of increasing energy demand. Demand-side management (DSM) results in effective savings on electricity consumption and cost. The present work proposes minimization of total electricity cost as well as the total energy consumption of a residential community consisting of number of residential customers by applying an effective DSM strategy. A solar photo voltaic (SPV) generation system has also been installed and is therefore taken into account. The activity level of the residential consumers is also given privilege in problem formulation. Models of different household loads as well as SPV modules have been considered in the work. Environmental factors including irradiance profiles as well as ambient temperature changes have been considered in modelling of SPV generation capacity. The optimization problem has been addressed using Artificial Bee Colony (ABC) algorithm based on improved-global-best-guided approach and adaptive-limit strategy (IGAL) algorithm. The calculated cost savings as well as energy consumption has been compared with that obtained using standard ABC algorithm. Results reveal considerable savings with effective DSM strategy in place. Furthermore a comparative analysis between ABC and IGAL-ABC algorithm shows effectiveness of IGAL-ABC algorithm over the ABC algorithm in terms of computational time as well as savings. Significant reduction in cost of up to 43% using HEMS was obtained.