Social Spider Optimization Algorithm-Based Optimized Power Management Schemes

Energy management (EM) is the essential factors of a smart grid, among residential consumers. These also include the demand side response and cost analysis. The aim of this paper is to be ecological benefit analysis for better consumption and load management. By shifting the load demand, the housing electricity cost reduced by the house energy management system (HEMS)-based cost analysis technique. The optimization is developed to minimize the cost, reduce greenhouse gases emissions and curtail dump energy. The implementation results are obtained by MATLAB R2016a working platform and the results are compared with different kind of algorithms such as ant lion optimization (ALO), Shuffled frog leaping algorithm (SFLA), flower pollination algorithm (FPA), Bees algorithm (BA), crow search optimization (CSO) algorithm. The reduction of electricity cost in a smart home is the main aim of the objective constrained problem and provides the solution to the proposed system. In addition, it uses to discover the operation modes of different loads with production systems. The simulated results obtained with the lowest price in the proposed system, which is about 10, 716.12Rs. Thus, the efficiency of the proposed system makes 76% better than the existing methods.