A Hybrid Algorithm for Energy Management in Smart Grid

Efficient energy management requires smart approaches in demand side as well as demand response management assisted by smart, innovative, and computationally feasible schemes. Artificial intelligence algorithms are increasingly becoming helpful in generating multiple scenarios for a range of real world problems on the pattern of human Intelligence. This paper draws on employing algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) to generate a hybrid algorithm inspired by the characteristics of these two. Finally simulations have been drawn graphically to compare the energy consumption patterns for appliance scheduling schemes as well as corresponding cost analysis for energy optimization.