Dеtеrmіnіng Thе Bеst Lοаd Schеdulіng Аlgοrіthm Fοr А Hοmе Wіth Еlеctrіcіty Supply Frοm Grіd Аnd Sοlаr

Abstract

Improving energy efficiency is becoming increasingly critical to reduce energy consumption and to solve the environmental crisis. The following paper describes a mixed-integer linear programming optimization algorithm to minimize the peak demand at the micro-grid level and to reduce the cost function in a smart home environment. The optimization methods take into account the timevarying electricity price and the varying energy demand peaks to determine the most suitable time to use home appliances. The algorithms are further used to compare the energy cost reduction results with and without the use of renewable resources and more precisely photovoltaic modules. Also, the sizing of a photovoltaic system is implemented to achieve further efficient energy optimization and appliance scheduling. Finally, a cost-benefit analysis is performed on all the scheduling algorithms to determine which is the most cost-effective.