A Price/Power Weighting Based Linearization Approach With a Battery Management System for an Appliance-scheduling Model

Abstract

In Demand Side Management framework, the models are generally complex, nonlinear, and highly constrained. This study proposes a price/power weighting-based linearization integrating a battery management system for an appliance-scheduling model to overcome constraints handling issues and computational challenges of the metaheuristic algorithms. To this end, the notion of a relative cost is introduced. Simulation results demonstrate that the proposed approach is capable of solving an appliance-scheduling problem, using Mixed Integer Linear Programming, with a shorter run time compared to the result provided by the nonlinear problem solved by genetic algorithm-based while ensuring self-consumption.