Dynamic programming for home appliance scheduling with renewable energy integration

This paper presents a simulation study on a home energy management system (HEMS) with the contribution of renewable energy sources (RESs) for effective demand-side management (DSM). The HEMS refers to a network that combines various smart home appliances and a control unit to optimize energy utilization and minimize overall energy costs. This study proposes an energy cost minimization model, which is solved using a single Knapsack algorithm combined with dynamic programming (DP). The Knapsack problem is used to schedule appliances and ensure that users and producers receive the maximum benefits in terms of cost minimization and peak-to-average ratio (PAR) reduction. The results of three different cases, minimum, average, and specific cost time slots, show that the system with RESs outperforms the case of without RESs, resulting in an 11.25% improvement in cost reduction and a 7.29% improvement in PAR reduction.