Battery storage bank is included in the system to provide the baseload power in the time when renewable sources are not suffice to meet the baseload power demand. Diesel generators equal to the rating of base load is kept as backup to avoid total black out in worse conditions. Our objective is to schedule and shift the controllable appliances by estimating hourly power generation and considering consumer demand as a variable function. The appliances are prioritized based on their need and demand to achieve optimum energy utilization. The main contribution of this paper include: A demand side management algorithm is proposed to fulfil the energy gap between generation and consumer’s demand for standalone renewable energy system. K-mean clustering is used to make clusters of the data based on two factors: probability of turning ON a specific appliance at time t and priority number given by consumer to that specific appliance. Linear integer programming is used to schedule the appliances clusters based on the available power and state of charge of the battery system. According to your suggestion, the novelty of the proposed work has been made more clear and understandable for readers in the introduction section as follows: In this work, a DSM algorithm is proposed by using renewable resources PV and wind turbines for those houses that are located far away from the main city.
The authors should carefully distinguish the new contributions of their work from the new existing studies.for example: DOI: 10.1016/j.est.2020.101221