Central Demand Side Management for Smart Buildings Using AHO Optimization Technique and Different Pricing Schemes

This paper proposes a central demand side management (DSM) for smart buildings based on an advanced optimization algorithm. The smart building loads are supplied with renewable energy sources (RESs). The paper’s objectives are to reduce the total electricity bill, improve the peak-to-average ratio (PAR), and enhance user comfort. Archerfish hunting optimizer (AHO) is applied to obtain an optimal load profile during the day to ensure the system’s objectives while ensuring system operational constraints. The smart building utilizes the Internet of Things (IoT) with Wi-Fi communication protocol to optimally facilitate communication between the system’s load, RESs, and the central control unit. The proposed method is applied and tested using MATLAB program on a hypothetical smart building. For the sake of comparison, the particle swarm optimization algorithm (PSO) and butterfly optimization method (BFA) are applied to prove the effectiveness of the proposed method. Two pricing principles are used including critical peak pricing (CPP) and time of use pricing (ToU). The results prove the ability of the proposed method to reduce the electricity bill, improve the PAR, and enhance user comfort.