A New Optimal Centralized Demand Side Management for a Campus Smart Microgrid

Based on demand response and energy theft detection, a novel optimal demand side management (DSM) is proposed for a smart microgrid (SMG). A campus SMG containing photovoltaic (PV), wind turbine, diesel station, smart meters, inverters, batteries, sensors, domestic loads, and central} {DSM unit is built in MATLAB. The SMG elements are communicated using Wi-Fi protocol and internet of things (IoT) technology. The proposed DSM is optimally designed using Grey Wolf Optimization (GWO) to minimize the customer's electricity bill, maximize the user comfort, and obtain the optimal load patterns in the hypothetical campus SMGs. It inspires consumers to alter their daily consumption patterns over a variable tariff according to real-time pricing (RTP), time of use (ToU), and critical peak pricing (CPP) methods. The results proved the proposed technique effectiveness for reducing the user's electricity bill and conserving utility resources through energy theft detection. Finally, the proposed GWO technique is compared with firefly algorithm (FFA) and bacteria foraging algorithm (BFA) to verify its superiority.