An Integrated Energy Control System to Provide Optimum Demand Side Management of a Grid-Interactive Microgrid

The use of renewables can make it more challenging to maintain a balance between supply and demand in microgrids due to their variable generation profiles. To address this issue, microgrids can be designed to be grid-interactive or to include energy storage units, or both. Additionally, demand-side management (DSM) strategies can be implemented to facilitate control during peak periods. This paper presents a control system for a grid-interactive microgrid with photovoltaic (PV) panels and energy storage units. The proposed system uses a fuzzy-based algorithm to control the energy storage units and provides DSM through the use of a hybrid daily pricing model that combines multi-time rate and inclining block rate pricing methods. To optimize the global maximum power point of the PV panels under partial shading conditions, the microgrid model is tested with several metaheuristic optimization algorithms, including particle swarm optimization (PSO), gray wolf optimization (GWO), and dragonfly algorithm (DA). A hybrid algorithm that combines PSO and DA is also proposed. The resulting integrated control system includes both demand-side and grid-side control operations.