Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response

This study tackles a key challenge in modern energy management: how to optimize energy distribution when expanding the network is not economically or practically feasible. It explores the integration of hybrid renewable energy sources into a microgrid (MG) and proposes an energy dispatch strategy for MGs operating in both grid-connected and standalone modes. The study incorporates various energy sources, including solar panels (PV), wind turbines (WT), fuel cells (FC), microturbines (MT), diesel generators (DG), and energy storage systems (ESS). Unlike many existing studies that focus only on reducing operating costs, this research also considers energy losses, environmental impacts, and demand response-a vital but often overlooked factor. The research introduces a new method using a mixed-integer linear programming approach to solve the microgrid energy management (MGEM) problem. This method provides a multi-objective solution that includes demand response scheduling and optimizes factors such as PV and WT capacities, energy storage strategies, battery usage, power exchange with the grid, and overall costs and environmental impacts. When compared to leading optimization algorithms, the proposed approach showed better performance. The study also highlights the benefits of demand response programs in improving MG operations. For instance, using a Real-Time Pricing (RTP)-based demand response program reduced operating costs by 3.31%, emission penalties by 2.61%, and power losses by 0.62%. Similarly, a Direct Load Control (DLC)-based program achieved reductions of 2.25%, 2.1%, and 3.56%, respectively. This work advances MG energy management by addressing overlooked factors and demonstrating the benefits of integrating demand response programs into energy optimization strategies.

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