Multi‐objective optimisation framework for standalone DC‐microgrids with direct load control in demand‐side management

• Published in: Electronics letters Vol. 60; no. 15
• Main Authors: Jayasinghe, Hasith, Gunawardane, Kosala, Zamora, Ramon
• Format: Journal Article
• Language: English
• Published: Wiley 01.08.2024
• Subjects: demand side management; energy management systems; energy storage
• DOI: 10.1049/ell2.13290
• ISSN: 0013-5194

Renewable energy‐powered DC microgrids have emerged as a sustainable alternative for standalone power systems in remote locations, which were traditionally reliant on diesel generators (DIG) only. To ensure power quality and reliability, energy storage systems (ESS) and demand‐side management (DSM) techniques are employed, addressing the intermittent nature of renewable energy sources (RES). This manuscript presents a novel multi‐objective optimisation framework to determine the equipment sizing, depth of discharge (DoD) of ESS, and share of controllable loads contributing to DSM in a standalone DC microgrid incorporated with RES as a primary energy source and a backup DIG. The proposed optimisation strategy utilises genetic algorithm with the objectives of minimizing lifecycle cost and carbon footprint. A novel battery energy storage system (BESS) management criterion is introduced, which accounts for battery degradation in the lifecycle cost calculation. The minimum allowable DoD of the BESS is considered a decision variable in the optimisation problem to assess the impact of higher DoD on lifecycle cost improvement. MATLAB simulation results demonstrate that the proposed optimisation model significantly reduces the levelized cost of electricity and per unit carbon footprint compared to previous models. Additionally, it identifies an optimal range of DoD for the BESS to enhance the lifecycle cost of a standalone DC microgrid. Renewable energy sources have emerged as a sustainable alternative to diesel generators in standalone power systems. Energy storage, coupled with demand‐side management, addresses the intermittency issues of renewable energy when integrating into standalone DC microgrids. This study presents a novel methodology of a multi‐objective optimization framework for integrating demand‐side management and a novel battery management methodology to minimize the cost, carbon footprint, and energy curtailment of standalone DC microgrids.