Excess energy management and techno-economic analysis of optimal designed isolated microgrid with reliability and environmental aspects

• Published in: Energy conversion and management Vol. 333; p. 119772
• Main Authors: Yadav, Subhash, Kumar, Pradeep, Kumar, Ashwani
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2025
• Subjects: administrative management; algorithms; Anisoptera (Odonata); Battery energy storage; Biogas generator; capital; carbon dioxide; energy conversion; Excess energy management; Hybrid renewable energy system; Levelized cost of energy; Metaheuristic optimization algorithms; power generation; probability; renewable energy sources; Wind and solar energy; wind turbines; Metaheuristic optimization algorithms; Biogas generator; Battery energy storage; Wind and solar energy; Excess energy management; Levelized cost of energy; Hybrid renewable energy system
• ISSN: 0196-8904
• DOI: 10.1016/j.enconman.2025.119772

•Optimal sizing of microgrid by minimizing LCOE and keeping high supply reliability.•Restricting the excess energy generation in isolated microgrid with fully HRES.•Optimization is performed with three metaheuristics algorithms: GWO, AVOA, and DA.•Performance of algorithms is analyzed based on results accuracy and execution time.•Analyze the effectiveness of proposed microgrid for the reduction of GHG emissions. Isolated microgrids generate excess energy (Pexg) up to 70.1% of total generation, disturbing supply reliability and protection systems. This study presents the Pexg management, optimal design, and techno-economic-environmental analysis in a Hybrid Renewable Energy System (HRES) based isolated microgrid. The optimal sizing is obtained with the minimization of Levelized Cost Of Energy (LCOE), subject to Deficiency of Power Supply Probability (DPSP), and Percentage of Excess Power Generation (PEPG) to maintain the supply reliability and restrict the Pexg generation. The outage rate of Solar Photovoltaic (SPV) and Wind Turbine (WT) units is also considered to obtain the microgrid design. The proposed model is optimized using the African Vultures Optimization Algorithm (AVOA), Dragonfly Algorithm (DA), and Grey Wolf Optimization algorithm (GWO). Results show that GWO performs superior to AVOA and DA in standings of execution time and accuracy. The proposed microgrid with energy management techniques restricts the Pexg at 4.84% and 9.64% for Case-A and Case-B, respectively. The minimized LCOE of most techno-economical-environmentally friendly configuration SPV-WT-BG-BES is 0.2414 $/kWh and 0.1133 $/kWh for Case-A and Case-B, respectively, obtained with GWO. This configuration reduces the GHG emissions by 76.09% and 89.33% for Case-A and Case-B, respectively. The sensitivity analysis shows that LCOE varies significantly with the growth in load demand and capital costs. The CO2 emissions increase almost linearly with the raise in load growth. Thus, the proposed isolated microgrid design offers a techno-economically-environmental friendly system as it offers minimum LCOE, lowest Pexg, high supply reliability, and 100% Renewable Energy Fraction (REF).