Optimal Operation of Microgrids Using biLevel Evolutionary Algorithm in the Presence of Uncertain Renewable Energy Resources

Saeid Shakerinia^{1} , Abbas Fattahi May Abadi ^{*} ^{2}, Mojtaba Vahedi^{1} , Nasrin Salehi^{3} , Mahmoud Samiei Moghaddam^{4} 
1 Department of Electrical Engineering, Shahrood Branch, Islamic Azad University, Shahrood, Iran 2 Hamedan University of Technology 3 Department of Basic sciences, Shahrood Branch, Islamic Azad University, Shahrood, Iran 4 Department of Electrical Engineering, Damghan Branch, Islamic Azad University, Damghan, Iran 

Abstract: (436 Views) 
With the increasing penetration of renewable energy sources such as wind and photovoltaic generation in future microgrids, challenges arise due to variable weather conditions. In this paper, a model is proposed to optimize the performance of microgrids under the worstcase scenario of renewable energy source failures using a bilevel optimization. In the upperlevel problem, optimization is carried out in terms of energy loss reduction, load shedding in the load management program, as well as optimal charging and discharging of energy storage systems. The lowerlevel problem considers maximizing the utilization of renewable energy. A bilevel optimization solution method is proposed, which involves binary variables at both levels and is solved using a nondominated sorting genetic algorithm (NSGAII). The proposed model and algorithm are implemented using the Julia programming language. The performance of the model is examined under various conditions using a 33bus microgrid, and the optimization results demonstrate the optimal performance of the microgrid under the worstcase scenario of renewable energy source failures.


Keywords: Microgrid, Demandside management, Optimization, Renewable resources, Energy storage system, Evolutionary algorithm 

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Type of Study: Research 
Received: 2023/07/7  Accepted: 2023/09/30  Published: 2023/12/23





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Shakerinia S, Fattahi May Abadi A, Vahedi M, Salehi N, Samiei Moghaddam M. Optimal Operation of Microgrids Using biLevel Evolutionary Algorithm in the Presence of Uncertain Renewable Energy Resources. ieijqp 2023; 12 (4) :7287 URL: http://ieijqp.ir/article1967en.html
