Abstract
Optimal energy management has become a challenging task to accomplish in today’s advanced energy systems. If energy is managed in the most optimal manner, tremendous societal benefits can be achieved such as improved economy and less environmental pollution. It is possible to operate the microgrids under grid-connected, as well as isolated modes. The authors presented a new optimization algorithm, i.e., Oppositional Gradient-based Grey Wolf Optimizer (OGGWO) in the current study to elucidate the optimal operation in microgrids that is loaded with sustainable, as well as unsustainable energy sources. With the integration of non-Renewable Energy Sources (RES) with microgrids, environmental pollution is reduced. The current study proposes this hybrid algorithm to avoid stagnation and achieve premature convergence. Having been strategized as a bi-objective optimization problem, the ultimate aim of this model’s optimal operation is to cut the costs incurred upon operations and reduce the emission of pollutants in a 24-h scheduling period. In the current study, the authors considered a Micro Turbine (MT) followed by a Wind Turbine (WT), a battery unit and a Fuel Cell (FC) as storage devices. The microgrid was assumed under the grid-connected mode. The authors validated the proposed algorithm upon three different scenarios to establish the former’s efficiency and efficacy. In addition to these, the optimization results attained from the proposed technique were also compared with that of the results from techniques implemented earlier. According to the outcomes, it can be inferred that the presented OGGWO approach outperformed other methods in terms of cost mitigation and pollution reduction.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference48 articles.
1. Combined Economic Emission Dispatch of Microgrid with the Incorporation of Renewable Energy Sources Using Improved Mayfly Optimization Algorithm;Nagarajan;Comput. Intell. Neurosci.,2022
2. A review of optimal operation of microgrids;Karthik;Int. J. Electr. Comput. Eng.,2020
3. Optimal management of hydrogen storage in stochastic smart microgrid operation;Konstantinopoulos;Int. J. Hydrogen Energy,2018
4. Multi-objective optimal operation in a micro-grid considering economic and environmental goals;Aghajani;Evol. Syst.,2019
5. Optimum operation management of microgrids with cost and environment pollution reduction approach considering uncertainty using Multi-objective NSGAII algorithm;Kamarposhti;IET Renew. Power Gener.,2022
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