Journal
JOURNAL OF ENERGY STORAGE
Volume 65, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.est.2023.107240
Keywords
Energy management system; Batteries; DC microgrids; Parallel processing; Metaheuristic methods; Variable power demand; Variable renewable generation; Particle swarm optimization; Vortex search algorithm; Ant lion optimizer
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This study focuses on the optimal operation of batteries in standalone and grid-connected DC Microgrids that include photovoltaic generators operating at maximum power point. A mathematical model with three objective functions was formulated to minimize operating costs, reduce energy losses, and minimize CO2 emissions. The model integrates constraints representing the operation of DC microgrids. Three parallel solution methodologies were used: PPSO, PVSA, and PALO. Tests were conducted to validate the effectiveness of the solution methods using MATLAB software. The results showed that PVSA performed the best in standalone grids, while PALO achieved the best results in grid-connected networks.
This study addresses the problem of optimal operation of batteries in standalone and grid-connected Direct Current (DC) Microgrids (MGs) that include photovoltaic (PV) generators operating at maximum power point. For that purpose, a mathematical model was formulated considering three objective functions: (1) the minimization of operating costs, (2) the reduction of energy losses associated with energy transport in DC MGs, and (3) the minimization of the total emissions of CO2 into the atmosphere produced by conventional generators. The model integrates a set of constraints that represent the operation of DC microgrids. Three parallel versions of well-known solution methodologies were used here: Parallel Particle Swarm Optimization (PPSO), the Parallel Vortex Search Algorithm (PVSA), and the Parallel Ant Lion Optimizer (PALO). These methodologies were implemented to optimize the hourly power flow method based on successive approxi-mations and evaluate the objective functions and constraints. To validate the effectiveness of the solution methods proposed in this paper, two test systems were used: a standalone network and a grid-connected network (both in Colombia). Furthermore, to test the effectiveness of the proposed energy management system (regarding solution, repeatability, and processing times) each solution methodology was executed 100 times in each test system using MATLAB software. Based on the results of the simulations, the methodology with the best performance for standalone grids was the PVSA. In turn, the methodology that achieved the best results in the grid-connected network was the PALO. In both scenarios, the best average reductions in energy fixed costs, variable costs, energy losses, and CO2 emissions were 0.0282%, 1.3039%, 9.1655%, and 0.1254%, respectively. Although these were important benefits in technical and environmental aspects, the results of the economic indicator suggest that the operation of electrical networks should consider variable costs in order to improve the impact of energy management systems in the future.
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