A Comparison of Energy Management System for a DC Microgrid
Source abstract
Abstract
This paper investigates the analysis of the energy management system for a DC microgrid. The microgrid consists of a photovoltaic panel and a batteries system that is connected to the microgrid through a bidirectional power converter. The optimization problem is solved by the hybrid internal point method with the genetic algorithms method and particle swarm optimization (PSO) method, by considering forecasting demand and generation for all the elements of the microgrid. The analysis includes a comparison of energy optimization of the microgrid for solar radiation data from two areas of the world and a comparison the efficiency and effectiveness of optimization methods. The efficiency of the algorithm for energy optimization is verified and analyzed through experimental data. The results obtained show that the optimization algorithm can intelligently handle the energy flows to store the largest amount in the batteries and thus have the least amount of charge and discharge cycles for the battery and prolong the useful life.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Microgrid Control and Optimization · Smart Grid Energy Management · Hybrid Renewable Energy Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Unidad de Energía Renovable, Centro de Investigación Científica de Yucatán AC., Mérida CO 97200, Yucatán, Mexico
Faculty of Computing, Engineering and Science, University of South Wales, Pontypridd CF37 1DL, UK
Funding
Consejo Nacional de Ciencia y Tecnología
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