期刊
IEEE ACCESS
卷 9, 期 -, 页码 5046-5068出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3048438
关键词
Decision making; distributed generation; distribution networks; electric vehicles; metaheuristic optimization algorithms; multi-objective optimization; optimal location and sizing; smart grids
资金
- Council for Scientific and Industrial Research, Pretoria, South Africa, through the Smart Networks Collaboration Initiative and IoT-Factory Programme (Department of Science and Innovation (DSI), South Africa)
- South Africa's National Research Foundation [114626, 112248, 129311]
- Korea Agency for Infrastructure Technology Advancement (KAIA) [129311] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This paper provides a comprehensive review of metaheuristic techniques for optimal integration of electrical units in distribution networks, emphasizing the importance of handling crucial objective functions and methods for integrating different electrical units. It also highlights the need for further research and development of efficient algorithms.
The optimal integration of electrical units, such as distributed generation units, power electronic devices, and electric vehicles, is a significant development of smart grids. This development has effectively transformed the traditional grid system, promising numerous advantages for economic values and autonomous energy source control. In smart grids development, metaheuristic algorithms are one of the optimization algorithms that have been applied extensively to mitigate the accompanying problems such as voltage instability, power loss, and high installation cost. This paper presents a comprehensive review of metaheuristic techniques for the optimal integration of electrical units in distribution networks, considering different phases of the optimization process. These include the approaches for handling of crucial objective functions and the optimal integration methods for different electrical units. This review shows a need for more research on developing efficient metaheuristic algorithms and the effective handling of multiple objective functions.
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