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Title New Energy Power Planning of Photovoltaic Power System for a Smart City Based on Genetic Algorithm
ID_Doc 42170
Authors Wang, SJ; Zhang, D; Ju, ZH
Title New Energy Power Planning of Photovoltaic Power System for a Smart City Based on Genetic Algorithm
Year 2023
Published Journal Of Testing And Evaluation, 51, 3
DOI 10.1520/JTE20220105
Abstract As a basic link, planning plays an important role in the orderly development of new energy. The traditional new energy power planning has poor accuracy and low service efficiency. In order to solve the above problems, new energy power planning research of a regional photovoltaic power system based on genetic algorithm is proposed. We use the network to connect a number of small power stations together and centrally allocate and improve the breadth and depth of energy utilization. Through the four areas of power data mining, power data processing, power data acquisition and transmission, and power data acquisition gateway, we build a large area photovoltaic power system new energy power planning structure, setting acquisition function, storage function, and display function. Based on the equivalent circuit of power network, combined with the coupling phenomenon elimination function adjustment mechanism, the load parameters of new energy power planning output line are extracted, and the load diagnosis model of new energy power planning output line of large-scale photovoltaic power system is constructed by genetic algorithm. The experimental results show that the planning method has high planning efficiency, good planning accuracy, and stability.
Author Keywords genetic algorithm; regional photovoltaic power system; new energy power planning; power data
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000882602400001
WoS Category Materials Science, Characterization & Testing
Research Area Materials Science
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