E3S Web Conf.
Volume 185, 20202020 International Conference on Energy, Environment and Bioengineering (ICEEB 2020)
|Number of page(s)||3|
|Section||Energy Engineering and Power System|
|Published online||01 September 2020|
Optimal multi-objective distributed generation location and capacity by elite strategy genetic algorithm considering timing characteristics
1 State Grid Shanghai Energy Interconnection Research Institute Co., Ltd., Shanghai, 201210, China
2 China Electric Power Research Institute Co., Ltd., Beijing, 100085, China
3 State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, Zhejiang Province, 310007, China
4 State Grid Zhejiang Electric Power Co., Ltd. Hangzhou Power Supply Company, Hangzhou, Zhejiang Province, 310016, China
* Corresponding author’s e-mail: firstname.lastname@example.org
In this paper, a distributed generation location and capacity optimization model considering the probability of scenario occurrence is established. The optimization objective is to minimize the total cost of investment, annual power loss of distribution network and node voltage deviation. The improved genetic algorithm with elitist retention mechanism is used to solve the model. The IEEE33 system is used to show the location and constant capacity of the distributed power supply under different conditions. It shows that the reasonable and optimized configuration of the distributed power supply can obtain better voltage quality and minimize the cost function, which verifies the effectiveness of the proposed model.
© The Authors, published by EDP Sciences, 2020
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