Limei Zhou, Wanxing Sheng, Wei Liu, 等. An optimal expansion planning of electric distribution network incorporating health index and non-network solutions[J]. 中国电机工程学会电力与能源系统学报(英文), 2020,6(3):681-692.
Limei Zhou, Wanxing Sheng, Wei Liu, et al. An optimal expansion planning of electric distribution network incorporating health index and non-network solutions[J]. CSEE Journal of Power and Energy Systems, 2020, 6(3): 681-692.
Limei Zhou, Wanxing Sheng, Wei Liu, 等. An optimal expansion planning of electric distribution network incorporating health index and non-network solutions[J]. 中国电机工程学会电力与能源系统学报(英文), 2020,6(3):681-692.DOI: 10.17775/CSEEJPES.2018.01230.
Limei Zhou, Wanxing Sheng, Wei Liu, et al. An optimal expansion planning of electric distribution network incorporating health index and non-network solutions[J]. CSEE Journal of Power and Energy Systems, 2020, 6(3): 681-692.DOI: 10.17775/CSEEJPES.2018.01230.
An optimal expansion planning of electric distribution network incorporating health index and non-network solutions
The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods. In order to effectively consider the health status and deal with the risk associated with load and renewable generation uncertainties
this paper presents a new optimal expansion planning approach for distribution network (EPADN) incorporating equipment's health index (HI) and non-network solutions (NNSs). HI and relevant risk are used to help develop the optimal equipment replacement strategy and temporary NNSs are considered as promising options for handling the uncertainties of load growth
reliability requirements of power supply and output of distributed energy resources (DERs) at a lower cost than network alternatives. An EPADN model using network solutions (NSs) and NNSs is proposed. The planning objectives of the proposed model are safety
reliability
economy
and ‘greenness’ that are also the meaning of distribution network HI. A method integrating an improved niche genetic algorithm (INGA) and a spanning tree algorithm (STA) is fitted to solve the model presented here for real sized networks with a manageable computational cost. Simulation results of an actual 22-node distribution network in China
illustrate the effectiveness of the proposed approach.