Optimal planning of photovoltaic and distribution static compensators in medium-voltage networks via the GNDO approach

被引:2
|
作者
Montoya, Oscar Danilo [1 ]
Gil-Gonzalez, Walter [2 ]
Grisales-Norena, Luis Fernando [3 ]
机构
[1] Univ Distrital Francisco Jose Caldas, Fac Ingn, Grp Compatibil Interferencia Electromagnet GCEM, Bogota 110231, Colombia
[2] Univ Tecnol Pereira, Fac Engn, Dept Elect Engn, Pereira 660003, Colombia
[3] Univ Talca, Fac Engn, Dept Elect Engn, Curico 3340000, Chile
关键词
Solar PV; D-STATCOMs; Distribution system planning; Operating cost minimization; Metaheuristic optimization; Master-slave optimizer; DISTRIBUTION-SYSTEMS; D-STATCOMS; OPTIMIZATION; INTEGRATION; GENERATION;
D O I
10.1016/j.rineng.2024.102764
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This research employs the generalized normal distribution optimizer (GNDO) to address the simultaneous integration of solar photovoltaic (PV) sources and distribution static compensators (D-STATCOMs) in medium- voltage distribution networks. Through a discrete-continuous codification process, the GNDO method determines the optimal locations (nodes) and capacities (sizes) of PV systems and D-STATCOMs. A power flow approach based on the successive approximations method is used to solve the power flow equations and assess the solution's technical characteristics, including voltage profiles and power injections. Using a master-slave optimization strategy, the GNDO and the power flow method are used to address the studied problem. Numerical results in the 33- and 69-bus grids demonstrate the effectiveness of the proposed approach, showing superior performance compared to the vortex search algorithm (VSA) and the sine-cosine algorithm (SCA). The results indicate reductions of approximately 35.5554% and 35.6839% when using the GNDO in both test feeders. Additionally, the GNDO reduces the computational efforts required to find solutions in both test feeders, in comparison with the VSA and the SCA. All numerical validations were performed using MATLAB 2024a.
引用
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页数:10
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