Optimal Configuration Method of Primary and Secondary Integrated Intelligent Switches in the Active Distribution Network Considering Comprehensive Fault Observability

• Published in: Energies (Basel) Vol. 17; no. 16; p. 3945
• Main Authors: Li, Yuan, Su, Shi, Hu, Faping, He, Xuehao, Li, Botong, Zhang, Jing, Chen, Fahui
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-08-2024
• Subjects: active distribution network; Algorithms; Analysis; Electric fault location; Electric power distribution; Fault diagnosis; fault observability; Infrastructure; Linear programming; Mathematical models; Methods; optimal configuration; Optimization; Power supply; primary and secondary integrated intelligent switch; Reliability (Engineering); China
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en17163945

As the demand for power supply stability and reliability in the active distribution network (ADN) increases, the primary and secondary integrated intelligent switch (PSIIS) has become the primary choice for smart grid transformation in many weak infrastructure areas. However, the number of PSIISs that can be configured is often limited. It is necessary to comprehensively utilize the measurement data and sectional capabilities of PSIISs through the optimal configuration method to find the optimal configuration scheme. Therefore, fault observability-related indexes (FORIs) are proposed based on the functional characteristics of PSIISs. These indexes include fault type observability, fault location observability, fault current distribution characteristics observability, transition resistance observability, and weak infrastructure area observability. An optimization configuration model of PSIISs considering the comprehensive fault observability (CFO) is constructed. The adaptive genetic algorithm (AGA) is selected as the model-solving method. Subsequently, an optimal configuration method of PSIISs considering CFO is proposed. Finally, an example analysis is conducted in MATLAB to verify the effectiveness and feasibility of the proposed method. This optimal configuration method aims to maximize the use of a limited number of PSIISs by considering CFO, and the AGA proves to be an effective tool in solving the optimal configuration scheme.