Optimal Coordinated Operation of Distributed Static Series Compensators for Wide-area Network Congestion Relief

Relieving network congestions is a critical goal for the safe and flexible operation of modern power systems, especially in the presence of intermittent renewables or distributed generation. This paper deals with the real-time coordinated operation of distributed static series compensators (DSSCs) t...

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Detalles Bibliográficos
Autores: Ordóñez M., Camilo Andrés, Gómez Expósito, Antonio, Vinasco M., Guillermo E., Maza Ortega, José María
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/143210
Acceso en línea:https://hdl.handle.net/11441/143210
https://doi.org/10.35833/MPCE.2021.000265
Access Level:acceso abierto
Palabra clave:Distributed static series compensation (DSSC)
Flexible AC transmission system (FACTS)
Mixed-integer nonlinear programming (MINLP)
Wide-area network control
Descripción
Sumario:Relieving network congestions is a critical goal for the safe and flexible operation of modern power systems, especially in the presence of intermittent renewables or distributed generation. This paper deals with the real-time coordinated operation of distributed static series compensators (DSSCs) to remove network congestions by suitable modifications of the branch reactance. Several objective functions are considered and discussed to minimize the number of the devices involved in the control actions, the total losses or the total reactive power exchanged, leading to a non-convex mixed-integer non-linear programming problem. Then, a heuristic methodology combining the solution of a regular NLP with k-means clustering algorithm is proposed to get rid of the binary variables, in an attempt to reduce the computational cost. The proposed coordinated operation strategy of the DSSCs is tested on several benchmark systems, providing feasible and sufficiently optimal solutions in a reasonable time frame for practical systems.