Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10495/36347
Título : Transmission Network Expansion Planning Considering Optimal Allocation of Series Capacitive Compensation and Active Power Losses
Autor : López Lezama, Jesús María
Huanca, Dany Huamanñahui
Gallego Pareja, Luis Alfonso
metadata.dc.subject.*: Sistemas de energía eléctrica--Pérdidas eléctricas
Electric power systems--Electric losses
Algoritmos genéticos
Genetic algorithms
Sistemas de transmisión de datos
Data transmission systems
Series capacitive compensation
Linearization
http://id.loc.gov/authorities/subjects/sh85041925
http://id.loc.gov/authorities/subjects/sh92002377
Fecha de publicación : 2022
Editorial : MDPI
Citación : Huanca, D.H.; Gallego, L.A.; López-Lezama, J.M. Transmission Network Expansion Planning Considering Optimal Allocation of Series Capacitive Compensation and Active Power Losses. Appl. Sci. 2022, 12, 388. https://doi.org/10.3390/app12010388
Resumen : ABSTRACT: This paper presents a modeling and solution approach to the static and multistage trans- mission network expansion planning problem considering series capacitive compensation and active power losses. The transmission network expansion planning is formulated as a mixed integer nonlinear programming problem and solved through a highly efficient genetic algorithm. Furthermore, the Villasana Garver’s constructive heuristic algorithm is implemented to render the configurations of the genetic algorithm feasible. The installation of series capacitive compensation devices is carried out with the aim of modifying the reactance of the original circuit. The linearization of active power losses is done through piecewise linear functions. The proposed model was implemented in C++ language programming. To show the applicability and effectiveness of the proposed methodology several tests are performed on the 6-bus Garver system, the IEEE 24-bus test system, and the South Brazilian 46-bus test system, presenting costs reductions in their multi-stage expansion planning of 7.4%, 4.65% and 1.74%, respectively.
metadata.dc.identifier.eissn: 2076-3417
metadata.dc.identifier.doi: 10.3390/app12010388
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