Optimization of Topological Reconfiguration in Electric Power Systems Using Genetic Algorithm and Nonlinear Programming with Discontinuous Derivatives

This article addresses a comprehensive analysis of power electrical systems, employing a combined approach of genetic algorithms and mathematical optimization through nonlinear programming with discontinuous derivatives (DNLP) in GAMS. The primary objective is to minimize economic losses and associa...

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Bibliographic Details
Published in:Electronics (Basel) 2024-02, Vol.13 (3), p.616
Main Authors: Vargas, Giovanny Andrés Diaz, Mosquera, Darin Jairo, Trujillo, Edwin Rivas
Format: Article
Language:English
Subjects:
Algorithms
Alternative energy sources
Colombia
Cost analysis
Cost control
Costs
Distributed generation
Economic impact
Electric power systems
Electrical loads
Energy
Energy distribution
Energy sources
Genetic algorithms
Integer programming
Literature reviews
Load shedding
Mathematical analysis
Mathematical models
Mathematical optimization
Nonlinear programming
Optimization
Optimization techniques
Planning
Reconfiguration
System effectiveness
Test systems
Topology
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Summary:This article addresses a comprehensive analysis of power electrical systems, employing a combined approach of genetic algorithms and mathematical optimization through nonlinear programming with discontinuous derivatives (DNLP) in GAMS. The primary objective is to minimize economic losses and associated costs faced by the network operator following disruptive events. The analysis is divided into two fundamental aspects. Firstly, it addresses the topological reconfiguration of the network, involving the addition of lines and distributed energy resources such as distributed generation. To determine the optimal topological reconfiguration, a genetic algorithm was developed and implemented. This approach aims to restore electrical service to the maximum load within the system. Secondly, an optimal energy dispatch was performed for each generator, considering the variation in load throughout the day. The system’s load curve is taken into account to determine the optimal energy distribution. Thus, the problem of economic losses is approached from two perspectives: the minimization of costs due to nonsupplied electrical energy and the determination of efficient energy dispatch for each generator after network reconfiguration. For the analysis and case studies, simulations were conducted on the IEEE 9- and 30-node test systems. The results demonstrate the effectiveness of the proposed solution, evaluated in terms of reduced load shedding and economic losses.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13030616