Multi-objective-based reactive power planning and voltage stability enhancement using FACTS and capacitor banks

Reactive power planning (RPP) and voltage stability improvement (VSI) consider two of the most important problems to meet a major challenge of the power system. In this work, a multi-objective genetic algorithm (MOGA) for RPP with objectives of cost minimization of the power losses, new reactive pow...

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Bibliographic Details
Published in:Electrical engineering 2022-10, Vol.104 (5), p.3173-3196
Main Authors: Eladl, Abdelfattah A., Basha, Mohamed I., ElDesouky, Azza A.
Format: Article
Language:English
Subjects:
Allocations
Capacitor banks
Capacitors
Economics and Management
Effectiveness
Electric power systems
Electrical Engineering
Electrical Machines and Networks
Energy Policy
Engineering
Flexible AC power transmission systems
Genetic algorithms
Optimization
Original Paper
Power Electronics
Reactive power
Tap changers
Voltage stability
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Summary:Reactive power planning (RPP) and voltage stability improvement (VSI) consider two of the most important problems to meet a major challenge of the power system. In this work, a multi-objective genetic algorithm (MOGA) for RPP with objectives of cost minimization of the power losses, new reactive power (VAR) sources, maximization of the VSI, and enhancement of total transfer capacity (TTC) is introduced. Different optimization variables are considered including generator voltages, transformer tap changers besides load, and different operational constraints. The best compromise solution is determined through a fuzzy min–max approach. Comparison studies among capacitor banks, flexible ac transmission systems (FACTS) or both as new VAR support sources to achieve better performance are explored. Moreover, the optimal allocations of switchable VAR sources are not determined in advance; instead, they are treated as control variables to improve the techno-economic operation of the network. Added to that many voltage stability indicators are presented, and their results are compared. The effectiveness of the proposed algorithm is examined on a modified IEEE 30-bus test system and South Egypt Electricity network where felicitous results have been acquired. The results expound on the effectiveness of the proposed approach compared with other optimization methods.
ISSN:0948-7921
1432-0487
DOI:10.1007/s00202-022-01542-3