Hybrid improved whales and sine cosine optimization algorithms for the optimal configuration of distribution networks in the presence of dispersed generation systems before, during, and after short circuit current propagation case study: overhead and underground networks in the laghouat region of Algeria
The optimization algorithms in electrical engineering present an important tool for improving the dynamic and static operation of electrical distribution networks (EDN) by supporting the regional operator system for distribution network reconfiguration with the presence of dispersed generation syste...
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Veröffentlicht in: | Electrical engineering 2024-02, Vol.106 (1), p.755-771 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The optimization algorithms in electrical engineering present an important tool for improving the dynamic and static operation of electrical distribution networks (EDN) by supporting the regional operator system for distribution network reconfiguration with the presence of dispersed generation systems based on the PV and wind turbine hybrid system. The short circuit current, in particular of the phase-to-ground type, is the most prevalent and intense on the EDN and affects voltage stability and increases power losses. In this work, we propose a new optimization technique, the hybrid improved whale and sine cosine optimization algorithm, based on the randomly determined distance between each whale’s current position and the best position using probabilistic-based sine and cosine functions, to improve the balance between exploitation and exploration phases. The objectives implemented are to minimize total active power losses and maximize the voltage profile. Two test systems were conducted for this work: overhead and undergrounding 63 bus systems using private data on the algerian electricity and gas distribution company and verifying the effectiveness of the proposed method through its application in the IEEE 33 bus standard distribution system. We then compared the results obtained with the latest research. |
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ISSN: | 0948-7921 1432-0487 |
DOI: | 10.1007/s00202-023-01972-7 |