Mitigation of total harmonic distortion and flicker emission in the presence of harmonic loads by optimal siting and sizing of wind turbines and energy storage systems
In distribution networks (DNs), there are significant technical challenges due to the high penetration of renewable energy resources (RERs), especially wind turbines (WTs) and the presence of non-linear electrical loads. One of the most important challenges is power quality. In such networks, to mit...
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| Vydáno v: | Journal of energy storage Ročník 86; s. 111312 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Ltd
10.05.2024
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| Témata: | |
| ISSN: | 2352-152X |
| On-line přístup: | Získat plný text |
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| Shrnutí: | In distribution networks (DNs), there are significant technical challenges due to the high penetration of renewable energy resources (RERs), especially wind turbines (WTs) and the presence of non-linear electrical loads. One of the most important challenges is power quality. In such networks, to mitigate flicker emission produced by WTs and network voltage harmonics, it is necessary to solve the planning problems considering power quality objectives and standards. For this aim, this paper attempts to improve DN performance by optimal siting and sizing of WTs and energy storage systems (ESSs). In the planning problem, to take into account the power quality issue, flicker emission, total harmonic distortion (THD), and network voltage deviation (NVD) are included in the optimization problem. To effectively solve the planning problem, which is a non-linear and non-convex optimization problem, three variants of genetic algorithm (GA) are used. Simulation results indicate that optimal sizing and siting of WTs not only significantly improve the power quality issue but also improves the network performance.
•Presence of wind turbines and non-linear loads make significant technical challenges.•It is essential to mitigate flicker produced by WTs and network voltage harmonics.•Optimal siting and sizing of WTs and energy storage systems improves power quality.•Three variants of genetic algorithm are introduced to optimally solve allocation problem. |
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| ISSN: | 2352-152X |
| DOI: | 10.1016/j.est.2024.111312 |