| Abstract: |
| A Simplified Grey Wolf Optimizer (SGWO) is suggested for resolving optimization tasks. The simplification in the
original Grey Wolf Optimizer (GWO) method is introduced by ignoring the worst category wolves while giving
priority to the better wolves during the search process. The advantage of the presented SGWO over GWO is a
better solution taking less execution time and is demonstrated by taking unimodal, multimodal, and fixed
dimension test functions. The results are also contrasted to the Gravitational Search Algorithm, the Particle Swarm
Optimization, and the Sine Cosine Algorithm and this shows the superiority of the proposed SGWO technique.
Practical application in a Distributed Power Generation System (DPGS) with energy storage is then considered by
designing an Adaptive Fuzzy PID (AFPID) controller using the suggested SGWO method for frequency control. The
DPGS contains renewable generation such as photovoltaic, wind, and storage elements such as battery and
flywheel, in addition to plug-in electric vehicles. It is demonstrated that the SGWO method is superior to the GWO
method in the optimal controller design task. It is also seen that SGWO based AFPID controller is highly efficacious
in regulating the frequency compared to the standard PID controller. A sensitivity study is also performed to
examine the impact of the unpredictability in the parameters of the investigated system on system performance.
Finally, the novelty of the paper is demonstrated by comparing with the existing publications in an extensively
used two-area test system. |
| Key words: Frequency control, Distributed power generation system, Adaptive fuzzy PID controller, Grey wolf
optimization, Electric vehicle |
| DOI：10.1186/s41601-021-00180-4 |
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| Fund: |
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