Comparison of Intelligence Control Systems for Voltage Controlling on Small Scale Compressed Air Energy Storage
Widjonarko,
Rudy Soenoko,
Slamet Wahyudi and
Eko Siswanto
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Widjonarko: Energy Conversion, Electrical Engineering Departement, Universitas Jember, Jalan Kalimantan No. 37, Jember, East Java 68121, Indonesia
Rudy Soenoko: Energy Conversion, Mechanical Engineering Departement, Universitas Brawijaya, Jalan M.T. Haryono No. 167, Malang, East Java 65145, Indonesia
Slamet Wahyudi: Energy Conversion, Mechanical Engineering Departement, Universitas Brawijaya, Jalan M.T. Haryono No. 167, Malang, East Java 65145, Indonesia
Eko Siswanto: Energy Conversion, Mechanical Engineering Departement, Universitas Brawijaya, Jalan M.T. Haryono No. 167, Malang, East Java 65145, Indonesia
Energies, 2019, vol. 12, issue 5, 1-23
Abstract:
This study presents the strategy of controlling the air discharge in the prototype of small scale compressed air energy storage (SS-CAES) to produce a constant voltage according to the user set point. The purpose of this study is to simplify the control of the SS-CAES, so that it can be integrated with a grid based on a constant voltage reference. The control strategy in this study is carried out by controlling the opening of the air valve combined with a servo motor using three intelligence control systems (fuzzy logic, artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS)). The testing scenario of this system will be carried out using two scenes, including changing the voltage set point and by switching the load. The results that were obtained indicate that ANN has the best results, with an average settling time of 2.05S in the first test scenario and 6.65S in the second test scenario.
Keywords: ANFIS; artificial neural network; fuzzy; small scale compressed air energy storage (SS-CAES); voltage controlling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:5:p:803-:d:209761
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