Frequency Control in Multi-Carrier Microgrids with the Presence of Electric Vehicles Based on Adaptive Neuro Fuzzy Inference System Controller

Subject Areas : Renewable energy

Seyed Ali Seyed Beheshti Fini ¹ , Seyed Mohammad Shariatmadar ² , Vahid Amir ³

1 - Department of Electrical and Computer- Kashan Branch, Islamic Azad University, Kashan, Iran
2 - Department of Electrical and Computer- Kashan Branch, Islamic Azad University, Kashan, Iran
3 - Department of Electrical and Computer- Kashan Branch, Islamic Azad University, Kashan, Iran

Received: 2022-01-04 Accepted : 2022-04-29 Published : 2023-11-22

Keywords: Microgrid, Electric Vehicle, fuzzy control, Frequency control, Adaptive Neuro Fuzzy Inference System, secondary frequency,

Abstract :

Nowadays, the use of renewable resources has increased because of fossil fuel price growth, resource shortage, and environmental pollution. This study investigates a microgrid composed of wind and solar systems with battery storage sources and flywheel, diesel generator, and multi-carrier energy systems (MCH) as combined electricity and heat (CHP). The microgrid frequency is controlled based on the gas network and its consumption peak. In a multi-carrier network, the load distribution in the gas network is simultaneously considered with the electric charge distribution. Besides, the frequency is controlled nonlinearly. On the other hand, the growing trend of producing and using electric vehicles has generated new loads on the electricity network. In this regard, if these loads are not properly managed to charge them, the network’s frequency deviations will increase and cause the collapse of the electricity network.Therefore, electric vehicles (V2G) are considered in microgrid frequency tuning operations through ANFIS adaptive fuzzy control method. In order to compare the proposed method in the simulations, a fuzzy controller is used. The results of the simulations are examined in five studies that express the optimal performance of the proposed method in reducing frequency deviations, strength against disturbances and resistance Uncertainties in the system. The proposed method also has a more stable output power in microgrid production resources.

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