Fuzzy logic control of energy storage system in microgrid operation

Teo, Tiong Teck, Logenthiran, Thillainathan, Woo, Wai Lok and Abidi, Khalid (2016) Fuzzy logic control of energy storage system in microgrid operation. In: 2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia). IEEE, pp. 65-70. ISBN 978-1-5090-5228-8

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/ISGT-Asia.2016.7796362


Recent development in Renewable Energy Sources (RES) have led to a higher penetration in existing power systems. As the majority of RES are intermittent by nature, it presents major challenges to the grid operators. An Energy Storage System (ESS) can be connected to mitigate this intermittent sources. When multiple renewable energy sources, flexible loads and ESS are connected to the grid, complexity of the system is significantly increased. Such problems have multiple constraints and objective hence it is challenging to design an effective rule-based control strategy. A control strategy based on fuzzy logic which is similar to human reasoning tolerates uncertainties and imprecision. The proposed fuzzy inference system (FIS) aims to reduce the grid fluctuation and increase the energy storage life-cycle by deciding when and how much to charge/discharge the ESS. A real data was used to test and validate the proposed FIS. In this paper, MATLAB/Simulink is used to create and implement the microgrid test bench and FIS. The proposed methodology is tested against a rule-based control strategy. Simulation studies were carried out on the developed model and results have shown that the proposed FIS can effectively reduce the fluctuation and prolong the life cycle of the ESS.

Item Type: Book Section
Uncontrolled Keywords: Energy Storage System, Fuzzy Inference System, Energy Management System, Battery Life Cycle, Microgrid
Subjects: G900 Others in Mathematical and Computing Sciences
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 04 Apr 2019 14:45
Last Modified: 10 Oct 2019 20:45
URI: http://nrl.northumbria.ac.uk/id/eprint/38764

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