Fuzzy Logic Power Management Strategy for a Residential DC-Microgrid

Power management strategies (PMS) are applied to keep a balance, between different energy sources (i.e. solar, wind, geothermal, hydro), storage units (i.e. fuel cell, batteries, fly wheel) and loads. Up to date, there has been reported several advance techniques to solve this task, for instance: Fu...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.116733-116743
Main Authors: Pena-Aguirre, Julio C., Barranco-Gutierrez, Alejandro-Israel, Padilla-Medina, Jose A., Espinosa-Calderon, Alejandro, Perez-Pinal, Francisco J.
Format: Article
Language:English
Subjects:
Batteries
Bayesian analysis
DC microgrid
Distributed generation
energy balance
Flywheels
Fuel cells
Fuzzy control
Fuzzy logic
Machine learning
Microgrids
power
Power management
Power management strategy
Power system management
renewable energy
State of charge
storage
Storage batteries
Storage units
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Summary:Power management strategies (PMS) are applied to keep a balance, between different energy sources (i.e. solar, wind, geothermal, hydro), storage units (i.e. fuel cell, batteries, fly wheel) and loads. Up to date, there has been reported several advance techniques to solve this task, for instance: Fuzzy Logic, Deep Learning, Droop Control, Bayesian Networks, among others. Nevertheless, some of those PMS are over simplified and others are too complex to be programmed in devices with limited resources. To solve these issues, this paper proposes a PMS based on Fuzzy Logic, which keeps a balance between those two goals. Characteristics of the proposed PMS are a small number of rules; fulfillment of the demanded power at every time; reducing use of the storage unit; and keeping a balance between the different sources, storage unit and loads. The proposed PMS is numerically evaluated by using SIMULINK-MATLAB®, in a 10kW residential DC Microgrid (MG), and validated by using a Hardware in the Loop platform (NI myRio-1900 and Typhoon HIL402). A comparison with three popular advance techniques demonstrates the feasibility of the proposed PMS.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3004611