This paper presents the fuzzy based charging-discharging control technique of lithium-ion battery storage in microgrid application. Considering available power, load demand and battery state-of
This article mainly focuses on the overview of the recent developments of microgrid EMS within the control strategies and the implementation challenges of the microgrid. storage devices
International Journal of Electrical and Electronic Engineering & Telecommunications Vol. 13, No. 2, 2024 Intelligent ANFIS-Based Distributed Generators Energy Control and Power Dispatch
The hierarchical control structure of microgrid. 3. Control Strategy for Microgrid Islanded Operation 3.1. Main Concept for Islanded Operation The main concept for islanded operation
Where: W wind and W pv are the wind and PV units power generation in the T time period. P T is the converted average power in the T time period.. 3 Device-level control of units in an AC
Abstract: This article presents the fuzzy-based charging-discharging control technique of lithium-ion battery storage in microgrid application. Considering available power, load demand, and
The lower-level real-time dispatch uses fuzzy control to dispatch electric energy storage and thermal energy storage in a real-time fashion based on the comparison of actual load and predicted power generation. To verify the
An energy management system for residential autonomous DC microgrid using optimized fuzzy logic controller considering economic dispatch. Energies 2019, 12, 1457. [ Google Scholar ] [ CrossRef ]
controlling the hybrid inverter. Simulation results prove that fuzzy-based controller reduces the DG fuel consumption by more than 12% compared to classical hysteresis management control.
predictive control-based methods, it reduces operational costs and voltage violation rate by 5% and 9%, respectively. Index Terms—Microgrid, online convex optimization, energy storage,
The lower-level real-time dispatch uses fuzzy control to dispatch electric energy storage and thermal energy storage in a real-time fashion based on the comparison of actual load and
A Micro grid is power distribution system that comprises of distributed generation, distributed storage and dispersed loads. To implement the smart involvement for the storage devices in
Real-time dispatch with no fuzzy control Table 3. Comparison of operating costs Cost Fuzzy control (¥) No fuzzy control(¥) Electricity purchase 3695.162 4048.129 ESS
The fuzzy logic controller method worked very well in the energy management of the proposed DC microgrid by taking the power balance between the load demand and the SOC of the battery as input. The power balance between the generation and load demand is crucial in controlling the DC microgrid's battery SOC (charging and discharging).
Fuzzy logic-based energy management of dispatchable and non-dispatchable energy units in a DC microgrid with an energy storage system is explored using a combination of theoretical analysis, mathematical modeling, and simulation studies.
On the one hand, regarding fuzzy-based EMS for grid-connected microgrids, the authors in design an EMS for a microgrid comprising PV and WT generators, battery ESS, electric vehicles (EV), and dynamic electricity prices and tariffs.
Distributed generators (Energy units) in DC microgrids can be dispatchable and non-dispatchable [ 11, 12 ]. Non-dispatchable energy units (solar and wind power generation) should have been operated in MPPT mode to extract the possible energy resources.
At t = 5 s, the total energy generation from renewable sources is increased from 2 to 2.5 kW. The two dispatchable energy sources used droop controllers to control the microgrid's current sharing and voltage regulation. Each unit has its converter, which has a similar topology.
The fuzzy logic controller (FLC) keeps the battery's SOC at a certain level and reduces fluctuation. By implementing the appropriate energy management system, this study utilizes renewable energy sources to their fullest potential. The DC microgrid's voltage variation and current sharing are considered when managing the microgrid's energy.
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