Grid power fluctuation reduction by fuzzy control based energy management system in residential microgrids

Smoothing grid profile plays a crucial role in dynamic operation of microgrid. This paper focuses on reducing the grid power fluctuation in a grid connected microgrid due to stochastic nature of renewable generations and its impact on the stability and quality of distribution network. To achieve this, the control strategies are designed to control the charging/discharging of battery storage system based on the difference between generations of renewable energy resources and load demand as well a battery state. Fuzzy logic controller is applied in energy management system (EMS) of microgrid by considering dramatic behavior of renewable energy resources while maintaining battery state within secure limits. A comparison with time-based constant and variable charge/discharge control of battery presents in simulation experiment to demonstrate the effectiveness of the proposed fuzzy controller in a residential AC microgrid.

[1]  Athula D. Rajapakse,et al.  Microgrids research: A review of experimental microgrids and test systems , 2011 .

[2]  Huapu Lu.  New York, United States , 2020 .

[3]  Ju Lee,et al.  AC-microgrids versus DC-microgrids with distributed energy resources: A review , 2013 .

[4]  Enrico Zio,et al.  A model predictive control framework for reliable microgrid energy management , 2014 .

[5]  Haoran ZHAO,et al.  Fuzzy logic based coordinated control of battery energy storage system and dispatchable distributed generation for microgrid , 2015 .

[6]  Junwei Lu,et al.  Optimisation of battery energy storage capacity for a grid-tied renewable microgrid , 2017, 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia).

[7]  R.H. Lasseter,et al.  Microgrid: a conceptual solution , 2004, 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551).

[8]  Francesc Guinjoan,et al.  Improved fuzzy controller design for battery energy management in a grid connected microgrid , 2014, IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society.

[9]  Soodabeh Soleymani,et al.  Scenario-based stochastic operation management of MicroGrid including Wind, Photovoltaic, Micro-Turbine, Fuel Cell and Energy Storage Devices , 2014 .

[10]  Ning Lu,et al.  A Demand Response and Battery Storage Coordination Algorithm for Providing Microgrid Tie-Line Smoothing Services , 2014, IEEE Transactions on Sustainable Energy.

[11]  Duong Tran,et al.  Composite Energy Storage System Involving Battery and Ultracapacitor With Dynamic Energy Management in Microgrid Applications , 2011, IEEE Transactions on Power Electronics.

[12]  Rodrigo Palma-Behnke,et al.  Energy management system for a renewable based microgrid with a demand side management mechanism , 2011, 2011 IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG).

[13]  Rodrigo Palma-Behnke,et al.  A Microgrid Energy Management System Based on the Rolling Horizon Strategy , 2013, IEEE Transactions on Smart Grid.

[14]  Shahin Sirouspour,et al.  An Optimal Energy Storage Control Strategy for Grid-connected Microgrids , 2014, IEEE Transactions on Smart Grid.

[15]  Luis Fontan,et al.  Optimal scheduling of a microgrid with a fuzzy logic controlled storage system , 2015 .

[16]  Francesc Guinjoan,et al.  Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting , 2017 .

[17]  Yu-Kai Chen,et al.  Design and Implementation of Energy Management System With Fuzzy Control for DC Microgrid Systems , 2013, IEEE Transactions on Power Electronics.

[18]  Tafreshi,et al.  [IEEE 2009 IEEE Bucharest PowerTech (POWERTECH) - Bucharest, Romania (2009.06.28-2009.07.2)] 2009 IEEE Bucharest PowerTech - A developed energy management system for a microgrid in the competitive electricity market , 2009 .

[19]  Hazlie Mokhlis,et al.  Smart power management algorithm in microgrid consisting of photovoltaic, diesel, and battery storage plants considering variations in sunlight, temperature, and load , 2014 .

[20]  Sukruedee Sukchai,et al.  Comparison the Economic Analysis of the Battery between Lithium-ion and Lead-acid in PV Stand-alone Application☆ , 2014 .

[21]  Jae Wan Park,et al.  On-line optimization of battery open circuit voltage for improved state-of-charge and state-of-health estimation , 2015 .

[22]  Shengbo Zhang.  The effect of the charging protocol on the cycle life of a Li-ion battery , 2006 .

[23]  Pablo Sanchis,et al.  Energy management strategy for a renewable-based residential microgrid with generation and demand forecasting , 2015 .