A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions

Abstract Renewable energy sources have been increasingly deployed as distributed generators in remote areas. Meanwhile, fluctuating power generation from renewable energy sources, together with variable power demand, poses challenges in stable and reliable power supply. In this paper, a microgrid with solar photovoltaic (PV) and battery energy storage (BES) is studied. A state of charge (SOC)-oriented charging scheme is developed to control the BES to smooth the PV output. Most importantly, a sophisticated control algorithm, consisting of a model predictive voltage control (MPVC) and a model predictive power control (MPPC), is proposed for the interlinking converter. It enables stable voltage in islanded mode. Also, in grid-connected mode, flexible reactive power can be injected into the main grid for grid support according to the voltage variation level. Finally, by considering the intermittent nature of the PV and the load profile, an energy management system (EMS) is designed to ensure power balance within the system. Case studies are provided to demonstrate the effectiveness of the proposed control strategy.

[1]  Robert Lasseter,et al.  Smart Distribution: Coupled Microgrids , 2011, Proceedings of the IEEE.

[2]  S. Gonzalez,et al.  Development of a MATLAB/Simulink Model of a Single-Phase Grid-Connected Photovoltaic System , 2009, IEEE Transactions on Energy Conversion.

[3]  Roberto Sacile,et al.  Coordinated Model Predictive-Based Power Flows Control in a Cooperative Network of Smart Microgrids , 2015, IEEE Transactions on Smart Grid.

[4]  A. Kaabeche,et al.  Techno-economic optimization of hybrid photovoltaic/wind/diesel/battery generation in a stand-alone power system , 2014 .

[5]  Federico Baronti,et al.  Online Adaptive Parameter Identification and State-of-Charge Coestimation for Lithium-Polymer Battery Cells , 2014, IEEE Transactions on Industrial Electronics.

[6]  Farzam Nejabatkhah,et al.  Overview of Power Management Strategies of Hybrid AC/DC Microgrid , 2015, IEEE Transactions on Power Electronics.

[7]  David G. Dorrell,et al.  Model-predictive control of grid-connected inverters for PV systems with flexible power regulation and switching frequency reduction , 2013, 2013 IEEE Energy Conversion Congress and Exposition.

[8]  Ahmad Zahedi,et al.  A Cooperative Operation of Novel PV Inverter Control Scheme and Storage Energy Management System Based on ANFIS for Voltage Regulation of Grid-Tied PV System , 2017, IEEE Transactions on Industrial Informatics.

[9]  Dong Hui,et al.  Battery Energy Storage Station (BESS)-Based Smoothing Control of Photovoltaic (PV) and Wind Power Generation Fluctuations , 2013, IEEE Transactions on Sustainable Energy.

[10]  Yan Xu,et al.  Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes , 2018 .

[11]  Oriol Gomis-Bellmunt,et al.  Trends in Microgrid Control , 2014, IEEE Transactions on Smart Grid.

[12]  Sungwoo Bae,et al.  Decentralized control of a scalable photovoltaic (PV)-battery hybrid power system , 2017 .

[13]  Wei Gu,et al.  Optimal siting and sizing of distributed generation in distribution systems with PV solar farm utilized as STATCOM (PV-STATCOM) , 2018 .

[14]  Despoina I. Makrygiorgou,et al.  Distributed stabilizing modular control for stand-alone microgrids , 2018 .

[15]  Evangelos Rikos,et al.  A Model Predictive Control Approach to Microgrid Operation Optimization , 2014, IEEE Transactions on Control Systems Technology.

[16]  Rachid Beguenane,et al.  Energy Management and Control System for Laboratory Scale Microgrid Based Wind-PV-Battery , 2017, IEEE Transactions on Sustainable Energy.

[17]  Jianzhong Wu,et al.  Distributed Energy and Microgrids (DEM) , 2018 .

[18]  Trudie Wang,et al.  Control and Optimization of Grid-Tied Photovoltaic Storage Systems Using Model Predictive Control , 2014, IEEE Transactions on Smart Grid.

[19]  Jang-Ho Lee,et al.  A novel approach for optimal combinations of wind, PV, and energy storage system in diesel-free isolated communities , 2016 .

[20]  Osama A. Mohammed,et al.  Control of a Hybrid AC/DC Microgrid Involving Energy Storage and Pulsed Loads , 2017, IEEE Transactions on Industry Applications.

[21]  Steven R. Weller,et al.  Scheduling residential battery storage with solar PV: Assessing the benefits of net metering , 2015 .

[22]  Zhongbao Wei,et al.  Online Model Identification and State-of-Charge Estimate for Lithium-Ion Battery With a Recursive Total Least Squares-Based Observer , 2018, IEEE Transactions on Industrial Electronics.

[23]  Peng Wang,et al.  A Hybrid AC/DC Microgrid and Its Coordination Control , 2011, IEEE Transactions on Smart Grid.

[24]  Juan C. Vasquez,et al.  Hierarchical Control of Droop-Controlled AC and DC Microgrids—A General Approach Toward Standardization , 2009, IEEE Transactions on Industrial Electronics.

[25]  Andoni Urtasun,et al.  State-of-charge-based droop control for stand-alone AC supply systems with distributed energy storage , 2015 .

[26]  Gerard Ledwich,et al.  Coordinated Control of Grid-Connected Photovoltaic Reactive Power and Battery Energy Storage Systems to Improve the Voltage Profile of a Residential Distribution Feeder , 2014, IEEE Transactions on Industrial Informatics.

[27]  Evangelos Rikos,et al.  Use of model predictive control for experimental microgrid optimization , 2014 .

[28]  R. Teodorescu,et al.  On the Perturb-and-Observe and Incremental Conductance MPPT Methods for PV Systems , 2013, IEEE Journal of Photovoltaics.

[29]  Hongwen He,et al.  An energy management strategy based on stochastic model predictive control for plug-in hybrid electric buses , 2017 .

[30]  Kenneth A. Loparo,et al.  Transient Stability and Voltage Regulation in Multimachine Power Systems Vis-à-Vis STATCOM and Battery Energy Storage , 2015, IEEE Transactions on Power Systems.