Predictive Operation and Optimal Sizing of Battery Energy Storage With High Wind Energy Penetration

High penetration of wind energy requires fast-acting dispatchable resources to manage energy imbalance in the power grid. Battery energy storage systems (BESS) are considered as an essential tool to decrease the power and energy imbalance between the scheduled generation (day ahead forecast) and the actual wind farm output. Control methodology or battery management greatly impacts performance of the ESS. Better performance of BESS reduces the minimum required size of batteries for wind variability mitigation. This paper proposes a novel control method for BESS to fulfill a production commitment. This method, called “predictive controller,” is based on updated forecast data to improve the performance of the energy storage and consequently reduce the required size of energy storage. The Sodium–Sulfur (NaS) type battery is selected for the simulation purposes. Results show that the predictive controller reduces the error (between scheduled generation and actual wind farm output) more than the simple method (also known as minute-by-minute method) and other proposed methods in the literature. Also, a new formulation for the battery lifetime estimation is introduced, and it is used to analyze the impact of the proposed method on the battery lifetime depreciation.

[1]  L.A.F. Ferreira,et al.  Distributed Reactive Power Generation Control for Voltage Rise Mitigation in Distribution Networks , 2008, IEEE Transactions on Power Systems.

[2]  C. Buenoa,et al.  Wind powered pumped hydro storage systems , a means of increasing the penetration of renewable energy in the Canary Islands , 2006 .

[3]  Saifur Rahman,et al.  Sizing Energy Storage to Mitigate Wind Power Forecast Error Impacts by Signal Processing Techniques , 2015, IEEE Transactions on Sustainable Energy.

[4]  Patrick Balducci,et al.  An energy storage assessment: Using optimal control strategies to capture multiple services , 2015, 2015 IEEE Power & Energy Society General Meeting.

[5]  Qiang Fu,et al.  Microgrid Generation Capacity Design With Renewables and Energy Storage Addressing Power Quality and Surety , 2012, IEEE Transactions on Smart Grid.

[6]  J.P. Barton,et al.  Energy storage and its use with intermittent renewable energy , 2004, IEEE Transactions on Energy Conversion.

[7]  Daniel S. Kirschen,et al.  Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment , 2018, IEEE Transactions on Smart Grid.

[8]  Vilayanur V. Viswanathan,et al.  The Wide-Area Energy Storage and Management System – Battery Storage Evaluation , 2009 .

[9]  Feng Gao,et al.  Coordinated Predictive Control of DFIG-Based Wind-Battery Hybrid Systems: Using Non-Gaussian Wind Power Predictive Distributions , 2015, IEEE Transactions on Energy Conversion.

[10]  S. M. Amin,et al.  Optimal mix and placement of energy storage systems in power distribution networks for reduced outage costs , 2012, 2012 IEEE Energy Conversion Congress and Exposition (ECCE).

[11]  Badrul H. Chowdhury,et al.  Working towards frequency regulation with wind plants: Combined control approaches , 2010 .

[12]  S. Bhattacharya,et al.  Control Strategies for Battery Energy Storage for Wind Farm Dispatching , 2009, IEEE Transactions on Energy Conversion.

[13]  Alfonso Damiano,et al.  Real-Time Control Strategy of Energy Storage Systems for Renewable Energy Sources Exploitation , 2014, IEEE Transactions on Sustainable Energy.

[14]  Darrell F. Socie,et al.  Simple rainflow counting algorithms , 1982 .

[15]  A. S. Safigianni,et al.  Optimum allocation of the maximum possible distributed generation penetration in a distribution network , 2010 .

[16]  Vijay Vittal,et al.  Impact of DFIG based wind turbine generators on transient and small signal stability of power systems , 2009, 2009 IEEE Power & Energy Society General Meeting.

[17]  Shaahin Filizadeh,et al.  Stability Analysis of Converter-Connected Battery Energy Storage Systems in the Grid , 2014, IEEE Transactions on Sustainable Energy.

[18]  Ronnie Belmans,et al.  Overview of new energy storage systems for an improved power quality and load managing on distribution level , 2001 .

[19]  Andreas Sumper,et al.  A review of energy storage technologies for wind power applications , 2012 .

[20]  D. A. Halamay,et al.  Optimal Energy Storage Sizing and Control for Wind Power Applications , 2011, IEEE Transactions on Sustainable Energy.

[21]  Hamidreza Zareipour,et al.  Energy storage for mitigating the variability of renewable electricity sources: An updated review , 2010 .

[22]  Ning Lu,et al.  Control and Size Energy Storage Systems for Managing Energy Imbalance of Variable Generation Resources , 2015, IEEE Transactions on Sustainable Energy.

[23]  Peng Kou,et al.  Stochastic predictive control of battery energy storage for wind farm dispatching: Using probabilistic wind power forecasts , 2015 .

[24]  A. Oudalov,et al.  Sizing and Optimal Operation of Battery Energy Storage System for Peak Shaving Application , 2007, 2007 IEEE Lausanne Power Tech.