Direct Control Strategy of Real-Time Tracking Power Generation Plan for Wind Power and Battery Energy Storage Combined System

To improve the overall economy of the wind-energy storage power station, a direct control strategy is proposed to track the deviation of the wind power plan. Compared with the traditional strategy of wind power fluctuation mitigation, the control strategy in this paper can change the charge and discharge power of energy storage in real-time according to the deviation of wind power and the state of charge (SOC). When the power of wind power changes suddenly, the strategy can make the valid judgment and prevent control failure, so that Grid-connected power of wind farm in extreme cases can also meet the requirements of the safe and stable operation of the power system. The strategy uses the discrete Fourier transform (DFT) to analyze the power deviation of the wind farm in the frequency domain and obtains power compensation requirements for different time scales. Energy storage equipment with corresponding characteristics is used to classify control of deviation of wind power. The compensated power deviation can meet the requirements in market competition. At the same time, the power exchange between storage systems is carried out to optimize the state of charge in real-time and make the energy-type energy storage in shallow charge/discharge state, which effectively reduces the repeated regulation of energy storage systems. Finally, this paper establishes a comprehensive economic benefit model of the energy storage system. Combining the Markov Chain Monte Carlo method (MCMC) and backward scenario reduction technology generate multiple scenarios. The calculation results show that the proposed strategy can effectively track the deviation of the wind power plan. Furthermore, prolong the service life of the energy storage system and improve the market competitiveness of wind power.

[1]  Joao P. S. Catalao,et al.  Comparative Study of Advanced Signal Processing Techniques for Islanding Detection in a Hybrid Distributed Generation System , 2015, IEEE Transactions on Sustainable Energy.

[2]  Haijiao Wang,et al.  A battery energy storage system dual-layer control strategy for mitigating wind farm fluctuations , 2013, 2014 IEEE PES General Meeting | Conference & Exposition.

[3]  Dirk Uwe Sauer,et al.  Optimizing vehicle-to-grid charging strategies using genetic algorithms under the consideration of battery aging , 2011, 2011 IEEE Vehicle Power and Propulsion Conference.

[4]  N. M. Muhamad Razali,et al.  Backward reduction application for minimizing wind power scenarios in stochastic programming , 2010, 2010 4th International Power Engineering and Optimization Conference (PEOCO).

[5]  W. Marsden I and J , 2012 .

[6]  Zhao Yang Dong,et al.  Improved Cycle Control and Sizing Scheme for Wind Energy Storage System Based on Multiobjective Optimization , 2017, IEEE Transactions on Sustainable Energy.

[7]  Chang Xu Study on Environmental Cost Accounting of Thermal Power Enterprises , 2019, DEStech Transactions on Social Science, Education and Human Science.

[8]  Badrul Chowdhury,et al.  Optimal sizing of Hybrid Energy Storage Systems to mitigate wind power fluctuations , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

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

[10]  Seyed Hossein Hosseinian,et al.  Mitigation of windfarm power fluctuation by adaptive linear neuron-based power tracking method with flexible learning rate , 2014 .

[11]  Jihong Wang,et al.  Overview of current development in electrical energy storage technologies and the application potential in power system operation , 2015 .

[12]  Bo Hu,et al.  A Novel Control Strategy of Energy Storage System Considering Prediction Errors of Photovoltaic Power , 2018, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV).

[13]  Tianmeng Yang Optimal sizing of the hybrid energy storage system aiming at improving the penetration of wind power , 2016, 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).

[14]  Wenjuan Du,et al.  Optimal Sizing and Control Strategies for Hybrid Storage System as Limited by Grid Frequency Deviations , 2018, IEEE Transactions on Power Systems.

[15]  Pingliang Zeng,et al.  Capacity planning of battery energy storage system within wind farm , 2016, 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).

[16]  Nand Kishor,et al.  Comparative study of advanced signal processing techniques for islanding detection in a hybrid distributed generation system , 2015, 2015 IEEE Power & Energy Society General Meeting.

[17]  阳育德,et al.  A Research on the Control Performance Standard and Energy Storage Control Strategy for Large Scale Wind Farms , 2017 .

[18]  Wang Guangx Recycling Valuable Metals from Spent Lithium Ion Batteries , 2015 .