4.6 Article

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

Journal

IEEE ACCESS
Volume 7, Issue -, Pages 147169-147178

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2946453

Keywords

Hybrid wind-energy storage (wind-ES) system; tracking wind power schedule output; discrete Fourier transform (DFT); electricity market

Funding

  1. National Natural Science Foundation of China [51767004]
  2. Guangxi Scientific Research and Technology Development Project [1599005-2-14]
  3. Natural Science Foundation of Guangxi [2018JJB160056, 2018JJB160064, 2018JJA160176]

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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.

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