A Data-driven Nonlinear Recharge Controller for Energy Storage in Frequency Regulation

Battery energy storage boosts up the response speed of power system frequency regulation, but must be recharged carefully to minimize the distortion to the frequency regulation response. This paper proposes a nonlinear feedback controller to optimize the recharge for storage resources in frequency regulation. This controller is designed using a data-driven best-hindsight optimization framework, the resulting nonlinear recharge controller’s gain depends on the storage state of charge as well as its power and energy rating. The developed controller is compared with two benchmark automatic generation control designs, one is a proportional-integral-based control from PJM Interconnection, the other one is based on linear-quadratic regulator. Simulation results using real area control error data from PJM Interconnection show the proposed controller achieves smaller deviations in both the area control error and the storage state of charge compared to the two benchmark controllers under various storage configurations.

[1]  Tingting Wang,et al.  Battery Assisted Conventional Generator in PJM Frequency Regulation Market , 2019, 2019 IEEE Power & Energy Society General Meeting (PESGM).

[2]  Yuri V. Makarov,et al.  Assessing the Value of Regulation Resources Based on Their Time Response Characteristics , 2008 .

[3]  Dirk Witthaut,et al.  Non-Gaussian power grid frequency fluctuations characterized by Lévy-stable laws and superstatistics , 2018, Nature Energy.

[4]  Sham M. Kakade,et al.  The Nonstochastic Control Problem , 2020, ALT.

[5]  Wen Tan,et al.  Load frequency control of power systems with non-linearities , 2017 .

[6]  Nahum Shimkin,et al.  Nonlinear Control Systems , 2008 .

[7]  Cesar A. Silva-Monroy,et al.  A comparison of policies on the participation of storage in U.S. frequency regulation markets , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[8]  Alex Zheng,et al.  Anti-windup design for internal model control , 1994 .

[9]  Luis Rouco,et al.  Improving AGC Performance in Power Systems With Regulation Response Accuracy Margins Using Battery Energy Storage System (BESS) , 2020, IEEE Transactions on Power Systems.

[10]  M. D. Ilic,et al.  Enhanced Automatic Generation Control (E-AGC) for future electric energy systems , 2012, 2012 IEEE Power and Energy Society General Meeting.

[11]  Goran Andersson,et al.  Impact of Low Rotational Inertia on Power System Stability and Operation , 2013, 1312.6435.

[12]  Daniel S. Kirschen,et al.  Optimal Battery Participation in Frequency Regulation Markets , 2017, IEEE Transactions on Power Systems.

[13]  Claire J. Tomlin,et al.  Frequency Regulation using Data-Driven Controllers in Power Grids with Variable Inertia due to Renewable Energy , 2019, 2019 IEEE Power & Energy Society General Meeting (PESGM).