Chance-Constrained Optimal Configuration of BESS Considering Uncertain Power Fluctuation and Frequency Deviation Under Contingency

With the accelerating integration of variable renewable energies (VREs), power systems become more vulnerable to active power disturbances, and more drastic frequency dynamics emerge. The battery energy storage system (BESS) is able to handle the uncertainties of VREs, and the decreasing system iner...

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Vydané v:IEEE transactions on sustainable energy Ročník 13; číslo 4; s. 2291 - 2303
Hlavní autori: Cao, Yongji, Wu, Qiuwei, Zhang, Hengxu, Li, Changgang, Zhang, Xuan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract With the accelerating integration of variable renewable energies (VREs), power systems become more vulnerable to active power disturbances, and more drastic frequency dynamics emerge. The battery energy storage system (BESS) is able to handle the uncertainties of VREs, and the decreasing system inertia and frequency regulation capability. This paper proposes a chance-constrained optimal configuration scheme for the BESS to maintain both the uncertain power fluctuations and frequency deviation within predefined limits. First, the required frequency regulation capability of the BESS constrained by the maximum transient frequency deviation (MTFD) and quasi-steady-state frequency deviation (QSSFD) is estimated. Then, the kernel density estimation method is utilized to model the net power fluctuations of VREs and load. A multi-objective chance-constrained programming model accounting for the life cycle cost, energy arbitrage, uncertain power fluctuation, MTFD, and QSSFD is established to optimize the capacity of the BESS. Furthermore, the Bernstein approximation is utilized to process the chance constraint, and transform the optimization model into a deterministic form. Based on the linear weighted method and Benders decomposition, the optimization model is solved through alternating iteration. Case studies were conducted to validate the proposed scheme, showing superior performance in smoothing uncertain power fluctuations, and reducing frequency deviation under contingencies.
AbstractList With the accelerating integration of variable renewable energies (VREs), power systems become more vulnerable to active power disturbances, and more drastic frequency dynamics emerge. The battery energy storage system (BESS) is able to handle the uncertainties of VREs, and the decreasing system inertia and frequency regulation capability. This paper proposes a chance-constrained optimal configuration scheme for the BESS to maintain both the uncertain power fluctuations and frequency deviation within predefined limits. First, the required frequency regulation capability of the BESS constrained by the maximum transient frequency deviation (MTFD) and quasi-steady-state frequency deviation (QSSFD) is estimated. Then, the kernel density estimation method is utilized to model the net power fluctuations of VREs and load. A multi-objective chance-constrained programming model accounting for the life cycle cost, energy arbitrage, uncertain power fluctuation, MTFD, and QSSFD is established to optimize the capacity of the BESS. Furthermore, the Bernstein approximation is utilized to process the chance constraint, and transform the optimization model into a deterministic form. Based on the linear weighted method and Benders decomposition, the optimization model is solved through alternating iteration. Case studies were conducted to validate the proposed scheme, showing superior performance in smoothing uncertain power fluctuations, and reducing frequency deviation under contingencies.
Author Zhang, Xuan
Zhang, Hengxu
Wu, Qiuwei
Cao, Yongji
Li, Changgang
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SubjectTerms Battery energy storage system
Benders decomposition
chance-constrained optimization
Configurations
Constraint modelling
Contingency
Energy storage
Fluctuations
Frequency control
Frequency deviation
frequency regulation
frequency stability
Iterative methods
Life cycle costs
Life cycles
Load modeling
Optimization
Optimization models
Power smoothing
Power system dynamics
Power system stability
Renewable energy
system frequency response model
Uncertainty
Title Chance-Constrained Optimal Configuration of BESS Considering Uncertain Power Fluctuation and Frequency Deviation Under Contingency
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