A wind power curtailment mitigation strategy via co-location and co-operation of compressed air energy storage with wind power generation

TY - JOUR

T1 - A wind power curtailment mitigation strategy via co-location and co-operation of compressed air energy storage with wind power generation

AU - Zhang, Xuecen

AU - Jenne, Sunku

AU - Ding, Yulong

AU - Spencer, Joseph

AU - He, Wei

AU - Wang, Jihong

N1 - Publisher Copyright: © 2024 The Author(s)

PY - 2025/4

Y1 - 2025/4

N2 - Wind power curtailment has resulted in notable economic and energy losses due to the rapid increase of wind energy in recent years. This paper presents our recent work on developing a wind power curtailment mitigation strategy via co-location and co-operation of compressed air energy storage (CAES) (in particular, Advanced Adiabatic CAES (AA-CAES)) with wind power generation. The work is built on our previous study on co-relation mapping of CAES storage locations and wind power resources. In this study, a stochastic optimisation (SO) model is formulated which successfully addresses the challenge of the lack of a modelling platform to accommodate and coordinate AA-CAES dynamics, uncertain wind power generation, integration with AC power networks, and dynamic co-operation analysis. The SO problem is described in a mixed-integer second-order cone programming (MISOCP) model. A novel generation ramp constraints temporal decoupling (GRC-TD) method is developed to cope with the temporal-coupling generation ramp constraints in the MISOCP problem. This method is integrated with the benders decomposition (BD) approach as an improved GRC-TD-BD algorithm. Numerical simulation studies using the UK transmission network data are conducted, which verify the feasibility and effectiveness of the proposed strategy. The simulation study shows very encouraging results. The co-location and co-operation of AA-CAES with wind power generation can make wind power more dispatchable and significantly reduce wind curtailment in the UK power system.

AB - Wind power curtailment has resulted in notable economic and energy losses due to the rapid increase of wind energy in recent years. This paper presents our recent work on developing a wind power curtailment mitigation strategy via co-location and co-operation of compressed air energy storage (CAES) (in particular, Advanced Adiabatic CAES (AA-CAES)) with wind power generation. The work is built on our previous study on co-relation mapping of CAES storage locations and wind power resources. In this study, a stochastic optimisation (SO) model is formulated which successfully addresses the challenge of the lack of a modelling platform to accommodate and coordinate AA-CAES dynamics, uncertain wind power generation, integration with AC power networks, and dynamic co-operation analysis. The SO problem is described in a mixed-integer second-order cone programming (MISOCP) model. A novel generation ramp constraints temporal decoupling (GRC-TD) method is developed to cope with the temporal-coupling generation ramp constraints in the MISOCP problem. This method is integrated with the benders decomposition (BD) approach as an improved GRC-TD-BD algorithm. Numerical simulation studies using the UK transmission network data are conducted, which verify the feasibility and effectiveness of the proposed strategy. The simulation study shows very encouraging results. The co-location and co-operation of AA-CAES with wind power generation can make wind power more dispatchable and significantly reduce wind curtailment in the UK power system.

UR - http://www.scopus.com/inward/record.url?scp=85211088532&partnerID=8YFLogxK

U2 - 10.1016/j.epsr.2024.111318

DO - 10.1016/j.epsr.2024.111318

M3 - Article

SN - 0378-7796

VL - 241

JO - ELECTRIC POWER SYSTEMS RESEARCH

JF - ELECTRIC POWER SYSTEMS RESEARCH

M1 - 111318

ER -