Work

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

Year: 2024

Type: article

Abstract: • Quantified analysis reveals the great potential of wind power curtailment mitigation via co-location and co-operation of AA-CAES with wind farms. • Develops a temporal decoupling algorithm to provide an effective method for solving the temporal-coupling MISOCP problem. • The outcomes of case studies using the UK transmission network data provide strong evidence to support the UK clean energy agenda. 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.

Source: Electric Power Systems Research

DOI: 10.1016/j.epsr.2024.111318

Authors: Xuecen Zhang, Sunku Prasad Jenne, Yulong Ding, Joseph Spencer, Wei He, Jihong Wang

Institutions: University of Warwick, University of Birmingham, University of Liverpool, King's College London

Language: English

Topic: Electric Power System Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,480