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A linearized transmission expansion planning model under <i>N</i> − 1 criterion for enhancing grid‐scale system flexibility via compressed air energy storage integration

Hesam Mazaheri, Moein Moeini‐Aghtaie, Mahmud Fotuhi‐Firuzabad, Payman Dehghanian, Mohammad Khoshjahan

2021IET Generation Transmission & Distribution20 citationsDOIOpen Access PDF

Abstract

Abstract The concept of flexibility is defined as the power systems’ ability to effectively respond to changes in power generation and demand profiles to maintain the supply–demand balance. However, the inherent flexibility margins required for successful operation have been recently challenged by the unprecedented arrival of uncertainties, driven by constantly changing demand, failure of conventional units, and the intermittent outputs of renewable energy sources (RES). Tackling these challenges, energy storage systems (ESS) as one important player of the new power grids can enhance the system flexibility. It, therefore, calls for an efficient planning procedure to ensure flexibility margins by considering ESS's role in modern power systems. This paper proposes a novel mixed integer linear programming (MILP) model for transmission expansion planning (TEP) framework taking into account the role of compressed air energy storage (CAES) integration on improvements in system flexibility. The proposed framework is housed with a quantitative metric of grid‐scale system flexibility, while a new offline repetitive mechanism is suggested to account for the N − 1 reliability criterion. The model is applied to different test systems, where the numerical results demonstrate the impacts of CAES units on system flexibility, investment plans, and the total costs.

Topics & Concepts

Flexibility (engineering)Energy storageCompressed air energy storageElectric power systemReliability engineeringGridRenewable energyComputer scienceTransmission (telecommunications)Mathematical optimizationPower (physics)EngineeringTelecommunicationsElectrical engineeringMathematicsPhysicsGeometryStatisticsQuantum mechanicsElectric Power System OptimizationSmart Grid Energy ManagementMicrogrid Control and Optimization