In recent years, increased integration of renewable energy sources (RES) calls for extensive and costly investments in transmission networks. In response, power system decisionmakers try to apply alternative solutions aimed to decrease the imposed investment costs. In this context, the presence of large-scale energy storage systems (ESSs) in transmission network can be a practical option for deferring investment in expansion plans of transmission lines, alleviating system congestions, and attaining higher flexibility. In this paper, an efficient model is proposed for co-planning expansion studies of compressed air energy storage (CAES) units and transmission networks. The associated optimisation formulation of co-planning problem is expressed as a MILP model, which can be efficiently solved. The proposed model is applied on the Garver as well as RTS test systems and N-1 criterion is considered to address the system reliability performance in expansion studies. The results demonstrate that the proposed co-planning framework has a superior performance in expansion plans of transmission systems. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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 gridscale 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.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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