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ELCC-based capacity value estimation of combined wind - storage system using IPSO algorithm

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  • Wen, Lei
  • Song, Qianqian

Abstract

Combined wind-storage systems (CWSSs) could significantly improve the reliability of power systems. In order to quantify the contribution of wind power and storage systems on adequacy of power systems, this paper proposes a novel algorithm based on equivalent load carrying capacity (ELCC), improved particle swarm optimization (IPSO). Simulation results are also provided. First, a novel algorithm IPSO for evaluating ELCC is presented. Second, the ELCC of wind power under different wind power permeability is studied using scenario simulation. Third, the ELCC of CWSS under diverse capacity combinations of wind power and energy storage is analyzed based on scenario simulation. Also, the superiority of IPSO is verified by comparing the results of ELCC evaluation with secant method and non-iterative smoothing spline (NISS). The simulation results show that, 1) ELCC of wind power increases with the augment of wind power permeability but finally stabilizes when wind power permeability is 60%. 2) When the permeability of wind power is constant, ELCC of CWSS increases and then does not change basically with the addition of the maximum capacity of energy storage. 3) The permeability of wind power and the maximum capacity of energy storage augment simultaneously will not increase ELCC of CWSS indefinitely.

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  • Wen, Lei & Song, Qianqian, 2023. "ELCC-based capacity value estimation of combined wind - storage system using IPSO algorithm," Energy, Elsevier, vol. 263(PB).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pb:s0360544222026706
    DOI: 10.1016/j.energy.2022.125784
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