Effect of optimal generation scheduling of compressed air energy storage and wind power generation on economic and technical issues

Effect of optimal generation scheduling of compressed air energy storage and wind power generation on economic and technical issues

High penetration of wind power increases the generation uncertainty in power systems. Large-scale energy storage systems, such as compressed air energy storage (CAES), can accommodate this uncertainty properly, if it is scheduled optimally. In this paper, a proposed stochastic AC-security constrained unit commitment (AC-SCUC) is performed considering CAES, wind power generation and thermal units, and a techno-economic assessment is conducted in the proposed stochastic methodology. A two-stage stochastic programming is employed to handle uncertainty of wind power generation. As the integration of CAES and wind power uncertainty affect voltage issue of power system, the techno-economic assessment is carried out in the proposed stochastic methodology to shed light on the effects of optimal generation scheduling on the static voltage stability. Due to its less computation cost, the wind power uncertainty is modeled using scenario-based approach. The ACSCUC problem and CAES scheduling are considered as an optimization problem which is solved using mixed-integer nonlinear programming (MINLP) approach. The proposed stochastic methodology is applied to a modified IEEE 30 bus test system

High penetration of wind power increases the generation uncertainty in power systems. Large-scale energy storage systems, such as compressed air energy storage (CAES), can accommodate this uncertainty properly, if it is scheduled optimally. In this paper, a proposed stochastic AC-security constrained unit commitment (AC-SCUC) is performed considering CAES, wind power generation and thermal units, and a techno-economic assessment is conducted in the proposed stochastic methodology. A two-stage stochastic programming is employed to handle uncertainty of wind power generation. As the integration of CAES and wind power uncertainty affect voltage issue of power system, the techno-economic assessment is carried out in the proposed stochastic methodology to shed light on the effects of optimal generation scheduling on the static voltage stability. Due to its less computation cost, the wind power uncertainty is modeled using scenario-based approach. The ACSCUC problem and CAES scheduling are considered as an optimization problem which is solved using mixed-integer nonlinear programming (MINLP) approach. The proposed stochastic methodology is applied to a modified IEEE 30 bus test system