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

机译:最佳发电调度压缩空气储存与风力发电对经济技术问题的影响

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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 AC-SCUC problem and CAES scheduling are considered as an optimization problem which is solved using mixed-integer non-linear programming (MINLP) approach. The proposed stochastic methodology is applied to a modified IEEE 30 bus test system.
机译:风能的高渗透提高了电力系统中的产生不确定性。大规模的能量存储系统,如压缩空气储能(CAES),可以适应这种不确定性,如果它定于最佳定期。在本文中,考虑到CAE,风力发电和热量单位进行了提出的随机AC安全约束单元承诺(AC-SCUC),并在提出的随机方法中进行技术经济评估。采用两阶段随机编程来处理风力发电的不确定性。随着CAES和风能不确定性的集成影响电力系统的电压问题,技术经济评估是以所提出的随机方法进行的,以揭示最佳发电调度对静态电压稳定性的影响。由于其较少的计算成本,使用基于场景的方法建模风电不确定性。 AC-SCUC问题和CAES调度被认为是使用混合整数非线性编程(MINLP)方法来解决的优化问题。所提出的随机方法应用于改进的IEEE 30总线测试系统。

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