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机构地区:[1]电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系),北京市海淀区100084
出 处:《中国电机工程学报》2015年第12期2919-2926,共8页Proceedings of the CSEE
基 金:国家重点基础研究发展计划项目(973项目)(2013CB228203);国家自然科学基金项目(51177080);新世纪优秀人才支持计划项目(NCET-11-0281)~~
摘 要:大规模风电接入电网给传统电力系统机组检修决策问题带来了新的挑战,如何在历史统计数据不足的情况下考虑风电对机组检修的影响成为难点之一。将鲁棒优化理论引入检修决策领域,构建机组检修鲁棒优化模型,并给出风电不确定集合的构造方法。模型以风电最恶劣情景下系统运行最优为优化目标,保证系统运行安全性,通过调整不确定集合边界,可控制鲁棒优化模型的保守性,实现决策的经济性与安全性平衡。算例对比证明所提模型和方法在计算效率和计算结果中的优势。通过调整保守性参数,鲁棒优化模型可获得比传统随机规划模型更优的结果。The integration of large scale wind power brings great challenges to the classical generator maintenance scheduling in power systems. One of the major difficulties is that how to consider the impact of wind power on the maintenance schedule under the absence of historical statistic data of wind power. The robust optimization theory was applied to the maintenance scheduling problems and a robust optimization model, as well as the method of constructing uncertainty set of wind power, was proposed in this paper. The security of power system was reflected in the objective of the robust optimization model, which was to optimize the operation cost under the worst case of uncertainty factors. The economy of the optimal decision could be achieved by adjusting the boundary of uncertainty set to control the conservatism of the model. The computational efficency and advantage of the model are demonstrated by numerical examples. By adjusting the uncertainty set, the optimal maintenance schedule obtained from the robust model is expected to be better than the one from the stochastic programming model.
分 类 号:TM73[电气工程—电力系统及自动化]
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