Due to the growing penetration of renewable energies(REs)in integrated energy system(IES),it is imperative to assess and reduce the negative impacts caused by the uncertain REs.In this paper,an unscented transformatio...Due to the growing penetration of renewable energies(REs)in integrated energy system(IES),it is imperative to assess and reduce the negative impacts caused by the uncertain REs.In this paper,an unscented transformation-based mean-standard(UT-MS)deviation model is proposed for the stochastic optimization of cost-risk for IES operation considering wind and solar power correlated.The unscented transformation(UT)sampling method is adopted to characterize the uncertainties of wind and solar power considering the correlated relationship between them.Based on the UT,a mean-standard(MS)deviation model is formulated to depict the trade-off between the cost and risk of stochastic optimization for the IES optimal operation problem.Then the UT-MS model is tackled by a multi-objective group search optimizer with adaptive covariance and Levy flights embedded with a multiple constraints handling technique(MGSO-ACL-CHT)to ensure the feasibility of Peratooptimal solutions.Furthermore,a decision-making method,improved entropy weight(IEW),is developed to select a final operation point from the set of Perato-optimal solutions.In order to verify the feasibility and efficiency of the proposed UT-MS model in dealing with the uncertainties of correlative wind and solar power,simulation studies are conducted on a test IES.Simulation results show that the UT-MS model is capable of handling the uncertainties of correlative wind and solar power within much less samples and less computational burden.Moreover,the MGSOACL-CHT and IEW are also demonstrated to be effective in solving the multi-objective UT-MS model of the IES optimal operation problem.展开更多
分析了2005年6月1日至11月31日以T213分析场为背景场和以AVN(Aviation)分析场为背景场条件下AREM(Advanced Regional Eta Model)模式降水预报效果,并对两分析场计算日平均偏差和均方根标准差,分析偏差分布、总结两者之间的差别。结果表...分析了2005年6月1日至11月31日以T213分析场为背景场和以AVN(Aviation)分析场为背景场条件下AREM(Advanced Regional Eta Model)模式降水预报效果,并对两分析场计算日平均偏差和均方根标准差,分析偏差分布、总结两者之间的差别。结果表明:AREM模式在其他条件完全相同,分别使用两种分析场做背景场条件下,出现了降水预报效果的较明显差异,总体上以AVN分析场为背景场条件下AREM模式的预报效果好于以T213分析场为背景场;对两分析场进行统计学对比,发现两分析场在高度、温度和相对湿度3个要素上存在较大的差异,两分析场在新疆北侧的西伯利亚、内蒙古东北部及俄罗斯东南部区域、孟加拉湾、青藏高原等地区存在较大偏差,而这些地区的天气系统对我国天气有重要的影响。展开更多
基金supported by the State Key Program of National Natural Science Foundation of China(No.51437006)the Fundamental Research Funds for the Central Universities and the China Postdoctoral Science Foundation(No.2017M622690).
文摘Due to the growing penetration of renewable energies(REs)in integrated energy system(IES),it is imperative to assess and reduce the negative impacts caused by the uncertain REs.In this paper,an unscented transformation-based mean-standard(UT-MS)deviation model is proposed for the stochastic optimization of cost-risk for IES operation considering wind and solar power correlated.The unscented transformation(UT)sampling method is adopted to characterize the uncertainties of wind and solar power considering the correlated relationship between them.Based on the UT,a mean-standard(MS)deviation model is formulated to depict the trade-off between the cost and risk of stochastic optimization for the IES optimal operation problem.Then the UT-MS model is tackled by a multi-objective group search optimizer with adaptive covariance and Levy flights embedded with a multiple constraints handling technique(MGSO-ACL-CHT)to ensure the feasibility of Peratooptimal solutions.Furthermore,a decision-making method,improved entropy weight(IEW),is developed to select a final operation point from the set of Perato-optimal solutions.In order to verify the feasibility and efficiency of the proposed UT-MS model in dealing with the uncertainties of correlative wind and solar power,simulation studies are conducted on a test IES.Simulation results show that the UT-MS model is capable of handling the uncertainties of correlative wind and solar power within much less samples and less computational burden.Moreover,the MGSOACL-CHT and IEW are also demonstrated to be effective in solving the multi-objective UT-MS model of the IES optimal operation problem.
文摘分析了2005年6月1日至11月31日以T213分析场为背景场和以AVN(Aviation)分析场为背景场条件下AREM(Advanced Regional Eta Model)模式降水预报效果,并对两分析场计算日平均偏差和均方根标准差,分析偏差分布、总结两者之间的差别。结果表明:AREM模式在其他条件完全相同,分别使用两种分析场做背景场条件下,出现了降水预报效果的较明显差异,总体上以AVN分析场为背景场条件下AREM模式的预报效果好于以T213分析场为背景场;对两分析场进行统计学对比,发现两分析场在高度、温度和相对湿度3个要素上存在较大的差异,两分析场在新疆北侧的西伯利亚、内蒙古东北部及俄罗斯东南部区域、孟加拉湾、青藏高原等地区存在较大偏差,而这些地区的天气系统对我国天气有重要的影响。
