The uncertainties from renewable energy sources(RESs)will not only introduce significant influences to active power dispatch,but also bring great challenges to the analysis of optimal reactive power dispatch(ORPD).To ...The uncertainties from renewable energy sources(RESs)will not only introduce significant influences to active power dispatch,but also bring great challenges to the analysis of optimal reactive power dispatch(ORPD).To address the influence of high penetration of RES integrated into active distribution networks,a distributionally robust chance constraint(DRCC)-based ORPD model considering discrete reactive power compensators is proposed in this paper.The proposed ORPD model combines a second-order cone programming(SOCP)-based model at the nominal operation mode and a linear power flow(LPF)model to reflect the system response under certainties.Then,a distributionally robust optimization(WDRO)method with Wasserstein distance is utilized to solve the proposed DRCC-based ORPD model.The WDRO method is data-driven due to the reason that the ambiguity set is constructed by the available historical data without any assumption on the specific probability distribution of the uncertainties.And the more data is available,the smaller the ambiguity would be.Numerical results on IEEE 30-bus and 123-bus systems and comparisons with the other three-benchmark approaches demonstrate the accuracy and effectiveness of the proposed model and method.展开更多
Summary What is already known about this topic?Antibiotic contaminations in the environment are understood to pose human health risks including disturbing the microbiome in the human body and producing antibiotic-resi...Summary What is already known about this topic?Antibiotic contaminations in the environment are understood to pose human health risks including disturbing the microbiome in the human body and producing antibiotic-resistant bacteria,which pose serious public health risks.Antibiotics have been detected in aquatic environments and drinking water worldwide.展开更多
基金This work was supported by grants from the National Basic Research Program of China （2016YFD0100402 2016YFD0100501+6 种基金 2017YFD0101701 2013CBA01401）, the National Natural Science Foundation of China （91735302 31771340 31500976 91535203 31425004 31400249）, the Chinese Academy of Sciences （XDA08020108）, the Ministry of Agriculture of China （2014ZX08009-003）, and the strategic pdodty research program ＂Molecular Mechanism of Plant Growth and Development＂ （XDBP401）.
基金supported in part by National Key Research and Development Program of China(No.2018YFB0905000)in part by Key Research and Development Program of Shaanxi(No.2017ZDCXL-GY-02-03)。
文摘The uncertainties from renewable energy sources(RESs)will not only introduce significant influences to active power dispatch,but also bring great challenges to the analysis of optimal reactive power dispatch(ORPD).To address the influence of high penetration of RES integrated into active distribution networks,a distributionally robust chance constraint(DRCC)-based ORPD model considering discrete reactive power compensators is proposed in this paper.The proposed ORPD model combines a second-order cone programming(SOCP)-based model at the nominal operation mode and a linear power flow(LPF)model to reflect the system response under certainties.Then,a distributionally robust optimization(WDRO)method with Wasserstein distance is utilized to solve the proposed DRCC-based ORPD model.The WDRO method is data-driven due to the reason that the ambiguity set is constructed by the available historical data without any assumption on the specific probability distribution of the uncertainties.And the more data is available,the smaller the ambiguity would be.Numerical results on IEEE 30-bus and 123-bus systems and comparisons with the other three-benchmark approaches demonstrate the accuracy and effectiveness of the proposed model and method.
文摘Summary What is already known about this topic?Antibiotic contaminations in the environment are understood to pose human health risks including disturbing the microbiome in the human body and producing antibiotic-resistant bacteria,which pose serious public health risks.Antibiotics have been detected in aquatic environments and drinking water worldwide.
