混合型潮流控制器(hybrid power flow controller,HPFC)可以有效解决风电并网系统中存在的支路潮流过载问题,且相较于统一潮流控制器成本更低。针对现有的HPFC潮流优化研究尚未计及支路潮流最大值约束和风电不确定性的问题,提出一种基...混合型潮流控制器(hybrid power flow controller,HPFC)可以有效解决风电并网系统中存在的支路潮流过载问题,且相较于统一潮流控制器成本更低。针对现有的HPFC潮流优化研究尚未计及支路潮流最大值约束和风电不确定性的问题,提出一种基于场景削减的含HPFC风电并网系统最优潮流模型。首先,建立HPFC的功率注入模型,并推导了注入功率表达式;其次,采用K均值算法削减风电、负荷概率场景,通过CH(+)指标选择最优场景集合;最后,建立兼顾发电机运行成本、系统网络损耗、正常运行及N-1故障下的支路负载率的多目标优化模型,采用多目标粒子群优化(multi-objective particle swarm optimization,MOPSO)算法进行求解,利用模糊满意度函数在Pareto解集中筛选出折衷解。在MATLAB中仿真验证所提方法的有效性,结果表明该方法可以计及风电不确定性,保证电网在不同场景下的安全经济运行。展开更多
Grain composition of debris flow varies considerably from fluid to deposit, making it uncertain to estimate flow properties(e.g., density,velocity and discharge) using deposit as done in practice. Tracing the variatio...Grain composition of debris flow varies considerably from fluid to deposit, making it uncertain to estimate flow properties(e.g., density,velocity and discharge) using deposit as done in practice. Tracing the variation of grain composition is thus more important than estimating some certain properties of flow because every debris flow event consists of a series of surges that are distinct in properties and flow regimes. We find that the materials of debris flows, both the fluid and the source soils, satisfy a universal grain size distribution(GSD) in a form of P(D) = CD –μexp(–D/D c), where the parameters C, μ and D c are determined by fitting the function to the grain size frequency. A small μ implies a small porosity and possible high excess pore pressure in flow; and a large D c means a wide range of grain composition and hence a high sediment concentration. Flow density increases as μ decreases or D c increases, in a power law form. A debris flow always achieves a state of certain mobility and density that can be well described by the coupling of μ and D c,which imposes a constraint on the fluctuations of flow surges. The GSD also describes the changes in grain composition in that it is always satisfied during the course of debris flow developing. Numerical simulation using the GSD can well illustrate the variation of μ and D c from source soils to deposits.展开更多
为提升智能电网的运行质量,解决当前智能电网存在的负荷波动大、经济效益低的问题,在考虑负荷动态模型的情况下,提出智能电网灵活规划方法。根据用电电压划分智能电网的供电区域,针对不同区域构建相应的负荷动态模型;利用动态负荷模型...为提升智能电网的运行质量,解决当前智能电网存在的负荷波动大、经济效益低的问题,在考虑负荷动态模型的情况下,提出智能电网灵活规划方法。根据用电电压划分智能电网的供电区域,针对不同区域构建相应的负荷动态模型;利用动态负荷模型分析电网负荷的波动特征,预测电网实时负荷值;从用电需求量、输电线路潮流和负荷平均密度3个方面,设置智能电网规划约束条件;通过对智能电网架构、线路等组成部分的规划,得出最终的规划结果。实验结果表明:所提方法规划后,智能电网负荷率的平均值更趋近于1,年线损量降低了2777.41 k W,投入成本节省了15724万元。展开更多
基金supported by the Key Research Program of the Chinese Academy of Sciences (Grant No.KZZD-EW-05-01)the National Natural Science Foundation of China (Grant No. 41471011)the Key Laboratory of Mountain Hazards and Earth Surface Processes,Chinese Academy of Sciences,China
文摘Grain composition of debris flow varies considerably from fluid to deposit, making it uncertain to estimate flow properties(e.g., density,velocity and discharge) using deposit as done in practice. Tracing the variation of grain composition is thus more important than estimating some certain properties of flow because every debris flow event consists of a series of surges that are distinct in properties and flow regimes. We find that the materials of debris flows, both the fluid and the source soils, satisfy a universal grain size distribution(GSD) in a form of P(D) = CD –μexp(–D/D c), where the parameters C, μ and D c are determined by fitting the function to the grain size frequency. A small μ implies a small porosity and possible high excess pore pressure in flow; and a large D c means a wide range of grain composition and hence a high sediment concentration. Flow density increases as μ decreases or D c increases, in a power law form. A debris flow always achieves a state of certain mobility and density that can be well described by the coupling of μ and D c,which imposes a constraint on the fluctuations of flow surges. The GSD also describes the changes in grain composition in that it is always satisfied during the course of debris flow developing. Numerical simulation using the GSD can well illustrate the variation of μ and D c from source soils to deposits.
文摘为提升智能电网的运行质量,解决当前智能电网存在的负荷波动大、经济效益低的问题,在考虑负荷动态模型的情况下,提出智能电网灵活规划方法。根据用电电压划分智能电网的供电区域,针对不同区域构建相应的负荷动态模型;利用动态负荷模型分析电网负荷的波动特征,预测电网实时负荷值;从用电需求量、输电线路潮流和负荷平均密度3个方面,设置智能电网规划约束条件;通过对智能电网架构、线路等组成部分的规划,得出最终的规划结果。实验结果表明:所提方法规划后,智能电网负荷率的平均值更趋近于1,年线损量降低了2777.41 k W,投入成本节省了15724万元。
