A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a...A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a study on optimal energy saving in DC-electrified railway with on-board energy storage system(OBESS) by using peak demand cutting strategy under different trip time controls.The proposed strategy uses OBESS to store recovered braking energy and find an appropriated time to deliver the stored energy back to the power network in such a way that peak power of every substations is reduced.Bangkok Mass Transit System(BTS)-Silom Line in Thailand is used to test and verify the proposed strategy.The results show that substation peak power is reduced by63.49% and net energy consumption is reduced by 15.56%using coasting and deceleration trip time control.展开更多
For a characteristic c-ray with interlaced overlap peak, and the case where its reliable and credible net count cannot be obtained using the current high-purity germanium(HPGe) multichannel γ-ray spectrum software, t...For a characteristic c-ray with interlaced overlap peak, and the case where its reliable and credible net count cannot be obtained using the current high-purity germanium(HPGe) multichannel γ-ray spectrum software, two new methods are proposed herein to obtain the γ-ray net peak count from the interlaced overlap peak in the HPGe cray spectrometer system, of which one is the symmetric conversion method based on Gaussian distribution and the other is where the energy average value of two close γ-rays is regarded as the γ-ray energy. The experimental results indicate that the two methods mentioned above are reliable and credible. This study is significant for the development of better γ-ray spectrum processing software for measuring complex γ-ray spectra concerning the nuclear reaction cross section, neutron activation analysis, and analysis of transuranium elements, using an HPGe detector.展开更多
This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand...This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.展开更多
基于2002—2025年IRI(International Research Institute for Climate and Society)实时多模式预测资料,构建了一个面向事件的ENSO(El Nino-Southern Oscillation)峰值诊断框架,定量评估预测系统对峰值强度与峰值时间两项关键特征的可...基于2002—2025年IRI(International Research Institute for Climate and Society)实时多模式预测资料,构建了一个面向事件的ENSO(El Nino-Southern Oscillation)峰值诊断框架,定量评估预测系统对峰值强度与峰值时间两项关键特征的可预报性。尽管IRI系统在ENSO时间序列上可维持8~9 mon的较高技巧,但传统统计指标难以反映具体事件在峰值阶段的系统性偏差。结果表明,随着预报时效延长,预测的峰值强度普遍减弱,并呈现出显著的强度依赖特征。中等和强事件往往被低估,但弱事件更容易被高估。在模式差异方面,动力模式在再现中、强事件的峰值振幅上更有优势,但在弱事件中,统计模式的预测反而更接近观测。在峰值时间方面,模式预测普遍存在偏晚现象,并且滞后误差会随着预报时效持续累积。峰值时间偏差还呈现明显的冷暖不对称结构,拉尼娜事件的滞后程度显著强于厄尔尼诺事件。在不同模式类型的比较中,统计模式在拉尼娜事件中的峰值时间偏差远大于动力模式,而在厄尔尼诺事件中两类模式的差异相对较小。总体而言,本研究揭示了现有ENSO预测系统在峰值特征上的偏差结构,并指出动力与统计模式的互补性,为改进多模式集合策略和提升ENSO预测性能提供了科学依据。展开更多
针对新能源汇集区域多储能系统在单一应用场景下储能利用率不高、汇集系统整体经济性较差的问题,考虑新能源跟踪计划误差分布特性和汇集区域电网净负荷峰谷特性,让储能协助新能源跟踪发电计划的同时辅助系统调峰。根据新能源出力特性和...针对新能源汇集区域多储能系统在单一应用场景下储能利用率不高、汇集系统整体经济性较差的问题,考虑新能源跟踪计划误差分布特性和汇集区域电网净负荷峰谷特性,让储能协助新能源跟踪发电计划的同时辅助系统调峰。根据新能源出力特性和负荷功率特征,将储能运行区域划分为调峰区、跟踪计划区及荷电状态(states of charge,SOC)优化区,并提出一种面向发电计划跟踪与调峰的汇集系统储能分区协调优化运行策略。考虑新能源调峰成本分摊,跟踪计划误差惩罚,储能循环寿命成本、储能充放电转换成本等因素,针对不同区域分别建立储能优化运行模型。构建汇集系统整体跟踪计划出力效果评价指标、储能辅助系统调峰评价指标以及储能系统SOC评价指标,针对汇集系统优化运行结果进行评价。仿真结果表明,所提策略可以有效提升新能源跟踪计划出力能力,缓解系统调峰压力,降低新能源汇集系统整体运行成本,保证储能后续动作的可持续性。展开更多
基金Supported by the National Creative Research Group Science Foundation of China （600421002） and the New Century 151 Talent Projects of Zhejiang Province
文摘为不明确的线性分离系统的一个班的 peak-to-peak 获得最小化的一条矩阵不平等途径被学习。我们最小化 * 是导致的 L 标准上的最好的上面的界限的 -norm, 由与逃避不了的椭圆体围住可达到的集合获得了，而不是直接最小化导致的 L 标准。基于这个想法，柔韧的 peak-to-peak 获得最小化的问题和控制器合成被归结为解决一套矩阵不平等的可行性问题。一个数字例子被用来表明介绍方法的可行性和有效性。
文摘A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a study on optimal energy saving in DC-electrified railway with on-board energy storage system(OBESS) by using peak demand cutting strategy under different trip time controls.The proposed strategy uses OBESS to store recovered braking energy and find an appropriated time to deliver the stored energy back to the power network in such a way that peak power of every substations is reduced.Bangkok Mass Transit System(BTS)-Silom Line in Thailand is used to test and verify the proposed strategy.The results show that substation peak power is reduced by63.49% and net energy consumption is reduced by 15.56%using coasting and deceleration trip time control.
基金supported by the National Natural Science Foundation of China(Nos.11575090,11605099)the Young Key Teachers Training Program of He’nan Higher Education in China(No.2015GGJS-258)
文摘For a characteristic c-ray with interlaced overlap peak, and the case where its reliable and credible net count cannot be obtained using the current high-purity germanium(HPGe) multichannel γ-ray spectrum software, two new methods are proposed herein to obtain the γ-ray net peak count from the interlaced overlap peak in the HPGe cray spectrometer system, of which one is the symmetric conversion method based on Gaussian distribution and the other is where the energy average value of two close γ-rays is regarded as the γ-ray energy. The experimental results indicate that the two methods mentioned above are reliable and credible. This study is significant for the development of better γ-ray spectrum processing software for measuring complex γ-ray spectra concerning the nuclear reaction cross section, neutron activation analysis, and analysis of transuranium elements, using an HPGe detector.
文摘This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.
文摘基于2002—2025年IRI(International Research Institute for Climate and Society)实时多模式预测资料,构建了一个面向事件的ENSO(El Nino-Southern Oscillation)峰值诊断框架,定量评估预测系统对峰值强度与峰值时间两项关键特征的可预报性。尽管IRI系统在ENSO时间序列上可维持8~9 mon的较高技巧,但传统统计指标难以反映具体事件在峰值阶段的系统性偏差。结果表明,随着预报时效延长,预测的峰值强度普遍减弱,并呈现出显著的强度依赖特征。中等和强事件往往被低估,但弱事件更容易被高估。在模式差异方面,动力模式在再现中、强事件的峰值振幅上更有优势,但在弱事件中,统计模式的预测反而更接近观测。在峰值时间方面,模式预测普遍存在偏晚现象,并且滞后误差会随着预报时效持续累积。峰值时间偏差还呈现明显的冷暖不对称结构,拉尼娜事件的滞后程度显著强于厄尔尼诺事件。在不同模式类型的比较中,统计模式在拉尼娜事件中的峰值时间偏差远大于动力模式,而在厄尔尼诺事件中两类模式的差异相对较小。总体而言,本研究揭示了现有ENSO预测系统在峰值特征上的偏差结构,并指出动力与统计模式的互补性,为改进多模式集合策略和提升ENSO预测性能提供了科学依据。
文摘针对新能源汇集区域多储能系统在单一应用场景下储能利用率不高、汇集系统整体经济性较差的问题,考虑新能源跟踪计划误差分布特性和汇集区域电网净负荷峰谷特性,让储能协助新能源跟踪发电计划的同时辅助系统调峰。根据新能源出力特性和负荷功率特征,将储能运行区域划分为调峰区、跟踪计划区及荷电状态(states of charge,SOC)优化区,并提出一种面向发电计划跟踪与调峰的汇集系统储能分区协调优化运行策略。考虑新能源调峰成本分摊,跟踪计划误差惩罚,储能循环寿命成本、储能充放电转换成本等因素,针对不同区域分别建立储能优化运行模型。构建汇集系统整体跟踪计划出力效果评价指标、储能辅助系统调峰评价指标以及储能系统SOC评价指标,针对汇集系统优化运行结果进行评价。仿真结果表明,所提策略可以有效提升新能源跟踪计划出力能力,缓解系统调峰压力,降低新能源汇集系统整体运行成本,保证储能后续动作的可持续性。
