智能化电网的快速建设,增加了电网的不确定性并提高了大面积停电的概率,为此,提出了基于蒙特卡洛和连锁故障停电模型(Monte Carlo and Cascading Failure Blackout Model,MC-CFBM)的停电风险评估方法,以制定相应的停电预防和控制策略。...智能化电网的快速建设,增加了电网的不确定性并提高了大面积停电的概率,为此,提出了基于蒙特卡洛和连锁故障停电模型(Monte Carlo and Cascading Failure Blackout Model,MC-CFBM)的停电风险评估方法,以制定相应的停电预防和控制策略。建立了连锁故障停电模型,包括继保装置的隐性故障模型,基于直流潮流的最小切负荷模型,连锁故行停电模型。在连锁故障停电模型的基础上,建立了MC-CFBM的停电风险评估方法,能够准确的得到短时间停电数据。基于简单随机采样法的MC方法提高了算法的收敛速度。建立了系统风险指标,支路风险指标和N-1风险指标等用于评估停电风险的方法。实验仿真结果验证了所提MC-CFBM收敛速度较快,具有可靠性;建立的停电风险指标能够准确描述停电风险,为停电预防和制定相应的控制策略提供了理论指导。展开更多
In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individua...In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.展开更多
文摘智能化电网的快速建设,增加了电网的不确定性并提高了大面积停电的概率,为此,提出了基于蒙特卡洛和连锁故障停电模型(Monte Carlo and Cascading Failure Blackout Model,MC-CFBM)的停电风险评估方法,以制定相应的停电预防和控制策略。建立了连锁故障停电模型,包括继保装置的隐性故障模型,基于直流潮流的最小切负荷模型,连锁故行停电模型。在连锁故障停电模型的基础上,建立了MC-CFBM的停电风险评估方法,能够准确的得到短时间停电数据。基于简单随机采样法的MC方法提高了算法的收敛速度。建立了系统风险指标,支路风险指标和N-1风险指标等用于评估停电风险的方法。实验仿真结果验证了所提MC-CFBM收敛速度较快,具有可靠性;建立的停电风险指标能够准确描述停电风险,为停电预防和制定相应的控制策略提供了理论指导。
文摘In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.
