针对强迫导向油循环风冷(oir directrd air forced,ODAF)结构变压器负荷能力受温升约束影响的问题,提出了3种负荷类型情况下变压器负荷能力评估方法。首先,考虑风扇与油泵的运行状态以及油粘度变化对热阻的影响等因素,基于热电类比法建...针对强迫导向油循环风冷(oir directrd air forced,ODAF)结构变压器负荷能力受温升约束影响的问题,提出了3种负荷类型情况下变压器负荷能力评估方法。首先,考虑风扇与油泵的运行状态以及油粘度变化对热阻的影响等因素,基于热电类比法建立了变压器热路模型,以计算绕组热点与顶部油温度;其次,采用粒子群优化(particle swarm optimization,PSO)算法拟合热路模型参数,并基于2台不同型号变压器的运行数据,对热路模型的计算精度与拟合参数适用性进行有效性验证;最后,参考GB/T1094.7负载导则给出的温升限值,基于温升特性提出了负荷能力评估模型。分析结果表明,该研究所提热路模型计算热点温度的误差不大于2.35℃,在工程允许范围内;正常周期性负荷下当环境温度低于1℃时,关闭1组子散热器后仍满足温升约束。展开更多
This paper proposes a day-ahead dispatch framework of thermostatically controlled loads(TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user’s indoor thermal comfort de...This paper proposes a day-ahead dispatch framework of thermostatically controlled loads(TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user’s indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a dayahead TCL scheduling model is formulated, which consists of 3 stages: TCL aggregator estimates maximal controllable TCL capacities at each scheduling time interval by solving a optimization model;[ the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator;and ′the TCL aggregator schedules the ON/OFFcontrol actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution(HDDE)algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model.展开更多
基金supported in part by an AustralianResearch Council Future Fellowship scheme (No. FT140100130)in part by an Australian Research Discovery Project (No. DP170103427)
文摘This paper proposes a day-ahead dispatch framework of thermostatically controlled loads(TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user’s indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a dayahead TCL scheduling model is formulated, which consists of 3 stages: TCL aggregator estimates maximal controllable TCL capacities at each scheduling time interval by solving a optimization model;[ the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator;and ′the TCL aggregator schedules the ON/OFFcontrol actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution(HDDE)algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model.