In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a...In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.展开更多
Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of ...Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of coordinating protective relays in electrical power systems consists of selecting suitable settings such that their fundamental protective function is met,given operational requirements of sensitivity,selectivity,reliability and speed.Directional over current relays are best suited for protection of an interconnected sub-station transmission system.One of the major problems associated with this type of protection is the difficulty in coordinating relays.To insure proper coordination,all the main/back up relay pairs must be determined.This paper presents an effective algorithm to determine the minimum number of break points and main/back up relay pairs using relative sequence matrix(RSM).A novel optimization technique based on evolutionary programming was developed using these main/back up relay pairs for directional over current relay coordination in multi-loop networks.Since the problem has multi-optimum points,conventional mathematics based optimization techniques may sometimes fail.Hence evolutionary programming(EP) was used,as it is a stochastic multi-point search optimization algorithm capable of escaping from the local optimum problem,giving a better chance of reaching a global optimum.The method developed was tested on an existing 6 bus,7 line system and better results were obtained than with conventional methods.展开更多
构网型储能的有功控制可为系统提供有效的频率支撑,但并联机组间控制策略不协调时,会引发荷电状态(state of charge,SOC)不均衡、低频振荡等问题。为此,首先建立了并联构网储能系统的状态空间模型,分析了控制参数对系统的频率稳定、振...构网型储能的有功控制可为系统提供有效的频率支撑,但并联机组间控制策略不协调时,会引发荷电状态(state of charge,SOC)不均衡、低频振荡等问题。为此,首先建立了并联构网储能系统的状态空间模型,分析了控制参数对系统的频率稳定、振荡抑制等性能的影响,并研究了并联机组间的有功分配机理。在此基础上,提出了适用于并联构网型储能系统的协调有功控制策略。最后,利用Matlab/Simulink的数字仿真与基于RT-LAB的硬件在环平台验证了所提控制策略的有效性。研究结果表明:所提方法在保证频率安全稳定的基础上,有效实现了并联储能机组间SOC均衡、功率分配优化以及振荡抑制的效果。展开更多
碳捕集、利用与封存(Carbon Capture,Utilization and Storage,CCUS)技术是煤电低碳化发展的重要途径之一,煤电CCUS的规模化发展是电力低碳转型的关键措施之一。基于计及煤电CCUS的电力转型技术-经济-排放仿真模型,在给定的参数条件下...碳捕集、利用与封存(Carbon Capture,Utilization and Storage,CCUS)技术是煤电低碳化发展的重要途径之一,煤电CCUS的规模化发展是电力低碳转型的关键措施之一。基于计及煤电CCUS的电力转型技术-经济-排放仿真模型,在给定的参数条件下对不同的煤电发展路径进行仿真,评估了不同煤电CCUS发展规模下电力转型路径的电力、排放与经济类指标,以总经济代价最小为目标函数比选了最优煤电CCUS发展路径。结果表明:煤电CCUS与新能源的协同发展有潜力降低电力低碳转型的总经济代价;在电力转型优化中不应将某个年份后不再新建煤电作为约束条件,应在给定的参数条件下优化煤电CCUS发展路径并分析其对相关参数的敏感性,并强调应及时根据最新的参数条件更新路径优化结果。展开更多
基金Project (70671039) supported by the National Natural Science Foundation of China
文摘In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.
文摘Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of coordinating protective relays in electrical power systems consists of selecting suitable settings such that their fundamental protective function is met,given operational requirements of sensitivity,selectivity,reliability and speed.Directional over current relays are best suited for protection of an interconnected sub-station transmission system.One of the major problems associated with this type of protection is the difficulty in coordinating relays.To insure proper coordination,all the main/back up relay pairs must be determined.This paper presents an effective algorithm to determine the minimum number of break points and main/back up relay pairs using relative sequence matrix(RSM).A novel optimization technique based on evolutionary programming was developed using these main/back up relay pairs for directional over current relay coordination in multi-loop networks.Since the problem has multi-optimum points,conventional mathematics based optimization techniques may sometimes fail.Hence evolutionary programming(EP) was used,as it is a stochastic multi-point search optimization algorithm capable of escaping from the local optimum problem,giving a better chance of reaching a global optimum.The method developed was tested on an existing 6 bus,7 line system and better results were obtained than with conventional methods.
文摘构网型储能的有功控制可为系统提供有效的频率支撑,但并联机组间控制策略不协调时,会引发荷电状态(state of charge,SOC)不均衡、低频振荡等问题。为此,首先建立了并联构网储能系统的状态空间模型,分析了控制参数对系统的频率稳定、振荡抑制等性能的影响,并研究了并联机组间的有功分配机理。在此基础上,提出了适用于并联构网型储能系统的协调有功控制策略。最后,利用Matlab/Simulink的数字仿真与基于RT-LAB的硬件在环平台验证了所提控制策略的有效性。研究结果表明:所提方法在保证频率安全稳定的基础上,有效实现了并联储能机组间SOC均衡、功率分配优化以及振荡抑制的效果。
文摘随着配电网中分布式光伏(distributed photovoltaic,DPV)大量并网,电压越限和电压波动越来越严重,考虑新型电能质量治理装置的电压无功优化协调控制方法需要进一步完善,以适应电网的新变化。该文考虑了新型柔性有载调压变压器(on-load tap changer,OLTC)的电能质量调节作用,提出一种两阶段电压无功优化协调控制方法,其中一阶段为日前小时级调度阶段,根据分布式光伏和负荷的预测数据,通过潮流计算和迭代优化,获取DPV的有功出力结果、柔性OLTC分接头和电容器组的投切结果;二阶段为分钟级无功优化阶段,在第一阶段的基础上,考虑柔性OLTC和DPV的无功出力特性,调节装备无功出力的同时修正第一阶段电容器组投切组合,进一步降低各个节点最大电压偏差,使配电网电压分布更合理。搭建了IEEE33节点配电系统仿真模型,所提出的考虑柔性OLTC的两阶段电压无功优化协调控制方法能够在常规经济性最优目标下的88.07%DPV消纳水平基础上提高9.29%,同时满足全节点全时段电压偏差小于0.1pu,综合经济性提高7.8%,结果证明了所提方法的合理性和有效性。
文摘碳捕集、利用与封存(Carbon Capture,Utilization and Storage,CCUS)技术是煤电低碳化发展的重要途径之一,煤电CCUS的规模化发展是电力低碳转型的关键措施之一。基于计及煤电CCUS的电力转型技术-经济-排放仿真模型,在给定的参数条件下对不同的煤电发展路径进行仿真,评估了不同煤电CCUS发展规模下电力转型路径的电力、排放与经济类指标,以总经济代价最小为目标函数比选了最优煤电CCUS发展路径。结果表明:煤电CCUS与新能源的协同发展有潜力降低电力低碳转型的总经济代价;在电力转型优化中不应将某个年份后不再新建煤电作为约束条件,应在给定的参数条件下优化煤电CCUS发展路径并分析其对相关参数的敏感性,并强调应及时根据最新的参数条件更新路径优化结果。
