电力系统过程状态估计研究
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摘要
状态估计所提供信息的准确性和及时性,对于电力系统的安全、经济运行具有十分重要的意义。现有的时间周期触发方式的状态估计,在网络状态监测和电网运行控制两方面用途之中,都存在一定的局限性。首先,由于状态估计触发和SCADA扫描在周期上差距很大,调度中心难以细致地掌握到系统运行过程中运行状态变化情况。其次,调度中心只能通过状态估计提供的单一时间断面状态来制定控制策略,然而单一时间断面状态无法全面地反映系统在一个过程中的运行情况,因而控制策略的制定难以做到安全性与经济性兼顾。
随着系统状态的不断变化,状态估计也需要不断地进行计算,从时间过程角度研究它,符合物理现象的本质。本文以改善状态估计在网络状态监测和电网运行控制两方面效用为目的,提出了面向过程的状态估计方法。
借助过程函数的概念,对基于过程的状态估计模型进行了描述。提出了由量测量的变化情况来引导状态估计触发,即每当状态估计器收到的一定比例的发生了较为明显变化的遥测量,或者出现遥信变位,就触发状态估计计算。变化量测触发方式(changed measurement triggering mode , CMTM)是一种智能的触发方式,能够根据网络状态变化的快慢,动态地选取状态估计的触发时刻。polling方式的追踪状态估计是应答式远动支持下的一种非完全处理状态估计,采用能够灵活处理量测量的方法,仅处理被更新量测,追踪求解状态量,属于以少许估计精度损失换取计算速度提升的方法。提出了两种polling方式的追踪状态估计算法——最小二乘递推法逐次追踪状态估计和灵敏度分析法逐次追踪状态估计。最小二乘递推法逐次追踪状态估计,即基于最小二乘递推估计,在每一计算时刻仅处理被更新量测,完成对状态向量的估计。灵敏度分析法逐次追踪状态估计则是在每一计算时刻,利用状态量估值、量测量以及功率估计值之间的灵敏度关系处理被更新量测。
根据状态量与量测量之间的灵敏度关系,提出了状态影响系数的概念,以表示量测量对系统状态量估值影响能力的大小。在网络拓扑和线路参数一定的条件下,影响状态影响系数的因素包括系统负荷水平、量测冗余度、量测类型等。基于状态影响系数,提出了触发阈值的个体选取方法。
提出了过程特征断面状态估计,即借助传统状态估计算法估计出能够表征系统在一个时段上典型运行特征的一组时间断面状态量,可作为全局控制的有效依据。过程特征断面至少包括极端过程特征断面和期望过程特征断面。
设计了过程状态估计模式。过程状态估计的动态周期是由变化量测触发方式状态估计环节提供,同时也作为polling方式追踪估计环节的追踪时段以及过程特征断面估计环节的运行控制分析时段。通过对触发阈值等参数的调整,使动态周期为一个分钟级的时间,以动态周期为纽带,便将三个环节有机的联系起来。
仿真算例表明了本文方法的可行性和优越性。首先,变化量测触发方式的状态估计能够根据网络状态变化的快慢,动态地选取过程状态估计的动态周期,并能够为polling方式的追踪状态估计提供高精度的追踪初值。其次,polling方式的追踪状态估计,处理量测量具有极快的速度,并且在精度上能够保证与WLS算法非常高的一致性,能够紧密追踪量测量的更新。最后,过程特征断面状态估计,能够为调度中心提供全面而关键的电网运行状态信息。三个环节各司其职,使得过程状态估计一方面能够实现高密度高精度的电网状态监测,另一方面能够作为评价系统稳态运行工况和运行控制决策的有力依据。
Accuracy and timeliness of Information provided by state estimation (SE) is very important to safe and economical operation of power grid. The existing period triggering mode state estimation (SE) has its limitations in the two purposes of power grid state monitoring and operating control. On one hand, there is big difference between SE triggering period and supervisory control and data acquisition (SCADA) scanning period. Therefore it is hard for dispatch control center to grasp the intensively operating state varying in power grid operating process. On the other hand, dispatch control center can make control strategies only by the single time section state provided by SE. However, the single time section state cannot reflect the power grid operating status in its entirety in the process. Therefore it is difficult for the control strategies to take account of security and economy.
With the ceaseless change of power grid state, it ought to be triggered ceaselessly for state estimation. Therefore, research based on time process meets the essence of physical phenomenon. Time process oriented state estimation is presented to improve the utility of state estimation in power grid state monitoring and operating control.
With the concept of process function, state estimation model based on time process is described. The mode is put forward in which state estimation is triggered by the variation of measured quantities. That is, state estimation is triggered when the state estimator receives certain proportion of telemetry measurements that changed comparatively obviously, or there is a remote signaling transposed. Changed measurement triggering mode (CMTM) is an intelligent triggering mode.
Tracking SE of polling type is an incomplete-processing SE with polling type telemechanics, which needs algorithms that can handle measurements flexibly. It handles the renewed measurements only and solve state variable by tracking method. It is a method that exchanges a little estimation precision for greater calculation speed. Then two tracking SE algorithms of polling type are put forward, which are recursive least squares method sequential tracking SE algorithm and sensitivity analysis method sequential tracking state estimation algorithm. The former algorithm only handles renewed measurements one by one at every calculation moment based on recursive least squares estimate to renew the state vector. And the latter algorithm handles only the renewed measurements one by one using the relations of sensitivity among state variable, measurements and estimate of power.
Based on the relations of sensitivity between state variable estimate and measurements, the concept of state affectois is presented representing the influence capacity of measurements to state variable estimate. With certain topology and line parameter, factors having effect on state affectois includes power grid load level, measurement redundancy, measurement type, and so on. Individual selective method of triggering threshold is put forward based on state affectois.
Characteristic time section SE is presented, which is based on conventional SE and provides state vectors of characteristic time sections within a period of time. At least, characteristic time sections include extreme time sections and expected time section.
Time process oriented state estimation mode is designed in this dissertation. Dynamic period of time process oriented SE is provided by SE link of CMTM, and it is also the tracking period of tracking SE link of polling type and operating control analysis period of characteristic time section SE link. Through adjustment of parameters, such as triggering threshold, the dynamic period can be a period of a few minutes. Three links are organically connected through the bond of dynamic period.
Test results prove the method presented in this dissertation predominant and feasible. Firstly, SE of CMTM can select dynamic period, according to the changing speed of power grid state. And it can provide accurate initial value for tracking SE of polling type. Secondly, Tracking SE of polling type not only has a great calculation speed in handling a measurement, but also guarantees a good estimation precision, which is very close to that of WLS algorithm. Tracking SE of polling type can track the measurement updating closely. Lastly, Characteristic time section SE can provide the key state information within a time process for dispatch control center, and help to make overall control decision. The three links assume their respective roles and cooperate perfectly. Therefore time process oriented state estimation cannot only achieve intensive monitoring power grid state, but also be the forceful basis of stable-state operating status assessment and decision-making.
随着系统状态的不断变化,状态估计也需要不断地进行计算,从时间过程角度研究它,符合物理现象的本质。本文以改善状态估计在网络状态监测和电网运行控制两方面效用为目的,提出了面向过程的状态估计方法。
借助过程函数的概念,对基于过程的状态估计模型进行了描述。提出了由量测量的变化情况来引导状态估计触发,即每当状态估计器收到的一定比例的发生了较为明显变化的遥测量,或者出现遥信变位,就触发状态估计计算。变化量测触发方式(changed measurement triggering mode , CMTM)是一种智能的触发方式,能够根据网络状态变化的快慢,动态地选取状态估计的触发时刻。polling方式的追踪状态估计是应答式远动支持下的一种非完全处理状态估计,采用能够灵活处理量测量的方法,仅处理被更新量测,追踪求解状态量,属于以少许估计精度损失换取计算速度提升的方法。提出了两种polling方式的追踪状态估计算法——最小二乘递推法逐次追踪状态估计和灵敏度分析法逐次追踪状态估计。最小二乘递推法逐次追踪状态估计,即基于最小二乘递推估计,在每一计算时刻仅处理被更新量测,完成对状态向量的估计。灵敏度分析法逐次追踪状态估计则是在每一计算时刻,利用状态量估值、量测量以及功率估计值之间的灵敏度关系处理被更新量测。
根据状态量与量测量之间的灵敏度关系,提出了状态影响系数的概念,以表示量测量对系统状态量估值影响能力的大小。在网络拓扑和线路参数一定的条件下,影响状态影响系数的因素包括系统负荷水平、量测冗余度、量测类型等。基于状态影响系数,提出了触发阈值的个体选取方法。
提出了过程特征断面状态估计,即借助传统状态估计算法估计出能够表征系统在一个时段上典型运行特征的一组时间断面状态量,可作为全局控制的有效依据。过程特征断面至少包括极端过程特征断面和期望过程特征断面。
设计了过程状态估计模式。过程状态估计的动态周期是由变化量测触发方式状态估计环节提供,同时也作为polling方式追踪估计环节的追踪时段以及过程特征断面估计环节的运行控制分析时段。通过对触发阈值等参数的调整,使动态周期为一个分钟级的时间,以动态周期为纽带,便将三个环节有机的联系起来。
仿真算例表明了本文方法的可行性和优越性。首先,变化量测触发方式的状态估计能够根据网络状态变化的快慢,动态地选取过程状态估计的动态周期,并能够为polling方式的追踪状态估计提供高精度的追踪初值。其次,polling方式的追踪状态估计,处理量测量具有极快的速度,并且在精度上能够保证与WLS算法非常高的一致性,能够紧密追踪量测量的更新。最后,过程特征断面状态估计,能够为调度中心提供全面而关键的电网运行状态信息。三个环节各司其职,使得过程状态估计一方面能够实现高密度高精度的电网状态监测,另一方面能够作为评价系统稳态运行工况和运行控制决策的有力依据。
Accuracy and timeliness of Information provided by state estimation (SE) is very important to safe and economical operation of power grid. The existing period triggering mode state estimation (SE) has its limitations in the two purposes of power grid state monitoring and operating control. On one hand, there is big difference between SE triggering period and supervisory control and data acquisition (SCADA) scanning period. Therefore it is hard for dispatch control center to grasp the intensively operating state varying in power grid operating process. On the other hand, dispatch control center can make control strategies only by the single time section state provided by SE. However, the single time section state cannot reflect the power grid operating status in its entirety in the process. Therefore it is difficult for the control strategies to take account of security and economy.
With the ceaseless change of power grid state, it ought to be triggered ceaselessly for state estimation. Therefore, research based on time process meets the essence of physical phenomenon. Time process oriented state estimation is presented to improve the utility of state estimation in power grid state monitoring and operating control.
With the concept of process function, state estimation model based on time process is described. The mode is put forward in which state estimation is triggered by the variation of measured quantities. That is, state estimation is triggered when the state estimator receives certain proportion of telemetry measurements that changed comparatively obviously, or there is a remote signaling transposed. Changed measurement triggering mode (CMTM) is an intelligent triggering mode.
Tracking SE of polling type is an incomplete-processing SE with polling type telemechanics, which needs algorithms that can handle measurements flexibly. It handles the renewed measurements only and solve state variable by tracking method. It is a method that exchanges a little estimation precision for greater calculation speed. Then two tracking SE algorithms of polling type are put forward, which are recursive least squares method sequential tracking SE algorithm and sensitivity analysis method sequential tracking state estimation algorithm. The former algorithm only handles renewed measurements one by one at every calculation moment based on recursive least squares estimate to renew the state vector. And the latter algorithm handles only the renewed measurements one by one using the relations of sensitivity among state variable, measurements and estimate of power.
Based on the relations of sensitivity between state variable estimate and measurements, the concept of state affectois is presented representing the influence capacity of measurements to state variable estimate. With certain topology and line parameter, factors having effect on state affectois includes power grid load level, measurement redundancy, measurement type, and so on. Individual selective method of triggering threshold is put forward based on state affectois.
Characteristic time section SE is presented, which is based on conventional SE and provides state vectors of characteristic time sections within a period of time. At least, characteristic time sections include extreme time sections and expected time section.
Time process oriented state estimation mode is designed in this dissertation. Dynamic period of time process oriented SE is provided by SE link of CMTM, and it is also the tracking period of tracking SE link of polling type and operating control analysis period of characteristic time section SE link. Through adjustment of parameters, such as triggering threshold, the dynamic period can be a period of a few minutes. Three links are organically connected through the bond of dynamic period.
Test results prove the method presented in this dissertation predominant and feasible. Firstly, SE of CMTM can select dynamic period, according to the changing speed of power grid state. And it can provide accurate initial value for tracking SE of polling type. Secondly, Tracking SE of polling type not only has a great calculation speed in handling a measurement, but also guarantees a good estimation precision, which is very close to that of WLS algorithm. Tracking SE of polling type can track the measurement updating closely. Lastly, Characteristic time section SE can provide the key state information within a time process for dispatch control center, and help to make overall control decision. The three links assume their respective roles and cooperate perfectly. Therefore time process oriented state estimation cannot only achieve intensive monitoring power grid state, but also be the forceful basis of stable-state operating status assessment and decision-making.
引文
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