CAJ | 학술논문

针对当前抗差状态估计存在的缺点,提出一种基于自适应核密度估计的电力系统抗差状态估计新算法.首先建立基于自适应核密度估计理论的电力系统状态估计新模型;进而提出该新模型核密度函数宽度的确定方法.为确定该新模型的自适应核密度带宽,基于概率密度估计的均方误差公式,结合电力系统状态各分量具有与局部量测强相关性的特点,即系统状态变量各分量与其直接量测的相关性明显强于所有非直接量测,推导新模型的状态变量分量的近似最优核带宽表达式;基于保证量测数据的冗余度、系统的可观性,及消除残差污染和残差淹没所导致的不良数据的漏辨识或正常数据的误辨识,提出新模型状态变量分量核密度带宽的约束条件,包括初始约束条件、修正约束条件及量测标准差约束条件;进而给出基于近似最优核密度带宽表达式及所有约束条件的核密度带宽综合确定方法.实际系统的应用表明:所建立的状态估计新模型,所推导的近似最优核函数带宽表达式,所提出的核密度带宽约束条件及核密度带宽综合确定方法是有效的.
침대당전항차상태고계존재적결점,제출일충기우자괄응핵밀도고계적전력계통항차상태고계신산법.수선건립기우자괄응핵밀도고계이론적전력계통상태고계신모형;진이제출해신모형핵밀도함수관도적학정방법.위학정해신모형적자괄응핵밀도대관,기우개솔밀도고계적균방오차공식,결합전력계통상태각분량구유여국부량측강상관성적특점,즉계통상태변량각분량여기직접량측적상관성명현강우소유비직접량측,추도신모형적상태변량분량적근사최우핵대관표체식;기우보증량측수거적용여도、계통적가관성,급소제잔차오염화잔차엄몰소도치적불량수거적루변식혹정상수거적오변식,제출신모형상태변량분량핵밀도대관적약속조건,포괄초시약속조건、수정약속조건급량측표준차약속조건;진이급출기우근사최우핵밀도대관표체식급소유약속조건적핵밀도대관종합학정방법.실제계통적응용표명:소건립적상태고계신모형,소추도적근사최우핵함수대관표체식,소제출적핵밀도대관약속조건급핵밀도대관종합학정방법시유효적.
To focus on the drawbacks of existing robust state estimation methods and algorithms, a novel robust state estimation algorithm based on adaptive kernel density estimation was hereby proposed. The new robust state estimation model based on adaptive kernel density estimation theory was firstly presented. In order to determine the bandwidth of adaptive kernel density, the approximative expression of optimal kernel bandwidths is deduced using mean integral square error of probability density estimation, and the characteristic of the state variable components having stronger correlation with the local direct measurements than with all un-direct measurements; and the constraints of kernel bandwidths for state variable components, including initial constraint, modified constraint and standard deviation constraint, are further designed, for insuring measurement redundancy and system observability and overcoming the issue of misidentification and unidentification of bad data; based on the above expression and constraints, the composite determination method of kernel bandwidths is finally made. Successful application of practice power system of the algorithm illustrate that: the new state estimation model, the expression of approximative optimal kernel bandwidths, constraints of kernel bandwidths and its composite determination method are all effective and reasonable.