电力系统最小信息损失状态估计的信息学原理

状态估计作为能量管理系统(EMS)和实时电力市场的基础和核心，正在变得日益重要。该文从信息科学的新视角，对电力系统状态估计的数学基础进行了研究。根据最小信息损失(MIL)决策原理，提出了能够适用于各种概率分布的通用的MIL状态估计新原理。并在理论上证明了加权最小二乘(WLS)和加权最小绝对值(WLAV)估计法都是MIL状态估计的特例，将传统状态估计方法在信息学的意义上统一起来，赋予了传统状态估计方法全新的信息学内涵。在MIL意义上，针对次输电系统和配电系统状态估计中普遍采用的电流幅值量测，得到了大电流是WLS估计法的近似条件。用算例比较了MIL和WLS状态估计的估计结果，进一步验证了WLS法在非正态分布时的近似条件。

INFORMATION PRINCIPLE FOR STATE ESTIMATION IN POWER SYSTEMS BASED ON MINIMUM INFORMATION LOSS

Researches on mathematic foundation of power system state estimation is done from the viewpoint of information theory. A novel and general principle of minimum information loss (MIL) for state estimation is presented to fit for various probability density distribution of measurement. The inner relationship between the MIL and traditional state estimation method is studied. It is proved theoretically that the traditional weighted least square (WLS) and weighted least absolute value (WLAV) state estimation methods are both the special cases of the proposed MIL based state estimation. And then these traditional state estimation methods are endowed with the connotation of information science. A research on how a current magnitude measurement is available in WLS state estimation for sub-transmission system and distribution system has been done and the result shows that a large enough current magnitude is a necessary condition for a WLS state estimation effective.. Comparison between the proposed MIL method and the traditional WLS method is carried out by several numerical tests, and the approximate condition of WLS state estimation method under non-Gaussian distribution is verified.