Medium-Voltage And Low-Voltage Integrated Distribution Network State Estimation And Application

ADO(Advanced Distribution Operation)is one of the main components of smart grid. It requires that the power grid should have flexible and reconfigurable distribution network topology and the ability of monitoring and analysis of the real-time state. To realize these functions, state estimation must be conducted to provide data supporting. With the expansion of the power system scale, power industry management system moving to the market continually, people have higher requirements of distribution state estimation accuracy and real-time data processing capability. In recent years, a variety of new theories and new technologies for distribution network appear constantly, making a more accurate estimates of the network running status.Advanced Metering Infrastructure(AMI) is an important foundation for the smart grid. Through the fundamental equipment of AMI, i.e. smart meters, utilities can get power consumers’ historical or near real-time various types of measurements, which enriches the measurement provision for the distribution network. These can effectively overcome the unobservability problem existing in a large number of distribution feeders and branches, due to lack of measurement devices or communication capability. The smart meter interval measurements collected by AMI could be applied to the distribution state estimation resulting in more accurate and comprehensive estimation of distribution network operating state and thus providing more reliable data supports for other high level applications.To begin with, for the asymmetric line and unbalanced load characteristics of the three-phase distribution network, the detailed mathematical models of three-phase components in distribution network is described in this paper. Taking the real and imaginary parts of node voltages as state variables, the Jacobian matrix of node power injection measurements, node voltage amplitude measurements, branch current amplitude measurements and branch power measurements is deduced. Based on OpenDSS, three-phase distribution network state estimation algorithm is established.Through the various measurements collected by smart meters of AMI, in middle-voltage distribution network, the AMI-based pseudo-measurement method for transformer load in distribution state estimation is proposed, which improves the accuracy of the state estimation. Furthermore, by using the multiple measurements of consumer smart meters, this paper also realizes the state estimation for the low-voltage distribution network. The effectiveness of the proposed method is illustrated by applications on system example.At last, this paper puts forward an AMI-Based medium-voltage and low-voltage mixed distribution state estimation method, which can comprehensively use variety of measurements information including SACDA measurements and smart meters measurements. It can avoid using the pseudo-measurement which has large errors when lack of transformer nodes’ load measurements or communication capability and the transformer node is no longer considered “assuming power source” when low-voltage distribution state estimation is conducted. Based on medium-voltage and low-voltage mixed distribution state estimation, methods of processing delayed measurements and energy theft detection are discussed and examples demonstrate the effectiveness.