In order to manage the power grid appropriately and to prevent widespread blackout, independent system operator always looks for monitoring the variables of power’s system such as active and reactive power passing through transmission lines, consumption and production power of system at different nodes, and voltage level momentarily. To this end, measurement installed at different points of network to measure network’s variables. then data is transferred to system’s operator through different communication platforms. Due to errors in measurement instruments and the probability of data change in telecommunication platforms, independent system operator should compute a proper estimate of state variables using collected data. Concerning the complexity power network, defect in collected data and cyber-attacks which power systems are faced with them currently. it is needed to review some of the power system processes such as state estimation which is threatened by these potential dangers. With the aim of reducing calculation’s volume in the process of state estimation and reducing the process dependence to measurement’s noise, manipulated measurement data, and unreached data, a method of dynamic state estimation was presented in this thesis. Dynamic state estimation consists of two general procedures namely prediction and filtering. In this investigation, prediction procedure was performed with regard to great dependence of angle state variable to active power, great dependence of voltage amount state variable to reactive power and the impressionability of state variables of each node from variables of previous moments of the same node and the connected nodes. In filtering procedure, in order to increase speed and decrease calculation’s volume in estimating process, network nodes were divided into three groups based on the amount of power that passes through the nodes, connection with other nodes and accessibility of data. The first group are those nodes whose data do not reach to system operator for state estimation on time due to defect of telecommunication system or cyber-attacks. The second group are normal nodes of the network which are not of great importance. The third group are especial nodes which are important. For estimating state variables of the first, second and third group of nodes, last estimated state, static state estimation, and dynamic state estimation are used respectively. At the end, the proposed method is applied on IEEE 14-bus test system. Normalized data of New York independent system operator in two consequent days, 21st and 22nd of March, 2016, is used as estimating data of previous moments and IEEE standard data is used as accurate and noise-free data of estimation moment. In order to approach the real conditions in each experiment, 1000 various noise with specific variances are added to accurate data and they are used as measured data in estimation moment. In the proposed method, the effect of increase in measurement’s noise, unreached data, selecting different combinations of buses as important buses, and effect of manipulated measurement data in buses and lines are investigated. in this research two indexes including the operation of relative error of state variables and relative error of measured amounts are used to assess the performance of the proposed estimation method. The simulation results show that the proposed estimation method is robust against the increase in noise of measurements, manipulated measurement data, and unreached data. Also the method can reach to appropriate estimate of state variables. |
