Power System Parameter Estimation

In order to achieve security, economic dispatching and analysis, power system advanced application software plays an important role as the improvement of the level of power system automation. The correctness of network parameters and the network topology is the foundation of power system advanced applications software. The parameters of power grid components are mainly obtained by calculating based on nameplate data in power system calculation. Even though the parameters are measured, some test parameters there may be more errors for the defect of testing principle or human negligence. Parameter errors lead to the calculation results do not fit the facts, so influence the correctness of decision-making. We need to estimate the parameters according to a certain algorithm and implement it by programming.There are two kinds of methods in power system parameters estimation: one is broaden state estimation which put the parameters as state variable and mainly include normal equation estimation and Kalman filter estimation. The other method is the measurement residual sensitivity analysis which estimates the parameters using the sensitivity relation between measurement residuals and parameter errors after the end of the state estimation. This paper describes the weighted least squares with equality constraints broaden the state estimation in detail and implements it using C programming language.The memory storing dada in the computer calculation will rapidly increase when the number of buses increases. So we adopt sparse matrix for storing datas. State estimation is the basis of broaden state estimation, so we describe the basic principles of state estimation firstly, then detailed introduce programming processes and the instruction for using parameter estimation program, lastly we take four nodes netwsork and Jinzhong power network as examples for calculation.Calculation results indicated that broaden state estimation has a good performance in the ring network, but it is not as good as in the radial branch.