Practical and efficient state estimation is essential for the safe and stable operation of future smart grid. In rectangular coordinates, distribution system state estimation (DSSE) problem can be described as a sparse quadratic constraint quadratic estimation (QCQE) model, which enhances efficiency of the program implementation for DSSE. However, the scarcity of measurements in distribution network brings a formidable challenge to provide reasonably meaningful estimation of the distribution system state. This paper is concerned about application of QCQE in under-determined distribution network. Observability analysis technique is proposed by considering the characteristics of actual distribution network. The observable islands are recognized accordingly, and then unobservable areas can be accurately defined. Pseudo-measurements are adopted to meet the observability requirement. Simulation on IEEE 33-bus shows effectiveness of the proposed method.
Even with modern smart metering systems, erroneous measurements of the real and reactive power in the power system are unavoidable. Multiple erroneous parameters and measurements may occur simultaneously in the state estimation of a bulk power system. This paper proposes a gross error reduction index (GERI)-based method as an additional module for existing state estimators in order to identify multiple erroneous parameters and measurements simultaneously. The measurements are acquired from a supervisory control and data acquisition system and mainly include voltage amplitudes, branch current amplitudes, active power flow, and reactive power flow. This method uses a structure consisting of nested two loops. First, gross errors and the GERI indexes are calculated in the inner loop. Second, the GERI indexes are compared and the maximum GERI in each inner loop is associated with the most suspicious parameter or measurement. Third, when the maximum GERI is less than a given threshold in the outer loop, its corresponding erroneous parameter or measurement is identified. Multiple measurement scans are also adopted in order to increase the redundancy of measurements and the observability of parameters. It should be noted that the proposed algorithm can be directly integrated into the Weighted Least Square estimator. Furthermore, using a faster simplified calculation technique with Givens rotations reduces the required computer memory and increases the computation speed. This method has been demonstrated in the IEEE 14-bus test system and several matpower cases. Due to its outstanding practical performance, it is now used at six provincial power control centers in the Eastern Grid of China.
To adapt to the distribution network unobservable problem from the scarcity of real-time measurements, the distribution system state estimation (DSSE) method based on hybrid measurements of the supervisory control and data acquisition (SCADA) and the advanced metering infrastructure (AMI) is proposed. Firstly, the ratio of energy data from AMI is used to construct pseudo-measurements, which satisfies the observability of DSSE. Secondly, multiple SCADA acquisition snapshots joint state estimation model is constructed by the SCADA measurements and the energy data of AMI with multiple snapshots. In a rectangular coordinate system, the joint state estimation model and the weighted least squares (WLS) method are described in quadratic polynomial form, leading to a quadratic constraint quadratic estimation (QCQE) model. The QCQE model can decouple the modeling and algorithm implementation of state estimation and enhance the efficiency of algorithm implementation significantly. Otherwise, more state estimation mature algorithms can be adopted for the joint state estimation model in quadratic polynomial form. Simulations on the IEEE 33-bus system verify the accuracy and effectiveness of the proposed method.
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