The proper analysis and successful operation of a power system implies a reliable estimate of its state. As a result state estimation (SE) is nowadays considered as the heart of modern control centers. Several dynamic state estimation algorithms based on the extended Kalman filtering theory (EKF) have been proposed in the literature but, as has been reported, numerical problems may arise in its implementation in practice. To circumvent the problems inherent to the Kalman filter algorithm the authors present in this paper an algorithm for power system state estimation based on the square root filtering technique. The estimator proposed is decoupled in nature due to modifications made in the measurement equations resulting in a new observation model. >

A square root filter algorithm for dynamic state estimation of electric power systems

The world-wide application of Phasor Measurement Units (PMUs) brings great benefit to power system state estimation. The synchronised measurements from PMUs can increase estimation accuracy, synchronise states among different systems, and provide greater applicability of state estimation in the transient condition. However, the integration of synchronised measurements with state estimation can introduce efficiency problems due to the substantial burden of data. 

The research is divided into two parts: finding a solution to cope with the computational efficiency problem and developing a transient state estimation algorithm based on synchronised measurements from PMUs.

The computational efficiency problems constitute important considerations in the operation of state estimation. To improve the low computational efficiency, two distributed algorithms are proposed in Chapters 4 and 5. In these two algorithms, the modelling, structure, and solution are described, and the corresponding procedures of bad data processing are presented. Numerical results on the IEEE 30-bus, 118-bus and 300-bus systems can verify the effectiveness of the two proposed algorithms.

A novel transient state estimation algorithm based on synchronised measurements is proposed in Chapter 6. Considering the scanning cycle and sampling rate of PMU measurements, the proposed algorithm can estimate transient states in a practical way. The performance of the proposed algorithm is demonstrated in a transient simulation on the IEEE 14-bus system.

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Distributed state estimation with the measurements of Phasor Measurement Units

Nowadays the fast-decoupled state estimation (FDSE) is widely used in almost every power system control centre. FDSE is effective and efficient for most transmission systems but it may not converge for systems with a large ratio of branch resistance to reactance (R/X); meanwhile the branch current magnitude measurements (BCMMs) cannot be reliably used in FDSE, thereby limiting its applications especially for the distribution systems where BCMMs abound. In this study, the above two problems have been addressed by transforming all measurements so that they can be classified as quasi-real power measurements and quasi-reactive power measurements, leading to a generalised FDSE (GFDSE) with a solid theoretical foundation. The formulation of GFDSE is based on only the assumption, rather than three assumptions used in FDSE. As a result, GFDSE has good adaptability to transmission systems as well as distribution systems; additionally, BCMMs can be reliably used in GFDSE. Case studies based on IEEE benchmark systems and a real grid of China demonstrate that the proposed GFDSE has very good convergence properties for transmission systems and distribution systems; and at the same time, the proposed GFDSE is also superior to FDSE in terms of computational efficiency under almost all cases.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2018.5076

Generalised-fast decoupled state estimator

Efficient Treatment of Parameter Errors in Power System State Estimation

From power system on-line operation and security control view point, state estimation, a methodology used to obtain reliable estimate of power system state, has become one of the important issues. Among some state estimation methods, the fast-decoupled state estimator is commonly used as a prevailed method and has been implemented by many utilities. However, it has been recognized that its convergence characteristics may become deteriorated when it encounters bad system conditions. Therefore, in this paper, first of all, we present the fast-decoupled state estimator which is used in present power systems. Next, we propose a method to improve the convergence characteristics of fast-decoupled state estimator (in rectangular coordinates) using the optimal multiplier μ, followed by a reliable technique to detect bad data. The proposed method has been tested on several types of load flow test systems and successful results have been obtained.

Convergence Improvement and Bad Data Detection for Fast Rectangular Coordinates State Estimator

The paper presents two different state estimation decoupling techniques using node voltages in rectangular co-ordinates: the exact-decoupled technique and the modified fast-decoupled technique. The proposed techniques decouple the Jacobian matrix into real- and reactive-power submatrices, which are evaluated only once at the beginning of the process. The paper also presents efficient data structure management algorithms to improve the computational process required in calculating the nonzero elements of the Jacobian matrix, and the elements of the mismatching vector, which are essential to any state estimation problem. The performance of these techniques and algorithms are evaluated using several power system networks.

http://ieeexplore.ieee.org/iel1/2205/3046/00092952.pdf

V.H. Quintana

Papers

Fast-decoupled rectangular co-ordinate state estimation with efficient data structure management