A blocked sparse matrix formulation for the solution of equality-constrained state estimation

Decoupled State-Estimation in Energy Control Centres

Observability analysis for state estimation using Hachtel’s augmented matrix method

This paper describes the implementation, testing, and performance of phasor measurements in an industrial state estimation at the New York Power Authority (NYPA). Phasor Measurement Units (PMU) with GPS synchronization were incorporated into the data acquisition subsystem of the Energy Management System (EMS). The modified State Estimator was subjected to pre- and post-field installation testing. The pre-field installation testing was done to verify the correctness of the solution algorithm, to identify the impact of phasor metering accuracy on the quality of estimator solution, to show the relative effectiveness of phasor measurements with respect to other measurements, to identify the effect of the reference bus selection, to detect the impact of PMUs on the State Estimator convergence, and to establish the minimum clock synchronization sampling accuracy required for the PMUs [10]. The post-field installation tests were conducted to identify the effectiveness of the PMUs in the State Estimator solution using the real-time data as well as to detect the effect of time skewing and measurement weights on the State Estimator solution.

This paper presents a review on major blackouts occurred in power grid across the world and importance for the need of state estimation (SE) solution. This work introduces the applications of phasor measurement units (PMU) to reduce the occurrence of blackouts in power system. The blackouts in power system can occur due to overload, light load conditions, heavy storms or due to line outages. The cascade failure due to line outages, i.e., measured as N-1 outages can lead to power system blackout. The necessity of power system state estimation (PSSE) solution for protection in view of blackouts is discussed in this paper. A Generalized Linear State Estimation (GLSE) method is proposed to obtain robust and accurate states of power system network. A matrix integrating phasor and conventional measurements are formulated to obtain accurate states. IEEE transmission bus network such as 14-bus network is considered as test case for proposed GLSE programming in MATLAB. The accurate states are computed and compared with standard weighted least squares (WLS) method to show its effectiveness.

While various industries heavily rely on electrochemical sensors for air and liquid quality monitoring and control, many electrochemical sensors are cross-sensitive to one or more interfering gases in addition to the target component, which may cause incorrect readings and lead to improper control measures. In this study, we proposed a direct algebraic approach-based state estimation and output decomposition algorithm which is suitable for state estimation for a class of nonlinear dynamic systems with output measurements that are highly cross-sensitive to multiple interfering gases. Using the cross-sensitive sensor measurement and its successive time derivatives, the proposed methodology can provide a closed-form solution for the actual system state estimation in a systematic way. The established state estimation algorithm was successfully validated in a numeric example. The proposed state estimation and output decomposition algorithm is applicable to a broad class of nonlinear dynamic systems which use sensors that are cross-sensitive to multiple interfering gases in order to improve the performance of the systems.

In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs) in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB) are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

Operation engineers at EMS control center are very interested in the potential use of State Estimation (SE) technologies for identifying parameter and model errors, especially when encountering the scenario of an invalid SE solution or an SE solution with non-trivial residuals. Some network parameter and model errors, like an incorrect transformer tap or an analog measurement with flipped sign, can be identified early using relatively simple pre-processing approaches. But other errors may be detectable only after running SE solutions in real-time operation. This paper will share our experience in working with operation engineers to deal with these SE issues.

Involutory transformations and variational principles with multi-varoables in thin plate bending problems

According to principle of model reference adaptation, a model reference fault diagnosis approach for on-orbit satellite attitude control system was proposed based on measurement and calculation of environmental torques acted on satellite. With satellite kinematics and attitude dynamics, a linear model for satellite attitude control system is established. On the basis of system parameter and structural characteristics, satellite attitude control system reference model modified by measurement and calculation of environmental torques is built. With fault residual vector generated by comparing output of reference model with real system, sensor fault detection and isolation is accomplished. Extended state observer is designed to estimate system disturbance using augmented matrix method. According to disturbance estimation and environment torque calculation, actuator fault residual vector is obtained to detect and isolate actuator fault. The simulation experiment result demonstrates that the proposed approach is effective and efficient for real-time fault diagnosis of on-orbit satellite attitude control system.

Motivated by some landslide models, and related estimation challenges, this paper presents an optimal estimation method for state and parameter in a special class of so-called ODE–PDE system based on the adjoint method for discrete-time asynchronous measurements. This system is described by a pair of coupled Ordinary Differential Equation (ODE) and Partial Differential Equation (PDE), with a mixed boundary condition for the PDE. The coupling appears both in the ODE and in the Neuman boundary condition of the PDE. For this system, initial conditions or state variables and some empirical parameters are assumed to be unknown and need to be estimated. The Lagrangian multiplier method is used to connect the dynamics of the system and the cost function defined as the least square error between the simulation values and the available measurements. The adjoint state method is applied to the objective functional to get the adjoint system and the gradients with respect to parameters and initial state. The cost functional is optimised, employing the steepest descent method to estimate parameters and initial state. This general approach is illustrated by two application examples corresponding to two different landslide models that validate the presented optimal estimation approach. The first one is about state and parameter estimation in an extended sliding-consolidation landslide model, and the second one is in the viscoplastic sliding-consolidation landslide model.

In this paper we execute the solution procedure for second order linear fuzzy difference equation by Lagrange's multiplier method. In crisp sense the difference equation are easy to solve, but when we take in fuzzy sense it forms a system of difference equation which is not so easy to solve. By the help of Lagrange's multiplier we can solved it easily. The results are illustrated by two different numerical examples and followed by two applications.

This paper is about the problem of optimization of bracing columns--height of the parallel chords, cross-sectional areas of the chord and bracing and area moments of inertia of the chord and bracing. Optimization parameters have been determined by Lagrange's multipliers method--inequality constraint functions. Total mass of the construction has been selected as the objective function. Criterions of buckling (general buckling of the bracing column, local buckling of the chord and local buckling of the bracing diagonal) and criterion of deformation are used as the constraint functions. Numerical examples are performed by usage of the obtained theoretical solutions.

Asymptotic bounded consensus tracking of multi-agent systems with a bounded-acceleration target via sampled-data control

The AC-DC hybrid microgrid is a credible evolution path for the microgrid. State estimation in complex distribution network is a significant foundation for the safe operation. In AC-DC hybrid microgrid, centralised state estimation algorithms have quite a few deficiencies such as large communication capacity and privacy protection. In response to these obstacles, this paper proposed a novel distributed state estimation algorithm. First, a three-stage state estimation model was established for AC-DC hybrid microgrid, in which the second stage is a nonlinear transform for the linearisation of the nonlinear state estimation progress so that the first and third stage can solve the linear state estimation problem. Furthermore, the Lagrangian relaxation method was ultilised for the distributed problem solution. In the proposed algorithm, AC subsystems and DC subsystems respectively execute state estimation through local information, and the overall consistency of the system state estimation can be eventually achieved according to the transfer iteration of the boundary information. The computational efficiency and convergence of the proposed method was ensured owing to the combination of bilinear theory and Lagrangian relaxation. Simulation results indicate that the proposed method can achieve its goal and be superior to existing method in efficiency.

Guest Editorial: Situational awareness of integrated energy systems