A General Decoupled Framework for State Estimation Based on Synchrophasor Measurements

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.

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 an analysis of unified systems for traction and battery charging of electric vehicles (EVs), regarding operation modes and implementation cost, when compared to dedicated systems that perform the same functionalities. Concerning the interface of the EV battery charging system with the power grid, four operation modes are analyzed: (1) grid-to-vehicle (G2V); (2) vehicle-to-grid (V2G); (3) vehicle-to-home (V2H); and (4) vehicle-for-grid (V4G), which, by using a unified system for traction and battery charging, can be linked both to single-phase and three-phase power grids. Moreover, a cost estimation is performed for EV unified systems and for dedicated systems that can perform the same functionalities when connected to the power grid, in order to prove the advantages of the system unification. The cost estimation is based on two power levels, namely 6 kW (single-phase), related to domestic installations and slow battery charging, and 50 kW (three-phase), related to industrial installations and fast battery charging. The relevance of unified systems for traction and battery charging of EVs is proven for single-phase and three-phase power grids both in terms of operationality and implementation cost.

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.

Robust state estimation and real-time dense mapping are two core capabilities for autonomous navigation of mobile robots. Global Navigation Satellite System (GNSS) and visual odometry/SLAM are popular methods for state estimation. However, when working between tall buildings or in indoor environments, GNSS fails due to limited sky view or obstruction from buildings. Visual odometry/SLAM are prone to long-term drifting in the absence of reliable loop closure detection. A state estimation method with global-consistent guarantee is desirable for navigation applications. As for realtime mapping, SLAM methods usually get a sparse map that is not good enough for obstacle avoidance and path-planning, and high-quality dense mapping is often computationally too demanding for mobile devices. Realizing the availability of city-scale 3D models, in this work, we improve our previous work on model-based global localization, and propose a modelaided monocular visual-inertial state estimation and dense mapping solution. We first develop a global-consistent state estimator by fusing visual-inertial odometry with the modelbased localization results. Utilizing depth prior from the model, we perform motion stereo with semi-global disparity smoothing. Our dense mapping pipeline is capable of online detection of obstacles that are originally not included in the offline 3D model. Our method runs onboard an embedded computer in real-time. We validate both the state estimation and mapping accuracy in real-world experiments.

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.

A generalized framework for improved state estimation in three-phase power grids

This paper aims to assess the performance of linear state estimation (SE) processes of power systems relying on synchrophasor measurements. The performance assessment is conducted with respect to two different families of SE algorithms, i.e., static ones represented by weighted least squares (WLS) and recursive ones represented by Kalman filter (KF). To this end, this paper firstly recalls the analytical formulation of linearWLS state estimator (LWLS-SE) and Discrete KF state estimator (DKF-SE). We formally quantify the differences in the performance of the two algorithms. The validation of this result, together with the comprehensive performance evaluation of the considered state estimators, is carried out using two case studies, representing distribution (IEEE 123-bus test feeder) and transmission (IEEE 39-bus test system) networks. As a further contribution, this paper validates the correctness of the most common process model adopted in DKF-SE of power systems.

Decoupled State-Estimation in Energy Control Centres

Phasor measurement units provide synchrophasor measurements that are more accurate and have a higher refresh rate than the conventional measurements obtained via remote terminal units. Estimating the state of a system after each update of synchrophasor data can allow for tracking dynamic behaviour of the system. However, the issue of partial system observability by synchrophasors needs to be overcome. In this paper, three fully linear weighted least square-based state estimation algorithms are proposed to address the mismatch between refresh rates of synchrophasor and conventional measurements. State estimates are provided at time instances when both types of measurements are refreshed, as well as when only a new set of synchrophasors arrives. Simulations are performed on a number of test systems of different sizes to evaluate and compare performance of the proposed algorithms.

State estimation is often a challenging task in distribution systems due to deploying a limited number of measurement devices. Moreover, the integration of precise distribution-level phasor measurement unites, a.k.a micro-PMUs, along with inaccurate pseudo-measurements in state estimation introduces another challenge. These issues might decrease the efficiency of traditional standard weighted least squares (WLS) for distribution system state estimation. This paper proposes a novel linear distribution system state estimation based on limited number of synchrophasor measurements and pseudo-measurements. To involve pseudo-measurements into the linear state estimation, Taylor's approximation is adopted to reformulate pseudo-measurement functions in a linear form. The results obtained via numerical simulations demonstrate that the proposed linear state estimation method performs as good as the standard nonlinear WLS estimator. Moreover, the sensitivity analyses results show that our method has a better performance compared to WLS once a limited number of highly precise micro-PMUs are accompanied with inaccurate pseudo-measurements in state estimation.

This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator and the generation of solutions using a Gaussian normal distribution based on the exploration and exploitation schemes of the vortex search algorithm. The master stage is entrusted with determining the configuration of the phases by using an integer codification. In the slave stage, a power flow for imbalanced distribution grids based on the three-phase version of the successive approximation method was used to determine the costs of daily energy losses. The objective of the optimization model is to minimize the annual operative costs of the network by considering the daily active and reactive power curves. Numerical results from a modified version of the IEEE 37-node test feeder demonstrate that it is possible to reduce the annual operative costs of the network by approximately 20% by using optimal load balancing. In addition, numerical results demonstrated that the improved version of the CBGA is at least three times faster than the classical CBGA, this was obtained in the peak load case for a test feeder composed of 15 nodes; also, the improved version of the CBGA was nineteen times faster than the vortex search algorithm. Other comparisons with the sine–cosine algorithm and the black hole optimizer confirmed the efficiency of the proposed optimization method regarding running time and objective function values.

The typical starting current for an asynchronous three-phase electric motor is in the range of five to ten times the rated current. To mitigate problems caused by this high current, various methods to start this type of motor exist. As an alternative method for starting up induction motors, a new starting current limitation method is proposed, which is based on using commercially available high-temperature superconductor tape. A prototype of the superconducting starting current limiter was constructed and tested with a 55-kW industrial induction motor, in a 440-V/60-Hz three-phase power grid. As the total starting time can be longer than the time the superconductor tape can support a high current, a shunt reactor receives the starting current after 80 ms to avoid damage to the tape. Performance evaluations of the superconducting limiter method were performed and were compared with a direct-on-line starter and an electronic soft starter. In addition to limiting the starting current, our method offers reduced current waveform distortion and lower harmonic pollution during startup.

The main problems of stray current and the low availability of the regenerative braking energy widely exist in DC traction power supply system which is currently widely used in China. The AC traction power supply system for Urban Rail Transit based on negative sequence current compensator is proposed as a kind of novel power supply scheme to solve these problems in DC system. And the construction of the AC traction power supply system is designed in detail. In the meantime, the system of negative sequence compensator based on three - phase three - level rectifier parallel is designed to compensate for the negative sequence generated by the proposed system in the paper. The negative sequence current compensation algorithm of the AC traction power supply system and the control method of the negative sequence current compensator are deeply analyzed and designed, and the proposed system is feasible to connect with three-phase power grid. Meanwhile, the equalization of the AC traction power supply system was also achieved. Finally, the performance of the power electronic compensator to eliminate the negative sequence current was verified by simulations and experiments.