In this paper, we proposed to evaluate the optimal phasor measurement unit (PMU) placement based on sum of variance (SV) robust estimators. Variance is traditionally used as a measure quality estimates. after satisfying requirements minimum number PMUs, maximum redundancy, and observability, placements obtained are further distinguished basis estimated states. Both weighted least squares (WLS) estimators considered. Examples IEEE 30-bus system using absolute value (LAV) estimation given. The...

Integer linear programming (ILP) has been widely applied to solve the optimal phasor measurement unit (PMU) placement (OPP) problem for its computational efficiency. Using ILP, a with minimum number of Phasor Measurement Units (PMUs) and maximum redundancy can be obtained while ensuring system observability. Author response: please delete this above sentence. However, existing ILP-based OPP methods does not guarantee full coverage solutions optimization problem, which may sequentially...

Phasor Measurement Units have been applied on power system to improve the performance of state estimator for decades. As it is not practical install one PMU at every bus in a due its high cost, plenty research focus solving optimal placement (OPP) problem which determine with minimum number PMUs while ensuring network's observability. Since are mostly employed within transmission networks, most OPP algorithms also designed networks. In recent years, distribution networks evolving from...

In this paper, we propose an optimal robust state estimator using maximum likelihood optimization with the t-distribution noise model. statistics literature, is used to model Gaussian and non-Gaussian statistics. The influence function, analytical tool in statistics, employed obtain solution resulting estimation problem, so that proposed can be implemented within framework of traditional estimators. Numerical results obtained from simulations IEEE 14-bus system, 118-bus experiment on a...

In practical power system applications, the distribution of measurement noise is sometimes unknown and deviates from assumed Gaussian model due to outliers. such cases, performances state estimators based on assumption may deteriorate significantly. this article, we propose a fully distributed robust estimation approach t-distribution maximum likelihood criterion. The used non-Gaussian statistics in field statistics. matrix-splitting techniques are employed carry out extensive matrix...

Even though the noise model applied in power system dynamic state estimation is usually assumed to be Gaussian, this not case due unknown inputs, influence from communication channel and outliers generated by phasor measurement units (PMUs). In paper a robust (DSE) method combining exponential absolute value based estimator unscented Kalman filter together proposed under non-Gaussian noise. Based on quadratic function function, derived, further mitigating effects of bad data or outliers. The...

The distribution of measurement noise applied in practical power system state estimation (PSSE) can deviate from the assumed Gaussian model, and performance an estimator becomes bad if model is still used. This article proposes a new distributed robust PSSE method for multiarea systems. non-Gaussian utilized to fit reach high accuracy. proposed derived based on maximum correntropy criterion further reduce impact outliers. influence function combined with finite-time average consensus...

Phasor Measurement Unit (PMU) has been applied on power system to improve the performance of state estimator for decades. It is anticipated that PMUs will observe distribution networks in future considering contribution transmission networks. The advent micro phasor measurement unit (μPMU) makes it possible employ devices Optimal PMU Placement (OPP) problem determine a minimal set such whole observable. Since are mostly employed within networks, most OPP algorithms also designed However,...

The distribution of measurement noise is commonly considered as an assumed Gaussian model in power systems, but this assumption not always true reality. This article introduces a distributed maximum-likelihood-based state estimation approach for multiarea systems using the student's t-distribution model. has property "thick tail" to better occurrence outliers and fairly flexible different statistics. finite-time average consensus algorithm utilized conjunction with influence function realize...

In realistic power system state estimation, the distribution of measurement noise is usually assumed to be Gaussian while many researcher have verified that it can non-Gaussian. this paper, a new robust estimator based on exponential absolute value function proposed address non-Gaussian and outliers. The influence function, statistics tool, used obtain estimates reduce its computational burden. A estimation mean squared error formula derived which as reference in wide area monitoring design...

In this paper, a distributed state estimation method based on moving horizon (MHE) is proposed for the large-scale power system estimation. The partitions systems into several local areas with non-overlapping states. Unlike centralized approach where all measurements are sent to processing center, distributes task centers collected. Inspired by partitioned (PMHE) algorithm, each area solves smaller optimization problem estimate its own states using and estimated results from neighboring...

A multi energy system with different types of carriers coupled together needs to improve utilization efficiency. This article proposes a demand response model that is able cover the unique characteristics heat in domestic heating scenario, and then, conventional price-based electricity load, forms comprehensive load for microgrid. In addition, influence relevant parameters on operation economy stability microgrid studied.

Abstract For state estimation (SE) of dynamic electro-thermal gas coupled systems, measurements usually assume that the measurement noise obeys a Gaussian distribution. The extended Kalman filter and unscented (UKF) are some widely used methods in SE. However, does not always follow distribution practice. When is non-Gaussian, performance these may be satisfactory. In this paper, we propose an filtering method based on minimizing radial basis kernel function criterion (MRBFC-UKF), which...