Practical state estimation model and algorithm based on kernel density theory

2022 ◽  
Vol 134 ◽  
pp. 107442
Author(s):  
Jikeng Lin ◽  
Chunqi Yang ◽  
Yangsheng Liu ◽  
Shanshan Luo ◽  
Lingfeng Wang
Keyword(s):  
State Estimation ◽  
Kernel Density ◽  
Estimation Model

scholarly journals Author Correction: An extended Weight Kernel Density Estimation model forecasts COVID-19 onset risk and identifies spatiotemporal variations of lockdown effects in China

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Wenzhong Shi ◽  
Chengzhuo Tong ◽  
Anshu Zhang ◽  
Bin Wang ◽  
Zhicheng Shi ◽  
...  
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Spatiotemporal Variations ◽  
Estimation Model

A Correction to this paper has been published: https://doi.org/10.1038/s42003-021-01924-6

scholarly journals Distributed State Estimation of Multi-region Power System based on Consensus Theory

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 900 ◽  
Author(s):  
Shiwei Xia ◽  
Qian Zhang ◽  
Jiangping Jing ◽  
Zhaohao Ding ◽  
Jing Yu ◽  
...  
Keyword(s):  
Power Systems ◽  
Power System ◽  
State Estimation ◽  
Solution Method ◽  
The State ◽  
Rapid Expansion ◽  
Estimation Model ◽  
Consensus Theory ◽  
Distributed State Estimation ◽  
Bus System

Effective state estimation is critical to the security operation of power systems. With the rapid expansion of interconnected power grids, there are limitations of conventional centralized state estimation methods in terms of heavy and unbalanced communication and computation burdens for the control center. To address these limitations, this paper presents a multi-area state estimation model and afterwards proposes a consensus theory based distributed state estimation solution method. Firstly, considering the nonlinearity of state estimation, the original power system is divided into several non-overlapped subsystems. Correspondingly, the Lagrange multiplier method is adopted to decouple the state estimation equations into a multi-area state estimation model. Secondly, a fully distributed state estimation method based on the consensus algorithm is designed to solve the proposed model. The solution method does not need a centralized coordination system operator, but only requires a simple communication network for exchanging the limited data of boundary state variables and consensus variables among adjacent regions, thus it is quite flexible in terms of communication and computation for state estimation. In the end, the proposed method is tested by the IEEE 14-bus system and the IEEE 118-bus system, and the simulation results verify that the proposed multi-area state estimation model and the distributed solution method are effective for the state estimation of multi-area interconnected power systems.

The neutral‐earth‐voltage ( NEV ) system state estimation model

2020 ◽  
Vol 30 (9) ◽  
Author(s):  
Paulo M. De Oliveira‐De Jesus ◽  
David F. Celeita ◽  
Gustavo A. Ramos
Keyword(s):  
State Estimation ◽  
System State ◽  
Estimation Model

scholarly journals A Fast State Estimator for Integrated Electrical and Heating Networks

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4488
Author(s):  
Chun Wang ◽  
Minghao Geng ◽  
Qingshan Xu ◽  
Haixiang Zang
Keyword(s):  
State Estimation ◽  
Balance Equation ◽  
Temperature Drop ◽  
Estimation Method ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
State Estimator ◽  
Estimation Model ◽  
Fast State ◽  
Heating Networks

Integrated electrical and heating networks (IEHNs) effectively improve energy utilization efficiency, reduce environmental pollution and realize sustainable development of energy. To realize the accurate, comprehensive and fast perception of the integrated electrical and heating networks, it is necessary to build a state estimation model. However, the robust state estimator of IEHNs based on the temperature drop equation, flow balance equation and power balance equation still have the problems of convergence and low computational efficiency. In this paper, a fast state estimation method based on weighted least absolute value is proposed, which makes partition calculation of ring-shaped heating network and radiant heating network under certain assumptions. Simulation results show that the method improves the efficiency of the robust state estimator on the premise of high accuracy.

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