2020
DOI: 10.1049/iet-gtd.2019.1010
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Dynamic state estimation of generators using spherical simplex unscented transform‐based unbiased minimum variance filter

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Cited by 5 publications
(6 citation statements)
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“…To sum up, it is important to say that the stochastic analysis and uncertainty modeling are essential to be considered in the P2P energy market in order to bring an accuracy consensus solution for each participant. 21) and (23), respectively. In contrast to the tidal unit whose uncertainty model led an increased generated power, there is a marked decline in the power generated by WT in the stochastic framework due to the generation-demand balance.…”
Section:  V Simulation Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…To sum up, it is important to say that the stochastic analysis and uncertainty modeling are essential to be considered in the P2P energy market in order to bring an accuracy consensus solution for each participant. 21) and (23), respectively. In contrast to the tidal unit whose uncertainty model led an increased generated power, there is a marked decline in the power generated by WT in the stochastic framework due to the generation-demand balance.…”
Section:  V Simulation Resultsmentioning
confidence: 99%
“…With the growing concern over the air pollutions in recent years, the renewable energy sources could attain a brighter and more effective role in the power grids [22][23]. The clean nature, high accessibility at different regions and local power generation too close to the end users are some of the most significant features of these sources which could support their role with higher penetration compared to the conventional fossil fuel based DGs.…”
Section: Introductionmentioning
confidence: 99%
“…The renewable energy sources (RESs) have brought many promising benefits to the power systems in terms of loss reduction, reliability improvement, and air pollutants diminishment [29,30] and roles markedly in the modern power grids. Apart from the RESs' advantages, they are of high uncertainty factor since their output power fluctuates, and this is a result from the climate changes [31].…”
Section: Allocation-based Energy Managementmentioning
confidence: 99%
“…The problem with unknown inputs is common in daily business applications, for example, electric vehicle driveline [2], lithium‐ion battery current estimation [3], power system state estimation [4, 5], fault detection [6], and many others. For linear discrete systems with unknown inputs, an unbiased minimum variance (UMV) estimation algorithm is proposed based on the Kalman filter [7, 8]. This two‐stage state estimation algorithm estimates the state variables and unknown inputs at the same time.…”
Section: Introductionmentioning
confidence: 99%