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You searched for subject:(state property estimation). Showing records 1 – 3 of 3 total matches.

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1. LI XIKUN. ERROR REGIONS FOR PROPERTIES OF THE QUANTUM STATE.

Degree: 2016, National University of Singapore

Subjects/Keywords: state property estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

XIKUN, L. (2016). ERROR REGIONS FOR PROPERTIES OF THE QUANTUM STATE. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/125205

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

XIKUN, LI. “ERROR REGIONS FOR PROPERTIES OF THE QUANTUM STATE.” 2016. Thesis, National University of Singapore. Accessed September 22, 2019. http://scholarbank.nus.edu.sg/handle/10635/125205.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

XIKUN, LI. “ERROR REGIONS FOR PROPERTIES OF THE QUANTUM STATE.” 2016. Web. 22 Sep 2019.

Vancouver:

XIKUN L. ERROR REGIONS FOR PROPERTIES OF THE QUANTUM STATE. [Internet] [Thesis]. National University of Singapore; 2016. [cited 2019 Sep 22]. Available from: http://scholarbank.nus.edu.sg/handle/10635/125205.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

XIKUN L. ERROR REGIONS FOR PROPERTIES OF THE QUANTUM STATE. [Thesis]. National University of Singapore; 2016. Available from: http://scholarbank.nus.edu.sg/handle/10635/125205

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Manchester

2. Jin, Zhaoyang. Static and Dynamic State Estimation of Power Systems.

Degree: 2018, University of Manchester

Power system state estimation has been playing a core part in the energy management system (EMS) utilised by power system operators since its establishment in the 1970s. The state estimator is responsible for providing accurate information (e.g. voltage magnitudes and angles of all buses in the network) for the EMS so that its security assessment functions can be deployed reliably. Recently, the power system is experiencing unprecedented evolution of complexity due to the increasing injection of renewable energy, increasing usage of power electronic devices and the increasing number of HVDC links in the network. One of the solutions to such challenges is to deploy Wide Area Monitoring System (WAMS) supported by the Synchronised Measurement Technology (SMT). Prior to state estimation, an observability analysis must be performed to make sure the measurements (e.g. power injection and flow measurements) received can support the normal functioning of the state estimator. If the measurements cannot provide full observability of the network, the observability analysis function identifies the observable islands where state estimation can still be performed within the observable islands. In this thesis it is shown that the existing method may not correctly identify the observable islands in the so called pathological cases; the thesis proposes a new method for observability analysis that overcomes this problem. Furthermore the execution time of the proposed method is shorter than existing methods. To support the deployment of the SMT in state estimation, the thesis also proposes a new method for including the synchronised measurements in the observability analysis function. The synchronised measurements provided by phasor measurement units (PMUs) have significantly higher accuracy and sampling rate than conventional measurements. However, the widespread installation of PMUs is limited by its high costs. A more feasible method that takes advantage of SMT is to use a hybrid state estimator (HSE). It uses a combination of PMU measurements and the existing conventional methods. To support the observability of the HSE, the thesis first proposes a new method for optimal PMU placement in the presence of conventional measurements. Then, the thesis performs simulations in the IEEE 14 and 118 Bus Test Systems comparing the performance of five different HSEs. It is found that even a small number of PMUs in a large network can significantly improve the estimation accuracy of the HSE compared to the conventional state estimator. Furthermore, the rectangular current type HSE has the best performance in terms of estimation accuracy, execution time and convergence. These conclusions are rigorously validated by mathematical analysis. The final work presented in this thesis is the development of a new algorithm for a dynamic state estimator (DSE) supported by SMT. The new method applies the Cubature Kalman Filter which is demonstrated to be more efficient but more sensitive to the anomalies compared to the DSEs using other nonlinear filters.… Advisors/Committee Members: MUTALE, JOSEPH J, Terzija, Vladimir, Mutale, Joseph.

Subjects/Keywords: Cubature Kalman Filter; convergence property; dynamic state estimation; estimation accuracy; Extended Kalman Filter; hybrid state estimation; observability analysis; observable islands; optimal PMU placement; PMU; synchronised measurements; state estimation; Unscented Kalman Filter

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jin, Z. (2018). Static and Dynamic State Estimation of Power Systems. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314416

Chicago Manual of Style (16th Edition):

Jin, Zhaoyang. “Static and Dynamic State Estimation of Power Systems.” 2018. Doctoral Dissertation, University of Manchester. Accessed September 22, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314416.

MLA Handbook (7th Edition):

Jin, Zhaoyang. “Static and Dynamic State Estimation of Power Systems.” 2018. Web. 22 Sep 2019.

Vancouver:

Jin Z. Static and Dynamic State Estimation of Power Systems. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2019 Sep 22]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314416.

Council of Science Editors:

Jin Z. Static and Dynamic State Estimation of Power Systems. [Doctoral Dissertation]. University of Manchester; 2018. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314416


University of Manchester

3. Jin, Zhaoyang. Static and dynamic state estimation of power systems.

Degree: PhD, 2018, University of Manchester

Power system state estimation has been playing a core part in the energy management system (EMS) utilised by power system operators since its establishment in the 1970s. The state estimator is responsible for providing accurate information (e.g. voltage magnitudes and angles of all buses in the network) for the EMS so that its security assessment functions can be deployed reliably. Recently, the power system is experiencing unprecedented evolution of complexity due to the increasing injection of renewable energy, increasing usage of power electronic devices and the increasing number of HVDC links in the network. One of the solutions to such challenges is to deploy Wide Area Monitoring System (WAMS) supported by the Synchronised Measurement Technology (SMT). Prior to state estimation, an observability analysis must be performed to make sure the measurements (e.g. power injection and flow measurements) received can support the normal functioning of the state estimator. If the measurements cannot provide full observability of the network, the observability analysis function identifies the observable islands where state estimation can still be performed within the observable islands. In this thesis it is shown that the existing method may not correctly identify the observable islands in the so called pathological cases; the thesis proposes a new method for observability analysis that overcomes this problem. Furthermore the execution time of the proposed method is shorter than existing methods. To support the deployment of the SMT in state estimation, the thesis also proposes a new method for including the synchronised measurements in the observability analysis function. The synchronised measurements provided by phasor measurement units (PMUs) have significantly higher accuracy and sampling rate than conventional measurements. However, the widespread installation of PMUs is limited by its high costs. A more feasible method that takes advantage of SMT is to use a hybrid state estimator (HSE). It uses a combination of PMU measurements and the existing conventional methods. To support the observability of the HSE, the thesis first proposes a new method for optimal PMU placement in the presence of conventional measurements. Then, the thesis performs simulations in the IEEE 14 and 118 Bus Test Systems comparing the performance of five different HSEs. It is found that even a small number of PMUs in a large network can significantly improve the estimation accuracy of the HSE compared to the conventional state estimator. Furthermore, the rectangular current type HSE has the best performance in terms of estimation accuracy, execution time and convergence. These conclusions are rigorously validated by mathematical analysis. The final work presented in this thesis is the development of a new algorithm for a dynamic state estimator (DSE) supported by SMT. The new method applies the Cubature Kalman Filter which is demonstrated to be more efficient but more sensitive to the anomalies compared to the DSEs using other nonlinear filters.…

Subjects/Keywords: Unscented Kalman Filter; state estimation; synchronised measurements; optimal PMU placement; observable islands; observability analysis; PMU; Extended Kalman Filter; estimation accuracy; dynamic state estimation; convergence property; Cubature Kalman Filter; hybrid state estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jin, Z. (2018). Static and dynamic state estimation of power systems. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/static-and-dynamic-state-estimation-of-power-systems(13b88285-a242-4de8-bf44-99252174fd6f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779589

Chicago Manual of Style (16th Edition):

Jin, Zhaoyang. “Static and dynamic state estimation of power systems.” 2018. Doctoral Dissertation, University of Manchester. Accessed September 22, 2019. https://www.research.manchester.ac.uk/portal/en/theses/static-and-dynamic-state-estimation-of-power-systems(13b88285-a242-4de8-bf44-99252174fd6f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779589.

MLA Handbook (7th Edition):

Jin, Zhaoyang. “Static and dynamic state estimation of power systems.” 2018. Web. 22 Sep 2019.

Vancouver:

Jin Z. Static and dynamic state estimation of power systems. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2019 Sep 22]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/static-and-dynamic-state-estimation-of-power-systems(13b88285-a242-4de8-bf44-99252174fd6f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779589.

Council of Science Editors:

Jin Z. Static and dynamic state estimation of power systems. [Doctoral Dissertation]. University of Manchester; 2018. Available from: https://www.research.manchester.ac.uk/portal/en/theses/static-and-dynamic-state-estimation-of-power-systems(13b88285-a242-4de8-bf44-99252174fd6f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779589

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