Backward Forward Sweep Algorithm for Unbalanced Three-Phase Power Flow Analysis in Distribution Systems Containing Voltage Regulator

This thesis focusses on three specific areas of integrating wind energy with power systems: 1) technical modeling of wind generators for power flow analysis, 2) probabilistic modeling of wind generators for planning studies, and 3) economic modeling for integration of wind energy in electricity markets. Wind generator output is a function of wind speed and 3-phase terminal voltages. Complete nonlinear three-phase models of wind generators are accurate but are computationally cumbersome and unsuitable for power flow analysis purposes. Intelligent models of wind generators are proposed for their accurate representation and use in power flow analysis algorithms. The main advantages of these intelligent models of wind generators are their mathematical simplicity, computational speed and numerical accuracy when the generators are connected to unbalanced three-phase distribution systems. These proposed intelligent models of wind generators were tested with the three-phase, unbalanced, IEEE 37-bus test system. The results show that the intelligent models of wind generators are computationally ten times faster than exact nonlinear models. In addition, simplicity of the proposed intelligent models of wind generators allows easy integration into commercial software such as PSS®E and PSS®SINCAL. In the second study, a probabilistic model of wind generators was integrated with algorithm for distribution system analysis. The proposed probabilistic power flow analysis method for distribution systems takes into account the stochastic nature of wind generation and forecasted bus-wise peak load. Probability distribution functions for bus voltages are reconstructed. The proposed method is tested on a modified 70-bus distribution system and the results are reported. Thirdly, an economic integration model for wind generators with electricity markets is proposed. The proposed model is in the form of a Wind Generators Cooperative (WGC). This proposed model overcomes challenges posed by uncertainty and intermittency of wind generation. The proposed cooperative model maximizes returns for wind generators by minimizing the effect of uncertainty by smoothing effect and using pumped-hydro facilities. A case study with actual data from Ontario (Canada) was completed. Analyses clearly demonstrate that the WGC increases returns to wind generators and reduces their exposure to uncertainty.

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Techno-economic models for integration of wind energy.

10.32920/ryerson.14663373 ◽

2021 ◽

Author(s):

Chandrabhanu Opathella Ganehi Kankanamalage

Keyword(s):

Wind Energy ◽

Electricity Markets ◽

Distribution System ◽

Power Flow ◽

Distribution Systems ◽

Flow Analysis ◽

Power Flow Analysis ◽

Wind Generators ◽

Three Phase ◽

Intelligent Models

This thesis focuses on three specific areas of integrating wind energy with power systems: 1) technical modeling of wind generators for power flow analysis, 2) probabilistic modeling of wind generators for planning studies, and 3) economic modeling for integration of wind energy in electricity markets. Wind generator output is a function of wind speed and 3-phase terminal voltages. Complete nonlinear three-phase models of wind generators are accurate but are computationally cumbersome and unsuitable for power flow analysis purposes. Intelligent models of wind generators are proposed for their accurate representation and use in power flow analysis algorithms. The main advantages of these intelligent models of wind generators are their mathematical simplicity, computational speed and numerical accuracy when the generators are connected to unbalanced three-phase distribution systems. These proposed intelligent models of wind generators were tested with the three-phase, unbalanced, IEEE 37-bus test system. The results show that the intelligent models of wind generators are computationally ten times faster than exact nonlinear models. In addition, simplicity of the proposed intelligent models of wind generators allows easy integration into commercial software such as PSS®E and PSS®SINCAL. In the second study, a probabilistic model of wind generators was integrated with algorithm for distribution system analysis. The proposed probabilistic power flow analysis method for distribution systems takes into account the stochastic nature of wind generation and forecasted bus-wise peak load. Probability distribution functions for bus voltages are reconstructed. The proposed method is tested on a modified 70-bus distribution system and the results are reported. Thirdly, an economic integration model for wind generators with electricity markets is proposed. The proposed model is in the form of a Wind Generators Cooperative (WGC). This proposed model overcomes challenges posed by uncertainty and intermittency of wind generation. The proposed cooperative model maximizes returns for wind generators by minimizing the effect of uncertainty by smoothing effect and using pumped-hydro facilities. A case study with actual data from Ontario (Canada) was completed. Analyses clearly demonstrate that the WGC increases returns to wind generators and reduces their exposure to uncertainty.

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Techno-economic models for integration of wind energy.

10.32920/ryerson.14663373.v1 ◽

2021 ◽

Author(s):

Chandrabhanu Opathella Ganehi Kankanamalage

Keyword(s):

Wind Energy ◽

Electricity Markets ◽

Distribution System ◽

Power Flow ◽

Distribution Systems ◽

Flow Analysis ◽

Power Flow Analysis ◽

Wind Generators ◽

Three Phase ◽

Intelligent Models

This thesis focuses on three specific areas of integrating wind energy with power systems: 1) technical modeling of wind generators for power flow analysis, 2) probabilistic modeling of wind generators for planning studies, and 3) economic modeling for integration of wind energy in electricity markets. Wind generator output is a function of wind speed and 3-phase terminal voltages. Complete nonlinear three-phase models of wind generators are accurate but are computationally cumbersome and unsuitable for power flow analysis purposes. Intelligent models of wind generators are proposed for their accurate representation and use in power flow analysis algorithms. The main advantages of these intelligent models of wind generators are their mathematical simplicity, computational speed and numerical accuracy when the generators are connected to unbalanced three-phase distribution systems. These proposed intelligent models of wind generators were tested with the three-phase, unbalanced, IEEE 37-bus test system. The results show that the intelligent models of wind generators are computationally ten times faster than exact nonlinear models. In addition, simplicity of the proposed intelligent models of wind generators allows easy integration into commercial software such as PSS®E and PSS®SINCAL. In the second study, a probabilistic model of wind generators was integrated with algorithm for distribution system analysis. The proposed probabilistic power flow analysis method for distribution systems takes into account the stochastic nature of wind generation and forecasted bus-wise peak load. Probability distribution functions for bus voltages are reconstructed. The proposed method is tested on a modified 70-bus distribution system and the results are reported. Thirdly, an economic integration model for wind generators with electricity markets is proposed. The proposed model is in the form of a Wind Generators Cooperative (WGC). This proposed model overcomes challenges posed by uncertainty and intermittency of wind generation. The proposed cooperative model maximizes returns for wind generators by minimizing the effect of uncertainty by smoothing effect and using pumped-hydro facilities. A case study with actual data from Ontario (Canada) was completed. Analyses clearly demonstrate that the WGC increases returns to wind generators and reduces their exposure to uncertainty.

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Phase-decoupled method for three-phase power-flow analysis of unbalanced distribution systems

IEE Proceedings - Generation Transmission and Distribution ◽

10.1049/ip-gtd:20040831 ◽

2004 ◽

Vol 151 (5) ◽

pp. 568 ◽

Cited By ~ 44

Author(s):

J.C.M. Vieira ◽

W. Freitas ◽

A. Morelato

Keyword(s):

Power Flow ◽

Distribution Systems ◽

Flow Analysis ◽

Power Flow Analysis ◽

Three Phase ◽

Decoupled Method

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Techno-Economic Models For Integration Of Wind Energy

10.32920/ryerson.14655294 ◽

2021 ◽

Author(s):

Chandrabhanu O.G. Kankanamalage

Keyword(s):

Wind Energy ◽

Electricity Markets ◽

Distribution System ◽

Power Flow ◽

Distribution Systems ◽

Flow Analysis ◽

Power Flow Analysis ◽

Wind Generators ◽

Three Phase ◽

Intelligent Models

This thesis focusses on three specific areas of integrating wind energy with power systems: 1) technical modeling of wind generators for power flow analysis, 2) probabilistic modeling of wind generators for planning studies, and 3) economic modeling for integration of wind energy in electricity markets. Wind generator output is a function of wind speed and 3-phase terminal voltages. Complete nonlinear three-phase models of wind generators are accurate but are computationally cumbersome and unsuitable for power flow analysis purposes. Intelligent models of wind generators are proposed for their accurate representation and use in power flow analysis algorithms. The main advantages of these intelligent models of wind generators are their mathematical simplicity, computational speed and numerical accuracy when the generators are connected to unbalanced three-phase distribution systems. These proposed intelligent models of wind generators were tested with the three-phase, unbalanced, IEEE 37-bus test system. The results show that the intelligent models of wind generators are computationally ten times faster than exact nonlinear models. In addition, simplicity of the proposed intelligent models of wind generators allows easy integration into commercial software such as PSS®E and PSS®SINCAL. In the second study, a probabilistic model of wind generators was integrated with algorithm for distribution system analysis. The proposed probabilistic power flow analysis method for distribution systems takes into account the stochastic nature of wind generation and forecasted bus-wise peak load. Probability distribution functions for bus voltages are reconstructed. The proposed method is tested on a modified 70-bus distribution system and the results are reported. Thirdly, an economic integration model for wind generators with electricity markets is proposed. The proposed model is in the form of a Wind Generators Cooperative (WGC). This proposed model overcomes challenges posed by uncertainty and intermittency of wind generation. The proposed cooperative model maximizes returns for wind generators by minimizing the effect of uncertainty by smoothing effect and using pumped-hydro facilities. A case study with actual data from Ontario (Canada) was completed. Analyses clearly demonstrate that the WGC increases returns to wind generators and reduces their exposure to uncertainty.

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Impedance Matching-Based Power Flow Analysis for UPQC in Three-Phase Four-Wire Systems

Energies ◽

10.3390/en14092702 ◽

2021 ◽

Vol 14 (9) ◽

pp. 2702

Author(s):

Xiaojun Zhao ◽

Xiuhui Chai ◽

Xiaoqiang Guo ◽

Ahmad Waseem ◽

Xiaohuan Wang ◽

...

Keyword(s):

Power Flow ◽

Control Strategies ◽

Impedance Matching ◽

Flow Analysis ◽

Point Of View ◽

Impedance Model ◽

Power Flow Analysis ◽

Three Phase ◽

System Node ◽

Power Quality Conditioner

Different from the extant power flow analysis methods, this paper discusses the power flows for the unified power quality conditioner (UPQC) in three-phase four-wire systems from the point of view of impedance matching. To this end, combined with the designed control strategies, the establishing method of the UPQC impedance model is presented, and on this basis, the UPQC system can be equivalent to an adjustable impedance model. After that, a concept of impedance matching is introduced into this impedance model to study the operation principle for the UPQC system, i.e., how the system changes its operation states and power flow under the grid voltage variations through discussing the matching relationships among node impedances. In this way, the nodes of the series and parallel converter are matched into two sets of impedances in opposite directions, which mean that one converter operates in rectifier state to draw the energy and the other one operates in inverter state to transmit the energy. Consequently, no matter what grid voltages change, the system node impedances are dynamically matched to ensure that output equivalent impedances are always equal to load impedances, so as to realize impedance and power balances of the UPQC system. Finally, the correctness of the impedance matching-based power flow analysis is validated by the experimental results.

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