A Non-iterative Three Phase Distribution System Power Flow Analysis

2019 ◽  
Author(s):  
Alamanda Sudheer Kumar ◽  
Boddeti Kalyan Kumar
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Phase Distribution ◽  
Flow Analysis ◽  
Power Flow Analysis ◽  
Three Phase ◽  
System Power

scholarly journals Three-Phase Distribution System Load Flow Analysis Using Sequence Components

2020 ◽  
Vol 4 (4) ◽  
Author(s):  
Rudy Gianto
Keyword(s):  
Electric Power ◽  
Distribution System ◽  
Power Flow ◽  
Flow Problem ◽  
Phase Distribution ◽  
Flow Analysis ◽  
Three Phase ◽  
Sequence Components ◽  
System Power ◽  
Power Flow Problem

Electric power distribution system are usually unbalance. Therefore, a power flow method that can handle the three-phase configuration of the power system is needed so that the system planning and operation can properly be carried out. In the case of three-phase distribution system power flow analysis, for each system bus (except for substation bus), the voltage magnitude and angle of the three phases must be calculated. These calculations are carried out under certain loading conditions. After these voltages have been calculated, the electric power flows and losses in the distribution lines, and the substation power can also be determined. This paper proposes a new technique for three-phase distribution system power flow analysis using sequence components. The new formulation for the power flow problem in terms of sequence components is also proposed and developed in this paper. The application of sequence components has the advantage that the size of the problem can effectively be reduced, and solution to the power flow problem will be easier to find. Case study using a representative distribution test system confirms the validity of the proposed method where comparative studies between the proposed (i.e. sequence components based) method and the phase components based method are carried out.

scholarly journals Techno-Economic Models For Integration Of Wind Energy

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.

scholarly journals Techno-economic models for integration of wind energy.

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.

scholarly journals Techno-economic models for integration of wind energy.

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.

Distribution system power flow analysis-a rigid approach

1991 ◽  
Vol 6 (3) ◽  
pp. 1146-1152 ◽  
Author(s):  
T.-H. Chen ◽  
M.-S. Chen ◽  
K.-J. Hwang ◽  
P. Kotas ◽  
E.A. Chebli
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Flow Analysis ◽  
Power Flow Analysis ◽  
System Power
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