Stochastic Power Flow Analysis of Unbalanced Distribution System based on cluster of SWTG-SPV

2020 ◽  
Author(s):  
Sangamesh Y. Goudappanavar ◽  
Suresh H. Jangamshetti
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Flow Analysis ◽  
Power Flow Analysis

A novel power flow analysis for microgrid distribution system

2013 ◽  
Author(s):  
Ting-Chia Ou ◽  
Ta-Peng Tsao ◽  
Whei-Min Lin ◽  
Chih-Ming Hong ◽  
Kai-Hung Lu ◽  
...  
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Flow Analysis ◽  
Power Flow Analysis

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 Power Flow Analysis of Weakly Meshed Distribution Network Including DG

2018 ◽  
Vol 8 (5) ◽  
pp. 3398-3404 ◽  
Author(s):  
A. Al-Sakkaf ◽  
M. AlMuhaini
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Power Flow ◽  
Distribution Systems ◽  
Flow Analysis ◽  
Load Flow ◽  
Power Distribution Systems ◽  
Power Flow Analysis ◽  
Bus Voltage ◽  
Flow Study

Power flow is one of the essential studies in power system operation and planning. All steady-state parameters for power distribution systems, such as bus voltage magnitudes, angles, power flows, and power losses, can be calculated by conducting power flow analysis. Distribution system features differ from those of transmission system, rendering conventional load flow algorithms inapplicable. In this paper, three distribution power flow techniques are presented and tested to evaluate their performance when applied to a networked distribution system including distributed generation (DG). These are the distribution load flow (DLF) matrix, the enhanced Newton Raphson (ENR), and the robust decoupled (RD) method. IEEE 33-bus system is adopted for implementing the above methods. Radial and weakly meshed configurations are applied to the tested system with DG inclusion to investigate their influence on the power flow study findings.

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.

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