Probabilistic Load Flow Based on Cumulant Method Considering Multi-Slack Balance

2014 ◽  
Vol 1070-1072 ◽  
pp. 943-951 ◽  
Author(s):  
Fei Shi ◽  
Yi Jun Yu ◽  
Shu Hai Feng ◽  
Jin Zhou ◽  
Peng Xu ◽  
...  

With constant improvement of intermittent energy source, its agglomeration effect and stochastic volatility will greatly influence the power system operation. It’s an inexorable trend that probabilistic power flow calculation shifts from offline analysis to real-time operation online. Among all probabilistic trend algorithms, probability flow calculation based on cumulant method is the fastest one; it has better prospect of online application. However, it requires random variables independent to each other, so the single slack bus always undertakes all unbalance power in conventional cumulant methods. When the fluctuation of system power injection becomes larger and larger, this calculation model will hardly adapted to the actual demand of the grid in the future. To improve the practicability, a improvement of probabilistic load flow based on cumulant method is proposed in this paper. By modify the calculation of the sensitivity matrix, the distribution of system unbalance power can be considered. The accuracy of this method is verified by the simulated analysis of the standard examples and actual power system model.

2014 ◽  
Vol 1070-1072 ◽  
pp. 193-199
Author(s):  
Min Jiang Chen ◽  
Yue Qing Chen ◽  
Wang Chao Dong ◽  
Bei Wu

This paper uses the optimal probabilistic load flow method for power containing wind farm analysis. Based on Computation of optimal load flow using the Interior point method ,considering the stochasticlal power output of wind generator and the random outage of synchronous generator and the stochastic of load power, calculating the probability distribution of branch power flow and node voltage. This paper uses RTS-24 as the example to analysis the method ,and comparison the results with that of the Monte-Carlo method, to analysis the change of power system after the grid connected of wind turbine.


Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 642
Author(s):  
Wallisson C. Nogueira ◽  
Lina Paola Garcés Negrete ◽  
Jesús M. López-Lezama

Modern power systems must deal with a greater degree of uncertainty in power flow calculation due to variations in load and generation introduced by new technologies. This scenario poses new challenges to power system operators which require new tools for an accurate assessment of the system state. This paper presents an interval load flow (ILF) approach for dealing with uncertainty in power system analysis. A probabilistic load flow (PLF), based on Monte Carlo Simulation (MCS), was also implemented for comparative purposes. The ILF and PLF are used to estimate the network states. Both methods were implemented in Python® using the IEEE 34-bus, IEEE 69-bus and 192-bus Brazilian distribution system. The results with the proposed ILF on the aforementioned benchmark test systems proved to be compatible with that of the MCS, evidencing the robustness and applicability of the proposed approach.


2015 ◽  
Vol 740 ◽  
pp. 438-441 ◽  
Author(s):  
Wei Zheng ◽  
Fang Yang ◽  
Zheng Dao Liu

The power flow calculation is study the steady-state operation of the power system as basic electrical calculations. It is given the power system network topology, device parameters and determines system health boundary conditions, draw a detailed operating status of the power system through numerical simulation methods, such as voltage amplitude and phase angle on the bus system the power distribution and the power loss. Flow calculation is the power system operation, planning and safety, reliability analysis, is fundamental to the system voltage regulation, network reconfiguration and reactive power optimization must call the function, so the trend has very important significance to calculate the power system.


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