Containing Wind Farm Power System Probabilistic Optimal Power Flow Calculation Using the Method of Combined Cumulants and Gram-Charlier Expansion

2014 ◽  
Vol 1070-1072 ◽  
pp. 193-199
Author(s):  
Min Jiang Chen ◽  
Yue Qing Chen ◽  
Wang Chao Dong ◽  
Bei Wu
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Wind Farm ◽  
Synchronous Generator ◽  
Load Flow ◽  
Probabilistic Load Flow ◽  
The Monte Carlo Method ◽  
Probabilistic Load ◽  
Node Voltage

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.

Distributed Network Power Flow of Distributed Generation

2012 ◽  
Vol 614-615 ◽  
pp. 1693-1699
Author(s):  
Qi Yang ◽  
Meng Cong Liu ◽  
Ying Chen ◽  
Yun Xiao Bai
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Flow ◽  
Simulation Method ◽  
Energy System ◽  
Load Flow ◽  
Probabilistic Load Flow ◽  
Probabilistic Load ◽  
Node Voltage ◽  
The Impact

With constrains imposed by natural conditions, the power generated from wind power, solar power and other intermittent energy system has great randomness and volatility. Thus, the impact from the intermittent energy to the system voltage and power flow is uncertainty. In view of this problem, this paper studies the characteristics of these double random variables and correlation. By using the typical probabilistic load flow and Monte Carlo simulation method, this paper poses the probability load flow adapted to the intermittent distributed generation. Finally, taking IEEE33 distribution system for example, this paper obtains the mutual relationship between the power from the intermittent distributed generation and the probability distribution of the node voltage, current distribution of each branch.

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 ◽  
...  
Keyword(s):  
Power System ◽  
Power Flow ◽  
Load Flow ◽  
Sensitivity Matrix ◽  
Online Application ◽  
Flow Calculation ◽  
Probabilistic Load Flow ◽  
Time Operation ◽  
Cumulant Method ◽  
Probabilistic Load

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.

scholarly journals Interval Load Flow for Uncertainty Consideration in Power Systems Analysis

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 642
Author(s):  
Wallisson C. Nogueira ◽  
Lina Paola Garcés Negrete ◽  
Jesús M. López-Lezama
Keyword(s):  
Power Systems ◽  
Power System ◽  
Distribution System ◽  
Power Flow ◽  
System Analysis ◽  
New Technologies ◽  
Load Flow ◽  
Probabilistic Load Flow ◽  
Probabilistic Load ◽  
Network States

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.

scholarly journals Analysis and Assessment of Operation Risk for Hybrid AC/DC Power System based on the Monte Carlo Method

2018 ◽  
Vol 38 ◽  
pp. 04010
Author(s):  
Xiaojing Hu ◽  
Qiang Li ◽  
Hao Zhang ◽  
Ziming Guo ◽  
Kun Zhao ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Power System ◽  
Power Flow ◽  
Assessment Method ◽  
Active Power ◽  
Dc Power ◽  
The Monte Carlo Method ◽  
Node Voltage ◽  
Operation Risk

Based on the Monte Carlo method, an improved risk assessment method for hybrid AC/DC power system with VSC station considering the operation status of generators, converter stations, AC lines and DC lines is proposed. According to the sequential AC/DC power flow algorithm, node voltage and line active power are solved, and then the operation risk indices of node voltage over-limit and line active power over-limit are calculated. Finally, an improved two-area IEEE RTS-96 system is taken as a case to analyze and assessment its operation risk. The results show that the proposed model and method can intuitively and directly reflect the weak nodes and weak lines of the system, which can provide some reference for the dispatching department.

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