Probabilistic optimal power flow calculation method considering sequential features and correlations of multi-uncertain source-load scenarios

2021 ◽  
Vol 13 (4) ◽  
pp. 045503
Author(s):  
Tiantian Qian ◽  
Shengchun Yang ◽  
Jian Geng ◽  
Shenghe Wang
Keyword(s):  
Calculation Method ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Power Flow Calculation ◽  
Flow Calculation ◽  
Optimal Power

scholarly journals The Optimization of the Location and Capacity of Reactive Power Generation Units, Using a Hybrid Genetic Algorithm Incorporated by the Bus Impedance Power-Flow Calculation Method

2020 ◽  
Vol 10 (3) ◽  
pp. 1034
Author(s):  
Insu Kim
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Calculation Method ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Hybrid Genetic Algorithm ◽  
Power Flow Calculation ◽  
Flow Calculation

Dynamic and static reactive power resources have become an important means of maintaining the stability and reliability of power system networks. For example, if reactive power is not appropriately compensated for in transmission and distribution systems, the receiving end voltage may fall dramatically, or the load voltage may increase to a level that trips protection devices. However, none of the previous optimal power-flow studies for reactive power generation (RPG) units have optimized the location and capacity of RPG units by the bus impedance matrix power-flow calculation method. Thus, this study proposes a genetic algorithm that optimizes the location and capacity of RPG units, which is implemented by MATLAB. In addition, this study enhances the algorithm by incorporating bus impedance power-flow calculation method into the algorithm. The proposed hybrid algorithm is shown to be valid when applied to well-known IEEE test systems.

scholarly journals Optimal Power Flow Calculation Considering Large-Scale Photovoltaic Generation Correlation

2020 ◽  
Vol 8 ◽  
Author(s):  
He Li ◽  
Huijun Li ◽  
Weihua Lu ◽  
Zhenhao Wang ◽  
Jing Bian
Keyword(s):  
Power Flow ◽  
Power Plants ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Short Term Memory ◽  
Photovoltaic System ◽  
Power Flow Calculation ◽  
Flow Calculation ◽  
Optimal Power ◽  
The Impact

In order to analyze the impact of large-scale photovoltaic system on the power system, a photovoltaic output prediction method considering the correlation is proposed and the optimal power flow is calculated. Firstly, establish a photovoltaic output model to obtain the attenuation coefficient and fluctuation amount, and analyze the correlation among the multiple photovoltaic power plants through the k-means method. Secondly, the long short-term memory (LSTM) neural network is used as the photovoltaic output prediction model, and the clustered photovoltaic output data is brought into the LSTM model to generate large-scale photovoltaic prediction results with the consideration of the spatial correlation. And an optimal power flow model that takes grid loss and voltage offset as targets is established. Finally, MATLAB is used to verify that the proposed large-scale photovoltaic forecasting method has higher accuracy. The multi-objective optimal power flow calculation is performed based on the NSGA-II algorithm and the modified IEEE systems, and the optimal power flow with photovoltaic output at different times is compared and analyzed.

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