scholarly journals Study on Modeling and Solving for Reactive Power Optimization of Large-scale Wind Power Integration

2015 ◽  
Vol 8 (4) ◽  
pp. 25-34
Author(s):  
Deyu Chen
2014 ◽  
Vol 986-987 ◽  
pp. 529-532
Author(s):  
Jie Ren ◽  
Jian She Tian

Aiming at problems which were brought by large-scale wind power integration, and the problem of multi-objective reactive power optimization considering the coexistence of discrete variables and continuous variables, a method of simulation based on genetic algorithm with adaptive weight is brought out. A solving thinking presents that capacitor switching and transformer tap adjusting and other discrete equipments are first, and the action sequence of generator and dynamic reactive power compensation (DRPC) devices and other continuous equipments setting follows, which is presented that optimization problem is decomposed into continuous variable optimization and discrete variable optimization, then they are solved respectively and cross iteration until convergence. In view of the optimization complexity and the coexistence of discrete variables and continuous variables, genetic algorithm with adaptive weight is presented for finding global optimal solution. Case studies show that the proposed thinking and algorithm for solving multi-objective reactive power optimization are reasonable.


2013 ◽  
Vol 380-384 ◽  
pp. 2972-2976
Author(s):  
Xiang Yu Lv ◽  
Tian Dong ◽  
Ye Yuan ◽  
De Xin Li ◽  
Xiao Juan Han

Large scale wind power integration has influenced the safety of power system. Taking wind power integration in Jilin as example, the paper describes the influencing factors of large scale wind power integration on reactive power of the grid in detail firstly, then analyze the reactive voltage in four typical ways, and discuss the impact of the wind power fluctuations on the grid reactive voltage.


Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3556
Author(s):  
Linan Qu ◽  
Shujie Zhang ◽  
Hsiung-Cheng Lin ◽  
Ning Chen ◽  
Lingling Li

The large-scale renewable energy power plants connected to a weak grid may cause bus voltage fluctuations in the renewable energy power plant and even power grid. Therefore, reactive power compensation is demanded to stabilize the bus voltage and reduce network loss. For this purpose, time-series characteristics of renewable energy power plants are firstly reflected using K-means++ clustering method. The time group behaviors of renewable energy power plants, spatial behaviors of renewable energy generation units, and a time-and-space grouping model of renewable energy power plants are thus established. Then, a mixed-integer optimization method for reactive power compensation in renewable energy power plants is developed based on the second-order cone programming (SOCP). Accordingly, power flow constraints can be simplified to achieve reactive power optimization more efficiently and quickly. Finally, the feasibility and economy for the proposed method are verified by actual renewable energy power plants.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaodong Shen ◽  
Yang Liu ◽  
Yan Liu

In order to solve the uncertainty and randomness of the output of the renewable energy resources and the load fluctuations in the reactive power optimization, this paper presents a novel approach focusing on dealing with the issues aforementioned in dynamic reactive power optimization (DRPO). The DRPO with large amounts of renewable resources can be presented by two determinate large-scale mixed integer nonlinear nonconvex programming problems using the theory of direct interval matching and the selection of the extreme value intervals. However, it has been admitted that the large-scale mixed integer nonlinear nonconvex programming is quite difficult to solve. Therefore, in order to simplify the solution, the heuristic search and variable correction approaches are employed to relax the nonconvex power flow equations to obtain a mixed integer quadratic programming model which can be solved using software packages such as CPLEX and GUROBI. The ultimate solution and the performance of the presented approach are compared to the traditional methods based on the evaluations using IEEE 14-, 118-, and 300-bus systems. The experimental results show the effectiveness of the presented approach, which potentially can be a significant tool in DRPO research.


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