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Robust Optimal Dispatch of Power Systems with Wind Farm

Zhang Jinhua, Gu Bo, Meng Hang, Fu Chentao, Zhu Xueling

Journal of Power Technologies

2020

Vol. 100, nr 2

92--101

With the rapid development of new energy power generation, large-scale wind power generation has been integrated into power grids. However, the fluctuation and discontinuity of wind power pose challenges to the safe and reliable operation of power systems. Therefore, constructing a reasonable dispatching method to manage the uncertainty of wind power outputhas become an important topic and this study was structured with this precise aim in mind. An ellipsoidal robust set of wind power outputs was initially constructed in accordance with the predicted value and predicted error of wind power. Second, a power system optimization dispatch model of automatic generation control (AGC) was established on the basis of the robust set. This model aimed to minimize the cost of power generation and maximize the use of wind power according to the following constraint conditions: power system power balance, upper andlower limit of wind and thermal power unit outputs, climbing power, and spinning reserve. Finally, the internal point method was employed to solve the example. Results show that, on the premise of safe operation, the total operating cost of the robust optimization dispatch method is decreased by 8.64% compared with that of the traditional dispatch method, and economic efficiency is improved. Robust optimal dispatch factors in the uncertainty of wind power output meaning the load shedding scenario seldom occurs, thereby enhancing operational reliability. This study can be used to improve the reliability and economics of power system operation and provide a basis for optimizing dispatch in power systems.

Optimal configuration of standalone wind-solar-storage complementary generation system based on the GA-PSO algorithm

Sun Qian, Ma Jianwei, She Yanjie, Zhang Jingchao, Gu Bo, Zhang Zichao

Journal of Power Technologies

2019

Vol. 99, nr 4

231--236

The capacity configuration of the standalone wind–solar–storage complementary power generation system (SWS system) is affected by environmental, climate condition, load and other stochastic factors. This makes the capacity configuration of the SWS system problematic when the capacity configuration method of traditional power generation is used. An optimal configuration method of the SWS system based on the hybrid genetic algorithm and particle swarm optimization (GA-PSO) algorithm is proposed in this study to improve the stability and economy of the SWS system. The constituent elements of investment, maintenance cost and various reliability constraints of the SWS system were also discussed. The optimal configuration of the SWS system based on GA-PSO was explored to achieve the optimization objective, which was to minimize investment and maintenance costs of the SWS system while maintaining power supply reliability. The investment and maintenance costs of the SWS system under different configuration methods were calculated and analyzed on the bases of the monthly mean wind speed, solar radiation and load data of Xiaoertai Village in Zhangbei County of Hebei Province in the last 10 years. Results show that the optimal configuration method based on the GA-PSO algorithm could effectively improve the economy of the system and meet the requirements of system stability. The proposed method shows great potential for guiding the optimal configuration of the SWS system in remote areas.