In this paper, the mixed integer linear programming (MILP) for solving unit commitment (UC) problems in a hybrid power system containing thermal, hydro, and wind power have been studied. To promote its efficiency, an improved MILP approach has been proposed, while the symmetric problem in MILP formulas has been solved by reforming hierarchical constraints. Experiments on different scales have been conducted to demonstrate the effectiveness of the proposed approach. The results indicate a dramatic efficiency promotion compared to other popular MILP approaches in large scale power systems. Additionally, the proposed approach has been applied in UC problems of the hybrid power system. Two indexes, fluctuation degree and output degree, have been proposed to investigate the performance of renewable energy sources (RES). Several experiments are also implemented and the results show that the integration of pumped hydroelectric energy storage (PHES) can decrease the output of thermal units, as well as balance wind power fluctuation according to the load demand.
Because of the uncertainty of the external environment, high penetration of renewable energy such as wind power and solar energy in the modern power system renders the traditional automatic generation control (AGC) methods more challenging. An improved AGC method named predictive optimal proportional integral differential plus second order derivative (PO-PID + DD) for multi-area interconnected grid is proposed in this paper to reduce the negative impacts of the uncertainty which is caused by the high penetration of renewable energy. Firstly, the mathematical model of the AGC system of multiarea power grid with penetration of photovoltaic (PV) and wind power is built. Then, PO-PID + DD controller is presented to improve the system robustness with respect to system uncertainties. In order to obtain the predictive sequence of the integral system output, the characteristic of the controller is included in the system model. Thus, according to the predictive sequence and designed objective function, the input of the controller can be readjusted to obtain the optimal effect of AGC. An IEEE 39-bus system is introduced as an example to testify the feasibility and effectiveness of the proposed method. The simulation results indicate that the system controlled by the proposed controller has desired dynamic performances.
High penetration of wind power in the modern power system renders traditional automatic generation control (AGC) methods more challenging, due to the uncertainty of the external environment, less reserve power, and small inertia constant of the power system. An improved AGC method named predictive optimal 2-degree-of-freedom proportion integral differential (PO-2-DOF-PID) is proposed in this paper, which wind farm will participate in the load frequency control process. Firstly, the mathematical model of the AGC system of multi-area power grid with penetration of wind power is built. Then, predictive optimal 2-degree-of-freedom PID controller is presented to improve the system robustness considering system uncertainties. The objective function is designed based on the wind speed and whether wind farm takes part in AGC or not. The controller solves the optimization problem through the predictive theory while taking into account given constraints. In order to obtain the predictive sequence of output of the whole system, the characteristic of the 2-DOF-PID controller is integrated in the system model. A three interconnected power system is introduced as an example to test the feasibility and effectiveness of the proposed method. When considering the penetration of wind power, two cases of high wind speed and low wind speed are analyzed. The simulation results indicate that the proposed method can effectively deal with the negative influence caused by wind power when wind power participates in AGC.
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