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Modern power grid has more and more requirements for system frequency stability. In order to improve the frequency stability level of power grid, we need to do more in-depth research on the frequency control strategy of power grid. However, there is no simulation model and simulation platform that can be used for frequency control strategy testing. There are no effective ways to test and study frequency control strategies. There are limitations in traditional methods and field experiments. In this paper, the modeling method of AGC control system is proposed by means of simulation, including the model of AGC control of main station and the simulation model of terminal actuator of power plant. A typical model of regional power grid is set up. Through the experiments of generator tripping, it is verified that the frequency characteristics of the simulation grid are the same as the actual frequency characteristics of the power grid. The established AGC control strategy model can be used for comparative analysis of different control strategies. The method proposed in this paper is an effective research method and means for power system AGC frequency control.

Data assimilation, a key technology for numerical weather forecast, has a very important influence on the forecast accuracy of photovoltaic (PV) generated power. In this paper, a multi-scale data assimilation method for surface temperature field based on measured data of PV power station is proposed. In this method, a multi-scale nested grid of temperature field is established based on DBSCAN clustering. Then, optimal statistical interpolation method is used to make data assimilation with different resolution of the multi-scale nested grid, in order to obtain the multi-scale temperature analysis field. Through the case analysis, this method makes full use of the operating data of PV power plants. It not only further improves the forecast accuracy of PV generated power, but also reduces the amount of calculation effectively, which verifies the feasibility of this method.

In this paper, a novel model of n opportunity cost of Automatic Generation Control (i.e. AGC) is proposed based on sequential dispatching. A model of strategic behaviors of generation firms based on conjectural variation is proposed to apply in monopoly AGC markets with incomplete information. According to the conjectural variation model, each firm rationally maximizes its profits while considering reactions of their competitors. The advantage of this method over others is that it is a real reflection of actual power markets without the need to know all firms’ actual costs. Examples are used to illustrate that the proposed model is logical and practical.