The Model And Algorithm Of Economic Dispatch Of Power System With The Wind Farms Based On The Carbon Trading

With more and more emphasis on environmental issues, wind power, as one of the major forms of clean energy, has been developed rapidly. Wind power has the qualities of randomness, volatility and intermittent, while has the anti-peaking characteristics to the system. With increasing grid-connected wind farm scale, the influence that wind power brings to a dynamic economic dispatch of power system cannot be ignored. This article will research on the dynamic economic dispatch of power system with the large-scale wind farm. And our country make a specific aim to reduce the amount of the carbon on the United Nations Climate Change Conference. The behavior of the power producer will play an important role in the realizing the aim. So the issue that economic dispatch of the power system with the wind farms considering the carbon will be discussed in this paper.First, the concept of carbon emissions trading is introduced, to adapt to the forthcoming introduction of a carbon emissions trading market, thereby combining the carbon emissions cost with the power suppliers benefit; then build the wind farm model to predict wind power output; construct the parameter identification model of wind farms that is proved to be More effective and superior. Predict the wind power based on the wind farm model. Then according to the load and wind power prediction, by scene analysis and reduction, the spinning reserve capacity will be figured out. In order to make the market more open, the paper will calculate the cost of spinning reserve capacity, including capacity costs and opportunity costs. And compare the economy of the different spinning reserve dispatch plans.Because the power market will be more consummate in the future, more competitive, this paper will build a model, in which maximizing the consummate benefit of power producer is the objective function. Certain constraints will be met in this model, including the impact of adjacent time periods, climbing effect of the turbines, in order to get closer to the actual production. The objective function established in this paper, effectively integrated the operating costs and income of the main power generation market, reserve market and carbon trading market, better adapted to future requirements of the power market. Finally, this paper presents an algorithm to work out this model, namely improved particle swarm optimization realized by the MATLAB. While the introduction of a certain probability to accept the idea of accepting a poor solution, so that the stable solution can be got gradually. The algorithm is stable and efficient, while avoiding premature convergence and local optimum solution.Finally, use the practical Shandong power grid as an example, calculating the dynamic economic dispatch of power system with large-scale wind farm, to verify the theory in this paper. After analysis of this paper, with the rise in the price of carbon, the operating profit will increase, but also carbon emissions will reduce; on the premise that wind power can be full access to the grid, the economic and reasonable solution is that thermal power units provide all the spinning reserve; wind power has a significant effect on the system operation profit, especially when wind power is abundant, and the load stays a low level. Hope to provide certain significance for carbon reduction and the development of wind power and the power markets in the future by this paper.