Planning Of Transmission System With Large Wind Farm Based On Uncertainty Theory

With the growing demand for energy and conventional fossil energy depletion, clean and renewable energy was thought more and more by people. Wind power, as a typical abundant and renewable clear energy, has tremendous development potential. Because wind is random, intermittent and non-adjustable, the wind power output is uncertainty. And there are also some other things have uncertainties, such as the load of new nodes, forced outage of wind turbine, the switching and updating of transmission equipment and changes in load, and so on. That bring new challenges to the network expansion planning. Considering the uncertainties in the transmission network expansion planning is necessary.This paper studies the characteristics of wind energy resources, and makes the two parameters of the Weibull distribution as the wind speed probability statistical model, then calculated the parameters of evaluation of the value of wind energy resources. On this basis, the impact that large wind farm add into the power is analysed, and a wind turbine output model and malfunction models are established. Considering on the uncertain variables that contained the both random and fuzzy aspects, this paper established a model based on the uncertainty theory for network expansion planning. The objective function in the model is aimed to make the random fuzzy expected value of the total cost of investment and construction of lines minimum.Then, aiming at solving the shortcomings of PSO, such as easy for the local minimum, premature, stagnation and so on, the feasible strategy to improve PSO was analysed. And three main elements to improved algorithm was summed up: inertia weight, neighborhood topology and the learning factor. The above-mentioned transmission network planning model based on uncertainty theory is sovled by combining the random fuzzy simulation and IPSO. The calculations in Garver6 simulation show that the proposed model is reasonable and efficient.