Study Of Multi-objective Trade Planning Of Power System With Wind Farm

With the problems of energy and environmental have become increasingly prominent, wind power as a new form of renewable energy generation, has been paid more and more attentions by the government and people because of its clean, renewable, no-pollution. Wind Power has positive meanings for the response to the national Energy-saving emission reduction strategy and solving the energy and environment problems. Addition, because market environmental interests increasingly diversified, multi-objective problems of the security, economic and environmental-friendly in power system operation are increasingly important.Wind Power research and development is input to yearly increasing in China, the proportion of wind power installed capacity in power grid is increasingly large, wind power has adverse effect to power system planning, electric power quality, voltage stability and system dispatching and trading plan. Therefore, researching the influence of wind power in system has great significance.In this thesis, by the means of OPF, mainly study on the optimal trade planning with wind farms system considering rand wind speed. The main content is as followed:(1) In this thesis, introducing a new algorithm of the optimal power flow in wind farm system considering the random wind speed. On the one hand according to the Wei-bull distribution of wind speed, the average mechanical power of wind turbine can be derived. Taking the wind turbine slip as state variables, the average mechanical power and electromagnetic power balance equation is added to the traditional optimal power flow. On the other hand we analysis wind turbines model in Steady State Analysis of Power System, and the Optimal Power Flow Model of power injection from wind generator node is built.(2) This thesis presents a multi-objective trade planning model with wind farm influence considering random wind speed and the corresponding algorithms based on power injection model, and a new multi-objective trading planning model with wind farm influence considering random wind speed, which consider the minimization of power purchase cost and the minimization of pollutants emission. The solving process is as follows: first, each single objective deterministic model is solved, getting the corresponding objective function value. Secondly, each objective function is fuzzed through defining objective membership function, then multi-objective programming problem is reformulated into nonlinear single objective programming problem by means of fuzzy satisfaction-maximizing. Finally, the nonlinear programming algorithm is used to solve the single objective optimization, obtaining the multi-objective trade planning.(3) It deduced and analyzed the relation between the control parameters of wind generators and multi-objective function. The Jacobian matrix at optimal operating point of system with wind farms considering random wind speed is also quantitatively analyzed. Thus obtains the sensitivity information of system at each trade mode. The computation results of IEEE-30 and IEEE-39 node system demonstrate the efficiency of the model and algorithm proposed in this thesis.