Research On Dynamic Economic Dispatch Of Power System With Wind Power

With the rapid development of renewable energy, there is a profound influence on optimal operation of the power industry. The dynamic scheduling including wind power system is to become one of the focus of many researchers. The in-depth study to related issues should be carried out. It will be conducive to better meet the present low-carbon electricity development policies.In this paper, the dynamic economic dispatch of power system with wind power is studied. The research is focus on the model study and the solution to the uncertainty influence factor. It can not be ignored that the development of the green electricity trading mechanism can promote the development of low carbon power. This article analyzes the connotation of green electricity trade. Then we will study the mechanism of carbon emissions trading and green certificate trading based on the analyses. How to optimize the scheduling is studied and it can promote the development of renewable energy.Firstly, the risk factors for the operation of the system are brought about by wind power randomness and uncertainty. Then the risk cost index in dynamic economic dispatch is defined in the paper. Based on the traditional model, the objective function is to minimize the total cost which is established by taking into account the wind power generation cost, risk cost and the negative efficiency of wind farm. Simulating work is carried out with using the basic particle swarm optimization algorithm and the improved particle swarm optimization algorithm to simulate the scheduling model, the results show that the performance of the improved particle swarm optimization algorithm is fast and accurate.On the basis of the study, a multi-objective model is put forward for the dynamic economic dispatch of wind power with considering the risk cost in paper. The function includes minimizing the total cost and the carbon emissions of the system. Based on the original constraint conditions, the total amount of carbon emissions is increased. The Pareto optimal solution set is obtained by using the improved multi-object particle swarm optimization algorithm. The comparison of two kinds of scheduling strategies is proceeded in whether or not including wind power. The result shows that it can meet the requirements of the economic and low carbon at the same time with the introduction of wind farm.Secondly, In view of the problem of the uncertainty of the load demand and the wind power output, namely the problem of existence of the prediction error which affects scheduling results, the load demand and the uncertainty of wind power output, the predicted the errors, a modeling method is proposed based on the scene probability. According to historical data, the probability model is established for the uncertainty factors of the system. The scene is sampled by Monte Carlo random sampling method in order to obtain the initial scene set. The scenes are cut in order to improve operation efficiency by the method of simultaneous backward reduction. Through the comparative analysis of different dispatching modes, we can know that the method of scene probability modeling takes into account the uncertainties of the input variables and avoids the blindness in the process of optimization. It is more in line with the actual situation.Again, with the development of the carbon emissions trading mechanism, the proportion of the auction quota will be arised in the initial quota allocation and increased gradually. Thus it can affect the cost and optimal operation of the power system. Futhermore, it is proposed of a new carbon emissions trading cost model, which considering the influence of two kinds of quota allocation scheme on scheduling at the same time. In this paper, we establish the dynamic economic dispatch multi-objective model with the minimum cost of purchasing power and the lowest cost of carbon emissions trading. Using stochastic simulation of hybrid particle swarm optimization algorithm, the three scheduling models are compared and analyzed. The results show that multi- objective scheduling can achieve the dual goals of low carbon emissions and save cost. In addition, it is analyzed that the impact of carbon emissions trading and auction price ratio on the purchase cost and the transaction cost of carbon emissions of system respectively. The research in the paper adapts to the direction of the development of electric power system in the future, and it provides a certain theoretical basis for its development.Finally, it is studied that the influence of renewable energy quota constraints on dynamic economic dispatch of electric power system. Furthermore, the dynamic economic dispatch model of power system with green certificate transaction cost is proposed. The constraint condition of the green electricity certificate is introduced. The simulation analyses of the effect of renewable energy quota ratio and green certificate price on dynamic economic dispatch of power system are carried out. The results show that the quota requirements higher, the more wind power consumptive amount, namely that the quota system can significantly promote the wind power consumptive and reduce the abandoned air volume. And when the green certificate price is high, the system will actively wind power accommodation in order to get more green certificates. The results of this study have some guiding significance for how to carry out the power dispatch scheduling including the wind power system in the mechanism of the green power certificate trading in the future.It has a certain guiding significance to better use of renewable energy such as wind energy.