Comprehensive Environmental Economic Dispatch Of Power Systems With Multiple Types Of Power Sources

As the energy crisis and environmental pollution have become more and more prominent,green renewable energy,mainly wind and solar energy,has developed rapidly worldwide,and the natural complementarity between the two,The combination system has become an important means to make full use of these two renewable sources,but its large-scale connection also has a great negative impact on the power system.Therefore,in order to solve the problem,scholars at home and abroad have done a lot of research on the joint system scheduling of energy storage device adding wind light electric field.As a result,the dynamic environmental economic scheduling of the combined system has also become one of the research focuses.The in-depth study of the scheduling problem of the combined system is conducive to meeting the macro-strategic requirements of the country's "energy conservation and emission reduction".In this context,this paper takes the dynamic environment and economic scheduling of the combined system of scenery storage as the framework,and has done some work on model research and solving the uncertainties of the new energy source of scenery,and has conducted research on this model and method.Its main contents are summarized as follows:(1)Considering the randomness of the scenery power supply,taking the system's comprehensive operating cost and pollution gas emissions as the optimization goals,and taking into account the constraints of power balance,power supply output,unit climbing,and energy storage devices,The positive and negative rotation reserve of the system is guaranteed in the form of opportunity constraint.Finally,a dynamic environmental economic scheduling model based on opportunity constraint planning is established.(2)For the more complex opportunity constrained programming model,this paper first uses the traditional multi-objective solution method to convert the multi-objective function into a single objective function,and then uses the particle swarm algorithm based on Monte Carlo random simulation technology to solve the joint system DEED model.The scheduling schemes under different confidence levels and the scheduling schemes of energy storage devices are compared in detail.The results verify the performance of the random simulation particle swarm algorithm and the correctness and validity of the model.At the same time,the results show that the wind power field can effectively solve the problem of wind and light disposal.(3)On the basis of the established joint system model,the multi-objective particle group algorithm is used to solve the problem,and its Pareto optimal solution set is obtained,and the optimal compromise solution is determined by the hierarchical composition class mixed strategy game theory.Then,we compare in detail the Pareto optimal frontier and the traditional multi-objective solution and multi-objective algorithm of energy storage device.The numerical results show that the optimal solution set obtained by the multi-objective intelligent algorithm can evaluate the advantages and disadvantages of the multi-objective solution more comprehensively and objectively than the single solution under the traditional multi-objective solution.The results show that the coordinated dispatching of wind power,photovoltaic green renewable energy and energy storage device is helpful to the green economy energy saving and emission reduction.