Research On Optimal Environmental/Economic Dispatch Of Power Systems

With the increasingly serious situation of global energy and environmental issues,the traditional economic dispatch for single generating cost objective has been difficult to meet the national macro strategy of “energy-saving and emission reduction”. The environmental/economic dispatch which can consider both environmental protection and economic benefits simultaneously has gradually become a research hotspot in the field of power optimal operation. Moreover, because the clean energy such as wind power, and the electric vehicles with environmental benefit and high efficiency, have great advantages in the adjustment of energy structure and reduction of pollution emissions, the related industries have been developing rapidly in recent years. Under the above background, this dissertation takes the framework of environmental/economic dispatch, launches research on the model and method of static/dynamic dispatch, and the dispatch problem with wind power and electric vehicles. The main work is summarized as follows.(1)A new environmental/economic dispatch method based on multi-objective optimization and multi-attribute decision making theory is proposed. The solution process includes two steps. Step one, the multi-objective evolutionary algorithm based on decomposition is applied in the field of power dispatching. So the approximation of dispatching optimal front is converted into single objective optimization problem based on neighborhood resource sharing using decomposition and evolutionary strategies. And effective treatment strategies for complex constraints to improve the algorithm are proposed simultaneously. Finally, the dispatch method based on MOEA/D to obtain Pareto-optimal solution set is established. Step two, the multi-attribute decision making theory based on the quantization mechanism of fuzzy objective satisfaction is adopted to help the decision maker determine the optimal compromise solution. This part is the dispatching algorithm basis of this dissertation.(2)The static environmental/economic dispatch model, and the dynamic model considering the coupling relationships between variables in different dispatchingperiods are established with the objectives of fuel costs and pollution emissions. And the constraints of active power balance, unit output, branch transmission power and unit ramp rate in load dispatch problem are also included. On the basis of above solution framework proposed in this dissertation, the dynamic heuristic constraints processing method based on classification adjustment and related evolutionary control strategies are presented to obtain the optimal dispatching scheme for static and dynamic models. Simulation results show that, the proposed algorithm can provide assistant decision guidance for decision makers, and has good convergence speed and accuracy comparing with other optimization methods.(3)To cope with the impacts of grid-connected wind farm on power system economic dispatch, a new dynamic environmental/economic dispatch model with wind power uncertainty is proposed. The model can consider the optimization of both fuel cost and pollution emission objectives simultaneously, and deal with the random fluctuation characteristic of wind power and its prediction errors by setting the related positive and negative spinning reserve constraints. Meanwhile, the factors of power network loss and the valve point effect are also included in the model in order to make the final dispatching results more in line with the actual system needs. The simulation results show that, the participation of wind energy in power dispatch is conducive to improve the economic and environmental benefits of the system, but with the increase of wind power, the demand of its randomness for the system reserve capacity is also increasing which will ultimately affect the safe and reliable operation of the power grid.(4)To solve the large-scale access problem of electric vehicles, a new dynamic environmental/economic dispatch model with V2 G mode is proposed. The model comprehensively considers the coupling of electric vehicles’ traffic attributes and energy properties, the factors of the owner travel demand, the battery charge and discharge characteristics, etc. Under the premise of meeting the system energy constraints and user needs, the V2 G behaviors of electric vehicles are dynamic managed in order to balance the economic and environmental benefits simultaneously.Moreover, according to the complex constraints of the model, a new stepwise dynamic processing method for decision variables is presented. The simulation resultsshow that, the electric vehicles, which participate in power dispatching with interactive V2 G mode, can significantly improve the economic environmental index and load characteristics of the power system under a certain access level. Furthermore,the cooperative energy dispatching with other renewable energy sources(such as wind power), can also contribute to the energy-saving and emission reduction of the power system.