Research On Optimization Methods Of Environmental Economic Dispatch Of Power System

Scheduling is one of an important part of the normal operation of power system, it must ensure the reliable, uninterrupted and high-quality power supply of load. Economic dispatch plays an import part in saving all the social cost of production. With the improvement of electricity use in social production and all aspects of the life, the electric power industry discharges a large amount of pollutants causing severe damage to the environment in the process of power generation, meanwhile restrict the sustainable development. So, it’s necessary to convert the dispath emphasis to environmental economic diapath which considering economy and environmental protection. It is significant to ensure efficient use of resources, taking into account the capacity of the environment by using multi-objective optimization techniques to provide a reasonable solution for environmental economic dispatch of power system.For the environmental economic power dispatch, based on the concepts and features of crisscross algorithm and combined the concepts of Pareto dominant, this paper expands crisscross optimization algorithm (CSO) to the field of multi-objective optimization, proposes a multi-objective crisscross optimization algorithm (MOCSO). In the model of the proposed algorithm, this paper presents a new double cross mechanism to enhance the ability of crossing feasible regions, so that the Pareto optimal solution may falls within the feasible region. Nondominated selected principle is designed to select non-dominated solutions to retian in an external elitist archive. Meanwhile, using crowded maintain mechanism to update the nondominated solutions in the external elitist archive. Finally, fuzzy theory is used to obtain the best compromise solution. And detailed procedure of the algorithm is given.Then on the basis of power system optimization theories, this paper extabilshes a model of static environmental economic dispath considering both the fuel cost and emissions. Following, the models of static dispatch in uniqued period is converted to dynamic dispatch in continued period, and a model of dynamic multi-objective environmental economic power dispatch considering the influences of random load is extabilshed. The paper presents the process of MOCSO solving the environmental economic dispath problems of IEEE 9、IEEE 30 and IEEE 39 bus test systems. The results show that system statuses have been significantly improved, reducing operating costs and network losses and operating efficiency and environmental protection have been improved. Compared to other algorithms, MOCSO exhibit more superior scheduling scheme.At last, combine the related mathematical concepts of fractional programming and Dinkelbach’s algorithm, a nonlinear fractional programming based multi-objective optimization approach is proposed. In the optimization process, a dual model mechanism with nonlinear constrain is provided. Model I contains a nonlinear fractional objective function. Model II contains a quadratic function of fuel cost. In the process of solving environmental economic dispatch optimization problems, Dinkelbach’s algorithm is adopted in model I to convert the nonlinear fractional objective function into a non-fractional fractional objective function. The total emission obtained in model I is further taken as a constraint condition in model II. Moreover, crisscross optimization algorithm is applied to solving the two models in IEEE 30 bus test system. The results show that the proposed method exhibit high accuracy and is easy to operate, demonstrates obvious advantage over other algorithms in terms of simplicity, stability and comprehensive performance on fuel cost and total emission.