Multi-objective Optimization Study On Electric Power Engineering Projects

As the basic energy industry and the first basic industry, the strategic position of the electric power industry in the national economy is very important. After the reform and opening up, economy in China has been developing rapidly which leads the fast development naturally of the electric power industry. Therefore,it is a trend to expand the scale of the this industry and in addition, it is great of significance to study whether the target can be finished on schedule or not for the continuous rise of power engineering projects. The factors that affect the success or failure of electric power engineering projects are many, generally including the construction period, cost, quality and so on. Thus, in order to guide the management of electric power engineering projects better, the work of how to optimize the electric power engineering project reasonably and scientifically matters.In view of the characteristics of the electric power engineering projects in China, this paper deeply analyzes the connotation of the project’s duration, cost and quality and the relationship between the three and the whole project, and establishes the quantitative model of power project duration, the quality and the quality of the project. The main research content of this paper is:(1) According to the characteristics of electric power engineering project, the content of the project, the cost and the quality of the project and the relationship between the three in the whole project. On this basis, the model of three objective functions including construction period, cost and quality are established and it is more applicable.(2) Artificial bee colony algorithm(ABC) is a swarm intelligence optimization algorithm, which simulates honey bees. It provides a new method to solve the problem of the optimization of the scientific field. On the basis of the standard artificial bee colony algorithm, the paper proposes a multi-objective artificial bee colony(MOABC) algorithm to solve the multi-objective optimization problem. Combined with multi-objective artificial bee colony algorithm, power engineering project duration cost quality optimization model is established, and the Pareto optimal solution can be obtained by optimizing the cost and quality of the project.(3) The feasibility and effectiveness of the multi objective artificial bee colony algorithm are verified by the special construction work of the Beijing gas thermal power project. The results show that the multi objective artificial bee algorithm can achieve the construction scheme, which can achieve the project "short duration, low cost and high quality".