Saving Potential Analysis Of Energy-efficient Power Plant Project

In recent years, the world’s energy crisis is becoming more and more serious, at the same time the pressure of environment protecting in every countries are also increasing. The sustainable development of power industry attracts more concerns of the community and become an important problem. Facing the stress of power development coming from rise in electricity consumption gradually, our country strengthen the construction of new energy supply, and start to realize the importance of Demand Side Management (DSM) conducting at the user side.DSM contains a wide range of contents, one important content of them is to encourage and promote the users to save energy and reduct emissions. However, there are many types of users and different energy saving measures, these measures are hard to conduct. The appearance of Efficiency Power Plant (EPP) solves these problems, it is a advanced management technique that can help the user side achieve energy conservation, it gets many saving reconstruction measures together, manages the whole project which consists of many reform measures effectively, and helps the project implementers to disperse project risk. But when users build efficient power plants, they will find that the transforming measures are wide range of large, and then how to find atheir own saving potential and select the appropriate transformation project is the biggest problem.This thesis mainly studies the optimization problem of project saving potential of EPP. Firstly, develops a saving potential analysis process aiming at solving the issue that the transformation of EPP lacks plans, describes specific content of each model in each process, this process can help the user arrange transformation of EPP more systematically and tap the user’s potential of saving to the maximum extent. Secondly, on the basis of saving potential analysis process, establishes the optimization model of electricity savings potential and model of peak load shifting potential, with these two models, the optimal value of energy efficiency power plant project can be calculated quantitatively under a certain capital investment.Considering the characteristics of the application of this two models, the particle swarm optimization(PSO) and the gray comprehensive clustering decision are choosed to solvemodel. Numerical example shows that these models can help users make saving plan and tap their own power-saving potential, thus be more targeted for energy efficiency transforming.