Study Of The Unit Commitment Problem Under Energy-conservation Power Generation Dispatching Based On Multiple Objectives Particle Swarm Optimization

The national economy maintains a sustained, rapid and sound development and the national requirement of electric power is increasing. Thus, it's safe to say that China power industry is going through a fast development for releasing the tension on electric requirement at the expense of energy waste and over discharged pollutions. The General Office of State Council published the regulation of Energy-Conservation Power Generation Dispatching. A schedule will be created according to the type and energy waste of all units, based on the regulation. Thus, in the whole work, unit commitment will be set to be the core.Unit Commitment problem is a highly dimension, discrete, non-linear optimal problem. Therefore, it is hard to find a theoretical optimal solution. However, optimal solution has a significant profit, thus people put a lot of efforts to study and try to propose variety methods to solve the problem.In this article, following the energy-conservation power generation dispatch regulation, for the sake of saving energies and reducing pollutions, author proposed a unit commitment model for energy-conservation power generation dispatching. In addition, the objective function considered the changes of transmission loss based on the changes of energy flow and the constrain conditions considered the power output constraints, bus voltage constraints,line power flow constraints,unit climbing rate constraints conditions and etc.Additionally, the paper also proposed a multiple objective particle swarm optimization algorithm to solve the unit commitment problem, based on analysis of three representational algorithms—Dynamic Programming, Lagrangian Relaxation, and Genetic Algorithm, and comparison of their advantage and disadvantage. An elitism set was introduced to store the excellent particles and drive the particle swarm flying to the global optimal. Further more, the model used the congestions of the particles as the principle of generating fitness for each particle.It is the first time that the multiple objectives particle swarm optimization was introduced into the unit commitment problem research under the energy-conservation dispatching. For handling the model of unit commitment problem, it has been adopted the method of using penalty function. Hence, the particles could fly without breaking constraints. On the other hand, the proposed algorithm has been adjusted for fitting real power system, by considering convergence of power flow calculation of each particle. The testing based on the EPRI-36 bus system proved that the optimal results are satisfied.