Research Of Microgrid Optimal Operation Base On Multi-objectice

The microgrid, which is a new type of energy network supply andmanagement structure, provides a channel for distributed generations to accessthe low voltage distribution network. It can reduce energy consumption andenvironmental pollution, and at the same time it can also improve the reliabilityand flexibility of the system. We need to optimal scheduling the distributedgenerations in the microgrid in order to highlight the characteristics of themicrogrid. First, the distributed generations in the microgrid have differentoperating characteristics, and them also can be influenced by objective weatherconditions and load demand easily; second, the environmental benefit is paidmore and more attention in consideration of the economy at the same time for alarge number of renewable energy in the microgrid; lastly, the kinds of powermarket plan also affects microgrid operation efficiency. All of these increasethe complexity of microgrid optimal scheduling.This paper put forward the microgrid multi-objective optimal operationmodel with different operation strategys base on the microgrid operation needs.The maximum fuzzy membership is introduced to solve the multi-objectiveproblem, the optimization problem is solved by a kind of adaptive simulatedannealing genetic algorithm(ASAGA). Based on simulating of the microgridsystem, this paper compared and analyzed the optimal results in the differentobjective functions and operation strategies. The main work is as follows:1. The microgrid optimal operation model which including the windpower generator, photovoltaic cell, micro gas turbine, fuel cell and battery hasbe set up. And putting forward the multi-objective functions includingoperation cost and environmental protection cost. Four different microgridoperation control strategies was be put up based on microgrid internal energystructure and external market plan.2. The maximum fuzzy membership which based on the fuzzy theory isapplied in the microgrid multi-objective optimal operation, and evaluating eachtarget satisfaction by fuzzy evaluation. The global convergence of the geneticalgorithm(GA) was improved, and introducing the simulated annealingalgorithm(SA) which has a strong local convergence at the same time, then akind of adaptive simulated annealing genetic algorithm is formed to solve themicrogrid optimal operation problem. 3. For the different objective functions and operation strategies in themicrogrid, the simulation results show that the multi-objective model is morereflect the operation efficiency of microgrid than the single objective model. Italso showed that the economy is the main factor to influence the microgridoptimal operation, the environmental is the second factor. The two-way energyexchange and time-of-use electricity price operation strategy can response themarket demand effectively, and reduce the operation cost of microgrid greatly.