Power System Load Distribution Based On Multi-Objective Particle Swarm Optimization Algorithm

The Environment problem of electrical power system has had the same status with economic,safe and quality.In the process of generating electricity,a mount of dangerous gases are emissioned,such as SO2?NOX and CO2,which will cause acid rain or greenhouse effect.Therefore,this has became a big problem that how to reasonably adjust the pollution gas emissions along with the index of PM2.5 becames more and more.So,In meeting the unit under different load conditions,we should consider economic and environment goals.Only through this way,the load distribution of generating set becames a two goals problem.In order to solve this problem,we adopt an improved multi-objective particle swarm optimization algorithm(PSO).First,facing the problem of getting into local optimum,the new method about w and c(IPSO)is raised.W and c are related closely and make c change with w.Through this way,we can reinforce global search and avoid getting into local optimum.Second,facing the problem of EELD,the preference multi-objective particle swarm optimization algorithm(HG-MOPSO)is raised,this can get local reference results effectively.This arithmetic makes reference point make the centre of reference,and the algorithm dynamically adjusts reference regions to increase selection pressure and control preference region in the process of moving of reference point.Besides,Through the improvement of the option modes of gBest of PSO algorithm by spherical sector dominance(ss-dominance)proposed in this paper,the search for Pareto optimal set of multi-objective optimization problems is implemented.The arithmetic of HI-MOPSO is used into the EELD,through data and comparision show that the proposed algorithm is effective,meanwhiles,getting the goal of reasonable allocate power,and get a new thinking for multi-objective control problem.