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

In recent years,with the increasing demand for environmental protection,the state put forward the policy of energy saving and emission reduction,and implemented it in the whole country,which has been actively responded by people.As one of the key enterprises in the country,the State Grid should respond to the call of the state,actively implement the policy of energy conservation and emission reduction,and strive to reduce coal consumption rate,increase power generation and reduce environmental pollution.In order to achieve this requirement,we should not only increase gas purification equipment,but also try hard to reduce the emission of pollution gas and reduce the cost of electricity generation by adjusting the generating capacity of each generation part.How to reasonably allocate the generating load of each generating unit to minimize the coal consumption rate and minimize the environmental pollution under the condition of known total power generation? This is the hot issue of EELD nowadays.In order to solve this problem,an improved multiobjective particle swarm optimization(PSO)algorithm is adopted in this paper.First,the basic PSO algorithm is improved.Aiming at the shortage of PSO is easy to fall into local optimum,the selection strategy of W and C linkage learning factor,so that the improved algorithm enhances the global search to avoid falling into local optima;while reducing the complexity of control algorithm,improve the accuracy of the algorithm,and the simulation and verification.Secondly,in order to obtain an ideal non-inferior solution,a multi-objective PSO algorithm based on grey correlation is proposed for multi-objective problems such as EELD.The grey correlation degree is combined with the multi-objective algorithm,and the global optimization is selected through the grey correlation degree.The improved algorithm is simulated and verified.Finally,the improved multiobjective PSO algorithm is applied to the EELD,and the data analysis and simulation are carried out to verify the feasibility of the improved method.The improved method solves the problem of EELD well,and puts forward a new idea for solving the EELD problem in the future.