| With the full deployment and implementation of "Thirteen Five Years Plan",China's economic development has entered a new phase. The rapid development of all walks of life made the electricity industry has higher requirements. the power industry as the country's economic, social and livelihood lifeblood of foundational industry, it will face significant improvements. Currently, along with economic development and people's living standards improvement, the power requirements continue to increase. Not only the need to ensure energy economy, but also taking into account the level of power quality and safety, reliability and stability. From a global view of energy, coal, oil, natural gas and other non-renewable energy are shortage. Besides, the depletion of non-renewable energy sources will lead to combustion pollution on the environment. It is necessary that the power industry needs to produce environmentally clean electricity. Modern power has entered into a multi-benefit age, and it related to global resources, environmental protection and sustainable development. At the same time, the requirements if power quality and reliability improve continually, the future development of power industry needs to become the safer and more reliable, clean and environmentally friendly generation,transmission, distribution and transform.At present, China has entered a stage of comprehensive construction of electric power. In the electric power construction, reasonable generation, transmission,distribution and transform has many advantages. It not only enhances the reliability of the power grid, but also improves the economics of the power grid, saving manpower and financial resources. Therefore, power system optimization problems need to be solved, electricity generation needs to be optimized, long-distance transmission of electrical energy needs to be optimized, voltage quality needs to be optimized.However, power system optimization problems are nonlinear, more constrained,non-convex, high-dimensional problems. Firstly, conventional mathematical calculations are difficult to solve such problems; secondly, the power system multiobjective optimization problem of the conventional methods are often solved by changing multiple objectives problem into a single objective problem. It is used by the weighting. However, it ignores the relationship between objective functions, and the weighting factors are not enough reasonable. It can not provide a set of suitable solution to the decision makers.Based on the above problems, this paper proposes an improved multi-objective particle swarm algorithm and it bases on the PSO algorithm.we improve PSO with the random black hole strategy, the dynamic update of inertia weight and learning factor, NSGA-II non-dominated sorting, crowding distance sort, leading particles selection, small probability random mutation.It results that the algorithm accelerates the convergence rate, improving the convergence precision, having good stable results, forming the Pareto front, more uniform distribution and more diverse of the solution. The proposed algorithm provides decision makers with multiple sets of Pareto frontier feasible solution to reach a better decision support. Finally, the improved multi-objective particle swarm optimization algorithm is applied to the power system of environmental economic dispatch calculation, and it will get both economical and environmentally friendly thermal power plants dispatch. What's more, the proposed algorithm is used to solve cascade hydropower stations optimization dispatching problem, and it results to obtain the optimal dispatch of cascade hydropower stations. Last but not least, theproposed algorithm is employed to deal with the power system reactive power optimization problem. It takes power loss, voltage quality and good stability into count. The results provide Pareto optimal front and a set of feasible solution for decision makers. |
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