Multi-power Supply Power Systems Power Generation Efficiency And The Study Of Indicators Optimal Dispatching

With the energy and the environmental pollution intensify day by day, the generating system which is the most consumes the electricity have the responsibility to carry on the energy conservation to fall consumes. Short-term optimal scheduling of hydropower and thermal power ystem can effectively improve the generation efficiency and reduce energy consumption. Hydro-thermal short-term optimization dispatch is a multi-dimensional constraints, complex, nonlinear problems, is also a hot topic of current research, study of this issue is now concentrated in the following areas, how to establish an appropriate model, select the appropriate indicator (goal) and its solution method etc.We introduced the background and significance of this article first, made the detailed elaboration for the present situationin algorithms, and selection of indicators of the multi-power source electrical power system optimization dispatch, which composed of the hydropower and thermal power.The operating characteristics of hydrothermal power system have been studied deeply. Detailed analysis the influence of hydro coupling characteristics of cascade hydropower stations in time and space; On the basis of the research and analysis of the standard particle swarm algorithm and data envelopment analysis algorithms, combined with the sensitivity analysis method, established the DEA sensitive model and apply it into the economic load dispatch of thermal power, take10thermal power plant in Guangxi as an example to calculat, the results show that the algorithm model is feasible and effective.The multi-objective hydrothermal optimal scheduling model was established, including cascade hydropower stations minimum water consumption, the coal consumption to be smallest and the pollutant discharge smallest. The particle swarm optimization was inproved, then testing the improved and not improved particle swarm optimization,we found that the inproved particle swarm optimization convergence accuracy was better than particle swarm particle.Then using the improved particle swarm optimization to solve the multi-objective questions. Using of Euclidean distance evaluation function to put the three conflicting and different dimensions multi-objective questions into the identical standard condition, then using the improved particle swarm optimization to optimize the objective function have been processed. To improve the uniqueness of the results of the particle swarm optimization algorithm, using the DEA dual model to evaluate the cost-effectiveness analysis of the optimal scheduling. Taking10thermal power plants and eight cascade hydropower stations on the Red River Basin of Guangxi grid one day’s running for example to simulating calculat, the data show that the hydropower commit the a greater load in the scheduling, and equivalent to replace the thermal power, reduced coal consumption and emission of pollutants, therefore the model help to achieve the energy saving, it can effectively improve the efficiency of power generation from the perspective of resource allocation; improved particle swarm optimization with high precision convergence, it can quickly find the global optimal solution; Policy-makers get a number of scheduling schemes after use DEA model to evaluat the optimal scheduling results, they can select the appropriate from the perspective of economic, environmental, shipping, irrigation scheduling program.