Robust Optimized Scheduling Of Power Grid Connected With Intermittent Power Sources

With the rapid development of economic, conventional energy sources face exhausteddilemma and a new type of renewable energy is needed urgently. Represented by photovoltaicand wind energy have great value for development because of its inexhaustible features, theoperation of large-scale intermittent power supplies connected to the grid is the trend ofdevelopment in the future. However, the output of intermittent power has some characteristics,such as intermittent and wave character, and is effected by natural conditions easily, so theaccuracy of intermittent power output prediction is still low. With large-scale intermittentpower supplies connected to the gird, the effects of intermittent power output uncertainty onthe reliability of system operation are increasing, traditional intermittent power optimizeddispatch method, which is based on certain factors to analysis and calculate, does not considerthese non-certainty factors. At this point, the original deterministic optimization methods willno longer apply, and the effects of wind power output’s uncertainties during the process ofdispatch decisions must be fully considered.Robust optimization is a powerful tool to solve uncertain problems, which describesuncertain variables by the form of "Set"(rather than by the probability distribution), it makesthe constraints can be met within the range of uncertainty variables, and then establishesrobust model of optimization objective function in the most extreme case. However, due torobust optimization is at the expense of the economy to exchange for the promotion ofrobustness, the optimal results are often conservative.In this study,aiming at the joint dispatch of intermittent power in conventional powersystem and thermal power,the application limitation of the large-scale intermittent powerintegrated access to the system,taking full advantage of clean energy, improving reliability ofthe system,ensuring the efficiency of thermal power units, thus to established a model for anadjustable robust optimal scheduling matched with reliability and economy of a large-scaleintermittent collaborative power system during uncertainty period.Intermittent power belongs to renewable energy, it has many advantages, such as lowgenerating cost, fast speed of generating start, easy to adjust and so on. In view of thedevelopment degree of conventional intermittent power and the proportion of it in the electricpower system in the future, this thesis will study the coordinated operation of large-scaleintermittent power, which are connected to the grid, and establish adjusted robust optimizationdispatching model of the collaborative power system of large-scale intermittent power withreliability and economy coordination, which see the lowest cost of operation and the minimum fluctuations of thermal power’s output as the objective. In addition, in order to takethe diversity of individuals and convergence speed into account in the process of differentialevolution, a new compound differential evolution algorithm (CDE) is designed in this thesis.The algorithm includes a series of operations, like individual ranking, population partition,compound differential evolution and population restructuring. CDE solves the contradictionbetween the depth optimization and velocity existing in swarm intelligence evolutionaryalgorithm skilfully through a fusion of above strategies and technique. Finally, the sampleapplication is carried out to verify the validity and practicability of the model and method.