Research Of Component-based Approach Load Modeling Based On Cloud Computing Platform

The mathematical model of power system load is the foundation of power system digital simulation,the precision of mathematical model directly affects the accuracy of simulation results planning and decision-making.In the past few decades,the generator,excitation system and the original system of modeling technology has been developed by leaps and bounds except power load,bacause of Time-varying,dispersive and nonlinear.Component-Based Modeling Approach,one of the load modeling methods is also out of date.With the development of global energy Interconnction strategy,China has to face a lot of problems.Complexity of the grid is increasing,the contradiction between the security and stability operation of power systems and the outdated load models is irreconcilable.Therefore,it is very important to establish a comprehensive load model adaptable to the country's situation based on the smart grid.Applying the Component-Based Modeling Approach,this dissertation presents a power load model,which attributes to the big data environment for the smart grid,the enormous amount of data acquired from various novel data collectors and the high performance cloud computing platform powered by MapReduce algorithm.This dissertation also introduces the static load model,the dynamic load model,the comprehensive method of load characteristics and identification of model parameters.For the first time,this dissertation is proposed to acquire data of power load composition with the current facilities in the smart grid environment.The construction method of information collection module based on cloud platform is designed.The module uses the MapReduce algorithm.MapReduce provides a programming model that abstracts the problem from disk reads and writes,transforming it into a computation over sets of keys and values.The important point for the present discussion is that there are two parts to the computation,the map and the reduce,and it's the interface between the two where the “mixing” occurs.Compared with traditional methods,this method can greatly speed up the data processing,fault tolerance and distributed system can be a good solution to the complex power grid structure.And the data can be easy to get by using this module.In addition,this article also developed a human-computer interfaces for software users who brought a best software application experience.Finally,the study uses the data as the experimental object,and uses the MapReduce algorithm and dynamic equivalence to modeling the static and dynamic load.The simulation results show that the static load model describe the load behavior well,and the cloud computing platform can work quickly and accurately.The dynamic model verifies that the load model established by the improved weighted average method fits the load characteristics well under the effective classification of the power load.