Research On Load Profile Analysis And Load Management Optimization

With the continuous development of the economy, the power load has grown rapidly in recent years. As a result, the traditional method, increasing the investment on power supply side, is no longer efficient or cost-effective. Demand side management can be used to motivate demand side resources to participate in the power system peak shaving, gradually plays an important role in easing the power supply crisis. Owning to the lack of electricity market in China, load shedding and rolling blackouts are the main methods to manage load profiles, which bring disasters both to the power utilities and the power consumers. Besides, the ignorance of power consumers’load profiles also leads to the negative effect in demand side management.In this paper, based on the existing research, several researches on the analysis of power consumers’load profile as well as on the demand dispatch optimization model based on power load clustering have been introduced.Firstly, a new DSM-oriented combinational electrical load analysis method is proposed. Density based clustering is applied to gain the representative load profile of single customers and k-means algorithm with cosine similarity is used to cluster customers into different clusters according to their similarity of load profiles. The results show that this new method could effectively find the representative load profiles and recognize the different load profiles, and thus confirm the value of this method in DSM applications.Secondly, a demand side bidding and dispatching mode for interaction demand side resources based on power consumer classification is proposed. Power utilities give interacting recommendations for different customer types and dispatch power load considering interaction load. Besides, a relevant mixed integer linear programming model is developed and introduced. The simulation shows that the bidding and dispatching mode could accomplish the peak shaving work as well as reduce the negative effect on both utilities and consumers.At the last, based on the former research, a prototype with B/S framework, which realizes load analysis and load management optimization applications, is introduced. The prototype is developed under several advanced techniques, Flex/Java/Oracle are all picked to build the prototype, and the application structure and the detailed technologies are introduced. The combination of BlazeDS and Tomcat realizes the web service function, leading the prototype to give support to advanced demand side applications.