Reputation-based electricity scheduling scheme for complex network of user electricity consumption

With the emergence of various high-powered electrical equipment, demand for electric energy has increased rapidly. Subsequently, it highlighted some issues electricity consumption, such as adjustment consumption peak. Although many scheduling schemes have been proposed to adjust and control user load current regulation is not accurate effective because different regional grid users a complex network system. In this paper, we propose reputation-based scheme whose purpose accurately related further improve our scheme, first model consumption. Then construct reputation calculation method users, where calculated one basis assigning tasks calculating price subsidy received by who complete tasks. Further, use machine learning train computation calculate coefficients load, then are adjusted based on coefficients. Finally, corresponding assigned selected respectively adjusting these users. Experiment results show effectiveness scheme. Our can effectively values their historical data, according real-time coefficients, so efficiently