Multi-objective Kinetic-molecular Theory Optimization Algorithm With Application to Automatic Demand Response

摘要

Intelligent household as an extension of smart grid in the user side highly integrates loads management and control. Home energy management system (HEMS) with automatic demand response (ADR) is a key part of intelligent household, which is able to fit their electricity demand without changing the residents' habits too much. Furthermore HEMS schedule their power consumption to save energy, reduce emission, shift peak load and reduce the financial burden. The characteristics of various electrical devices were analyzed in this paper, and a mathematical model of ADR was established. Multi-objective kinetic-molecular theory optimization algorithm was used to optimize the solution of the ADR model. Implementation results showed that the KMTOA was more accurate and reliable than other algorithms for the complexities of model and data size considered in this study. Compared with some similar algorithms, the multi-objective kinetic-molecular theory optimization algorithm shows more advantages.