Driven by the climate change and energy shortage, smart grid has obtained rapid growth worldwide as a solution for the sustainable development of human society. How to extract information from the demand side big data and optimize the grid operation based on the two-way communication infrastructure and advanced metering infrastructure of the smart grid has become an important research topic. As a technology of data analysis and information filtering, personalized recommendation technology is expected to support the information retrieval from the grid data, and recommend energy-oriented products/services/suggestions to the end user. This paper firstly introduces the basic principles of personalized recommendation technology as well as the prospect of introducing this technology into the demand side. Then, some key technologies of implementing the personalized recommendation systems in the smart grid are presented. Furthermore, this paper reviews the existing research in this field and discusses some potential and promising demand side recommendation systems in future. Finally, some challenges of practically deploying the personalized recommendation systems in the smart grid are examined.