Driven by the energy crisis and global warming problem, smart grid was proposed in the early 21th century as a solution for the sustainable development of human society. With the two-way communication infrastructure available in smart grids, a current challenge is to interpret and gain knowledge from the collected grid big data to optimize grid operations. Service recommendation techniques provide promising tools to discover knowledge from the grid data, and recommend energy-aware products/services/suggestions to the smart grid participators. This paper is among the first to investigate the prospective of introducing service recommendation techniques into the smart grid demand side management (DSM). In the first part of the paper, the backgrounds of smart grid DSM and service recommendation techniques are reviewed, followed by the presentation and discussion of key technologies that can facilitate the development of smart grid recommender systems. An outline on potential application scenarios of smart grid recommender systems as well as future challenges are also provided.