Automated demand side management in microgrids using load recognition

Microgrids missing a tie-line to a supporting grid may suffer from a lack of power generation. This is especially the case if they are heavily based on renewable energy resources as e.g. in remote area electrification. This paper follows a demand side management approach, where unessential loads get selectively disconnected from the grid in an under-generation scenario. In order to automatically detect unessential loads, load recognition on the basis of measured consumption data can be performed. In this article, different approaches for automatic load recognition are analyzed. It is found that especially a Hidden Markov Model based approach is suitable to fulfill the given task and provide good recognition rates. The recognition system is aimed to be part of a novel control architecture for off-grid microgrids in developing countries.