| description abstract | As the level of renewable and distributed energy resources (DER) increases in power systems, there is a coincident effort to ensure ongoing reliability. Microgrids are likely to play a central role in this development globally. However, a counterpoint is the high cost of microgrid operations, and there exists a need to develop efficient tools to operate microgrids optimally and economically. In this paper, the potential of demand response (DR) to reduce microgrid operation cost while supporting renewable integration is investigated. Three types of DR, namely thermostatically controlled load (TCL), deferrable load (DL), and elastic load (EL), are explored in the context of various system conditions. Because systems with significant renewables and DER are subject to high levels of uncertainty, the investigation is conducted under a stochastic rolling-horizon optimization framework that leverages the update of renewable generation forecast and the energy market real-time prices (RTP). A case study illustrates that certain system conditions, such as price peaks and moderate temperatures, facilitate best demand response performance. Conversely, inaccurate price forecast information can lead to ineffectual operation of microgrids and result in higher cost. The insights provided by the study of various types of DR are helpful for microgrid design with consumers’ preferences taken into consideration. | |
