Comparative analysis of tertiary control systems for smart grids using the Flex Street model
Renewable Energy , Volume 69 p. 260- 270
Various smart grid control systems have been developed with different architectures. Comparison helps developers identify their strong and weak points. A three-step analysis method is proposed to facilitate the comparison of independently developed control systems. In the first step, a microgrid model is created describing demand and supply patterns of controllable and non-controllable devices (Flex Street). In the second step, a version of Flex Street is used to design a case, with a given control objective and key performance indicators. In the last step, simulations of different control systems are performed and their results are analysed and compared. The Flex Street model describes a diverse set of households based on realistic data. Furthermore, its bottom-up modelling approach makes it a flexible tool for designing cases. Currently, three cases with peak-shaving objectives are developed based on scenarios of the Dutch residential sector, specifying various penetration rates of renewable and controllable devices. The proposed method is demonstrated by comparing IntelliGator and TRIANA, two independently developed control systems, on peak reduction, energy efficiency, savings and abated emissions. Results show that IntelliGator---a real-time approach---is proficient in reducing peak demand, while TRIANA---a planning approach---also levels intermediate demand. Both systems yield benefits (\geneuro5--54 per household per year) through reduced transport losses and network investments in the distribution network.
|Flex Street, Smart grid, Control system, Comparison method, IntelliGator, TRIANA|
|Energy (theme 4)|
|Organisation||Intelligent and autonomous systems|
Claessen, F.N, Claessens, B, Hommelberg, M.P.F, Molderink, A, Bakker, V, Toersche, H.A, & van den Broek, M.A. (2014). Comparative analysis of tertiary control systems for smart grids using the Flex Street model. Renewable Energy, 69, 260–270. doi:10.1016/j.renene.2014.03.037