Modeling Energy and Technology Choices in Smart Regional Energy Systems

This paper deals with the modeling of the long term evolution of regional energy systems in a smart city and smart grid environment. It is shown that demand response and distributed grid energy storage, driven by dynamic pricing schemes, based on locational marginal costs, can be represented in the linear programming framework of the models of the MARKAL/TIMES family. An implementation in the ETEM-SG modeling tool, which is an energy model tailored to the representation of regional energy systems is then described. An illustration is provided, based on energy scenarios concerning the Arc L ́emanique region in Switzerland. Finally the SESCOM modeling framework, which is under development in a project on smart energy systems for smart cities in Qatar is introduced. This modeling approach expands ETEM-SG to the representation of useful energy demands influenced by changes in life styles, smart transmission and interconnection between regions and market price revelation at distribution levels

ETEM-SG: Optimizing Regional Smart Energy System with Power Distribution Constraints and Options

This paper gives a detailed description of the ETEM-SG model, which pro- vides a simulation of the long term development of a multi-energy regional energy system in a smart city environment. The originality of the modeling comes from a representation of the power distribution constraints associated with intermittent and volatile renewable energy sources connected at the transmission network like, e.g. wind farms, or the distribution networks like, e.g. roof top PV panels). The model takes into account the options to optimize the power system provided by grid friendly flexible loads and distributed energy resources, including variable speed drive powered CHP micro-generators, heat pumps, and electric vehicles. One deals with uncertainties in some parameters, by implementing robust optimization techniques. A case study, based on the modeling of the energy system of the “Arc L ́emanique” region shows on simulation results, the importance of introducing a representation of power distribution constraints and options in a regional energy model