Within the framework of AMBASSADOR, a collaborative project funded by European Commission under FP7, a Modelica® library for the modelling of thermal-energy transport in district heating systems has been developed. This library comprises detailed models of the distribution and consumption components commonly found in district heating systems. In this paper, the detailed models are discussed, along with their validation against Apros® and IDA-ICE® Software. The results show that, although most of the models perform similarly, they do not equally reproduce the dynamics. Some of the limitations detected from the simulation results are currently being solved in new developments within the EU-funded INDIGO project. Furthermore, with the aim of avoiding problems derived from the simulation of large models, the methodology for developing reduced mathematical models, implemented in Simulink®, is also presented in this research work. This methodology includes identifying the relevant model dynamics. During the procedure, additional information about the models can be obtained. For instance, the mass flow rate and the temperature can be assumed to be decoupled, without losing accuracy in the case of the distribution pipe model

The European research project AmI-MoSES is focused on developing energy efficiency enhancement service solutions for SME manufacturing companies. The planned service concept is based on Industrial Ambient Intelligence (AmI) Reference Architecture and Energy Key Performance Indicators in the form of Energy Use Parameters (EUP). EUP indicators are based on monitored energy consumption data (ECD), other measured data and related energy use context data showing in detail how energy was used. AmI-MoSES project focuses on enabling manufacturing SMEs to efficiently and promptly (online) acquire/provide information/knowledge needed for optimisation of energy consumption. It also aims to assist in effective use of such knowledge to support decisions regarding Life-Cycle oriented Energy Use Management, applying the energy efficiency services. This paper provides theoretical background to RTD practitioners who would like to apply AmI-MoSES approaches in future energy efficiency optimisation activities. The topics comprise Energy Consumption Data (ECD) and Ambient Intelligence (AmI) Monitoring, Energy Use Parameters (EUP) Monitoring and Advisory and context modelling for turning EUPs into knowledge assets.