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The paper discusses the outcomes of the conference organized by the InDeal project. The conference took place on 12 December 2018 in Montpellier as part of the EnerGaia energy forum 2018. A holistic interdisciplinary approach for district heating and cooling (DHC) networks is presented that integrates heterogeneous innovative technologies from various scientific sectors. The solution is based on a multi-layer control and modelling framework that has been designed to minimize the total plant production costs and optimize heating/cooling distribution. Artificial intelligence tools are employed to model uncertainties associated with weather and energy demand forecasts, as well as quantify the energy storage capacity. Smart metering devices are utilized to collect information about all the crucial heat substations’ parameters, whereas a web-based platform offers a unique user environment for network operators. Three new technologies have been further developed to improve the efficiency of pipe design of DHC systems: (i) A new sustainable insulation material for reducing heat losses, (ii) a new quick-fit joint for an easy installation, and (iii) a new coating for reducing pressure head losses. The results of a study on the development and optimization of two energy harvesting systems are also provided. The assessment of the environmental, economic and social impact of the proposed holistic approach is performed through a life cycle analysis. The validation methodology of the integrated solution is also described, whereas conclusions and future work are finally given.

This paper primarily deals with the design of an Information and Control Technology (ICT) network for an advanced metering infrastructure (AMI) on the IEEE 34 node radial distribution network. The application is comprised of 330 smart meters deployed in the low voltage system and 33 data concentrators in the medium voltage system. A power line carrier (PLC) communication system design is developed and simulated in Network Simulator 3 (NS-3). The simulation result is validated by comparing the communication network performance with the minimum performance requirements for AMI. The network delay of a single data frame is calculated and compared with the simulation delay. The design methodology proposed in this article may be used for other smart grid applications. The secondary goal is to provide AMI network traffic based on the IEC Std. 61968 and a discussion on whether or not AMI could possibly be a source of big data on the future power grid.