In Europe, different prognosis show an increase in cooling demand of almost 60% in 2030 with respect to nowadays. District cooling (DC) can play a part in satisfying this demand in a sustainable way (since can offer 5 to 10 times higher efficiency solutions than on‐site stand‐alone distributed systems). Even if DC captures only minor portion of the prospective market, this will translate into a dramatic increase in the size of the global DC sector. INDIGO aims to develop a more efficient, intelligent and cheaper generation of DC systems by improving system planning, control and management, anticipating the aforementioned scenario. This target will be achieved through the following specific objectives: • Contribute to the wider use of DC systems and motivate the competiveness of European DC market by the development of two open-source tools: o A planning tool for DC systems with the aim of supporting their optimal design o A library with thermo-fluid dynamic models of DC System components which will provide the designers detailed information about their physical behaviour • Primary energy reduction over 45% addressed by a ground breaking DC system management strategy focused mainly on energy efficiency maximization but also on energy cost minimization. Its main characteristics is the predictive management but it also will address other challenges such as: o Integration of Renewable Energy Sources o Dealing with different types of cooling sources o Suitable coupling between generation, storage and demand All this, with the help of intelligent and innovative component controllers (Predictive Controllers) to be developed at all DC system levels. Some of them include embedded self-learning algorithms, allowing components to respond appropriately to the set-points established. Developments carried out within INDIGO will be validated in a real District Heating and Cooling installation with appropriate conditions for testing the new functionalities.

Buildings consume most of the world’s electricity and as much as 50% of their consumption is used to cover thermal demands. Some actual developments, such as the growing use of electrical vehicles and the usage of heat pumps, are affecting electricity consumption and peak demand, and their impacts will only increase in the future. The excessive high energy demand entails significant negative environmental and economic impacts. Consequently, it is imperative to increase use of demand response strategies that shift electricity use from peak to off-peak periods. The BEST-Storage project is an important step to achieve the goal of peak load reduction and shifting, energy saving and energy cost minimization. Moreover, technologies for storing renewables for longer time-spans of months or seasons are scarce and costly and thus not widely used yet. Large amounts of energy are needed for heat supply of buildings in cold winter months, when solar energy is scarce and in general when renewable sources cannot cover the demand. Thus, seasonal storage solutions will be a necessary technology for a full decarbonisation of the energy supply system. In BEST-Storage, long and short-term high-energy density storage solutions will be developed and demonstrated in four demo cases around Europe. A thermo-chemical and loss-free storage technology will be developed as a seasonal storage. Two phase change materials slurry concepts and a vacuum insulated water storage will be developed, for cold and warm applications respectively, with the aim of shifting peak load demands. Finally, storage solutions will be integrated within smart building energy management systems featuring model predictive controls to reduce operation cost for short-term applications.

InterPED aims to enable the concept of PEDs via sector coupling, cross-vector integration, demand flexibility and consumer engagement, while improving utilisation of local RES, storage and excess/waste heat (E/WH) sources. InterPED will couple RES, storage and E/WH sources (community assets) available in the pilots with the necessary know-how and ICT expertise to ensure improved operation of PEDs and grid robustness. This will allow InterPED’s end users (aggregators, service providers, urban planners) to deliver benefits to both, grid stakeholders (DSO/TSOs) and final consumers (and prosumers). To do so, InterPED will deliver a scalable and adaptable cloud-based platform composed of analytical, modelling and optimization services for planning, supervision and control of integrated PEDs (including power, heating and cooling, mobility). Optimized PED operations will be demonstrated at pilot sites, while enabling a cooperative demand response (DR) strategy at community/district level. In addition to automated control actions, InterPED intends to engage the consumers via community building (e.g. CECs or RECs), representing a still largely untapped source of flexibility, while enabling them to play an active role in grid balancing. By making it cloud-based and by ensuring system interoperability (both syntactic and semantic), InterPED will enable aggregators and actors positioned to adopt proposed business model (e.g. ESCOs, energy retailers, DSOs) to deploy the InterPED solution immediately almost anywhere, while reducing the cost to its scalability. The key strategy to ensure solutions will work well in an everyday context of consumers, is that InterPED will involve the consumers (community) and service providers in the design of the solutions through participatory co-design processes. InterPED will verify the technical and commercial feasibility of its integrated package in four large-scale pilots, each representing an existing PED.

Artificial-Intelligence-Augmented Cooling System for Small Data Centres “ECO-Qube”; is a holistic management system which aims to enhance energy efficiency and cooling performance by orchestrating both hardware and software components in edge computing applications. ECO-Qube is a data driven approach which utilizes valuable unused data from active data centre components. Created big data is being used by an artificial intelligence augmented system which detects cooling and energy requirements instantaneously. ECO-Qube differentiates from conventional cooling systems which keep operating temperatures within a strict interval and do not evaluate measurable cooling performance. Unmeasured cooling performance leads underperformed airflow, thermal disequilibrium, and high energy consumption. On the contrary, ECO-Qube offers a zonal heat management system which benefits from Computational Fluid Dynamics (CFD) simulations to adapt cooling system for the best airflow and cooling performance with minimum energy consumption. Moreover, ECO-Qube realizes smart workload orchestration to keep the CPUs at their most energy efficient state and maintain the thermal equilibrium to reduce overheating risk. Sustainability is another priority for ECO-Qube’s smart energy management system (EMS), which is designed to track the energy demand and operate the energy supply in cooperation with building/district’s EMS. This synergy maximizes the energy supplied from renewable energy sources and minimizes the energy supplied from sources with big carbon footprint. ECO-Qube solution will be assessed in three different pilots from different climatic conditions to validate energy efficiency under different external variables.