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

Today, Concentrating Solar Power (CSP) plants and components incorporate a low degree of intelligence and autonomy that makes it expensive and makes quality control difficult. The degree of automation of CSP plants is low; the development of protocols, procedures and standards to ensure quality control during assembly, construction, commissioning and operation of the plant are still in their early stages. Meanwhile, Industry 4.0 and Industrial Internet of Things (IoT) paradigm are the key technological breakthroughs for the manufacturing industry since the last century; and such can be SMARTCSP for the CSP since its commercial inception 50 years ago. SMARTCSP benefits from this experience in the application of ICT (Information and Communication Technology) or Lean Manufacturing in mature industrial fields such as automotive or manufacturing to create a new generation of SMARTCSP Components that include a full set of relevant functionalities right from the production line. SMARTCSP will provide higher levels of distributed intelligence, autonomy and decision making in CSP plants through distributed and miniaturized processors, sensors, and communications embedded in CSP components. Moreover, a new CSP plant concept is proposed that allows for an optimized operation and maintenance of the plant. All this entails the first step towards the crystallization of the Industry 4.0 paradigm in the field of CSP technologies.

Background Energy communities facilitate several advantages, including energy autonomy, reduced greenhouse gas emissions, poverty mitigation, and regional economic development. They also empower citizens with decision-making and co-ownership prospects in community renewable projects. Integrating renewable energy sources and sector coupling is a crucial strategy for flexible energy systems. However, demonstrating clean energy transition scenarios in these communities presents challenges, including technology integration, flexibility activation, load reduction, grid resilience, and business case development. Methods Based on the system of systems approach, this paper introduces a 4-step funnel approach and a 4-step reverse funnel approach to systematically specify and detail demonstration scenarios for energy community projects. The funnel approach involves four steps. First, it selects demonstration scenarios promoting energy-efficient state-of-the-art renewable technologies and storage systems, flexibility through demand side management techniques, reduced grid dependence, and economic viability. Second, it lists all existing and planned project technologies, analysing energy flows. Third, it plans actions at different levels to implement the demonstration scenarios. Fourth, it validates the strategies using key performance indicators (KPI) to quantify the effectiveness of the planned measures. Furthermore, the reverse funnel approach delves deeper into the demonstration scenarios. The four steps involve identifying stakeholder perspectives, describing scenario scopes, listing conditions for realisation, and outlining business models, including value chains and economic assumptions. Results This approach provides a detailed analysis of the demonstration scenarios, considering actors, objectives, boundary conditions, and business assumptions. The methodologies are exemplified in three diverse European energy communities extending across residential, commercial, tertiary, and industrial establishments, allowing power-to-x and sector coupling opportunities. The paper also suggested thirteen KPIs for validating renewable-focused energy community projects. Conclusions Finally, the paper recommends increased collaboration between energy communities, knowledge sharing, stakeholder engagement, transparent data collection and analysis, continuous feedback, and method improvement to mitigate policy, technology, business, and market uncertainties.

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This paper approaches the energy transition towards decarbonization and lower primary energy use in the steel and glass industries through the exploitation of radiant waste heat. In contrast with exhaust gases heat recovery, radiant waste heat has typically not been used. This energy waste is found in energy intensive processes in which high temperatures are reached. For instance, in the steel making process, the cast steel is red hot and emits a considerable amount of radiant energy. In this paper the conceptual design of a radiant heat capturing device is presented. This device enables the recovery of currently unused energy while solving the radiative emission-related problems. The achieved design gets to an optimized solution regarding view factors and optical properties of the involved surfaces. In this research work, those factors are optimized to maximize the amount of heat recovered by the presented device. Simulation tools are used to test different designs and define the most appropriate solution for a given case.