Integrated model concept for district energy management optimisation platforms

District heating systems play a key role in reducing the aggregated heating and domestic hot water production energy consumption of European building stock. However, the operational strategies of these systems present further optimisation potential, as most of them are still operated according to reactive control strategies. To fully exploit the optimisation potential of these systems, their operations should instead be based on model predictive control strategies implemented through dedicated district energy management platforms. This paper describes a multiscale and multidomain integrated district model concept conceived to serve as the basis of an energy prediction engine for the district energy management platform developed in the framework of the MOEEBIUS project. The integrated district model is produced by taking advantage of co-simulation techniques to couple building (EnergyPlus) and district heating system (Modelica) physics-based models, while exploiting the potential provided by the functional mock-up interface standard. The district demand side is modelled through the combined use of physical building models and data-driven models developed through supervised machine learning techniques. Additionally, district production-side infrastructure modelling is simplified through a new Modelica library designed to allow a subsystem-based district model composition, reducing the time required for model development. The integrated district model and new Modelica library are successfully tested in the Stepa Stepanovic subnetwork of the city of Belgrade, demonstrating their capacity for evaluating the energy savings potential available in existing district heating systems, with a reduction of up to 21% of the aggregated subnetwork energy input and peak load reduction of 24.6%.The research activities leading to the described developments and results, were funded by the European Uniońs Horizon 2020 MOEEBIUS project, under grant agreement No 680517. Authors would like to ex-press their gratitude to the operator of the Vozdovac district heating system (Beogradske elektrane) for the specifications used to develop and calibrate the models, and to Solintel M&P, SL for developing the initial versions of the EnergyPlus models (including only the geometrical and constructive definition of the buildings), in the framework of the MOEEBIUS project

Modelling and Co-simulation of Multi-Energy Systems: Distributed Software Methods and Platforms

L'abstract è presente nell'allegato / the abstract is in the attachmen

Optimisation Of Controller Parameters For Adaptive Building Envelopes Through A Co-Simulation Interface: A Case Study

Adaptive building envelopes can dynamically adapt to environmental changes, often supported by a control system. While building performance simulation (BPS) tools can be employed to test different design alternatives, representing control strategies within current BPS tools can be challenging, especially for systems with a fast, dynamic response. Another challenge in current BPS tools is the ability to tune and select parameters for the particular use case. In this study, a modelling approach is presented for the integrated analysis of control strategies of adaptive building envelopes linking thermal performance and control with an optimisation algorithm. The proposed modelling approach was evaluated using a case study with an automated motorised blind with two distinct control strategies. Simulation results suggest that the window heat gains were 72.7 % lower when the controller model was coupled with an optimiser to identify optimised controller parameters compared to a baseline control strategy. The results of this study are suggestive of the benefits that can be obtained from adjusting the dynamic aspects of the building envelope. The results support the thesis of using optimisation as standard building envelope design practice in the future

Modelling and Simulation of the Fifth-Generation District Heating and Cooling

District heating and cooling are efficient systems for distributing heat and cold in urban areas. They are a key solution for planning future urban energy-efficient systems due to their high potential for integrating renewable energy sources. The systems also play an important role in community resilience, which makes them a multidisciplinary research topic. The continuous development of these systems has now reached the fifth-generation whereby end-customers can benefit from the intrinsic synergies this generation offers. A typical Fifth-Generation District Heating and Cooling (5GDHC) system consists of connected buildings that together have simultaneous heating and cooling demands. Local heat pumps and chillers in decentralised substations modulate the low network temperature to the desired building supply temperatures. The demands are potentially balanced by the means of recovering local waste heat from chillers, while also utilising heat pumps to provide direct cooling. The heat carrier fluid in the distribution pipes can therefore flow in either direction in the so-called bidirectional low-temperature network. A balancing unit is incorporated to compensate for network energy imbalances. The exchange of energy flows is realised at different stages within the individual building and across connected buildings. Numerous factors influence the quantity and quality of the exchanged energy flows. Demand profiles in each building, the efficiency of building energy systems, and control logics of system components are some examples of these factors. Investigating this generation using traditional computational tools developed using imperative programming languages is no longer suitable due to system complexity, size variability, and changes adopted in different use cases. Modelica is a free open-source equation-based object-oriented language used for the modelling and simulation of multi-domain physical systems. Models are described by differential-algebraic and discrete equations. The mathematical relations between model variables are encapsulated inside an icon that represents the model. Different component models interface variables through standardised interfaces and connection lines. Large complex systems are composed by the visual assembly of components in a Lego-like approach. Models developed in Modelica can be easily inherited for rapid virtual prototyping and/or edited to adopt changes in the model use. This dissertation has a fourfold objective. Firstly, it demonstrates the development of a simulation model for an installed 5GDHC system located in Lund, Sweden. Secondly, it characterises the components that constitute a 5GDHC system. Thirdly, it unravels the exchange of energy flows at different system levels and describes, in a logical progression, the modelling of 5GDHC with Modelica. Fourthly, it presents ethical risk analyses of the different role-combinations that may arise in 5GDHC business models. The developed model is used in performing annual simulations and to evaluate the system performance under two different substation design cases. The results indicate that adding a direct cooling heat exchanger in each substation can reduce the electric energy consumption at both substation and system levels by about 10 and 7 %, respectively. Moreover, the annual waste heat to ambient air can be decreased by about 17 %. The dissertation fosters an ethical discourse that engages the public and all who take part in the multidisciplinary research on 5GDHC to guarantee safe operation and appropriate services. Future research will build on the models presented in this dissertation to investigate different network temperature and pressure control strategies, in addition to adopting several design concepts for balancing units and thermal energy storage systems

A comparison study of co-simulation frameworks for multi-energy systems: the scalability problem

The transition to a low-carbon society will completely change the structure of energy systems from a standalone hierarchical centralised vision to cooperative and dis- tributed Multi-Energy Systems. The analysis of these complex systems requires the collaboration of researchers from different disciplines in the energy, ICT, social, economic, and political sectors. Combining such disparate disciplines into a single tool for modeling and analyzing such a complex environment as a Multi-Energy System requires tremendous effort. Researchers have overcome this effort by using co-simulation techniques that give the possibility of integrating existing domain-specific simulators in a single environment. Co-simulation frameworks, such as Mosaik and HELICS, have been developed to ease such integration. In this context, an additional challenge is the different temporal and spatial scales that are involved in the real world and that must be addressed during co-simulation. In particular, the huge number of heterogeneous actors populating the system makes it difficult to represent the system as a whole. In this paper, we propose a comparison of the scalability performance of two major co-simulation frameworks (i.e. HELICS and Mosaik) and a particular implementation of a well-known multi-agent systems library (i.e. AIOMAS). After describing a generic co-simulation framework infrastructure and its related challenges in managing a distributed co-simulation environment, the three selected frameworks are introduced and compared with each other to highlight their principal structure. Then, the scalability problem of co-simulation frameworks is introduced presenting four benchmark configurations to test their ability to scale in terms of a number of running instances. To carry out this comparison, a simplified multi-model energy scenario was used as a common testing environment. This work helps to understand which of the three frameworks and four configurations to select depending on the scenario to analyse. Experimental results show that a Multi-processing configuration of HELICS reaches the best performance in terms of KPIs defined to assess the scalability among the co-simu- lation frameworks

Special Session on Industry 4.0

No abstract available

Optimisation of the simulation of advanced control strategies for adaptive building skins

Adaptive building skins dynamically adapt to environmental changes, often supported by a control system. Whereas building performance simulation (BPS) tools can be employed to predict the performance of adaptive building skins, the associated control strategies within currently available BPS tools are approximated, which limits tool capability regarding properly capturing the influence of the control strategy on adaptive building skins. This study aims to assess this through the use of a co-simulation modelling framework demonstrated through a case study with automated motorised blinds with two distinct control strategies. Simulation results suggest that the cooling rate was 12.1 % higher when the blind position depended only on solar gains, but not on solar gains and sun tracking. The results of this study imply that the modelling framework predicted the performance of the case study more accurately than what would be expected for currently available BPS tools, which can increase the credibility of building performance simulations

Design of knowledge-based systems for automated deployment of building management services

Despite its high potential, the building's sector lags behind in reducing its energy demand. Tremendous savings can be achieved by deploying building management services during operation, however, the manual deployment of these services needs to be undertaken by experts and it is a tedious, time and cost consuming task. It requires detailed expert knowledge to match the diverse requirements of services with the present constellation of envelope, equipment and automation system in a target building. To enable the widespread deployment of these services, this knowledge-intensive task needs to be automated. Knowledge-based methods solve this task, however, their widespread adoption is hampered and solutions proposed in the past do not stick to basic principles of state of the art knowledge engineering methods. To fill this gap we present a novel methodological approach for the design of knowledge-based systems for the automated deployment of building management services. The approach covers the essential steps and best practices: (1) representation of terminological knowledge of a building and its systems based on well-established knowledge engineering methods; (2) representation and capturing of assertional knowledge on a real building portfolio based on open standards; and (3) use of the acquired knowledge for the automated deployment of building management services to increase the energy efficiency of buildings during operation. We validate the methodological approach by deploying it in a real-world large-scale European pilot on a diverse portfolio of buildings and a novel set of building management services. In addition, a novel ontology, which reuses and extends existing ontologies is presented.The authors would like to gratefully acknowledge the generous funding provided by the European Union’s Horizon 2020 research and innovation programme through the MOEEBIUS project under grant agreement No. 680517

Dissemination, Future Research and Education:

This booklet is one of three final documentations of the results of the COST-Action TU 1403 ‘ADAPTIVE FACADE NETWORK’ to be published next to the proceedings of the Final COST Conference ‘FACADE 2018 – ADAPTIVE!’ and a Special Issue of the Journal of Façade Design & Engineering (JFDE). While the proceedings and the journal present current scientific research papers selected through a traditional peer review process, these three final documentations have another focus and objective. These three documentations will share a more holistic and comparative view to the scientific and educational framework of this COST-Action on adaptive facades with the objective to generate an overview and a summary – different from the more specific approach of the proceedings and connecting to the first publication that was presenting the participating institutions. The three titles are the following and are connected to the deliverables of the responsible Working Groups (WG): Booklet 3.1 Case Studies (WG1) Booklet 3.2 Building Performance Simulation and Characterisation of Adaptive Facades (WG2) Booklet 3.3 Dissemination, Future Research and Education (WG4) Booklet 3.1 concentrates on the definition and classification of adaptive facades by describing the state of the art of real-world and research projects and by providing a database to be published on COST TU 1403 website (http://tu1403.eu/). Booklet 3.2 focusses on comparing simulation and testing methods, tools and facilities. And finally, Booklet 3.3 documents the interdisciplinary, horizontal and vertical networking and communication between the different stakeholders of the COST-Action organised through Short Term Scientific Missions (STSM), Training Schools and support sessions for Early Stage Researchers (ESR) / Early Career Investigators (ECI), industry workshops, and related surveys as specific means of dissemination to connect research and education. All three booklets show the diversity of approaches to the topic of adaptive facades coming from the different participants and stakeholders, such as: architecture and design, engineering and simulation, operation and management, industry and fabrication and from education and research. The tasks and deliverables of Working Group 4 were organized and supported by the following group members and their functions: – Thomas Henriksen, Denmark ESR/ECI – Ulrich Knaack, The Netherlands Chair (2015-16) – Thaleia Konstantinou, The Netherlands ESR/ECI – Christian Louter, The Netherlands Vice-Chair, STSM Coordinator – Andreas Luible, Switzerland Website, Meetings – David Metcalfe, United Kingdom Training Schools – Uta Pottgiesser, Germany Chair (2017-18) As editors and Chairs, we would like to thank the Working Group members and authors from other Working Groups for their significant and comprehensive contributions to this booklet. Moreover, we sincerely thank Ashal Tyurkay for her great assistance during the whole editing and layout process. We also want to thank COST (European Cooperation in Science and Technology)