Videoverslag waarin de aanpak, maatschappelijke relevantie en belangrijkste uitkomsten van het RAAK Onderzoek 'Making GREEN Energy Sources Greener' worden besproken. In dit onderzoek is op verschillende drijvende zonneparken gekeken naar effecten van de installaties op waterkwaliteit en ecologie. De resultaten hiervan vormen aanleiding voor vervolgonderzoeken die inmiddels zijn gestart
YOUTUBE
The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
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Author supplied: Within the Netherlands the interest for sustainability is slowly growing. However, most organizations are still lagging behind in implementing sustainability as part of their strategy and in developing performance indicators to track their progress; not only in profit organizations but in higher education as well, even though sustainability has been on the agenda of the higher educational sector since the 1992 Earth Summit in Rio, progress is slow. Currently most initiatives in higher education in the Netherlands have been made in the greening of IT (e.g. more energy efficient hardware) and in implementing sustainability as a competence in curricula. However if we look at the operations (the day to day processes and activities) of Dutch institutions for higher education we just see minor advances. In order to determine what the best practices are in implementing sustainable processes, We have done research in the Netherlands and based on the results we have developed a framework for the smart campus of tomorrow. The research approach consisted of a literature study, interviews with experts on sustainability (both in higher education and in other sectors), and in an expert workshop. Based on our research we propose the concept of a Smart Green Campus that integrates new models of learning, smart sharing of resources and the use of buildings and transport (in relation to different forms of education and energy efficiency). Flipping‐the‐classroom, blended learning, e‐learning and web lectures are part of the new models of learning that should enable a more time and place independent form of education. With regard to smart sharing of resources we have found best practices on sharing IT‐storage capacity among universities, making educational resources freely available, sharing of information on classroom availability and possibilities of traveling together. A Smart Green Campus is (or at least is trying to be) energy neutral and therefore has an energy building management system that continuously monitors the energy performance of buildings on the campus. And the design of the interior of the buildings is better suited to the new forms of education and learning described above. The integrated concept of Smart Green Campus enables less travel to and from the campus. This is important as in the Netherlands about 60% of the CO2 footprint of a higher educational institute is related to mobility. Furthermore we advise that the campus is in itself an object for study by students and researchers and sustainability should be made an integral part of the attitude of all stakeholders related to the Smart Green Campus. The Smart Green Campus concept provides a blueprint that Dutch institutions in higher education can use in developing their own sustainability strategy. Best practices are shared and can be implemented across different institutions thereby realizing not only a more sustainable environment but also changing the attitude that students (the professionals of tomorrow) and staff have towards sustainability.
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Cities, the living place of 75% of European population, are crucial for sustainable transition in a just society. Therefore, the EU has launched a Mission for 100 Climate-Neutral Smart Cities (100CNSC). Construction is a key industry in making cities more sustainable. Currently, construction consumes 50% resources, uses 40% energy, and emits 36% greenhouse gasses. The sector is not cost-efficient, not human-friendly, and not healthy – it is negatively known for “3D: dirty, dangerous, demanding”. As such, the construction sector is not attractive for educated and skilled young professionals that are needed for the sustainable transition and for resolving the housing crisis. In contrast with the non-circular designs, materials and techniques that are still common in the construction industry, some other industries and fields have cultivated higher standards for sustainable products, especially in clean and efficient assembly and disassembly. Examples can be found in the maritime and off-shore industry, smart manufacturing, small electronics, and retail. The Hague University of Applied Sciences (THUAS) aims to become the leader of a strong European consortium for preliminary research to develop knowledge that is needed for the upcoming Horizon Europe proposal (within Cluster 4, Destination 1 - Re-manufacturing and De-manufacturing technologies) in relation with the EU Mission 100CNSC. The goals of this preliminary research are: (a) to articulate new concepts that will become an input for a new research proposal and (b) to organize a high-quality European consortium with high-quality partners for a lasting collaboration. This preliminary research project focuses on the question: How can the construction sector adopt and adapt the best practices in assembly and disassembly from other industries –including maritime, manufacturing and retails– in order to enhance circular urban construction and renovation with an active involvement of educated and skilled young professionals?
The Netherlands is facinggreat challenges to achieve (inter)national climate mitigation objectives inlimited time, budget and space. Drastic innovative measures such as floatingsolar parks are high on political agendas and are entering our water systems.The clear advantages of floating solar (multifunctional use of space) led to afast deployment of renewable energy sources without extensive research toadequately evaluate the impacts on our environment. Acquisition ofresearch data with holistic monitoring methods are urgently needed in order toprevent disinvestments.In this project 10 SMEs with different expertiseand technologies are joining efforts with researchers and four public parties(and 12 indirectly involved) to answer the research question “Which monitoringtechnologies and intelligent data interpretation techniques are requiredto be able to conduct comprehensive, efficient and cost effective monitoring ofthe impacts of floating solar panels in their surroundings?"The outputs after a two-yearproject will play a significant and indispensable role in making Green EnergyResources Greener. Specific output includes a detailed inventory of existingprojects, monitoring method for collection/analysis of datasets(parameters/footage on climate, water quality, ecology) on the effects offloating solar panels on the environment using heterogeneous unmanned robots,workshops with public & private partners and stakeholders,scientific and technical papers and update of national guidelines for optimizingthe relationship between solar panels and the surrounding environment. Projectresults have a global interest and the consortium partners aim at upscaling forthe international market. This project will enrich the involved partners withtheir practical knowledge, and SMEs will be equipped with the new technologiesto be at the forefront and benefit from the increasing floating solar marketopportunities. This project will also make a significant contribution tovarious educational curricula in universities of applied sciences.The Netherlands is facinggreat challenges to achieve (inter)national climate mitigation objectives inlimited time, budget and space. Drastic innovative measures such as floatingsolar parks are high on political agendas and are entering our water systems.The clear advantages of floating solar (multifunctional use of space) led to afast deployment of renewable energy sources without extensive research toadequately evaluate the impacts on our environment. Acquisition ofresearch data with holistic monitoring methods are urgently needed in order toprevent disinvestments.In this project 10 SMEs with different expertiseand technologies are joining efforts with researchers and four public parties(and 12 indirectly involved) to answer the research question “Which monitoringtechnologies and intelligent data interpretation techniques are requiredto be able to conduct comprehensive, efficient and cost effective monitoring ofthe impacts of floating solar panels in their surroundings?"The outputs after a two-yearproject will play a significant and indispensable role in making Green EnergyResources Greener. Specific output includes a detailed inventory of existingprojects, monitoring method for collection/analysis of datasets(parameters/footage on climate, water quality, ecology) on the effects offloating solar panels on the environment using heterogeneous unmanned robots,workshops with public & private partners and stakeholders,scientific and technical papers and update of national guidelines for optimizingthe relationship between solar panels and the surrounding environment. Projectresults have a global interest and the consortium partners aim at upscaling forthe international market. This project will enrich the involved partners withtheir practical knowledge, and SMEs will be equipped with the new technologiesto be at the forefront and benefit from the increasing floating solar marketopportunities. This project will also make a significant contribution tovarious educational curricula in universities of applied sciences.
The Netherlands is facing great challenges to achieve (inter)national climate mitigation objectives in limited time, budget and space. Drastic innovative measures such as floating solar parks are high on political agendas and are entering our water systems . The clear advantages of floating solar (multifunctional use of space) led to a fast deployment of renewable energy sources without extensive research to adequately evaluate the impacts on our environment. Acquisition of research data with holistic monitoring methods are urgently needed in order to prevent disinvestments. In this proposal ten SMEs with different expertise and technologies are joining efforts with researchers and four public parties (and 12 indirectly involved) to answer the research question “Which monitoring technologies and intelligent data interpretation techniques are required to be able to conduct comprehensive, efficient and cost-effective monitoring of the impacts of floating solar panels in their surroundings?" The outputs after a two-year project will play a significant and indispensable role in making Green Energy Resources Greener. Specific output includes a detailed inventory of existing projects, monitoring method for collection/analysis of datasets (parameters/footage on climate, water quality, ecology) on the effects of floating solar panels on the environment using heterogeneous unmanned robots, workshops with public & private partners and stakeholders, scientific and technical papers and update of national guidelines for optimizing the relationship between solar panels and the surrounding environment. Project results have a global interest and the consortium partners aim at upscaling for the international market. This project will enrich the involved partners with their practical knowledge, and SMEs will be equipped with the new technologies to be at the forefront and benefit from the increasing floating solar market opportunities. This project will also make a significant contribution to various educational curricula in universities of applied sciences.
