BEST
Energy Efficient Spa Technologies
Wellness facilities are on the rise all over Europe. The technology used for saunas and steam baths nowadays is based entirely on electric resistance heating and is therefore extremely energy-intensive and costly to operate. The project develops concepts and technologies based on high-temperature CO2 heat pumps, which can be expected to save 70% of electricity. In a full-scale test installation within the research and demonstration platform NEST the effectiveness of the solutions developed is being verified and operation is being optimized.
Funding: Commission for Technology and Innovation (CTI)
Partners: University of Applied Sciences Buchs NTB, University of Applied Sciences Lucerne HSLU (Research), Suissetec (Industry assocoiation), other industry partners
Contact: Robert Weber
Involved group: BEST
Swiss Competence Center for Energy Research – Future Energy Efficient Buildings & Districts SCCER FEEB&D
The vision of the Swiss Competence Center for Energy Research on Future Energy Efficient Buildings & Districts (SCCER FEEB&D) is to develop solutions for the Swiss building stock which will lead to a reduction of the environmental footprint of the sector by a factor of three by 2035 thanks to efficient, intelligent and interlinked buildings.
The SCCER FEEB&D is addressing this challenge in a combined effort by leading Swiss and international partners from academia, industry and the public sector.
Funding: Innosuisse – Swiss Innovation Agency
Partners: Empa, ETH Zurich, EPFL, HSLU, Uni Geneve, FHNW
Contact: Matthias Sulzer
Involved groups: BEST, MES, ehub
Swiss Competence Center for Energy Research “Heat and Electricity Storage” (SCCER HaE) – Phase II, WP1 Storage of Heat – Task 1 – Sorption-based Seasonal Heat Storage.
The major goal within this four years project is to increase the technology readiness level (TRL) of the technology from a 4 to 6-7. Development steps include lab-scale absorber testing, upscaling of lab-scale absorber to 5 kW, integration of upscaled absorber in hybrid pilot-scale plant from a former EU FP-7 research project COMTES and prototype storage plant installation in NEST/energy hub research facilities.
Funding: Innosuisse – Swiss Innovation Agency
Academic partners: Institute for Solar Technology SPF / University for Applied Sciences-HSR
Contact: Luca Baldini
Involved group: BEST
Swiss Competence Center for Energy Research “Efficiency of Industrial Processes” (SCCER EIP) – Phase II, WP4 Decentralized Wastewater Management – Task 4 – Wastewater Heat Recovery
A significant potential of wastewater heat recovery has been identified at household level, which shall be explored in the course of Empa’s contribution to this SCCER. It is the goal to evaluate different available technologies and novel system combinations through simulation and punctually through experimental evaluation within NEST. Further, different integration options for wastewater heat recovery in buildings along with possibilities for technology/system developments with industry involvement will be evaluated and finally, guidelines and recommendations shall be deduced and made available for planning engineers in the field.
Funding: Innosuisse – Swiss Innovation Agency
Academic partners: Eawag – Aquatic Research, University for Applied Sciences-HSR, University of Applied Sciences FHNW
Contact: Luca Baldini
Involved group: BEST
COMTES - Combined development of compact thermal energy storage technologies; Line B – Liquid Sorption Heat Storage
The three heat storage technologies that are addressed in the COMTES project are ‘compact thermal storage technologies’, that need less volume and have much lower heat losses over the time (a season) than conventional water based storage systems. Moreover, the new systems demand less collector area compared to water-based seasonal storage systems.
This makes these technologies promising candidates for the next generation of seasonal solar heat storage technologies that will enable the step to nearly fully renewable heat supply of buildings in Europe.
The overall goal of the COMTES project is the technological development and demonstration of three compact thermal energy storage technologies, in three parallel development lines.
Empa was involved in line B: Liquid sorption heat storage; heat storage by absorption of water vapor in a liquid. Sodium hydroxide (NaOH) is used as the liquid sorption material.
Funding: An European Union Seventh Framework Program Project, EU grant number 295568
Partners: SPF Institute for Solar Technologies (Research), Kingspan Environmental Ltd (Industry)
Contact: Robert Weber
NaOH-Speicher für saisonale Wärmespeicherung
In the scope of this project, a NaOH sorption storage for seasonal solar thermal storage has been developed, built and tested. Rather than sensible thermal storage, this novel concept is based on the principle of the a sorption heat pump operation. In this manner a theoretical energy density increase of 3 to 6 times compared to that of the sensible thermal water storage is achieved and the system is not susceptible to thermal loss during storage time. This system was built in two steps, initially with one heat pump stage and then extended to a two stage system to increase the output temperature. Computer simulations accompanied this deve opment in order to improve the design process.
Funding: Swiss Federal Office of Energy, Pilot and Demonstration Project
Contact: Robert Weber
MES
Energy System Modeling for the Real World: Transforming Modeling Approaches for Sustainable and Resilient Urban Development (MEASURES)
Energy system models are vital decision support tools. However, developing countries grapple with socio-technical and economic factors rarely represented in conventional energy modeling approaches; these include power sector failures, informal economies, and suppressed energy demand, for example. Developing cities will also experience climate change impacts more acutely than industrialized nations; thus, maximizing their resilience is essential. This study pioneers methods to address these gaps in energy system models.
Our team consists of multiple experts across disciplines and geographic boundaries. We employ the expertise of economists, climate change experts, and energy modelers across Switzerland and Africa in order to identify synergies and integration opportunities between modeling methods. We will build up-on existing open-source optimization/simulation models and demonstrate developed methods through a case study city committed to sustainable energy planning. The developed methods will describe how to represent various socio-technical, economic, and climate change impacts on developing cities through scenario and modeling framework advancements.
We aim to ensure knowledge transfer, especially to member cities of transnational municipal networks (e.g., the Global Covenant of Mayors, consisting of over 10000 cities), by sharing all models, data, methods, and findings on open-source, web-based platforms and through workshops. In this way, cities around the world can apply demonstrated models and methods to their own sustainable energy strategy development. The case study municipality also directly benefits from this work in developing their climate strategy.
Funding body: SNF (SPIRIT)
Partners: The Brew-Hammond Energy Center at the Kwame Nkrumah University of Science and Technology (KNUST); Department of Economics at KNUST; Regional Centre for Energy and Environmental Sustainability at the University of Energy and Natural Resources (UENR); ECOWAS Centre for Renewable Energy and Energy Efficiency (ECREEE); Energy Commission of Ghana (EC); Municipality of Accra (MA)
Contact: Mashael Yazdanie
Involved group: MES
Sustainable well-being for the Individual and the Collectivity in the Energy Transition SWICE - Sweet working and living – Start 2023
The project aims to identify and quantify the energy saving potential and opportunities for increased quality of life that can emerge from future urban scenarios involving new modalities of living and working, changes in leisure and mobility behaviours, and different business models. Besides aiming to propose environmental and technological solutions, this proposal builds upon the premise that energy demand is, first and foremost, an outcome of social dynamics, involving complex patterns of energy usage and requiring creative approaches in material flows. As a result, it considers the focus on the wellbeing of people, seen both as individuals and as a collectivity, as a crucial component of the energy transition, which, to be successful, must be socially embraced and implemented in the physical spaces we inhabit. More specifically, the project seeks to experiment and implement sustainable social change practices based on less energy-intensive behaviours through carefully co-designed interventions on the physical environment taking place in daily living, working and leisure. While people and socio-material dynamics are considered the main “agents of change” in this energy transition, three main “sectors of change” are identified in terms of impact on energy demand and supply management: the built environment, open spaces and mobility. For these distinct - yet strongly interrelated - areas of action, the project will provide solutions and best practices for a sustainable congruence between an apparently insatiable desire for “more” (more living space and material comfort) and requirements for greenhouse gas emission reductions and circular economy, while improving quality of life.
Finish Date: 12/2029
Funding body: SFOE
Partners: EPFL, Empa TSL, ETHZ, UNIL, UNIGE, UNIFR, HSLU, HEIAFR, ZHAW, SUPSI, INTEP, INTER, JUD, ECO
Contact: Kristina Orehounig
Cooling Singapore 2.0
Cooling Singapore is a multi-disciplinary research project dedicated to developing solutions to address the urban heat challenge in Singapore. In the present phase of the project, the team develops an island-wide Digital Urban Climate Twin (DUCT) in Singapore by integrating computational models (environmental, land surface, industrial, traffic, building energy) as well as regional- and micro-scale climate models. Building on work done in earlier phases, the team works closely with government agencies to explore the heat effects of buildings, transport and industry. More information can be found at: https://sec.ethz.ch/research/cs.html
Finish Date: 08/2023
Funding body: NRF
Partners: CREATE, SEC, SMART, TUM, CAERS, NUS, SMU
Contact: Kristina Orehounig
Dynamic CO2 emission model of Zürich
The city of Zurich, has adopted the targets of the 2000 Watt Society, which proposes an 82% reduction in emissions by 2050 compared to 2005 levels. However, tracking progress towards these reduction targets requires consistent, reliable, and timely information on CO2 concentrations and emissions. In this project, we integrate bottom-up and top-down CO2 modelling approaches. Using a detailed building model including occupancy and heating and cooling systems, we provide better approximations of CO2 sources; particularly oil, natural gas, biomass, and district systems. This is combined with additional datasets (e.g. human activities, traffic, industrial emissions, power production) to estimate, “bottom-up” local contributions by each economic sector. Measurements of atmospheric CO2 concentrations provide independent “top-down” information. This project is a collaboration between the Urban Energy Systems and the Air Pollution / Environmental Technology Labs at Empa.
Finish Date: 12/2022
Funding body: Empa – Internal call
Partners: Air Pollution / Environmental Technology Laboratory - Empa
Contact: Fazel Khayatian
VSE "Energiezukunft 2050 – Wege in die Energie- und Klimazukunft der Schweiz"
The conversion of the Swiss energy system away from fossil energy sources to a renewable, climate-neutral power supply by 2050 is broadly accepted in politics, business and society. The crucial question: How will Switzerland achieve its energy and climate goals? To answer this, we carry out the comprehensive energy and climate study "Energiezukunft 2050" commissioned by the Association of Swiss Electricity Companies VSE. This study provides a fact-based view of the energy and climate strategy on a scientific basis. Within "Energiezukunft 2050" we simulate the entire energy system of Switzerland up to the year 2050. At the heart of the study there are four possible and realistic scenarios. They result from two dimensions, the characteristics of which are defined by social and political decisions in Switzerland. One grounds on Switzerland's cooperation with Europe, the other on the domestic acceptance of new energy infrastructures and technologies. These scenarios allow us to make what-if comparisons about the energy and climate future. Depending on which path Switzerland takes in the solution space between these dimensions, we show in detail what the consequences and the necessary measures are in terms of security of supply, costs and sustainability.
Funding body: VSE (Verband Schweizerischer Elektrizitätsunternehmen)
Partners: Universität St.Gallen (ior/cf-HSG)
Contact: Martin Rüdisüli
Involved groups: MES
ERA-Net: Underground Sun Conversion – Flexible Storage (USC FlexStore)
The ERA-Net “Underground Sun Conversion – Flexible Storage” (USC FlexStore) project aims at developing a large-scale, seasonal storage solution for erratic renewable energy. This involves injecting CO2 and H2 produced from renewable surplus electricity into a porous underground gas storage facility (a depleted gas reservoir), where microbial conversion of CO2 and H2 to methane (CH4), the main component of natural gas, takes place. Technology-wise, “Underground Sun Conversion” (USC has already been demonstrated at a test site in Pilsbach (Austria) by RAG Austria AG . The aim of the "USC FlexStore" project is now to take the USC technology to a next level and also provide a first estimation of its potential in Switzerland. Investigations will centre on the technological, commercial, energy-sector and legal requirement. Our lab's contribution is to quantify the specific needs for seasonal storage of renewable electricity to cover the expected renewable energy demand in Switzerland.
Funding body: BFE (ERA-Net)
Partners: Energie 360°, OST, Uni Bern, RAG Austria AG, IFA-Tulln BOKU, WIVA P&G
Contact: Martin Rüdisüli
Involved groups: MES
CO2-OPTIMIST: Renovated or replaced? Finding optimal solutions for the German building stock considering cumulative CO2 emissions
The buildings sector is responsible for 37% of global final energy consumption and nearly 40% of total direct and indirect CO2 emissions. In Europe, one third of the energy-related emissions comes from the building sector. This has led to actions towards decarbonization with great efforts on the renovation of the existing building stock. Yet, the application of energy efficiency measures such as upgrading the buildings’ envelope and heating systems is costly. In addition, for some cases this is not enough to achieve a satisfactory energy efficiency level. Hence, demolition and replacement might become the most cost-optimal solution. However, if the cumulative CO2 emissions were considered in both cases, what would be the cost-emissions trade-off in order to meet the overall EU emissions target for 2030? The objective of this project is to develop a case study for a typical building in the German building sector to simulate both renovation and replacement cases to identify the tradeoff between energy consumption, CO2 emissions and cost. This, by considering not only the operational energy-related CO2 emissions, but also the embodied ones in the building components.
Funding body: Industry
Partners: Industry
Contact: Cristina Dominguez, Kristina Orehounig
Involved group: MES
Abklärungen Sanierungen (MuKEn)
The aim in this project is to develop methods for the selection of renovation strategies on a national level. Energy demand of the Swiss building stock is simulated using a clustering-based approach while taking into account the evolution of the building stock (new buildings, replacement buildings and demolitions) and different renovation rates. A developed methodological approach is then used to test the effect of mandatory renovation for different building elements and building element combinations. The modeling of the Swiss building stock and its simulation of the heating energy demand allows the analysis of different renovation obligations on the national heating energy demand.
Funding body: MuKEn
Contact: Natasa Vulic, Kristina Orehounig
PACE-REFITS - Policies for accelerating renewables and effi cient building & district retrofi ts
Energy demand and CO2 emissions from buildings can be drastically reduced with state-of-the-artrenewable and energy-effi cient technologies on the building and district scales. For new buildings, thesetechnologies have been implemented widely, however for retrofi ts they are far from standard. Focusing onlarge-scale investors (LSIs), this project analyses their motivation and barriers, and which regulatoryconditions support their investment in renewable and energy-effi cient retrofi tting technologies on thebuilding scale and for in-stock district-level renewable energy systems. To assess their economicperformance, we apply static and dynamic modelling and evaluation techniques.
Funding: BFE
Academic partners: ETHZ-Group for Sustainability and Technology
Contact: Andrew Bollinger
Aliunid
Existing infrastructure in buildings, such as heat pumps or domestic hot water heaters is usually operated to purely satisfy the thermal needs of residents. However, thanks to thermal storage capacities available in buildings' thermal mass or water tanks, there exists energy flexibility in when to charge these storages. These flexibilities can be coordinated to satisfy other interests, e.g. from other players in the electric or thermal distribution grid. In a joint project with aliunid AG, controllers that optimally utilize these flexibilities are developed and implemented in the NEST demonstrator.
Funding body: Swiss Federal Office of Energy SFOE
Partners: aliunid AG, HSG, BFH
Contact: Martin Rüdisüli, Hanmin Cai
Involved groups: MES, ehub
Coherent Energy Demonstrator Assessment (CEDA)
In Switzerland, six energy demonstrators serve as research platforms for different technologies, systems, and scaling. In their analysis, CEDA will standardize these demonstrators in order to show the impact of existing technologies on nationwide implementation in Switzerland. For this purpose, Switzerland-wide communication and collaboration between four SCCERs will be carried out with a total of six demonstrators. The harmonized data collection and modelling of state-of-the-art technologies makes it possible to plan their use in industry more effectively. Case studies will be carried out in order to obtain a direct benefit from the foundation that has been developed. Empa's ehub provides ideal conditions for other demonstrators still in the planning or construction phase.
Funding body: Innosuisse
Partners: ETH Zurich, PSI, EPFL, HSR
Contact: Philipp Heer
Involved groups: MES, ehub
Renewable powered district heating networks – Repodh
Space heating accounts for around 70% of the final energy consumption in Swiss households. Therefore, as Switzerland looks towards its 2050 CO2 emission targets which require an 80% reduction in annual CO2 emissions per capita, there is a pressing need to increase the utilisation of energy efficient and renewable heating sources in the residential sector. It is claimed that district heating networks powered by local thermal energy sources like renewables (such as solar thermal energy, heat pumps, or waste heat) are considered a sustainable way to cover future heating and cooling demands in urban areas. However, existing types of district heating networks are not designed for decentralized renewable energy sources, and their integration becomes a challenging task. Existing networks are typically built in a branching configuration, whereas future renewable powered networks tend to be in ring topologies. Also, the efficiency of a thermal network is very much dependent on temperature levels of the thermal energy sources. These temperature levels can be easily controlled in networks that rely on centralized thermal energy generation sources like combined heat and power (CHP) or boiler units. However, temperature levels of non-dispatchable renewables cannot be controlled as easily as they are highly time variant. Also, the efficiency of a thermal network is strongly coupled to the supply and demand temperatures and flow rates of consumers connected to the network, and with the more frequent utilization of renewable energy sources it will become increasingly challenging to cover the temporal mismatch of demand and supply. Based on this background, a deeper knowledge is required in order to evaluate the potential of renewable energy in thermal networks. This project aims to deepen the knowledge by developing a holistic modelling framework to design and ideally operate renewable powered district heating networks (RePoDH). In this project a bi-level simulation approach is envisioned, which employs detailed dynamic modelling tools to evaluate the thermal performance and control of a network, and a simplified multi-energy modelling representation allowing to optimize the system design, for which dynamic tools are too complex, and computationally intensive. The two simulation approaches will be connected with a geographical information system, to evaluate potential network configurations using geo-referenced information. With the modelling framework we will assess how networks with a high share of renewable energy sources should be designed, in order to improve the operation of the network in terms of security and energy autarky. Moreover, we will evaluate what types of districts are suitable for RePoDH networks, and what types of networks should be used for which district in order to contribute to reaching future emission targets for our society.
Funding: SNF
Contact: Kristina Orehounig, Danhong Wang
Involved group: MES
Swiss Competence Center for Energy Research – Future Energy Efficient Buildings & Districts SCCER FEEB&D
The vision of the Swiss Competence Center for Energy Research on Future Energy Efficient Buildings & Districts (SCCER FEEB&D) is to develop solutions for the Swiss building stock which will lead to a reduction of the environmental footprint of the sector by a factor of three by 2035 thanks to efficient, intelligent and interlinked buildings.
The SCCER FEEB&D is addressing this challenge in a combined effort by leading Swiss and international partners from academia, industry and the public sector.
Funding: Innosuisse – Swiss Innovation Agency
Partners: Empa, ETH Zurich, EPFL, HSLU, Uni Geneve, FHNW
Contact: Matthias Sulzer
Involved groups: BEST, MES, ehub
Energy turnaround – Technical – Regulations – EnTer
The research project focusses on the aspect of technical regulations (TER). To support the achievement of the first mile stone of the energy strategy 2050 (ES2050) in the year 2035, which combination of regulatory measures, in particular energy regulations, can be most effective and efficient? The cantonal model regulations in the energy sector (MuKEn) are used as a research subject. Today's MuKEn2014 reaches technical, economical, and social boundaries. New methods, concepts and elements in the field of technical energy regulations are to be investigated and possibly considered in a future regulation.
Funding: SNF- NFP, EnDK
Partners: ETH-SuSTec, HSLU
Contact: Matthias Sulzer, Kristina Orehounig
EBM - Electricity Based Mobility
The main goal of the EBM project is to compare future CO2 emissions from electricity based mobility to the conventional mobility technologies and their developments and show CO2 emission reduction potentials with those technologies. In this project, commissioned by the Competence Center Energy and Mobility (CCEM), the actual CO2 content of future electricity based mobility (EBM) is assessed in terms of CO2 emission per km driven. To this end, a Life Cycle Analysis (LCA) with respect to CO2 emissions is conducted on both vehicles and fuels. The CO2 intensity of the used electricity is based on different future passenger car fleet compositions, mobility demand and charging/fueling patterns. Moreover, strate-gies, such as time-delayed fuel production / electricity supply, are derived to minimize these grid-related CO2 emissions of EBM.
Funding Source: CCEM
Contact: Sinan Teske
Partners: PSI, ETHZ, EPFL
H2E - Hydrogen Production for Mobility (H2 Energy)
As part of an R&D project funded by the Federal Office of Energy (FOE) on the hydrogen (H2) production at a run-of-river power plant, this accompanying study investigates in particular the arrangement. Based on the pilot operation at the Eniwa hydropower plant, it is analysed how the production of H2 by means of electrolysis for a logistics fleet of 200 fuel cell trucks can be integrated into the local and national electricity supply. The complex relationships between regional electricity production and consumption, the design of hydrogen production and filling stations, and the needs of fleet operation are analysed for a past year and an operating strategy for the H2 production is made.
Funding Source: H2 Energy AG
Contact: Sinan Teske
Partners: H2 Energy AG
ehub
BFE S-DSM
The aim of this project is to develop and practically test a building automation system that regards the CO2 footprint (carbon footprint, CF) of the Swiss grid electricity and thus supports a sustainable operation of buildings. Two control concepts shall be compared. On the one hand a concept aiming at distribution network operators (VNB), on the other hand a concept to be implemented directly at prosumers, i.e. the Building. Since today's building operations do not take the CF profile into account, we assume that there is great potential for savings of CO2 emissions. An estimate based on historical data shows a potential saving of 22% for a poorly insulated two-family house, which can lead to a saving of one tonne of CO2 equivalent per year. This exclusively by adjusting the operation of the plant. In this project, this potential is to be analysed and exploited by means of an office/commercial use (K3 superstructure, Wallisellen) and a residential use (NEST Demonstrator, Dübendorf) by quantifying and validating in a practical test. At both locations, the building operation is extended in such a way that the practicability of the developments can be demonstrated and expected reductions of the CF can be assigned on the basis of measurement data.
Funding body: BFE
Partners: die werke Wallisellen
Contact: Philipp Heer
Energy and comfort optimization in living and working environments through a user-centered predictive control (UC-DPC)
User need for comfort is one of the most critical barriers for energy efficient living and working. Recent advancements in automatic optimization of room climate successfully foster energy efficiency, but usually ignore comfort needs. In this project, we will introduce an approach, which aims at maximizing energy efficiency and user comfort at the same time. For this purpose, Empa NEST is used as a testbed. Machine learning based state of the art energy optimization algorithms (Reinforcement Learning) are combined with real time user feedback. Our previous work suggests an energy saving potential of around 20%.
Funding body: BFE
Partners: mehr als wohnen, Bouygues, Empa BEMC, Empa AMP, Empa NEST
Contact: Bratislav Svetozarevic
Carbon footprint optimization of electricity in smart buildings (CAPITAL)
In Switzerland, ~50% of our final energy demand is linked to the building stock with an increasing electricity demand that depends on a national mix with significant variations of its carbon footprint (CF). Traditional load profiles of buildings are not coordinated with nationwide renewable energy production meaning that electricity with a low CF is not utilized optimally.
Recent research activities on the dynamic life cycle assessment (DLCA) of energy flows in Swiss buildings, and on data-driven control of buildings, should be combined to tackle the reduction of present and future GHG emissions from electricity uses in buildings. This potential reduction can then be optimized with data-driven operationalization of energy flexibility that has been developed within recent research activities.
It is envisioned that up to 20% of indirect emissions can be reduced due to a sustainability aware smart building Operation.
Funding body: Empa Board
Involved Labs: Empa UESL, Empa TSL, Empa NEST
Contact: Philipp Heer
Innosuisse Oxygen at Work: Development of a non-intrusive, data-driven algorithm for occupant detection using indoor air quality data
A robust, grey-box approach for occupant detection based on indoor air quality data is developed, using Oxygen At Work's previous development and Empa NEST's extensive measurement infrastructure and expertise in data-driven smart home solutions.
Funding body: Innosuisse
Partners: Oxygen at Work
Contact: Michael Locher
Aliunid
Existing infrastructure in buildings, such as heat pumps or domestic hot water heaters is usually operated to purely satisfy the thermal needs of residents. However, thanks to thermal storage capacities available in buildings' thermal mass or water tanks, there exists energy flexibility in when to charge these storages. These flexibilities can be coordinated to satisfy other interests, e.g. from other players in the electric or thermal distribution grid. In a joint project with aliunid AG, controllers that optimally utilize these flexibilities are developed and implemented in the NEST demonstrator.
Funding body: Swiss Federal Office of Energy SFOE
Partners: aliunid AG, HSG, BFH
Contact: Martin Rüdisüli, Hanmin Cai
Involved groups: MES, ehub
Coherent Energy Demonstrator Assessment (CEDA)
In Switzerland, six energy demonstrators serve as research platforms for different technologies, systems, and scaling. In their analysis, CEDA will standardize these demonstrators in order to show the impact of existing technologies on nationwide implementation in Switzerland. For this purpose, Switzerland-wide communication and collaboration between four SCCERs will be carried out with a total of six demonstrators. The harmonized data collection and modelling of state-of-the-art technologies makes it possible to plan their use in industry more effectively. Case studies will be carried out in order to obtain a direct benefit from the foundation that has been developed. Empa's ehub provides ideal conditions for other demonstrators still in the planning or construction phase.
Funding body: Innosuisse
Partners: ETH Zurich, PSI, EPFL, HSR
Contact: Philipp Heer
Involved groups: MES, ehub
Data Predictive Control
The building sector is responsible for more than one third of the global final energy consumption. Heating and cooling of buildings requires approximately half of this energy. Improving the operation of heating and cooling systems has therefore a significant impact on the mitigation of the climate change. Model Predictive Control (MPC) has been shown to be an energy efficient approach for building climate control. However, the costs to generate the required first-principle based models might be a bottleneck for widespread industrial application of MPC in the building domain.
This project aims at the replacement of first-principle based building models by data-driven models in the MPC framework (called Data Predictive Control (DPC)). Recent experiments with data-driven models based on adapted Random Forests revealed the high potential of DPC for energy efficient climate control in residential buildings. Further comparisons with state-of-the-art controllers like conventional MPC as well as the implementation of the DPC algorithm into an embedded system, is part of this project. With the implementation into an embedded system, we are able to test and evaluate a thermostat retrofit case for residential buildings.
Funding body: internal
Partners: ETH Zurich
Contact: Benjamin Huber
Involved group: ehub
Ecobilan Dynamique des Bâtiments (EcoDynBat)
The aim of the EcoDynBat project is to study the influence of temporal variability when calculating the environmental impacts of consumed electricity in buildings. This work will consider the temporal fluctuations of 1) national electricity generation, 2) electricity imports, 3) network losses and conversions, 4) decentralized electricity generation and 5) electricity demand within buildings.
Funding body: Swiss Federal Office of Energy SFOE
Partners: HES-SO, SUPSI
Contact: Philipp Heer
Involved group: ehub
RAPIDE
A major barrier limiting the installation of photovoltaics are voltage quality problems they cause in the distribution grids. Instead of expensive grid reinforcements, these issues can be solved by using the photovoltaics’ inverters to optimize the feed-in of reactive power. Today parameters controlling reactive power are pre-set at the factory and do not consider the situation in the local grid.
By using grid measurements and a self-learning algorithm the proposed method can optimize parameters in-situ without the need for a network model. The parameters can be updated regularly, i.e. to reflect different seasonal power flows or the addition of new plants.
In this project the performance of a developed algorithm is tested on the ehub infrastructure.
Funding body: Innosuisse
Partners: Fleco Power, CSEM
Contact: Philipp Heer
Involved group: ehub
Swiss Competence Center for Energy Research – Future Energy Efficient Buildings & Districts SCCER FEEB&D
The vision of the Swiss Competence Center for Energy Research on Future Energy Efficient Buildings & Districts (SCCER FEEB&D) is to develop solutions for the Swiss building stock which will lead to a reduction of the environmental footprint of the sector by a factor of three by 2035 thanks to efficient, intelligent and interlinked buildings.
The SCCER FEEB&D is addressing this challenge in a combined effort by leading Swiss and international partners from academia, industry and the public sector.
Funding: Innosuisse – Swiss Innovation Agency
Partners: Empa, ETH Zurich, EPFL, HSLU, Uni Geneve, FHNW
Contact: Matthias Sulzer
Involved groups: BEST, MES, ehub
SAlt, LIthium-ion and SuperCapacitors storages in the distribution grid (SALISC)
Decentral Batteries or district sized battery installations provide a layer of flexibility to the distribution grid and its stakeholder. In SALISC Empa investigates in the design and operational stages of battery usages to determine their profitability in 2018 and in 2025. Multiple storage technologies, sizes, locations and control schemes are analyzed according the general conditions of a distribution grid of Glattwerke AG acting as DCO. The most promising solutions are implemented on the ehub platform and its storage technologies to exemplary validate the performance of the found solutions.
Especially the effect of Molten Salt (NaNiCl2) and Lithium Ion (NMC-G) Storages is investigated. The impact of additional of Super Capacitors shall highlight the significance of this technology to a storage setup in a distribution grid.
Funding body: Industry
Partners: Glattwerk AG, FZSonick
Contact: Philipp Heer
Efficient tethered drones for airborne wind energy (T10)
TwingTec develops together with Empa the next generation of wind energy using a tethered drone that flies like a kite. During this project a full scale tethered drone prototype will be developed and tested.
The goal of this project is to design, build and test a full scale tethered drone prototype for a 10kW pilot system. This prototype will address the two critical remaining challenges before development of an upscaled system can begin: efficiency and energy autonomy.
Funding body: Innosuisse
Partner: TwingTec AG
Contact: Philipp Heer
Eco-friendly and Ageing-Aware Energy Management Software for Li-ions Battery (ECOBATTEM)
The main goal of the project ECOBATTEM is to experimentally proof that the large installation of battery storage systems (BSS) equipped with an ageing-aware energy management software is the best way to satisfy the 2050 Swiss Energy Strategy. The main reasons behind this goal are:
- The BSS will allow to increase the energy self-consumption and consequently reduce the global CO2 emissions;
- An ageing-aware strategy for BSS deployment allows for maximizing the lifetime of the BSS itself with a consequent large renewable energy self-consumption and CO2 reduction;
- A BSS with a minimum state of ageing can be deployed by utility/DSO in order to provide ancillary services to the power grid (such as peak-shaving and frequency/voltage control)
Funding body: BFE
Partners: Aurora’s Grid LLC, Leclanché SA, HES-SO VD, HES-SO Fribourg
Contact: Philipp Heer
Nanoterra heatreserves
The project aims to make recommendations about the implementation of control, communications, and business schemes for enabling thermal loads to provide ancillary services in the form of control reserves for the Swiss power grid. Ancillary services provide a fast-reacting compensation for a power shortage or surplus in the transmission grid.
Thermal loads such as building HVAC systems and household appliances have an inherent thermal storage capacity, which provides flexibility in their power consumption without compromising their original purpose. Hence, one can envision effective demand response schemes exploiting these thermal loads to balance the power grid locally, reducing transmission congestions, improving ancillary service market operations, and reducing power peaks. Most importantly, this facilitates the integration of renewable energy sources, which critically rely on ancillary services today. heatreserves is the first external project using the ehub platform after its launch
CCEM ideas4cities
In Switzerland and many other European countries, the future energy system will rely heavily on renewable energy. This will cause an important reengineering of this part of the electrical infrastructure. Therefore, a massive penetration of distributed power sources and distributed storage devices calls for a new layout and system design of the urban energy system.
The results of our studies will form the basis for the planning such systems and grids. Both the design (planning) of the energy system and the operation will be considered.
The developed microgrid framework consists of independent resource and grid agents communicating with each other. The goal is that the grid operates in a safe state as it can determine the load on its lines and the resources can operate flexibly and independently. This cooperation based, distributed control scheme has a cycle time of 100ms leading to fast corrections form optimal trajectories. With this scheme one can also operate in islanding mode with the ability to connect and disconnect whole districts to the distribution grid.
Optimized local control scheme for active distribution grids using machine learning techniques
Poster
Description: The decentralized control scheme based on Machine Learning (ML) technique proposed in [1] is applied to the NEST microgrid, allocated in the Empa Laboratory in Dübendorf. However, due to the low voltage magnitudes over the grid, in order to have consistent results, the battery is forced to operate into a high injection regime, increasing the local voltages and allowing to adopt the Reactive Power Control (RPC) as active measure to achieve network-wide optimal operation. In this approach, the online optimization problem is performed in two stages. First, a day-ahead optimization problem for the BESS is implemented with the objective to impose high injections during noon hours and guarantee a secure operation. Second, a centralized, OPF-based scheme is used to generate a sequence of optimal DER setpoints accounting for BESS injections. Finally, the local DER controllers are developed as explained in [1] and applied in the real-time operation.
[1] F. Bellizio, S. Karagiannopoulos, P. Aristidou, and G. Hug, "Optimized local control schemes for distribution grids using machine learning techniques," IEEE Power and Energy Society General Meeting, 2018.
Partner: ETH Zürich
Contact: Philipp Heer
Google Summer of code: Visualization Dashboard for Empa-NEST
Contact: Reto Fricker
Felix Bünning
Building energy systems can be expected to undergo radical change in order to adapt to the needs of the future renewable energy environment. This includes the integration of renewable energy sources in the building itself (such as solar-thermal and PV), possibilities to interact with the electricity grid in smart-grids as a reserves provider, possible connection to novel district energy concepts such as combined heating and cooling networks, etc. Consequently, new concepts to control such systems are required, which leads to the following governing research questions:
What are the upcoming challenges in this field and how can they be tackled?
Novel technologies call for novel methods or the adoption of established control concepts. Electrical and thermal reserves through buildings, the integration of buildings in combined heating and cooling networks, renewable integration and other new topics are addressed by adapting existing control concepts to new problems and by developing new approaches based on data-driven methods and machine learning.
How can building and district energy control be made more real-life relevant, meaning cheaper and implementable?
Although proven effective, even conventional MPC for thermal zones has never found mass-adaption in the building energy industry so far, because the implementation is very complex and cost-inefficient. Thus, simplifications and new methods need to be found that allow intelligent control of district and building energy systems in real life applications.
Loris Di Natale
With the ratification of the Paris Agreement in 2015, many countries in Europe and in the world, including Switzerland, committed to ambitious greenhouse gas emission targets in 2050. In that context, electrification of the end-use services is required and developed around the globe.
In particular, the share of electrical vehicles (EVs) in the car market is growing faster than ever to replace classical Internal Combustion Engine (ICE) vehicles. Simultaneously, buildings are undergoing a similar transition to electricity, with heat pumps-based heating systems. Additionally, new constructions are now pushed to install on-site renewable generation capacity - typically through the installation of photovoltaic (PV) panels.
Taking all these changes into account, we can today use the growing share of EVs as an opportunity rather than a burden, due to the additional electricity demand required to charge them. Taking advantage of the introduction of EVs with bidirectional chargers and smart charging/discharging strategies, we can indeed simultaneously reduce the peak in the electricity demand and maximize the utilization of renewable energy production. The key is to consider EVs as energy storage systems as well as transportation means.
The following research question arises: What is the optimal use of electric vehicle batteries to maximize the utility from self-generated renewable energy and decrease the demand during peak-hours, thereby reducing the global energy costs of households? To answer it, in this project we aim to use state-of-the-art data-driven control techniques, like reinforcement learning, to tackle this problem.
Cristina Dominguez
Ensuring access to affordable, reliable, sustainable and modern energy for all was listed as one of the Sustainable Development Goals (SDG) proposed by the United Nations for the year 2030. Due to the strong link between electricity access and socioeconomic development, electrification projects are often listed as a top priority in developing countries. Still, according to the International Energy Agency, around 17% of the global population lack access to electricity, and 84% are located in rural areas from sub-Saharan Africa, Asia and Latin America. Due to the high investment required for infrastructure works to extend the electric grid to these areas, other potential solutions are developed, such as the installation of stand-alone systems and micro or mini-grids. For any chosen solution, the starting point is to have an accurate knowledge of the energy demand of these areas, which is currently estimated through field studies, knowledge transfer and other modeling tools. Due to the lack of reliable data for these areas, some of these methods make general assumptions and use macroeconomic drivers that do not represent the rural population, which results in an overestimation of the energy demand, consequently, in an overinvestment of resources.
The aim of this research is to develop a methodology to model the current and future energy demand of rural households in developing countries in order to improve and support the planning of rural electrification projects. This methodology is based on a hybrid approach combining bottom-up and top-down modeling techniques, utilizing available data from household to national level in order to create a robust framework that can be generalized to a broad geographic scope.
Marc Hohmann - Predictive optimal operational strategies for urban energy systems
website | poster
Distributed energy systems require active control strategies in order to balance multiple energy streams and to ensure a reliable, economic and environmentally friendly operation. Multi-carrier energy systems offer additional degrees of freedoms compared to single carrier operational schemes managing only electricity, gas or heat. The objective is to increase energy efficiency, decrease carbon emissions and handle the uncertainty and intermittency of renewable energy sources. Active control strategies are therefore crucial to the transformation of energy systems, a central element of climate change mitigation measures.
The objective of this work is to develop improved central local energy management systems for urban districts. These must be able to include non-convex characteristics of energy conversion processes, decision-making for short- and long-term storage and avoid suboptimal results due to the self-interest of the energy system's agents. Using mixed-integer linear programming, energy conversion processes can be modeled with high accuracy. Aggregation methods can reduce the computation load when making long-term decisions. Mechanism design and locational marginal pricing can ensure that optimal operation modes are achieved in complex systems.
A prototype controller is implemented and tested on the NEST platform, located at Empa in Dübendorf, Switzerland. Distributed controller architectures are compared to the central control scheme proposed by this work.
Julien Marquant - Facilitating Multi-Scale Urban Energy Systems Modelling
website | poster
Network-level energy optimisation approaches can determine the optimal location of generation technologies within a region and the optimal layout of energy distribution networks to link them. This is a multi-scale problem as it must encompass decentralisation at the building, district, city or regional scale. However, computational limitations arise at larger spatial scales if full resolution is re-tained, and difficulties emerge in the quantification of different urban agglomeration levels when attempting to model network be-haviour at multiple spatial scales. Nevertheless, a tractable multi-scale optimisation of a large urban area is possible using a clustered, aggregated energy hub repre-sentation.
The main objective of this research is to model and optimise the interaction of complex energy net-works in order to understand the trade-off between centralised and decentralised energy systems at different urban scales. A method for multi-scale urban energy systems modelling with a hierarchical approach will be developed to facilitate this. An evaluation of the approximations necessary to make this modelling computationally feasible will then be conducted. Finally the process developed will be applied to a case study, and the outcomes analysed in the context of the Swiss Energiewende 2050.
Georgios Mavromatidis - Modelling of decentralized energy systems under uncertainty
website | poster
“Distributed Energy Systems (DES) are expected to be a core component of future urban energy systems incorporating a multitude of generation and storage technologies to supply the energy needs of urban districts. The motivation for this paradigm shift stems from global challenges like climate change, the high degrees of urbanization, cities’ high energy demand density and the potential for building integrated renewables.
The challenge to optimally design and operate DES relies heavily on modelling; however, as with any numerical modelling effort, models for the optimal DES design are irrevocably affected by uncertainty. Human behavior and the uncertain future global economic and energy outlook are only a subset of factors that can introduce uncertainty to a DES model.
Therefore, the aim of this research is to create an integrated modelling framework that will in a systematic way incorporate uncertainty into the design process of distributed urban energy systems. Embarking from a design model based on the energy hub concept, techniques from Uncertainty and Sensitivity Analysis are employed to investigate uncertainty’s impacts and identify its main drivers. Subsequently, techniques for Optimization under Uncertainty are used in order to select single optimal designs that will be robust in the face of uncertainty.”
Somil Miglani – Optimal energy system and retrofit measures for residential buildings/districts: A detailed modeling perspective on ground source heat pumps
website | poster
Future cities, urban areas and buildings are expected to undergo a transformation towards more sustainable energy systems. This transformation involves a move towards increased use of renewable energy resources, decentralized forms of energy production, energy efficient buildings, thermal networks etc. The aim is to achieve such a transformation optimally, considering economic and environmental constraints. The current energy systems in buildings, especially heating systems, are based on fossil fuels and must give way to more energy efficient and environmentally benign alternatives. Each building can either be connected to a district heating system or it can be individually heated through a fully decentralized standalone systems such as solar thermal for instance. Since the potential for decentralized energy sources exhibits a high degree of spatial and temporal variability, the optimal integration of these technologies in existing buildings remains an open question.
This research aims at investigating the technological tradeoff between renewable energy based standalone systems and a small scale district heating system taking the total costs and carbon emissions savings into account. More specifically, methods will be developed to evaluate optimal configurations of energy systems for single buildings and clusters of buildings representing spatially and temporally differentiated energy demand and supply patterns. Finally, this analysis of the above mentioned technological tradeoff is carried out on multiple case studies representing urban areas, diverse with regard to technical parameters that differentiate them in their spatial characteristics.
Boran Morvaj - Holistic optimisation of distributed multi energy systems for sustainable urban areas
website | poster
The aim of this PhD project is to develop a holistic optimisation model of distributed multi energy sys-tems to explore how existing urban areas can be best transformed into sustainable ones. Models are based on the energy hub concept. It combines models of distributed energy resources, electrical grids, decentralised district heating networks and building energy systems into one integrated optimisation model in order to find synergistic effects between them. The model is used to determine the optimal design and operation of distributed multi energy systems under different objectives such as the multi-objective minimisation of carbon emissions and costs, energy import independency and optimal power flow. Furthermore, the impact and benefits of decentralised district heating networks as well as large-scale integration of renewables in the existing electrical network are analysed. Finally, key influencing factors affecting the optimal solutions are identified.
Portia Murray - Integration of sustainable multi-hub systems from the building performance perspective
Developing a method to assess the best combination of technologies for decentralized district heating systems to analyze district heating performance on the neighborhood scale. Storage technologies are of particular focus in this research, especially power-to-gas and battery storage technologies for storing excess renewable energy during off-peak demand. These methods are compared against more traditional storage and conversion technologies, such as thermal storage tanks, heat pumps and boilers. All technologies are incorporated into both a centralized and decentralized Energy-Hub model on the neighborhood scale for analysis.
Emmanouil Thrampoulidis - Large-scale building retrofit towards more effective energy policies and strategies
The building sector accounts for more than 40% of the total energy consumption and emissions in Europe. Building retrofit is of greatest importance to reduce the environmental footprint of the existing building stock. It may refer to two types of interventions: the first pertaining to interventions on the building envelope, for instance by enhancing the thermal insulation of a building’s walls, and the second one to building energy system replacements and renewable technologies integration. Even though building-specific solutions are important there is much more to gain if those are part of a coordinated large-scale retrofit plan. A more systematic and effective solution to derive energy policies, strategies and incentives is one of the benefits of such large-scale retrofit approaches.
Building retrofit is a complex process, which involves the use of highly heterogeneous building information (census data, 3D building data, weather data) and computationally intensive tools (multi-objective optimization, building simulation). Usually, due to the limited timeline and investment of the retrofit projects the building process is extensively simplified, for instance by just performing some steady state calculations. Moreover, most large-scale retrofit projects are based on archetypes and arbitrary generalize. Eventually, such approaches might lead to results that highly deviate from reality.
Therefore, the aim of this research is to exploit the principled generalization ability of machine learning to develop a large-scale data-driven retrofit approach with the use of both simulation and real building data. This approach can be more beneficial than the conventional ones in terms of: (i) generalization ability and adjustability, (ii) ease of application, (iii) retrofit selection time and (iv) computational cost. Last but not least, such a surrogate retrofit approach can contribute towards deriving more effective energy strategies and eventually accelerating the adoption of building retrofit measures.
Christoph Waibel - Hyper-Heuristic Framework for Multi-Objective Optimization of Urban Systems
website | poster
A major share of global resource and energy consumption can be associated with cities. Considering the ongoing trends of urbanization and population growth it becomes evident that their evolution is a crucial keystone in tackling global environmental and economic challenges. It has been shown that cities and buildings are far from the ”efficiency possibility frontier” and could achieve much higher utility with less energy and resource input. One reason for inefficient designs can be found in the inherent complexity of the design process, which requires the expertise of multiple disciplines. The traditional approach to cope with this is to separate responsibilities and to exchange information in sequential steps. However, generating, processing and exchanging information is a costly practice and every change in design requires re-evaluation of other related disciplines. Thus, only a low degree of reciprocity is realized.
Holistic optimization methods may overcome this issue, as they can inform the design process by exploring vast numbers of design solutions across multiple performance criteria simultaneously. One of the practical challenges lies in the selection of appropriate optimization algorithms best suited to specific problem formulations. Hyper-heuristics deals with this by introducing a higher-level method for automatically selecting and tuning a tailored heuristic from a set of algorithmic operators. This research focuses on the development and application of a hyper-heuristic framework for multi-objective urban design, including building morphology and urban energy systems. Questions to be addressed using the hyper-heuristic optimization framework include the range and degree of multi-energy network connectivity within and across neighborhoods, the degree of densification for optimal demand and renewable energy generation, and the use of building standards (Passivhaus, nZEB, active house) in the context of a connected multi-energy-grid. Hyper-heuristic methods have the potential to change the overall design approach and enable holistic design and planning, where reciprocities between different disciplines and scales can be captured, thus leading to more efficient urban systems.
Danhong Wang - Renewable powered district heating networks
website | poster
Space heating accounts for around 70% of the final energy consumption in Swiss households. Therefore, as Switzerland looks towards its 2050 CO2 emission targets which require an 80% reduction in annual CO2 emissions per capita, there is a pressing need to increase the utilisation of energy efficient and renewable heating sources in the residential sector. It is claimed that district heating networks powered by local thermal energy sources like renewables (such as solar thermal energy, heat pumps, or waste heat) are considered a sustainable way to cover future heating and cooling demands in urban areas. However, existing types of district heating networks are not designed for decentralized renewable energy sources, and their integration becomes a challenging task. Existing networks are typically built in a branching configuration, whereas future renewable powered networks tend to be in ring topologies. Also, the efficiency of a thermal network is very much dependent on temperature levels of the thermal energy sources. These temperature levels can be easily controlled in networks that rely on centralized thermal energy generation sources like combined heat and power (CHP) or boiler units. However, temperature levels of non-dispatchable renewables cannot be controlled as easily as they are highly time variant. Also, the efficiency of a thermal network is strongly coupled to the supply and demand temperatures and flow rates of consumers connected to the network, and with the more frequent utilization of renewable energy sources it will become increasingly challenging to cover the temporal mismatch of demand and supply. Based on this background, a deeper knowledge is required in order to evaluate the potential of renewable energy in thermal networks. This phd project aims to deepen the knowledge by developing a holistic modelling framework to design and ideally operate renewable powered district heating networks (RePoDH). In this project a bi-level simulation approach is envisioned, which employs detailed dynamic modelling tools to evaluate the thermal performance and control of a network, and a simplified multi-energy modelling representation allowing to optimize the system design, for which dynamic tools are too complex, and computationally intensive. The two simulation approaches will be connected with a geographical information system, to evaluate potential network configurations using geo-referenced information. With the modelling framework we will assess how networks with a high share of renewable energy sources should be designed, in order to improve the operation of the network in terms of security and energy autarky. Moreover, we will evaluate what types of districts are suitable for RePoDH networks, and what types of networks should be used for which district in order to contribute to reaching future emission targets for our society.
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