Category: Energy

Fit4Green

Federated IT for a sustainable environmental impact

Duration: 01/2010 – 06/2012  Funding:  FP7 – ICT for Energy Efficiency

FIT4Green

FIT4Green contributes to ICT energy reducing efforts by creating an energy-aware layer of plug-ins for data center automation frameworks. 

The FIT4Green platform gives users insights into their energy consumption. The plug-ins enhance IT solutions deployment strategies with respect to energy consumption, for example by moving computation and services around a federation of data centers, and switching of idle machines. FIT4Green implements these energy-saving measures without having to compromise for Quality of Service or compliance with Service Level Agreements. Being a generic solution, the plug-in may easily be adapted to different systems in both single site and federated data centers. 

FIT4Green is expected to reduce energy consumption by at least 20% in direct server and network devices. An additional 30% savings in cooling needs is expected. 

Contribution

Almende has been involved in all phases of the FIT4Green project but was mainly responsible for the energy control plug-ins; from design to implementation, testing and validation. The research has taken different perspectives into account, namely, the business and functional requirements of the FIT4Green platform, the reference architecture and design of the plug-ins, the data centre and energy models, the energy aware optimization policies, and exploitation and dissemination activities of the project. 

Results

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Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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All4Green

All4Green

All4Green brings together relevant stakeholders to create a ‘sustainable ICT ecosystem’ for the datacentre sector. By enabling more collaboration between energy providers, data centres and their clients, based on their expected flexibilities in supply and demand, ICT resources can be allocated more efficiently to provide the requested services, while saving energy and reducing greenhouse gas (GHG) emissions. It turns out that this collaboration can result in a 10 to 20 % reduction in the overall data centre energy demand.

For this purpose smarter communication structures have been developed, in the form of plug-in systems consisting of agents using the negotiation strategies developed in the R&D work packages of the All4Green project. Both data centres and energy providers are represented by agents in their negotiations. This allows both parties to match supply and demand. Based on these negotiations, the data centres adjust their job scheduling and migration and resource allocation across the federated data centres.

The systems have been tested in three scenarios. The pilot in Passau (Germany) was of particular importance because it involved an actual energy provider and an actual data centre. As the project has come to a close, the research results are being disseminated and exploited. According to market analysis, the area around London and the region of Paris are particularly appropriate regions for implementing the All4Green negotiation platform.

Contribution

The contribution of Almende consisted of developing negotiating software agents that represent and act on behalf of all parties involved. Negotiation factors or objectives include the energy costs, greenhouse gas savings, private priorities and other external factors to optimally coordinate and match the dynamic service requests with available energy supplies.

Results

This was the first time we used our open-source, multi-purpose web-enabled agent platform Eve in the context of a European research project. Based on lessons learned in this experience, Eve has been confirmed as a reliable agent platform and extended with new functionalities. Also, Almende has developed new algorithms that can be applied to new domains and successfully developed and employed new agent-based simulation models and tools for studying negotiation behaviours at the micro and macro levels.

More info?

Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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Adapt4EE

Adapt for Energy Efficiency

Duration: 10/2010 – 10/2014  Funding: FP7

Adapt4EE

Energy efficiency criteria are usually only set in relation to the construction or maintenance of buildings. Energy consumption resulting from actual use of the structure is often left ignored. This is a waste, because most energy is consumed during the operation phase of a building. Altering aspects of the building to accomodate for real life use, results in high costs.

The Adapt4EE project partners developed new simulation and modeling tools, which allow designers and architects to use information about occupants (presence, movement, activities) early on in the design phase of architectural project.

Simulation tools that were previously available often allowed for modeling of thermal processes, lighting, acoustics and fluid dynamics, but did not not take into account the actual human occupants. Further, they were mainly meant for research purposes, and were therefor rarely used by actual designers, because of their steep learning curve.

Multi-type sensors have been used to evaluate user behaviour and occupancy. Based on these observation, future occupancy and business patterns can be predicted.

The challenge was to incorporate many diverse factors, from environmental factors (climate, (day)light) and maintenance, to business processes and occupant behaviour (psychological processes, personal preferences). Adapt4EE combined different existing modeling languages and methods to develop a holistic multi-agent based simulation framework that could aggregate information from many different sources.

Contribution

Almende delivered a training tool for calibrating (predifined) business proces models, such that they better explain real-world measurements, related to occupancy and energy consumption of the building. Also, a generic agent-based simulation tool was developed which is able to co-simulate with the widely used EnergyPlus to help evaluate buildings designs in terms of economical, ecological and social performance (that is business efficiency, energy costs and occupant comfort).

Results

To Almende, the benefits of this project were among others the creation of the simulation toolkit including algorithms for ad-hoc allocation of resources to business process instances. It also enabled Almende to apply several newly developed visualizations of Almende's vis.js toolkit. Besides that, the company extended the expertise, skills and competencies in among others agile development, business processes modelling, semantic reasoning and evolutionary competition.

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Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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SEAM4US

Sustainable Energy Management for Underground Stations

Duration: 10/2011 – 12/2014  Funding: FP7-ICT

SEAM4US

In large metropoles such as London or Delhi, the underground transportation system is the biggest energy consumer of the city, using as much electricity as 250,000 households. Over 30% of this energy is used by lighting, ventilation, climate control, security, information and communication, ticketing, and signalling systems in and around the underground stations. Although energy efficiency is internationally high on the political agenda, little is known about day-to-day energy consumption in these massive transportation hubs. Through empirical modelling of energy consumption and designing distributed control mechanisms for the metro station, the SEAM4US project was expected to reduce energy consumption by 5% – 10%. The Barcelona metro system has been used as a live test grounds.

The SEAM4US project proposed several steps towards reducing energy consumption. First, analysis would point out which systems are wasting energy under real-world conditions. Energy consumption by these systems has been empirically modelled during and off peak hours and under different daily and seasonal weather conditions.

In order to increase energy savings for such systems, users were encouraged to use the station in an energy-saving way. During off-peak hours, passengers could for instance be guided towards the main areas, so that in the auxiliary areas the lights could be dimmed, or elevators and ticket machines shut down. Of course, these areas had to be monitored for increased use, so passenger occupancy and flow models had to be acquired.

Another way to improve energy efficiency in the station’s systems, for example for ventilation, is exploiting external factors, such as outside temperature, wind or air flow from moving trains. These form renewable energy sources, which make overall climate and air quality operations cheap and low-power. In order to take full advantage of such factors, they must be predicted by empirical models, and a sensor-actuator network must be in place to open or close doors and windows.

Contribution

Almende has designed and developed the passenger occupancy monitoring system via advanced computer vision algorithms performed over the videos taken by the existing CCTV infrastructure. The company also took care of the deployment of such system in the pilot station and integration with the rest of the SEAM4US architecture. Besides that, Almende contributed to the development of the intelligent control algorithms of SEAM4US and to the development and deployment of the overall SEAM4US architecture.

Results

The project contributed to our expertise in working with computer vision algorithms to draw meaningful patterns from raw image data, as well as our expertise functioning as a system integrator. Finally, the project improved our knowledge on the development of data-driven control algorithms.

More info?

Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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ACCUS

ACCUS

Many automated urban systems – like traffic lights, energy distribution grids, and outdoor lighting – are managed by self-contained embedded systems. This is an undesirable situation, because these systems are highly co-dependent, on each other, and on the behaviour of people.

In ACCUS, the project partners developed the necessary infrastructure to integrate (sub)urban embedded systems into a system-of-systems, allowing them to cooperate. Such a system-of-systems improves (energy)efficiency and their ability to adapt to and anticipate human behaviour. The ACCUS infrastructure was expected to provide the basis on which third parties can run various applications. Unfortunately, the project ended after roughly two years.

Contribution

Almende joined the ACCUS project as a member of DevLab. Almende and DevLab focused chiefly on gathering and interpreting sensor data from heterogeneous sources, such as the urban embedded systems themselves, wireless sensor networks and mobile devices.

In addition, we developed prediction algorithms to allow the urban system-of-systems to anticipate real-life behaviour of occupants and other objects, such as cars.

Results

The project contributed valuable techniques for heterogeneous sensor data analysis and fusion of different data sources into higher-level states, as well as predictive analytics techniques based on the data collected. These techniques offer applications in other mobility-related projects as well.

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Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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INERTIA

Integrating Active, Flexible and Responsive Tertiary Prosumers into a Smart Distribution Grid

Duration: 10/2012 – 9/2015  Funding: FP7-ICT

INERTIA

The current energy grid is still based on a centralized and inflexible management of supply and demand for energy. But the modern energy market is becoming much more dynamic. The current grid is not prepared for a distributed energy market, in which individual households cause energy supply peaks by generating their own solar power on a sunny day. On the one hand, energy supply rates fluctuate very quickly. Renewable energy sources, such as wind and solar power, are especially unpredictable. On the other hand, the demand for energy is quite uncontrollable. Imagine the spike in demand when all across the country people come home to charge their electric cars. The energy grid must be prepared for such spikes because at this moment, the market has no way to influence and soften these peaks.

The INERTIA project proposed an Internet-of-Things-approach to the problem of energy management: Consumers gradually become ‘prosumers’; households that generate their own green energy, sell the energy when they have too much to use by themselves, and buy extra (grey) power when they need it. All these ‘prosumer hubs’ become active nodes (rather than passive elements), and are equipped with the technology to provide contextual information to the grid. In order to be able to ‘share’ energy, the different stakeholders must share information on supply and demand. Having such an information network in place, a truly free energy market emerges. Energy will be more realistically priced, based on actual supply and demand.

Contribution

Within INERTIA, Almende developed the Pi5 aggregator control software tools and approach: a secure agent-based energy demand prediction framework for the smart grid. By applying a 15-minute energy forecast, it enables the negotiation of energy deals at MV level. Thereby, it is possible to actively manage an energy budget within given/negotiated boundaries by making prioritized use of equipment based on both comfort and energy budget restrictions.

Results

The project contributed to our expertise in applying multi-agent-based systems and simulations to energy markets, and to use collaborative decision-making models to dynamically solve challenges in energy supply and demand in real-time conditions which are difficult to forecast.

More info?

Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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SG-BEMS

Smart Grids – Building Energy Management Systems: The Art of Optimizing Energy Supply and Demand for Comfort

Duration: 11/2012 – 11/2016  Funding: TKI Smart Grids 2012

Partners: Kropman, TU Eindhoven, CWI

SG-BEMS

The energy market is radically changing due to the advent of Smart Grids (SG) and Building Energy Management Systems (BEMS). Smart Grids help manage the supply and demand on the (renewable) energy market in a dynamic way, while BEMS optimize individual buildings for comfort and energy efficiency. The SG-BEMS project develops an agent-based ICT framework that fosters the synergy between Smart Grids and Building Energy Management Systems (BEMS), allowing user behaviour and demand to influence the energy market, and vice versa. In this respect, the project looks at both B2C (housing) and B2B (office buildings) applications. The proposed solution is an agent-based platform that will provide communication and interaction between different BEMS and Smart Grids. The modular character of such a system allows for scalability.

Contribution

Almende has acquired plenty of experience on the subject of smart energy grids in several closely related European FP projects, in particular Adapt4EE, SEAM4US and INERTIA. In this project, Almende contributed its open source Common Hybrid Agent Platform for developing agent-based SG-BEMS that are coupled to wireless sensor-actuator networks for internal building ventilation, air, heating and lighting management. In addition, Almende contributed to the preference modelling for the B2B and B2C applications.

Results

SG-BEMS aligned well with our vision on the Energy domain, by transforming conventional power grids to dynamic smart grids suited to the real-world interplay of supply and demand. The project contributed to our understanding of smart grids and led to the further development of our open-source Common Hybrid Agent Platform along with these principles.

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Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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OPSCHALER

Open Platform voor Smart data in Combinatie met Holistische Analyse Leidend tot Energie Reductie

Duration: 1/2016 – 9/2019  Funding: TSE – iDEEGO                                    

OPSCHALER

Getting a clear picture of the energy savings that can be obtained through the numerous sustainable upgrades that exist for buildings proves to be a big challenge for building owners. Most advices assume a certain ‘standard’ level of use and pay no mind to actual usage levels. With the advent of smart energy meters there is a wealth of data available about actual energy usage, however due to privacy regulations these are currently only publicly available after aggregation at the zip-code level, and summed over a period of months or even years. This makes it hard to use this data for actual savings calculations for individual buildings, and optimization of energy usage and production at micro levels. The goal of OPSCHALER is to develop tooling for households, homeowners’ associations (VVEs), real estate corporations, and municipal governments to use the data from smart meters to gain insight into the actual savings potential in existing households, in order to create more transparency and eliminate the barriers that currently prevent owners of real estate from investing in sustainable upgrades.

Contribution

Almende aim is to develop an agent-based multi-level data aggregation platform that is able to present and analyse energy usage data based on the use cases described above. This requires the development of technology which can ensure the privacy of individual household data at the various levels, while nonetheless providing the required insights.

Results

Almende benefits from the project through the use of agent-based technology in the practical use case of analysing and presenting energy savings, keeping in mind the privacy of the end user, which is a challenge in projects outside the energy domain as well.

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Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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MOEEBIUS

Modeling Optimization of Energy Efficiency in Buildings for Urban Sustainability

Duration: 11/2015 – 4/2019  Funding: H2020                                     

MOEEBIUS

With the increasing demand for more energy efficient buildings, the construction and energy services industries are faced with the challenge to ensure that the energy performance and savings predicted during the definition energy efficiency measures is actually achieved during operation. There is, however, significant evidence to suggest that buildings underperform, illustrating a so-called ‘performance gap’, which is attributed to a variety of causal factors related to both predicted and in-use performance, implying that predictions tend to be unrealistically low whilst actual energy performance is usually unnecessarily high.

MOEEBIUS introduces a Holistic Energy Performance Optimization Framework that enhances current (passive and active building elements) modelling approaches and delivers innovative simulation tools which deeply grasp and describe real-life building operation complexities in accurate simulation predictions that significantly reduce the ‘performance gap’ and enhance multi-fold, continuous optimalization of building energy performance as a means to further mitigate and reduce the identified ‘performance gap’ in real-time or through retrofitting.

Contribution

Almende builds software solutions targeted at providing insights relevant to retrofitting buildings with energy saving solutions. This software will analyse actual performance data of buildings to identify the "performance gap", and suggest multiple strategies that can be employed for retrofitting.

Results

The project contributes to Almende's vision on the Energy domain, specifically when it comes to creating awareness about drivers of energy waste within a network (ie. a household or cluster of households), and presenting strategies to reduce or eliminate these drivers.

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Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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PERDYNKA

Persoonlijk Dynamisch licht en binnenklimaat voor kantoren

Duration: 01/2018 – 09/2020  Funding: TKI Urban Energy 2017

PERDYNKA

Office buildings are generally climatized in a uniform fashion during working hours, which results in higher energy usage than necessary. A constant temperature is equated to a higher experience of comfort by users, but there is a large amount of individual variation in experienced comfort. Furthermore, comfort should not be seen as a synonym for health. Research by the University of Maastricht shows that exposure to mildly cold temperatures can significantly improve people’s health by activating brown adipose tissue and improving glucose levels. DYNKA adds the dimension of light to this equation as another factors which can influence health. Research has shown that varying light levels can positively affect the circadian rhythm, comfort, alertness, and general health of workers, while simultaneously lowering energy consumption.

PERDYNKA builds upon the project DYNKA by creating technology targeted at the individual user, which enable them to exert some degree of control on the system to further personalize its parameters to their own experience of comfort. These manual adjustments can also provide input for the system when it comes to learning about optimal temperature and lighting conditions, as well as lowering the adoption threshold from the user’s perspective by giving them back some control.

Contribution

Almende develops a software platform that can dynamically control the light and temperature in an office building based on principles of self-learning and self-organization, as well as manual input from individual users, and deploy said platform in an experimental pilot setting over the course of the project.

Results

The project represents a bridge between the health and energy domains, both of which are highly relevant for Almende. We expect to be able to apply the insights and tools developed in the project in other energy-related projects, specifically when it comes to using self-learning systems to optimize energy usage over time. Finally, the insights from the personalization module will be useful in mapping individual preference levels.

More info?

Need specific information regarding the project? Please contact our senior consultant for more information.

Jan Kraaijeveld

Senior consultant

+31 (0)10 404 9444

jan@almende.com

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