RESPOND Events: Meet us at our Workshop in LDAC2019

LDAC2019 - Tekniker and RESPOND

Our Partner Tekniker, represented by Iker Esnaola-Gonzalez and Francisco Javier Diez, will participate in the LDAC2019 – 7th Linked Data in Architecture and Construction Workshop on the 19th – 21th June 2019.

Read our full paper¬†about “Integrating Building and IoT data in Demand Response Solutions” here ūüĎČ: Read Article.

Register to the LDAC2019 event and attend to our workshop: LDAC2019 Website

Stay tuned and check our latest News!

Semantic Technologies for Integrating Demand Response Data

Renewable Energy Sources (RES) are increasingly penetrating the energy production side, and in combination with DR programs and improvement in energy storage options, could contribute to significantly reduce peak demands. However, the integration of the different systems and technologies involved in the distributed energy consumption and generation is a big challenge.

The different pilot dwellings of the RESPOND project have different devices deployed including sensors, appliances, meters or energy assets produced by different manufacturers. Over the years, device manufacturers have embraced different communication technologies that are mutually incompatible. As a matter of fact, there are cases where even devices using same communication technology (e.g. ZigBee) produced by different manufacturers are mutually incompatible, impeding the easy upgrade of the system with new devices or features. In addition, data coming from external systems such as weather forecasting systems or aggregators will also be leveraged in RESPOND to perform different activities such as energy data analytics to detect potential energy conservation opportunities. Having such a variety of data sources poses a big integration challenge, not only because every data source has its own data model, but also because the same concept may be defined in different ways. Furthermore, the interoperability is another hurdle to be solved.

Interoperability is defined as the ability of a system to work with or use the parts of equipment of another system. There exist three interoperability layers, as shown in the following image: technical interoperability, syntactic interoperability and semantic interoperability.

Interoperability - Demand Response

Semantic Technologies can be leveraged to remedy the aforementioned issue as they enable integrating data across several data sources. More specifically, ontologies are foreseen as the main drivers to address this challenge. An ontology can be defined as a formal, explicit specification of a shared conceptualisation.  The conceptualisation specified by each ontology is usually devoted to representing a certain phenomenon, topic, or subject area, and designed with a certain purpose.

The RESPOND ontology has been created as a solution for the integration of heterogeneous data available in the RESPOND project. Its development has followed the good practices of modularity and reuse and it has been guided by the well-known NeOn Methodology. A study of related domain ontologies has been conducted and some of them have been selected to reuse based on a conceptual agreement with the RESPOND requirements, axiomatic richness relating their terms, simplicity of the structure to facilitate querying, popularity of the ontology to improve interoperability, and documentation accessibility to facilitate new users.

As a matter of fact, RESPOND ontology’s core is built by reusing and extending three well-known ontologies: BOT to represent the dwelling topology, and SAREF and SEAS Feature Of Interest ontologies to represent devices, features of interest and qualities monitored and controlled by sensors and smart appliances. Furthermore, parts of other ontologies and vocabularies have been reused and extended to represent units of measurements (QUDT Unit) and different qualities (M3-Lite taxonomy). The following figure shows the main classes and properties defined in the RESPOND ontology.

Demand Response - Ontology

The RESPOND ontology is leveraged to semantically annotate data coming from different pilot sites. Semantic Annotation is the process of linking existing syntactic information with specific ontologies to provide both machine understandable and human readable descriptions. Ontologies provide semantics to existing data and furthermore link different information together via predefined relations.

Likewise, this ontology is working in conjunction with a Canonical Data Model (CDM), whose key role is to define a common vocabulary that will be used for communication among all the devices ensuring the syntactic interoperability of the RESPOND solution. The next figure showcases RESPOND’s ontology and CDM approach to integrate data coming from different sources.

Demand Response - CDM

Afterwards, this semantically annotated data is stored in an RDF Store, where it will remain accessible to be used by different applications or services. SPARQL (SPARQL Protocol and RDF Query Language) is the most commonly used query language to query the information available in an RDF Store, as it provides a set of query functionalities (e.g. join, sort and aggregate), together with graph traversal syntax.

Among the services that may exploit this semantically annotated data, the RESPOND project is developing a set of analytic services. These services include the demand forecasting at house and neighbourhood levels, which may derive in specific DR recommendations. Furthermore, this semantically annotated data is also available to be used by the user interface.

All in all, it can be concluded that Semantic Technologies are an important actor of the RESPOND project, as not only do they enable the integration of heterogeneous data, but also contribute to the development of services and applications.

Iker Esnaola

Demand Response and Space Heating Practices in Homes

In Europe, approximately 40% of the total energy consumption is used in buildings. Providing a comfortable and healthy indoor environment for occupants is responsible for a major part of the energy used in buildings. Demand response can be utilised in different ways within heating and ventilation of buildings to reduce or time shift the energy consumption on both utility and consumer level. During demand response control, some of the indoor environmental parameters are affected. These parameters include, e.g., room air temperature or air quality (which relates to ventilation practices and emissions from people and materials.
Hence, demand response is a bargaining process between energy consumption and an acceptable impact on the indoor environmental quality. Since Europeans spend around 90% of their time indoors, the indoor environment affects occupants’ comfort and health significantly. DR programs shall preferably not compromise residents’ experienced indoor environment too much, as this will jeopardise their acceptance of these programs.

In Denmark, 64% of all households are connected to the district heating grid. Like the electricity grid, the district heating grid is challenged by periods with a high consumer demand, so-called peak loads. In dwellings, for example, there is a peak in the morning, when there is a simultaneous demand for space heating and hot water for the morning activities, especially showering. For various reasons, the district heating suppliers would like to make it possible to time-shift some of the heating in dwellings away from this morning peak. The most important reason for this is that the suppliers in various areas are experiencing a growing heat demand due to new-built homes that are being connected to the grid.
This means that the suppliers either have to invest in upgrading the district heat system, which might cost a lot of money and make the heat more expensive for customers, or alternatively find ways to time-shift some of the consumption away from the peak hours.

One way to time-shift some of the consumption away from the peak hour in the morning is to install equipment in homes that can control the heating. In this way, the residents and/or the supplier of district heating can turn off the heat shortly during the few hours with peak consumption, e.g. between 6 and 9 am. Of course, only with the prior acceptance from the residents. Such a set-up will be tested at the Danish pilot site of the RESPOND project. Here 20 apartments with central heating in a social housing settlement will be used for demonstration. The apartments is situated in a settlement of terraced houses of flats, erected in 1975.
The heating system is using hot water directly from the district heating grid, i.e. there is no heat exchange and no buffer tank with hot water. Therefore, the thermal mass of the building is used as a buffer to allow to time shift the consumption.

Thermal simulations of the dwellings in the Danish pilot site have indicated that it will only result in a limited drop in temperature during the hours when the heating is switched off due to the heat accumulated in the construction. Roughly, the temperature will drop approximately 1¬įC per hour, depending on factors like occupancy, solar radiation and where the dwelling is situated in the blocks of flats. To maintain the temperature within a comfortable range for a longer period, the temperature may be slightly raised before switching off the heat. This altogether shows that switching off the heat for a short time (e.g. 3 hours) in the housing block seems feasible as a measure to reduce peaks in district heating in the morning.
Whether switching off the heat, as suggested above, is actually acceptable for residents in social housing needs to be verified in real life scenarios. This will be done through a focus group interview and by testing the concept in 20 dwellings.

In the Danish part of the RESPOND project, a focus group interview with residents has been performed targeting the demand response actions in relation to space heating practices in their homes as described above. The “DR concept” was fairly well received. There was some concern that it would be too cold in the morning. But if it could be controlled so that it is comfortable warm before switching the heat off, and so it is not cold when getting up in the morning, it seemed acceptable. The hardware and the RESPOND app must be simple and flexible to use and allow the residents to decide the temperature level themselves and when, for how long and how much the temperature is allowed to fall when the heat is switched off.
The residents agreed that the concept must be automated, so that they do not have to turn the heat on and off themselves on a daily basis, or as expressed by one of the female residents ‚ÄúI just don’t want to bother and deal more with it, so it just has to run‚Ķ‚ÄĚ.

The residents pointed out that not all weekdays/weekends are identical. Therefore, the idea of being able to “deactivate” the DR settings, for example in the next 24 hours, after which it returns to the DR settings and runs automatically again, was well received. Some kind of information about the indoor environment provided by the app would be appreciated since it is by some considered complex. Another relevant feature in the app that would be appreciated, is some kind of feedback with advices to improve the indoor environment, e.g. airing out if the humidity in the dwelling is high. Including information about the indoor environment (and recommendations for improvements) in DR solutions can be part of making these solutions meaningful and engaging to people.

Figure caption: This figure was used during the focus group interview to illustrate the DR concept of switching off the heat for a limited time in the morning to time shift the energy consumption for space heating without getting outside the comfortable temperature range.

Respond_Demand Response for Heat in Homes


Henrik N. Knudsen
SBi, Aalborg University Copenhagen