Protecting data privacy is key to a smart energy future

Véliz, Carissa; Grünewald, P

doi:10.1038/s41560-018-0203-3

Cited by 38 publications

(20 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this approach would lead to a different compromise, under which ATES operators would trade off the implicit value of information about their use of ATES and other building energy systems. The privacy implications of smart energy systems have drawn increased scrutiny in the literature [20][21][22] ; in the case of industrial energy users, thermal demand profiles could for instance be used to infer sensitive information about production processes 23 . Similarly, in the case of residential users, aggregation across multiple sources and levels of energy usage may make it impossible for participating individuals to offer genuinely informed consent towards the use of their data 21 .…”

Section: Discussionmentioning

confidence: 99%

“…The privacy implications of smart energy systems have drawn increased scrutiny in the literature [20][21][22] ; in the case of industrial energy users, thermal demand profiles could for instance be used to infer sensitive information about production processes 23 . Similarly, in the case of residential users, aggregation across multiple sources and levels of energy usage may make it impossible for participating individuals to offer genuinely informed consent towards the use of their data 21 . Although dedicated research is needed to assess these issues in the specific context of ATES, we note that the DSMPC approach is entirely compatible with differential privacy methods, under which the required information is pre-processed to maintain a level of privacy for the participating agents 24 .…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Aquifer Thermal Energy Storage (ATES) smart grids: Large-scale seasonal energy storage as a distributed energy management solution

et al. 2019

View full text Add to dashboard Cite

Aquifer Thermal Energy Storage (ATES) is a building technology used to seasonally store thermal energy in the subsurface, which can reduce the energy use of larger buildings by more than half. The spatial layout of ATES systems is a key aspect for the technology, as thermal interactions between neighboring systems can degrade system performance. In light of this issue, current planning policies for ATES aim to avoid thermal interactions; however, under such policies, some urban areas already lack space for the further development of ATES, limiting achievable energy savings. We show how information exchange between ATES systems can support the dynamic management of thermal interactions, so that a significantly denser layout can be applied to increase energy savings in a given area without affecting system performance. To illustrate this approach, we simulate a distributed control framework across a range of scenarios for spatial planning and ATES operation in the city center of Utrecht, in The Netherlands. The results indicate that the dynamic management of thermal interactions can improve specific greenhouse gas savings by up to 40% per unit of allocated subsurface volume, for an equivalent level of ATES economic performance. However, taking advantage of this approach will require revised spatial planning policies to allow a denser development of ATES in urban areas. Case study ATES performance assessmentThe simulation case study uses key performance indicators which build on an earlier assessment framework 6 , to evaluate the performance of the DS and DSMPC control methods from the perspectives of ATES system owners and policymakers. For the former, three indicators will be used (with details for the computation of each indicator being presented in appendix):• The average thermal efficiency of ATES systems (η tot ), i.e. the fraction of injected thermal energy which is recovered 3/22

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Aquifer Thermal Energy Storage (ATES) smart grids: Large-scale seasonal energy storage as a distributed energy management solution

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Other insights can be gained from smart electricity metering, which shares characteristics with water metering. For instance, utilities looking to introduce fair data collection could have an opt-in policy for data sharing [19], possibly with a compensation for participants. In such a case, users should have the freedom to select the resolution of the data shared and be informed of what aspects of their privacy they are potentially giving up.…”

Section: Responding To Smart Water Challengesmentioning

confidence: 99%

Smart urban water systems: what could possibly go wrong?

Vitry

Schneider

Wani

et al. 2019

Environ. Res. Lett.

View full text Add to dashboard Cite

Urban water systems are being redefined for a digital age, promising substantial advantages for service users and providers, and for society as a whole. However, beside the much-discussed benefits of smart urban water systems in future smart cities, the transition will also bring unique challenges, particularly with respect to privacy and cybersecurity. A preemptive delineation of these risks and providing appropriate recommendations will help to guide digital transformations of urban water towards sustainable solutions. Faced with emerging risks of digitalization, urban water management needs to look beyond technology while recognizing the central and multifaceted role of research.In smart city initiatives, urban water systems remain largely out of the digitalization spotlight compared to other types of infrastructure. Oftentimes, the management and planning of urban water systems still follow traditional, steel and concrete-based approaches that treat used water as waste and not as a resource [1]. The need for innovation, however, is significant: the infrastructure, operation, and maintenance cost of urban water systems around the world already ranges in the hundred billion dollars annually and water-related stresses are expected to continue rising. Digitalization could not only increase the flexibility and effectiveness of existing urban water systems, but could also allow for the provisions of new services to society. The envisioned transformation, as outlined for example in the literature [2][3][4], entails novel data collection and transmission techniques, analytical methods, models, and automation. For example, smart water meter data can be combined with noise loggers to detect and roughly locate leaks in water mains. Together with automated control infrastructure, pressure can be regulated to reduce water losses [4]. By this and numerous other smart solutions, not only water distribution but also sewers and wastewater treatment will be transformed. In particular, digitalization facilitates large-scale implementation of disruptive technologies like decentralized wastewater treatment [5] and direct potable reuse, which will help cities to cope with climate change and urbanization.However, we argue that as the benefits of smart urban water systems are increasingly explored and showcased in literature, it is time to also give attention to potential risks that might emerge. Recurring data breaches and the growing use of cyber-attacks for geopolitical ends are a reminder that the digitalization of society indeed carries risks. Given the critical role of water services in society and within the water-energyfood nexus, these risks must be identified and managed pro-actively. In the following, we raise awareness and suggest ways forward in approaching the unique privacy and security issues that accompany the digitalization of urban water systems. Finally, we highlight the central role of researchers in assessing and mitigating the potential risks of the smart urban water solutions they propose. Water tells more th...

show abstract

“…Fears that households might be identifiable once datasets are linked are not unfounded, and consumers 138 have specific concerns if data are combined for profiling activities for commercial services, resulting in their 139 becoming rationally disengaged [16]. Data privacy and protection must not be taken lightly [17], but many data 140 privacy concerns can be resolved with appropriate safeguarding and statistical disclosure procedures such as 141 the "5 Safes" protocol used by the UK Data Archive. It is also important to keep consumers fully informed and 142 in control of access to their data.…”

Section: Potential Solutions 114mentioning

confidence: 99%