Smart Grid Challenges Through the Lens of the European General Data Protection Regulation

The General Data Protection Regulation (GDPR) was conceived to remove the obstacles to the free movement of personal data while ensuring the protection of natural persons with regard to the processing of such data. The Smart Grid has similar features as any privacy-critical system but, in comparison to the engineering of other architectures, has the peculiarity of being the source of energy consumption data. Electricity consumption constitutes an indirect means to infer personal information. This work looks at the Smart Grid from the perspective of the GDPR, which is especially relevant now given the current growth and diversification of the Smart Grid ecosystem. We provide a review of existing works highlighting the importance of energy consumption as valuable personal data as well as an analysis of the established Smart Grid Architecture Model and its main challenges from a legal viewpoint, in particular the challenge of sharing data with third parties.This work is funded by the PDP4E project, H2020 European Project Number: 787034. We would like to thank all PDP4E project partners for their valuable inputs and comments, and Marta Castro and Mikel Vergara for their discussions

A data-driven approach for generating load profiles based on InfoGAN and MKDE

High-quality demand-side management requires an abundance of load profiles to support decision-making processes. However, customer energy consumption data often contains sensitive personal information, and service providers face significant challenges in accessing a substantial amount of energy consumption data. To generate a large volume of customer data without compromising privacy, this study introduces a data-driven approach integrating Information Maximizing Generative Adversarial Networks (InfoGAN) with Multivariate Kernel Density Estimation (MKDE) for the generation of load profiles. InfoGAN is firstly trained based on existing customer load profiles, with the Q network disentangling the load into feature variables and the generator producing realistic profiles. Subsequently, MKDE is utilized to assess the distribution of these features, enabling the generation of new profiles by sampling new feature variables. The proposed method circumvents the need for intricate sampling or modeling processes and generates realistic data that represents the inherent uncertainties and fluctuations characterizing customers’ electricity consumption. The generated data could be used as the substitution for real electricity consumption data, thereby facilitating further applications without compromising privacy concerns

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

Vehicle-to-grid (V2G) refers to efforts to bi-directionally link the electric power system and the transportation system in ways that can improve the sustainability and security of both. A transition to V2G could enable vehicles to simultaneously improve the efficiency (and profitability) of electricity grids, reduce greenhouse gas emissions for transport, accommodate low-carbon sources of energy, and reap cost savings for owners, drivers, and other users. To understand the recent state of this field of research, here we conduct a systematic review of 197 peer-reviewed articles published on V2G from 2015 to early 2017. We find that the majority of V2G studies in that time period focus on technical aspects of V2G, notably renewable energy storage, batteries, or load balancing to minimize electricity costs, in some cases including environmental goals as constraints. A much lower proportion of studies focus on the importance of assessing environmental and climate attributes of a V2G transition, or on the role of consumer acceptance and knowledge of V2G systems. Further, there is need for exploratory work on natural resource use and externalities, discourses and narratives as well as social justice, gender, and urban resilience considerations. These research gaps need to be addressed if V2G is to achieve the societal transition its advocates seek

Socio-material constructs of domestic energy demand: Household and housing practices in Pakistan

Domestic energy demand in the Global South is predicted to grow to nearly three times that of the developed nations by 2040, under rapid urbanisation, economic development and the emergence of a new, high-consuming middle-class. Current energy policy, with its largely technological template and economic focus fails to address the ways of living and patterns of demand that emerge and evolve as a result of the specific socio-material and cultural contexts that underpin how the need for energy arises and evolves. This research adopts a socio-technical perspective to explore various nexuses of practices and spatial arrangements of urban housing that have emerged, persisted and transformed over time, giving rise to unsustainable levels of electricity consumption in middle-class housing in Lahore, Pakistan. It further investigates how household practices fit within the wider system of housing practices and how this can inform low-energy interventions in house design and use. The research combines practice theories from the social sciences with architectural knowledge of spatial agency to explore the interlinked social and material structures that form domestic electricity demand. This is achieved through a mixed-methods approach including semi-structured interviews with homeowners and housing practitioners, cross-cultural comparative analysis, house case-studies, oral history narratives, environmental monitoring, spatiotemporal mapping of household practice-arrangements through time-use diaries as well a detailed review of archival documents relating to building regulations and house plans. The study highlights the significance of local socio-material and cultural context in everyday household practices and resulting electricity demands. It reveals that understanding the longitudinal dynamics of practice-arrangements and their diversity in cross-cultural contexts can help identify and prevent normalisation of unsustainable configurations that gradually become embedded in social structures and practices. It shows how a shift from outdoor to indoor activities, transformation from inward- to outward-oriented design and a spatial dispersion of practices have resulted in increased household electricity consumption. It further highlights the implications of cross-cultural transfer of technology and demand response strategies that are bound by local socio-cultural and material dynamics in the performance, bundling and synchronisation of practices. The study makes the connections between “good” and “bad” housing and household practices visible and identifies various energy transitions needed in housing practices that, through interventions in house design, can lead to less energy intensive household practice-arrangements.Cambridge Commonwealth, European and International Trus

Energy Data Analytics for Smart Meter Data

The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal