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Social License for Digital Energy

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "C: Energy Economics and Policy".

Deadline for manuscript submissions: closed (15 December 2022) | Viewed by 13157

Special Issue Editors


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Guest Editor

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Guest Editor
Department of Process and Energy, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Mekelweg 5, 2628 CD Delft, The Netherlands
Interests: solar photovoltaics; renewable energy; electric mobility

Special Issue Information

Dear Colleagues,

Along with decarbonisation, the energy transition also involves the digitisation of the energy sector. The climate crisis has moved energy systems into a greater public focus, while digitisation has enhanced the visibility of energy usage. This has led to greater awareness and engagement of end-users as well as opportunities for new interactive roles for them.

The widespread and rapid adoption of innovative hardware as well as digital technologies have made energy transactions highly visible and, therefore, comprehensible to a wider range of users than ever before. Distributed generation, community energy systems, and aggregation have made it possible for traditionally passive consumers to play a more participatory role in the production of energy as well as its consumption. These shifts have created novel challenges for traditional stakeholders in the energy sector, requiring new expertise and responsibilities. They have also brought opportunities for various market players. In this Special Issue, we wish to cover several themes that lie at the intersection of energy and society, in order to conceptualise a social license which is enabled and shaped by the digitisation of the energy sector.

 Potential topics to be covered:

  1. Social/consumer acceptance of demand response/automation;
  2. User trust, participation, and engagement;
  3. Human–computer interaction and interfaces;
  4. Consumer/prosumer behaviour in energy systems;
  5. Actor analyses and perspectives;
  6. Household energy practices;
  7. Institutional, regulatory, and governance aspects of digital energy;
  8. Adoption of smart energy hardware/services;
  9. Innovative business models;
  10. Infrastructure for socio-technical systems.

Prof. Dr. Zofia Lukszo
Dr. Rishabh Ghotge
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • user acceptance
  • consumer acceptance
  • demand response
  • digital energy

Published Papers (5 papers)

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Research

31 pages, 719 KiB  
Article
Encouraging Trust in Demand-Side Management via Interaction Design: An Automation Level Based Trust Framework
by Lisa Diamond, Alexander Mirnig and Peter Fröhlich
Energies 2023, 16(5), 2393; https://doi.org/10.3390/en16052393 - 2 Mar 2023
Viewed by 1318
Abstract
The energy transition requires increased end-user flexibility in consumption as a response to the more volatile production patterns of renewable resources. Automated demand-side management solutions can provide support in achieving this but struggle with trust and acceptance issues from end-users. This paper contributes [...] Read more.
The energy transition requires increased end-user flexibility in consumption as a response to the more volatile production patterns of renewable resources. Automated demand-side management solutions can provide support in achieving this but struggle with trust and acceptance issues from end-users. This paper contributes insights into how communicating trustworthiness can be achieved through careful and context-aware interaction design in such systems. Core interface features such as feedback, automation transparency, control options, benefit information, and actionable information were identified and fifteen case studies from six countries were analysed with regard to provided interaction features, automation level, and end-user experiences. The results provide insights into the form and frequency of these features used at different automation levels and their varying role in trust and acceptance building. Based on our results, we recommend particular attention to providing actionable information and actively reaching out to users at a low automation level, to provision and communication of control at a medium automation level, and to providing transparency at a high automation level in order to promote trust successfully, while benefit information is central for a “social license to automate” independently of the automation level. Full article
(This article belongs to the Special Issue Social License for Digital Energy)
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16 pages, 294 KiB  
Article
AI and Energy Justice
by Merel Noorman, Brenda Espinosa Apráez and Saskia Lavrijssen
Energies 2023, 16(5), 2110; https://doi.org/10.3390/en16052110 - 22 Feb 2023
Cited by 5 | Viewed by 3614
Abstract
Artificial intelligence (AI) techniques are increasingly used to address problems in electricity systems that result from the growing supply of energy from dynamic renewable sources. Researchers have started experimenting with data-driven AI technologies to, amongst other uses, forecast energy usage, optimize cost-efficiency, monitor [...] Read more.
Artificial intelligence (AI) techniques are increasingly used to address problems in electricity systems that result from the growing supply of energy from dynamic renewable sources. Researchers have started experimenting with data-driven AI technologies to, amongst other uses, forecast energy usage, optimize cost-efficiency, monitor system health, and manage network congestion. These technologies are said to, on the one hand, empower consumers, increase transparency in pricing, and help maintain the affordability of electricity in the energy transition, while, on the other hand, they may decrease transparency, infringe on privacy, or lead to discrimination, to name a few concerns. One key concern is how AI will affect energy justice. Energy justice is a concept that has emerged predominantly in social science research to highlight that energy related decisions—in particular, as part of the energy transition—should produce just outcomes. The concept has been around for more than a decade, but research that investigates energy (in)justice in the context of digitalized and data-driven electricity systems is still rather scarce. In particular, there is a lack of scholarship focusing on the challenges and questions that arise from the use of AI technologies in the management of electricity systems. The central question of this paper is, therefore: what may be the implications of the use of AI in smart electricity systems from the perspective of energy justice, and what does this mean for the design and regulation of these technologies? Full article
(This article belongs to the Special Issue Social License for Digital Energy)
25 pages, 1064 KiB  
Article
Building Social License for Automated Demand-Side Management—Case Study Research in the Swiss Residential Sector
by Julien Lancelot Michellod, Declan Kuch, Christian Winzer, Martin K. Patel and Selin Yilmaz
Energies 2022, 15(20), 7759; https://doi.org/10.3390/en15207759 - 20 Oct 2022
Cited by 3 | Viewed by 3170
Abstract
Demand-side management (DSM) is increasingly needed for answering electricity flexibility needs in the upcoming transformation of energy systems. Use of automation leads to better efficiency, but its acceptance is problematic since it is linked with several issues, such as privacy or loss of [...] Read more.
Demand-side management (DSM) is increasingly needed for answering electricity flexibility needs in the upcoming transformation of energy systems. Use of automation leads to better efficiency, but its acceptance is problematic since it is linked with several issues, such as privacy or loss of control. Different approaches investigate what should be done for building community support for automation for the purpose of DSM, but it is only recently that literature has shown interest in the application of social license as a concept merging several issues traditionally treated separately. The social license concept emerged in the mining sector before being adopted for other problematic resources. It serves to identify different levels of community support for a project/company as well as various factors that influence it, such as economic and socio-political legitimacy and interactional trust. This paper investigates, through empirical evidence from eight case studies, what has been done in different contexts to build trust and legitimacy for an automated DSM project. Our findings suggest that patterns exist in respect of benefits, risks and rationale presented, the retention of control, information gathered, and inclusion and that these factors differ according to appliances/devices automated, operators of automation, and end-users targeted. Full article
(This article belongs to the Special Issue Social License for Digital Energy)
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21 pages, 2586 KiB  
Article
Tariff Menus to Avoid Rebound Peaks: Results from a Discrete Choice Experiment with Swiss Customers
by Patrick Ludwig and Christian Winzer
Energies 2022, 15(17), 6354; https://doi.org/10.3390/en15176354 - 31 Aug 2022
Cited by 1 | Viewed by 1355
Abstract
While automation helps to increase load-shifting, the combination of automation with time-of-use (TOU) or critical-peak prices (CPP) may lead to rebound peaks at the beginning of low-tariff periods which may exceed the original peak. Using a discrete choice experiment with a representative sample [...] Read more.
While automation helps to increase load-shifting, the combination of automation with time-of-use (TOU) or critical-peak prices (CPP) may lead to rebound peaks at the beginning of low-tariff periods which may exceed the original peak. Using a discrete choice experiment with a representative sample of 696 Swiss consumers, we find that a tariff menu including (i) a flat price with direct load control (DLC) and (ii) a time-of-use tariff without direct load control could avoid this problem. The majority (57%) of mostly younger customers, which could be interested in automation would likely sign up for a DLC with flat prices, while the remaining customers would either chose a TOU tariff with manual load control (28%) or avoid any form of load-shifting incentives (15%). Full article
(This article belongs to the Special Issue Social License for Digital Energy)
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22 pages, 561 KiB  
Article
Use before You Choose: What Do EV Drivers Think about V2G after Experiencing It?
by Rishabh Ghotge, Koen Philippe Nijssen, Jan Anne Annema and Zofia Lukszo
Energies 2022, 15(13), 4907; https://doi.org/10.3390/en15134907 - 5 Jul 2022
Cited by 6 | Viewed by 2775
Abstract
This study aims to investigate the consumer acceptance of Vehicle-to-Grid (V2G) charging of electric vehicle (EV) drivers. To the best of the authors’ knowledge, this is the first V2G acceptance study that is based on actual users’ experience of V2G charging. A test [...] Read more.
This study aims to investigate the consumer acceptance of Vehicle-to-Grid (V2G) charging of electric vehicle (EV) drivers. To the best of the authors’ knowledge, this is the first V2G acceptance study that is based on actual users’ experience of V2G charging. A test set up with a V2G charge point at a solar carport was constructed at the Delft University of Technology. Seventeen participants in the study were given access to a V2G-compatible Nissan LEAF and the constructed V2G charging facilities, after which they were interviewed. Clear communication of the impacts of V2G charging cycles on EV batteries, financial compensation covering these impacts, real-time insight on the battery state-of-charge and the ability to set operational parameters through a user-friendly interface were all found to foster acceptance. The main barriers for acceptance were the uncertainty associated with battery state-of-charge, the increased need for planning charging and trips, the increased anxiety about the ability of the vehicle to reach its destination, economic and performance-related effects on the EV’s battery and the restriction of the freedom that users associated with their personal vehicles. The participants were found to be divided across high, conditional and low acceptance of V2G charging. The use of V2G charging over the trial period was found to inform their opinions: tangible factors such as range anxiety and the user interface were given more importance than abstract concepts such as lack of standards that were discussed by users without experience of V2G charging. Our study indicates that V2G charging in its current form is acceptable to a section of current EV users. The discussion provides insights on extending the relevance of our findings across other user groups and over further developments in the field. Full article
(This article belongs to the Special Issue Social License for Digital Energy)
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