Smart charging has been the focus of considerable research efforts but so far there is little notion of users' acceptance of the concept. This work considers potentially influential factors for the acceptance of smart charging from the literature and tests their viability employing a structural equation model, following the partial least squares approach. For a sample of 237 early EV adopters from Germany our results show that grid stability and the integration of renewable energy sources are key motivational factors for acceptance of smart charging. In addition, the individual need for flexibility should not be impaired through charging control. Further well known influential factors like economic incentives do not seem to have a significant impact in the sample group under scrutiny. These and further findings should be taken into account by aggregators when designing attractive business models that incentivize the participation of early adopters and ease market rollout.
This paper presents an empirical analysis for 24 European countries that procure balancing power with auctions. We find that there is no predominant market design in Europe but qualitatively identify three key drivers for the variety in market designs: the share of volatile renewable energy sources, shortterm flexibility and market coupling. The inconsistency of auction designs, however, cannot be traced back to the energy market framework conditions. We argue that this is a consequence of the applied multi-part auction mechanism and offer a brief review of auction-theoretic literature.
This is the author's version of a work that was published in the following source:Salah, F.; Flath, C. M.; Schuller, A.; Weinhardt, C. (2017).Morphological analysis of energy services: Paving the way to quality differentiation in the power sector .Energy policy, 106, 614-624. doi:10.1016/j.enpol.2017.03.024 Please note: Copyright is owned by the author(s) and / or the publisher. The commercial use of this copy is not allowed. AbstractThe activation of the still predominantly passive demand side is necessary to further guarantee a stable power system in the short term and ensure capacity adequacy in the long run.A system with a high share of generators with nearly no marginal costs requires new services that facilitate transmitting the right economic signals to the system stakeholders. To this end we refine the notion of energy services and propose a framework to systematically design quality differentiated energy services for consumers. This approach facilitates a value-based economic assessment of energy services that deviates from the marginal-cost-paradigm. We further illustrate pricing options for these new energy service products and outline infrastructural needs and additional use case-specific product properties. Moreover, we discuss how the morphological approach can be formalised using a mathematical programming formulation and introduce a complexity measure that facilitates assessing potential adoption obstacles for end consumers. Additionally, we illustrate the practical applicability of these findings by using a prototypical implementation of a decision support system. To foster differentiated energy services, we recommend a more lenient regulatory regime lowering the barriers for new market entrants.
Plug-in electric vehicles (PEV) are considered to reduce oil dependency, noise, and local air pollution as well as greenhouse gas emissions caused by road transportation. Today, the early market penetration phase has started and can be observed in many countries. But how could the diffusion and adoption of PEV be modeled to create consistent scenarios? With which PEV driving and charging behavior can these scenarios be associated and what load-shifting potentials can be derived? This work provides an answer to these questions by describing a hybrid modeling approach of a PEV diffusion scenario consisting of a top-down macro-econometric Bass model, answering the question as to at what point in time how many PEV will be on the market, and a bottom-up micro-econometric binary logistic PEV adoption model answering who is likely to adopt. This set of methods is applied to representative mobility data sets available for France and Germany in order to simulate driving and charging behaviors of potential French and German PEV adopters. In addition, a sampling method is presented, which reduces computational times while intending to remain representative of the population of PEV adopters considered. This approach enables the consideration of PEV at a detailed level in an agent-based energy system model focusing on European day-ahead markets. Results show that PEV diffusion dynamics are slightly higher in France than in Germany. Furthermore, average plug-in times, average active charging periods, average load-shifting potentials, and average energy charged per PEV differ slightly between France and Germany. Computational times can be reduced by our approach, resulting in the ability to better integrate PEV diffusion, adoption, and representative charging demand in bottom-up energy system models that simulate European wholesale electricity markets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.