An automated residential demand response pilot experiment, based on day-ahead dynamic pricing

2015 ◽  
Vol 155 ◽  
pp. 195-203 ◽  
Author(s):  
Koen Vanthournout ◽  
Benjamin Dupont ◽  
Wim Foubert ◽  
Catherine Stuckens ◽  
Sven Claessens
2016 ◽  
Vol 8 (9) ◽  
pp. 929 ◽  
Author(s):  
Kris Kessels ◽  
Carolien Kraan ◽  
Ludwig Karg ◽  
Simone Maggiore ◽  
Pieter Valkering ◽  
...  

Many smart grid projects make use of dynamic pricing schemes aimed to motivate consumers to shift and/or decrease energy use. Based upon existing literature and analyses of current smart grid projects, this survey paper presents key lessons on how to encourage households to adjust energy end use by means of dynamic tariffs. The paper identifies four key hypotheses related to fostering demand response through dynamic tariff schemes and examines whether these hypotheses can be accepted or rejected based on a review of published findings from a range of European pilot projects. We conclude that dynamic pricing schemes have the power to adjust energy consumption behavior within households. In order to work effectively, the dynamic tariff should be simple to understand for the end users, with timely notifications of price changes, a considerable effect on their energy bill and, if the tariff is more complex, the burden for the consumer could be eased by introducing automated control. Although sometimes the mere introduction of a dynamic tariff has proven to be effective, often the success of the pricing scheme depends also on other factors influencing the behavior of end users. An important condition to make dynamic tariffs work is that the end users should be engaged with them.


2021 ◽  
Vol 9 (1) ◽  
pp. 36-44
Author(s):  
Robert Mieth ◽  
Samrat Acharya ◽  
Ali Hassan ◽  
Yury Dvorkin

Author(s):  
Xiao Kou ◽  
Yan Du ◽  
Fangxing Li ◽  
Hector Pulgar-Painemal ◽  
Helia Zandi ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2795
Author(s):  
Nikolaos Iliopoulos ◽  
Motoharu Onuki ◽  
Miguel Esteban

Residential demand response empowers the role of electricity consumers by allowing them to change their patterns of consumption, which can help balance the energy grid. Although such type of management is envisaged to play an increasingly important role in the integration of renewables into the grid, the factors that influence household engagement in these initiatives have not been fully explored in Japan. This study examines the influence of interpersonal, intrapersonal, and socio-demographic characteristics of households in Yokohama on their willingness to participate in demand response programs. Time of use, real time pricing, critical peak pricing, and direct load control were considered as potential candidates for adoption. In addition, the authors explored the willingness of households to receive non-electricity related information in their in-home displays and participate in a philanthropy-based peer-to-peer energy platform. Primary data were collected though a questionnaire survey and supplemented by key informant interviews. The findings indicate that household income, ownership of electric vehicles, socio-environmental awareness, perceived sense of comfort, control, and complexity, as well as philanthropic inclinations, all constitute drivers that influence demand flexibility. Finally, policy recommendations that could potentially help introduce residential demand response programs to a wider section of the public are also proposed.


2018 ◽  
Vol 96 ◽  
pp. 411-419 ◽  
Author(s):  
Xing Yan ◽  
Yusuf Ozturk ◽  
Zechun Hu ◽  
Yonghua Song

Author(s):  
Oladayo O. Olakanmi ◽  
Oluyemi Adetoyi ◽  
Oluwafemi Fajemisin

Abstract Despite the benefits of demand response in energy management, the non-existence of its key concepts; dynamic pricing and smart grid, in some countries makes its impracticable in these countries, therefore making energy management unattainable for their consumers. This paper proposed a Smart Distribution Board (SDB) using a priority model for energy management in non-smart grid network. An historical consumption signatures of user’s loads were used to develop a priority model for load units of the SDB. Performance comparison was carried out between the SDB and a conventional Distribution Board which has no level of intelligence. Results obtained indicated that the SDB correctly emulated the energy usage pattern of users, thereby ensuring load preference is maximally satisfied autonomously within a limited budgeted energy and period.


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