Key Drivers in the Adoption of the Demand Response Assessment System for Efficient Energy Management

被引:0
作者
Chitchaitheekul, Lanchaya [1 ]
Thavorn, Jakkrit [2 ]
Gowanit, Chupun [1 ]
Muangsin, Veera [3 ]
机构
[1] Chulalongkorn Univ, Grad Sch, Technopreneurship & Innovat Management Program, Bangkok 10330, Thailand
[2] Thammasat Univ, Thammasat Business Sch, Dept Org Entrepreneurship & Human Resource Managem, Bangkok 10200, Thailand
[3] Chulalongkorn Univ, Fac Engn, Dept Comp Engn, Bangkok 10330, Thailand
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Electricity; Energy efficiency; Power system stability; Demand side management; Technology acceptance model; Demand response; Usability; Thermal stability; Production; Energy management systems; Low carbon economy; Energy management; demand-side management; demand response; decarbonization; diffusion of innovation; technology acceptance model; TECHNOLOGY ACCEPTANCE MODEL; PERCEIVED EASE; FIT INDEXES; INNOVATION; DIFFUSION; INTENTION; DETERMINANTS; PERSPECTIVE; EXTENSION; INTERNET;
D O I
10.1109/ACCESS.2024.3490182
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A zero-carbon emission energy system requires significant indicative shifts in energy production and consumption. Demand Response (DR) is an essential aspect of demand-side management (DSM) in an intelligent grid framework. DR allows customers to reduce electricity costs by adjusting their consumption levels while ensuring system stability. A survey of 409 experienced industrial customers examined factors influencing the adoption of a DR assessment system using the Technology Acceptance Model and the Diffusion of Innovation theory. The results were analyzed using structural equation modeling. The output shows that the independent variables directly and indirectly affect the intention to use the DR assessment system (BI). Perceived usefulness (PU) and attitude towards use (ATU) significantly influence BI. More importantly, relative advantage, compatibility, and perceived ease of use (PEOU) positively influence ATU, and PEOU and ATU directly impact PU. Moreover, non-complexity, trialability, visibility, and compatibility positively impact PEOU. These findings can guide the design and implementation of effective DR programs, promoting energy efficiency, grid stability, and long-term economic benefits for Commercial and industrial customers.
引用
收藏
页码:162217 / 162236
页数:20
相关论文
共 142 条
[91]   Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation [J].
Moore, Gary C. ;
Benbasat, Izak .
INFORMATION SYSTEMS RESEARCH, 1991, 2 (03) :192-222
[92]   Current Status and Willingness to Adopt Renewable Energy Technologies in Saudi Arabia [J].
Mosly, Ibrahim ;
Makki, Anas A. .
SUSTAINABILITY, 2018, 10 (11)
[93]  
Noh N. H. M., 2022, P INT C ENG EM TECHN, P1
[94]   Knowledge management systems usage: application of diffusion of innovation theory [J].
Okour, Mohammad Khaleel ;
Chong, Chin Wei ;
Fattah, Fadi Abdel Muniem Abdel .
GLOBAL KNOWLEDGE MEMORY AND COMMUNICATION, 2021, 70 (8-9) :756-776
[95]   Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology [J].
Oliveira, Tiago ;
Thomas, Manoj ;
Baptista, Goncalo ;
Campos, Filipe .
COMPUTERS IN HUMAN BEHAVIOR, 2016, 61 :404-414
[96]   Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads [J].
Palensky, Peter ;
Dietrich, Dietmar .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2011, 7 (03) :381-388
[97]   Consumer Acceptance Analysis of the Home Energy Management System [J].
Park, Eung-Suk ;
Hwang, ByungYong ;
Ko, Kyungwan ;
Kim, Daecheol .
SUSTAINABILITY, 2017, 9 (12)
[98]   An overview of Demand Response: Key-elements and international experience [J].
Paterakis, Nikolaos G. ;
Erdinc, Ozan ;
Catalao, Joao P. S. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 69 :871-891
[99]   A Case Study of Socially-Accepted Potentials for the Use of End User Flexibility by Home Energy Management Systems [J].
Pfeiffer, Christian ;
Puchegger, Markus ;
Maier, Claudia ;
Tomaschitz, Ina V. ;
Kremsner, Thomas P. ;
Gnam, Lukas .
SUSTAINABILITY, 2021, 13 (01) :1-19
[100]   Shopping intention at AI-powered automated retail stores (AIPARS) [J].
Pillai, Rajasshrie ;
Sivathanu, Brijesh ;
Dwivedi, Yogesh K. .
JOURNAL OF RETAILING AND CONSUMER SERVICES, 2020, 57