电力需求响应系统的信息处理观点:印度和澳大利亚的比较研究

IF 2.4 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Pacific Asia Journal of the Association for Information Systems Pub Date : 2020-06-01 DOI:10.17705/1PAIS.12402
Silpa Sangeeth L.R., Saji K. Mathew, V. Potdar
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引用次数: 0

摘要

摘要背景:近年来,需求响应(DR)越来越受到公用事业、监管机构和市场聚集者的关注,以满足日益增长的电力需求。成功的DR计划的关键方面是有效地处理数据和信息,以获得关键的见解。本研究旨在找出资讯处理需求与能力的相互作用,以提高能源防灾效能。为此,组织信息处理理论(OIPT)被用来理解信息系统(is)资源在实现期望的DR计划性能中的作用。本研究还探讨了发展中国家(印度)和发达国家(澳大利亚)DR系统的信息处理有何不同。方法:本研究采用个案研究的方法,提出了一个使用OIPT在DR系统中进行信息处理的理论框架。该研究进一步采用了澳大利亚和印度DR计划之间的比较案例数据分析。结果:我们的跨案例分析确定了DR项目设计中价值创造的变量——需求方参与的定价结构、供应方的可再生能源整合、监管工具的改革和新兴技术。本研究认为,信息处理能力的高低在信息处理需求对能量DR有效性的影响中起中介作用。此外,我们提出了基于任务的信息处理需求和能力之间的相互作用以及它们对DR有效性的影响的五个命题。结论:该研究对信息系统资源的作用产生了见解,可以帮助电力价值链中的利益相关者做出明智的决策,以提高DR计划的绩效。Sangeeth L R, Silpa;马修,Saji K.;和Potdar, Vidyasagar (2020)“电力需求响应系统的信息处理观点:印度和澳大利亚的比较研究”,《亚太信息系统协会杂志》,第12卷,第4期,第2条。pais.12402 DOI: 10.17705/1可在:https://aisel.aisnet.org/pajais/vol12/iss4/2
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Information Processing view of Electricity Demand Response Systems: A Comparative Study Between India and Australia
Abstract Background: In recent years, demand response (DR) has gained increased attention from utilities, regulators, and market aggregators to meet the growing demands of electricity. The key aspect of a successful DR program is the effective processing of data and information to gain critical insights. This study aims to identify information processing needs and capacity that interact to improve energy DR effectiveness. To this end, organizational information processing theory (OIPT) is employed to understand the role of Information Systems (IS) resources in achieving desired DR program performance. This study also investigates how information processing for DR systems differ between developing (India) and developed (Australia) countries. Method: This work adopts a case study methodology to propose a theoretical framework using OIPT for information processing in DR systems. The study further employs a comparative case data analyses between Australian and Indian DR initiatives. Results: Our cross case analysis identifies variables of value creation in designing DR programs - pricing structure for demand side participation, renewable integration at supply side, reforms in the regulatory instruments, and emergent technology. This research posits that the degree of information processing capacity mediates the influence of information processing needs on energy DR effectiveness. Further, we develop five propositions on the interaction between task based information processing needs and capacity, and their influence on DR effectiveness. Conclusions: The study generates insights on the role of IS resources that can help stakeholders in the electricity value chain to take informed and intelligent decisions for improved performance of DR programs. Recommended Citation Sangeeth L R, Silpa; Mathew, Saji K.; and Potdar, Vidyasagar (2020) "Information Processing view of Electricity Demand Response Systems: A Comparative Study Between India and Australia," Pacific Asia Journal of the Association for Information Systems: Vol. 12: Iss. 4, Article 2. DOI: 10.17705/1pais.12402 Available at: https://aisel.aisnet.org/pajais/vol12/iss4/2
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