Power outages and bill savings: A choice experiment on residential demand response acceptability in Delhi

Srivastava, Aman; Passel, Steven Van; Valkering, Pieter; Laes, Erik

doi:10.1016/j.rser.2021.110904

Cited by 8 publications

(2 citation statements)

References 48 publications

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“…Among them, family-related characteristics mainly include living types, types of electrical appliances and the use of drying machines. Srivastava et al. (2021) segmented users based on resident income to study the response of higher-income groups to demand response programs in India.…”

Section: Literature Reviewmentioning

confidence: 99%

Mining research on correlation factors of residential electricity stability based on improved FP-growth algorithm

Pan,

Liu

2023

MEQ

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PurposeOn the one hand, this paper is to further understand the residents' differentiated power consumption behaviors and tap the residential family characteristics labels from the perspective of electricity stability. On the other hand, this paper is to address the problem of lack of causal relationship in the existing research on the association analysis of residential electricity consumption behavior and basic information data.Design/methodology/approachFirst, the density-based spatial clustering of applications with noise method is used to extract the typical daily load curve of residents. Second, the degree of electricity consumption stability is described from three perspectives: daily minimum load rate, daily load rate and daily load fluctuation rate, and is evaluated comprehensively using the entropy weight method. Finally, residential customer labels are constructed from sociological characteristics, residential characteristics and energy use attitudes, and the enhanced FP-growth algorithm is employed to investigate any potential links between each factor and the stability of electricity consumption.FindingsCompared with the original FP-growth algorithm, the improved algorithm can realize the excavation of rules containing specific attribute labels, which improves the excavation efficiency. In terms of factors influencing electricity stability, characteristics such as a large number of family members, being well employed, having children in the household and newer dwelling labels may all lead to poorer electricity stability, but residents' attitudes toward energy use and dwelling type are not significantly associated with electricity stability.Originality/valueThis paper aims to uncover household socioeconomic traits that influence the stability of home electricity use and to shed light on the intricate connections between them. Firstly, in this article, from the perspective of electricity stability, the characteristics of the power consumption of residents' users are refined. And the authors use the entropy weight method to comprehensively evaluate the stability of electricity usage. Secondly, the labels of residential users' household characteristics are screened and organized. Finally, the improved FP-growth algorithm is used to mine the residential household characteristic labels that are strongly associated with electricity consumption stability.HighlightsThe stability of electricity consumption is important to the stable operation of the grid.An improved FP-growth algorithm is employed to explore the influencing factors.The improved algorithm enables the mining of rules containing specific attribute labels.Residents' attitudes toward energy use are largely unrelated to the stability of electricity use.

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Section: Literature Reviewmentioning

confidence: 99%

Mining research on correlation factors of residential electricity stability based on improved FP-growth algorithm

Pan,

Liu

2023

MEQ

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“…DCEs are also used in studies covering the topic of energy and renewable energy development. Some researchers use them in order to determine public preferences for specific attributes of RES projects or electricity services (e.g., location, type of energy, size or even electricity tariff preferences) (Srivastava et al, 2021;Oehlmann et al, 2022). Other studies use DCEs to calculate consumer WTP for the development of RES (Longo et al, 2008;Ku and Yoo, 2010).…”

Section: Discrete Choice Experiments and Public Preferencementioning

confidence: 99%

Why Are Households Willing to Pay for Renewable Energy? Lessons From Romania

Maxim

Jijie

Roman

2022

Front. Environ. Sci.

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Renewable energy is seen as a key tool in addressing the dual issue of increasing energy demand and climate change mitigation. In the current geopolitical climate, it may also play a key long-term role in increasing energy security. In order to reach the ambitious green energy targets set for each European Union member state public support for fiscal and other support mechanisms is required. The purpose of this paper is to determine to what extent the population in the North-East region of Romania is willing to make financial sacrifices for further development of renewable energy. We also explore what lifestyle and socio-demographic factors influence willingness to pay. We applied a discrete choice experiment on a sample of 602 households from the populous North-East region of Romania. Our results show that the creation of new jobs and the increase of the national energy independence, followed by the reduction of pollution are societal benefits that would convince households to pay a premium in order to support renewable energy development. Increased local budgets for rural communities resulting from the taxation of new energy companies is not one of the desired outcomes of green energy development. The study is useful in the design of adequate fiscal and renewable support policies and serves companies by identifying willingness to pay influence factors, as well as by demonstrating a market segmentation procedure.

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Residents' willingness to be compensated for power rationing during peak hours based on choice experiment

Xu,

Yang,

Deng

et al. 2024

Applied Energy

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Power outages and bill savings: A choice experiment on residential demand response acceptability in Delhi

Cited by 8 publications

References 48 publications

Mining research on correlation factors of residential electricity stability based on improved FP-growth algorithm

Mining research on correlation factors of residential electricity stability based on improved FP-growth algorithm

Why Are Households Willing to Pay for Renewable Energy? Lessons From Romania

Residents' willingness to be compensated for power rationing during peak hours based on choice experiment

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