4.7 Article

Is it more effective to bring time-of-use pricing into increasing block tariffs? Evidence from evaluation of residential electricity price policy in Anhui province

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 181, Issue -, Pages 703-716

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.01.209

Keywords

TOU-IBTs for household electricity; Price elasticity; Peak shaving; Electricity conservation; Anhui urban residents

Funding

  1. National Natural Science Foundation of China [71503065, 71501056]
  2. Ministry of education of humanities and social science research youth fund of China [14YJC630061]

Ask authors/readers for more resources

Reform of energy prices in China has stepped into a crucial stage. It has become a controversial issue after the reform of increasing block tariffs (IBTs) for household electricity, followed by a time-of-use (TOU) pricing policy. Using ELES model, this paper estimates the price elasticity of residential electricity demand; based on perceived price and price elasticity, a power structure model demand response for nonlinear electricity price is proposed; taking Anhui province as a case, this paper analyzes the attainment situation of such policy objectives as electricity saving, consumer welfare, equity improvement and peak shaving, with the introduction of TOU pricing into IBTs for household electricity. The results show that IBTs helps reduce electricity consumption by 0.74%0.93%, with minor energy effect;IBTs may lead to a maximum 1.57CNY increase of electricity expense per household per month, which is acceptable for residents. It also may reduce cross-subsidy to some extent. After introducing TOU pricing, the efficiency of peak shaving is only 2.25%2.78%, and the load decrement at peak periods is far lower than the increase at valley periods; while the effect of electricity conservation and cross-subsidy reduction have been alleviated. In other words, peak-valley price is not only difficult to achieve its own objective effectively, but also prohibits the effect of IBTs. Based on the above conclusions, some policy recommendations are provided to improve the price reform of residential electricity, natural gas and other public resources in various regions of China and foreign regions with similar electricity market. (C) 2018 Elsevier Ltd: All rights reserved

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Biodiversity Conservation

Measurement and calculation of carbon intensity based on ImPACT model and scenario analysis: A case of three regions of Jiangsu province

Ruyin Long, Ranran Yang, Malin Song, Ling Ma

ECOLOGICAL INDICATORS (2015)

Article Green & Sustainable Science & Technology

The Influence of Household Heterogeneity Factors on the Green Travel Behavior of Urban Residents in the East China Region

Ranran Yang, Ruyin Long, Yu Bai, Lanlan Li

SUSTAINABILITY (2017)

Article Green & Sustainable Science & Technology

The impacts of government R&D subsidies on green innovation: Evidence from Chinese energy-intensive firms

Yu Bai, Siyi Song, Jianling Jiao, Ranran Yang

JOURNAL OF CLEANER PRODUCTION (2019)

Article Environmental Sciences

The Influence of Information Intervention Cognition on College Students' Energy-Saving Behavior Intentions

Ranran Yang, Chunxiao Yue, Jingjing Li, Junhong Zhu, Hongshu Chen, Jia Wei

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020)

Article Green & Sustainable Science & Technology

Exploring the driving orientations and driving mechanisms of environmental innovation: The case study of the China Gezhouba

Jianling Jiao, Chunxue Wang, Ranran Yang

JOURNAL OF CLEANER PRODUCTION (2020)

Article Green & Sustainable Science & Technology

The Impact of Policy Factors and Users' Awareness on Electricity-Saving Behaviors: From the Perspective of Habits and Investment

Lanlan Li, Huayang Ming, Ranran Yang, Xuan Luo

SUSTAINABILITY (2020)

Article Green & Sustainable Science & Technology

Key Factors of Rural Households' Willingness to Pay for Cleaner Heating in Hebi: A Case Study in Northern China

Wu Xie, Chen Chen, Fangyi Li, Bofeng Cai, Ranran Yang, Libin Cao, Pengcheng Wu, Lingyun Pang

Summary: As coal-fired heating in winter exacerbates air pollution in rural areas of northern China, promoting cleaner heating transition is crucial. However, intentions and actions of rural households are deficient. The study found that willingness to pay for cleaner heating is influenced by economic and environmental factors, with higher household income and environmental concern enhancing willingness to pay.

SUSTAINABILITY (2021)

Article Engineering, Civil

Influence of Internal and External Pressure Sensing on Green Travel Intention: Based on a Theoretical Model of the Theory of Planned Behavior and Pressure-state-response Model

Ranran Yang, Lanlan Li, Cuicui Wang, Chunxiao Yue, Jia Wei

Summary: Understanding the factors and mechanisms that affect environmentally sustainable travel behavior is important for energy conservation and emission reduction. This study found that attitudes, perceived behavior control, and subjective norms have significant impacts on green travel intentions. Additionally, urban residents' cognitions of external and internal pressures also affect their intentions towards green travel.

TRANSPORTATION RESEARCH RECORD (2023)

Review Green & Sustainable Science & Technology

How to promote green travel effectively: a study of niche information interventions based on meta-analysis

Jianling Jiao, Nuonuo Chen, Ranran Yang

Summary: Green travel is an effective way to conserve energy and reduce emissions, and consumer behavior plays a crucial role in its promotion. Through a meta-analysis of 22 English-language publications from 1977-2022, it was found that niche information interventions have a positive effect on promoting green travel behavior. Factors such as information type, test sample, intervention duration, intervention frequency, and intervention timing were identified to influence the intervention effect.

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY (2023)

Article Economics

Impact of R&D technology spillovers on carbon emissions between China's regions

Jianling Jiao, Guili Jiang, Ranran Yang

STRUCTURAL CHANGE AND ECONOMIC DYNAMICS (2018)

Article Green & Sustainable Science & Technology

Relative evaluation of probabilistic methods for spatio-temporal wind forecasting

Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad

Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

Comparison of ethane recovery processes for lean gas based on a coupled model

Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang

Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

A novel deep-learning framework for short-term prediction of cooling load in public buildings

Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu

Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

The impact of social interaction and information acquisition on the adoption of soil and water conservation technology by farmers: Evidence from the Loess Plateau, China

Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang

Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

Study on synergistic heat transfer enhancement and adaptive control behavior of baffle under sudden change of inlet velocity in a micro combustor

Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He

Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.

JOURNAL OF CLEANER PRODUCTION (2024)