Article
Economics
Jihyo Kim, Soomin Lee, Heesun Jang
Summary: This study analyzes a large-scale Time of Use (TOU) pricing experiment in South Korea. The results show that households effectively reduce peak demand in response to higher prices. However, the price responsiveness of the treatment groups decreased in the post-experimental period, resulting in increased intermediate consumption. This suggests a need to reexamine the price schedule under TOU pricing for social welfare.
Article
Environmental Sciences
Lanlan Li, Xinpei Song, Jingjing Li, Ke Li, Jianling Jiao
Summary: Global warming affects climate adaptability and increases the impact of temperature on electricity consumption behavior. Understanding the temperature-electricity consumption response curve helps in planning power investment and production and promotes a green and low-carbon transformation of the power system.
Article
Thermodynamics
Misbah Aslam, Eatzaz Ahmad
Summary: This study analyzes the income and price elasticities of household energy demand using micro data from eight independent household surveys conducted between 2001 and 2019. A pseudo-panel approach is used to construct 1200 cohorts based on variables such as region, climatic zone, months, and expenditure deciles. The findings indicate a high own price elasticity, suggesting that household electricity usage decreases with higher electricity prices. The study also reveals that electricity is a substitute for gas and firewood in Pakistan, and identifies variations in elasticities at different levels of electricity usage and among different income and geographical groups.
Article
Economics
Adrienne Ohler, David G. Loomis, Yewande Marquis
Summary: This study estimates household electricity demand using data from the 2015 Residential Energy Consumption Survey. The results show that price elasticity is influenced by household income and the number of appliances. As income increases, households rely less on electricity for heating but have more electronic appliances. These findings have important policy implications for electricity demand and low-income households.
Article
Engineering, Environmental
Feng Xu, Chang Shu, Jing Shao, Nan Xiang
Summary: The study found that economic factors are the main drivers of residential energy conservation behaviors, with significant variations in electricity elasticity among different demographic and income groups. Price interventions can effectively reduce electricity demand, decrease carbon emissions, and improve energy conservation.
RESOURCES CONSERVATION AND RECYCLING
(2021)
Article
Business, Finance
Li Wang, Xin-Hua Zhang, Yue-Jun Zhang
Summary: This study proposes a classified self-selection sales electricity pricing mechanism for different household sizes. The results indicate that this mechanism can save energy, increase supplier's income, and reduce residents' electricity consumption.
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
(2023)
Article
Construction & Building Technology
Bo Wang, Ziyue Yuan, Xiangxiang Liu, Yefei Sun, Bin Zhang, Zhaohua Wang
Summary: This research analyzes the effects of electricity prices and habits on electricity consumption behavior and finds that habits are a more important factor affecting residents' electricity consumption, while the effect of electricity prices is not significant. Residents without electricity-saving habits consume an average of 15.54 kWh more electricity each month compared to those with such habits.
ENERGY AND BUILDINGS
(2021)
Article
Economics
Jun-Jun Jia, Jin Guo, Chu Wei
Summary: The study found that residential electricity demand is price inelastic and electricity is an essential commodity for households in the short run. Additionally, there are significant urban-rural disparities and regional heterogeneity in short-run income elasticity. These estimated parameters can provide valuable references for policy-making at both nationwide and regional levels.
Article
Engineering, Civil
Arpita Asha Khanna, Ilka Dubernet, Patrick Jochem
Summary: This paper analyzes the heterogeneity in fuel price elasticities among German households for different socio-economic and regional characteristics using a pooled OLS model estimated on a German refuelling diary data set. The results contradict the existing literature and provide important insights for policy modellers in mitigating greenhouse gas emissions in road transport.
Article
Thermodynamics
Kabelo Masike, Cobus Vermeulen
Summary: This paper estimates the price and income elasticity coefficients of domestic electricity demand in South Africa from 1980 to 2018. It finds that electricity consumption was unresponsive to price changes when real electricity prices were falling, but the price elasticity coefficient increased markedly when real prices started increasing. Policymakers should take note that aggregate price sensitivity is notably higher when real prices are increasing, potentially leading consumers to switch to alternative energy sources.
Article
Engineering, Multidisciplinary
Erbao Xu, Yan Li, Yong Liu, Jingyi Du, Xinqin Gao
Summary: This study addresses the energy-saving scheduling issue in job shops of order-oriented manufacturing enterprises, proposing an improved Firefly Algorithm to tackle the discontinuous domain problem. By redesigning the coding structure and updating operations, the algorithm shows effectiveness in reducing energy consumption costs.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Energy & Fuels
Mingguang Zhang, Weiqiang Xu, Wenyuan Zhao
Summary: This paper constructs a wind-light-fire-storage joint optimal dispatching model based on electricity price response and uncertainty of wind and photovoltaic power. The model guides customers to change their electricity consumption habits through electricity price response and considers the impact of wind and photovoltaic output uncertainty on power grid peaking. Simulation in the modified IEEE30 node system verifies the feasibility and effectiveness of the model.
Article
Green & Sustainable Science & Technology
Yuexia Pang, Yuanying Chi, Bingying Tian
Summary: To address the lack of understanding regarding the effects of links among carbon price, feed-in tariff (FIT), and peak shaving price on flexible transformation in coal-fired power plants, this study designed multi price links, analyzed their effects on coal-fired power plant operation, constructed an economic evaluation model for flexible transformation, and proposed strategies for encouraging transformation. The results indicate that the matching of peak shaving models and depth is a key factor influencing profits, the effects of multi price links on market value are mainly influenced by the transferring rate of the carbon price to FIT and elastic electricity demand, and increasing the peak shaving depth gradually realizes positive effects on market value.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Yujie Bi, Shoujun Lyu
Summary: This study develops a real options model to assess peak-valley electricity prices and electricity price subsidies for photovoltaic microgrids. The results show that optimal subsidies range from 0.30 RMB/kWh to 1.05 RMB/kWh, and optimal peak-valley price rates range from 3.09 to 6.32. Rapid cost variations hinder commercial adoption of PV microgrids.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2022)
Article
Energy & Fuels
Alireza Riahi, Soheil Kavian, Hassan Jafari Mosleh, Mohammad Behshad Shafii
Summary: This study investigated the utilization of vapor-compression cooling system with different phase change materials (PCMs) to shift electricity consumption peak load, indicating that using PCM can reduce electricity consumption during peak load hours and increase accessible cooling load. Different PCMs have varying effects on peak load reduction, with SP224A at 150 L volume achieving the highest reduction in peak load.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Biodiversity Conservation
Ruyin Long, Ranran Yang, Malin Song, Ling Ma
ECOLOGICAL INDICATORS
(2015)
Article
Green & Sustainable Science & Technology
Ranran Yang, Ruyin Long
Article
Green & Sustainable Science & Technology
Ranran Yang, Ruyin Long, Yu Bai, Lanlan Li
Article
Green & Sustainable Science & Technology
Yu Bai, Siyi Song, Jianling Jiao, Ranran Yang
JOURNAL OF CLEANER PRODUCTION
(2019)
Article
Environmental Sciences
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
Jianling Jiao, Chunxue Wang, Ranran Yang
JOURNAL OF CLEANER PRODUCTION
(2020)
Article
Green & Sustainable Science & Technology
Lanlan Li, Huayang Ming, Ranran Yang, Xuan Luo
Article
Energy & Fuels
Jian Chen, Fangyi Li, Ranran Yang, Dawei Ma
Article
Green & Sustainable Science & Technology
Pengzhen Yin, Min Yang, Ranran Yang
Article
Green & Sustainable Science & Technology
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.
Article
Engineering, Civil
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
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
Green & Sustainable Science & Technology
Ranran Yang, Lanlan Li, Junhong Zhu
JOURNAL OF CLEANER PRODUCTION
(2020)
Article
Economics
Jianling Jiao, Guili Jiang, Ranran Yang
STRUCTURAL CHANGE AND ECONOMIC DYNAMICS
(2018)
Article
Green & Sustainable Science & Technology
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
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
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
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
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)