Optimal plan for energy conservation and CO2 emissions reduction of public buildings considering users' behavior: Case of China

Huang, He; Wang, Honglei; Hu, Yu-Jie; Li, Chengjiang; Wang, Xiaolin

doi:10.1016/j.energy.2022.125037

Cited by 25 publications

(8 citation statements)

References 55 publications

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“…Based on the decomposition results, a system dynamics model was further constructed to predict the peak carbon emissions from public buildings in China. Based on existing public buildings in the hot-summer and cold-winter regions of China, Huang et al [35] identified the best combination of energy efficiency strategies through global sensitivity analysis and dynamic simulation. The optimal solution for energy saving and emission reduction was obtained using a time-of-use tariff strategy.…”

Section: Research On Influencing Factors Of Carbon Emission Of Public...mentioning

confidence: 99%

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

Yangwen

Gong

et al. 2023

Sustainability

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With the continuous development of the social economy, carbon emissions from various buildings are increasing. As the most important category of building carbon emissions, the rapid peaking of public buildings is an important part of achieving carbon peak and carbon neutrality. This paper is based on the industrial background of the energy consumption structure of Henan Province, a central province in the developing country of China. Firstly, the energy consumption intensity of buildings and public buildings in Henan Province from 2010 to 2020 was calculated according to the energy balance sheet. The Kaya–LMDI decomposition method was also used to analyse the carbon emissions of public buildings, determining the impact of each influencing parameter on public buildings. Secondly, the scenario prediction model Monte Carlo was run 100,000 times to set the stochastic parameters of the variables in the model to predict the time of carbon peak and carbon emissions. The analysis results indicated that: ① Carbon emissions in Henan Province have exhibited a steady growth trend, increasing from 1533 t in 2010 to 6561 t in 2020; ② The primary factors influencing carbon emissions of public buildings in Henan Province were urbanization rate, public floor area per capita, and energy intensity per unit of public floor area; and ③ Carbon emissions of public buildings in Henan Province followed an inverted U-shaped distribution and are expected to peak at approximately 7423 t by the year 2035. The research method in this paper can guide the simulation study of peak carbon emission prediction in Henan Province based on the influencing parameters of carbon emission from different types of buildings. Moreover, the results of this paper can provide a reference for a more precise study of building carbon reduction in similar regions of developing countries.

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Section: Research On Influencing Factors Of Carbon Emission Of Public...mentioning

confidence: 99%

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

Yangwen

Gong

et al. 2023

Sustainability

View full text Add to dashboard Cite

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“…A large body of building flexibility research, however, is at the individual building or buildingcluster/community level (Li et al 2021) and is about developing control strategies for specific equipment or technologies (e.g., HVAC) to provide a limited set of grid services such as ancillary services (Tina, Aneli, and Gagliano 2022;Hao et al 2014;Pavlak, Henze, and Cushing 2014). Though most of such work focuses on cost savings based on current electricity tariffs (Yoon, Bladick, and Novoselac 2014;Vedullapalli, Hadidi, and Schroeder 2019), recent studies (Miara et al 2014;Lizana et al 2018;Huang et al 2022;Yildiz, Yilmaz, and Celik 2022) have begun to evaluate the environmental and climate benefits from specific building loads. Highgeographical resolution, technology-agonistic frameworks are needed that can evaluate the revenue and carbon emission impacts for any load-shiftable building technology, under many possible DER programs, for a variety of grid conditions at the national scale.…”

Section: List Of Tablesmentioning

confidence: 99%

Reducing Grid Costs while Abating Emissions: Opportunities for Flexible Building Loads

Zhou

Hale

Stephen

et al. 2023

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This study evaluates the value of technology-agnostic, shiftable flexible building loads in modeled 2030 and 2040 U.S. grids for four types of customers under three potential aggregated distributed energy resources programs. The value examined includes monetary value from providing grid services (e.g., energy, capacity, flexibility reserve, regulation reserve, contingency reserve) and from reducing greenhouse gas emissions. By comparing 845,164,800 simulated shifting opportunities, the study finds that the timing of consumption is critical for profit-driven customers. A program that is activated for 30 critical hours of system operation can result in up to $73/kW per year in revenue for 1 kW of shiftable load. Emission reduction, on the other hand, is best accumulated through a year-round program: shiftable loads can lead to up to 488 kg CO2e/kW carbon reduction per year. The report also provides detailed insights on the trade-off between revenue and emissions, regional variation, short-versus medium-term value, and impacts from various building flexibility parameters, such as shifting window and dissipation. vii This report is available at no cost from the National Renewable Energy Laboratory at www.nrel.gov/publications.

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“…Past studies primarily focused on assessing and reducing the carbon footprint of the overall power system (Shi et al, 2023). However, current optimization scheduling of air conditioning systems often emphasizes improving user comfort (Hernández et al, 2022) and reducing electricity costs with relatively less attention given to their contribution to carbon emission reduction as referenced (Jung and Jazizadeh, 2019;Huang et al, 2022). Air conditioning systems have significant potential to reduce the cost of carbon source energy and lower overall energy costs.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimal scheduling considering low-carbon operation of air conditioner load with dynamic carbon emission factors

Shen,

Li,

Yin

et al. 2024

Front. Energy Res.

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As global temperatures rise and climate change becomes more severely. People realize that air conditioning systems as a controllable resource and play an increasingly important role in reducing carbon emissions. In the past, the operation optimization of air conditioning systems was mainly oriented to user comfort and electricity costs ignoring the long-term impact on the environment. This article aims to establish a multi-objective model of air-conditioning load to ensure user temperature comfort performance and reduce the total cost (i.e., electricity cost and carbon emission cost) simultaneously. Multi Sand Cat Swarm Optimization (MSCSO) algorithm combined with gray target decision-making (GTD) is used to explore optimal solution. Meanwhile four competitive strategies are applied to validate the effectiveness of the proposed method, i.e., genetic algorithm (GA), MSCSO-comfort objective, MSCSO-total electricity cost objective and unoptimization. The simulation results show that the MSCSO-GTD based objective method can significantly reduce total costs while taking into account appropriate indoor temperature comfort.

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Optimal plan for energy conservation and CO2 emissions reduction of public buildings considering users' behavior: Case of China

Cited by 25 publications

References 55 publications

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

Reducing Grid Costs while Abating Emissions: Opportunities for Flexible Building Loads

Multi-objective optimal scheduling considering low-carbon operation of air conditioner load with dynamic carbon emission factors

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