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Journals
Processes
Special Issues
Innovative Technology for Low Carbon Development
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Innovative Technology for Low Carbon Development

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (20 June 2023) | Viewed by 6353

Special Issue Editors

Prof. Dr. Xiuwei Li

E-Mail Website
Guest Editor
College of Power Engineering, Nanjing University of Science and Technology, Nanjing, China
Interests: green buildings; high efficiency energy sysetms; HVAC systems; fuel cell; CO2 capture and utilization; energy storage
Dr. Qing Cheng

E-Mail Website
Guest Editor
School of Energy Science and Engineering, Nanjing Tech University, Nanjing, China
Interests: air dehumidification; building energy-saving and solar energy use; solar heat pump and heat pump drying and reverse Brayton air circulation
Prof. Dr. Donggen Peng

E-Mail Website
Guest Editor
School of Civil Engineering and Architecture, Nanchang University, Nanchang 330031, China
Interests: air dehumidification; solar energy utilization; HVAC systems; heat pump drying; building energy-saving

Special Issue Information

Dear Colleagues,

Climate change is growing to be a bigger threat to mankind. Rising temperature, along with higher sea level, would someday bring disasters. To meet this crisis, the goal of carbon peak and neutrality has been proposed aiming at reducing the emission of carbon dioxide. This goal can only be achieved with joint efforts of novel technologies from different areas. We need the technologies to reduce the emitted carbon dioxide, by capture, storage, conversion and utilization. As a large amount of carbon dioxide comes from the combustion of fossil fuels, the renovation of energy system could change the energy supply mode and reduce the gas emission: spread the use of renewable energies, make systems more efficient and take the energy storage strategy as much as possible. Moreover, green buildings and green industrial processes are also important for curbing the carbon dioxide emission. Those technologies are the hope for a low carbon development, and the related scientific topics will be hot spots in the following years. This issue would like present the most innovative and potential ones for readers.

We solicit contributions on topics including but not limited to:

  • Novel technology in carbon dioxide capture and storage;
  • Novel technology in carbon dioxide conversion and utilization;
  • Innovation of high efficiency energy systems;
  • Innovation, exploration and application of renewable energies;
  • Novel energy storage technology in new energy systems;
  • Novel green building technologies, green HVAC systems;
  • Novel green industrial processes;

Prof. Dr. Xiuwei Li
Dr. Qing Cheng
Prof. Dr. Donggen Peng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon dioxide capture and storage
  • carbon dioxide conversion and utilization
  • high efficiency energy systems
  • innovation of renewable energies
  • energy storage in new energy systems
  • green building technologies
  • green industrial processes

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

19 pages, 8336 KiB  
Article
Green Innovation under the Constraint of Economic Growth Targets: Evidence from Prefecture Level Cities in China
by Tao Ma and Shuchen Wang
Processes 2023, 11(4), 1197; https://doi.org/10.3390/pr11041197 - 13 Apr 2023
Viewed by 1412
Abstract
The demand for sustainable economic growth highlights the trade off between environmental and economic targets. From the perspective of economic growth target (EGT) management and green innovation (GI) practice, in this study, we constructed dynamic panel, spatial Dubin, quantile, [...] Read more.
The demand for sustainable economic growth highlights the trade off between environmental and economic targets. From the perspective of economic growth target (EGT) management and green innovation (GI) practice, in this study, we constructed dynamic panel, spatial Dubin, quantile, and threshold models to measure the impact of EGT on GI using the panel data of 284 prefecture cities in China from 2006 to 2018. The results show that EGT has a negative impact on GI, which is characterized by dynamic, superposition, spatial, and nonlinear effects; there is remarkable heterogeneity in different regions, development stages, and urban characteristics, and the empirical conclusion is still credible under many robustness tests. We also studied the heterogeneous impact of economic growth targets with different characteristics on green innovation. This study puts forward policy implications from two perspectives: optimizing top-level design and maximizing the trade off in multi-objective accountability. Full article
(This article belongs to the Special Issue Innovative Technology for Low Carbon Development)
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19 pages, 14490 KiB  
Article
Physical Environment Study of Traditional Village Patterns in Jinxi County, Jiangxi Province Based on CFD Simulation
by Zhiyi Zhou, Jun Deng, Pengfei Wang, Chunlei Zhou, Yuxuan Xu, Wanping Jiang and Kai Ma
Processes 2022, 10(11), 2453; https://doi.org/10.3390/pr10112453 - 19 Nov 2022
Cited by 11 | Viewed by 2264
Abstract
As a theory in ancient China, Feng Shui is used in terrain exploring to find ideal living environments. In this study, 62 traditional villages documented on China’s and Jiangxi’s protection lists in Jinxi County, Jiangxi Province were divided into four categories according to [...] Read more.
As a theory in ancient China, Feng Shui is used in terrain exploring to find ideal living environments. In this study, 62 traditional villages documented on China’s and Jiangxi’s protection lists in Jinxi County, Jiangxi Province were divided into four categories according to their landscape patterns and were simulated by CFD (computational fluid dynamics) with PHOENICS and quantitatively analyzed based on their wind and thermal environments. The results showed that hills greatly improve the wind environment of villages when they are in the windward direction. Concerning thermal environments, water and vegetation effectively reduced the summer temperatures in villages, while hills kept villages warm in winter. This paper verified the positive effect of elements such as mountains, water and forests on the improvement of wind and thermal environments of villages and the rationality of the site election principle of Bei Shan Mian Shui, also known as back mountain facing water, which is upheld by Feng Shui. This paper explored the philosophy of traditional village location selection, demonstrating the ecological wisdom of ancient Chinese people in creating a good living environment, and provides a new direction for current sustainable development planning. Full article
(This article belongs to the Special Issue Innovative Technology for Low Carbon Development)
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15 pages, 5683 KiB  
Article
Deep-Learning Algorithmic-Based Improved Maximum Power Point-Tracking Algorithms Using Irradiance Forecast
by Chan Roh
Processes 2022, 10(11), 2201; https://doi.org/10.3390/pr10112201 - 26 Oct 2022
Cited by 4 | Viewed by 1942
Abstract
Renewable energy is a key technology for achieving carbon-free energy transitions, and solar power systems are one of the most reliable resources for achieving this. Solar power systems have a simple structure and are inexpensive. However, depending on the input irradiance, the existing [...] Read more.
Renewable energy is a key technology for achieving carbon-free energy transitions, and solar power systems are one of the most reliable resources for achieving this. Solar power systems have a simple structure and are inexpensive. However, depending on the input irradiance, the existing maximum output control algorithm (P&O) has disadvantages due to its slow transient response and steady-state vibration. Therefore, in this paper, we propose a maximum output control algorithm based on a deep learning algorithm that can predict the input irradiance. This can achieve a quick transient response and steady-state stability. The proposed method predicts the irradiance based on the output voltage/current and power of the photovoltaic (PV) system and calculates the duty ratio that can accurately follow the maximum output point according to the irradiance. The deep learning model applied in this study was trained based on the experimental results using a 100 W PV panel, and the performance of the proposed algorithm was verified by comparing its performance with that of the conventional algorithm under various input irradiance conditions. The proposed algorithm exhibits a maximum efficiency increase of 11.24% under the same input conditions as those of the existing algorithms. Full article
(This article belongs to the Special Issue Innovative Technology for Low Carbon Development)
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