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Article
Green & Sustainable Science & Technology
Siqin Xiong et al.
Summary: China's road transport sector is striving to achieve an early carbon peak and significant emissions reductions. This study evaluates the probabilities of achieving carbon peak goals and reduction targets using a comprehensive model and Monte Carlo simulation. The results suggest that carbon peaking before 2028 is likely without intervention, but achieving a 20% reduction by 2035 is difficult with only a 15% probability. The study proposes increasing electrification rate targets and incorporating real-world fuel efficiency values in policy compliance measurements. Additional actions such as banning high fuel consumption vehicles, implementing carbon taxes, and focusing on the truck sector are recommended.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Energy & Fuels
Zhimin Guo et al.
Summary: Hydrogen (H-2) energy is an ideal non-polluting renewable energy source that can achieve long-term energy storage and effectively regulate the intermittence and seasonal fluctuation of solar energy. Solid oxide fuel cells (SOFC) can generate electricity from H-2 with only outputs of water, waste heat, and almost no pollution. A hybrid PV-SOFC power generation system has become a feasible solution to solve the power generation instability and discontinuity of solar photovoltaic (PV) systems.
Article
Energy & Fuels
Pengcheng Ni et al.
Summary: This paper proposes a wide-area distributed energy model based on digital twins to optimize the coordination of wide-area distributed energy and minimize power deviation. A cooperative game co-optimization algorithm was applied to quickly obtain a high-quality power command scheduling scheme. Simulation and comparison experiments showed significant reduction in tracking error, average error, and total error, improving tracking accuracy and reducing total power deviations by about 61.1%, 55.7%, 53.1%, and 74.8%.
Article
Energy & Fuels
Qiang Li et al.
Summary: This study aims to achieve intelligent decision making in HVDC systems using knowledge graphs (KGs). An integrated KG of the whole life cycle of an HVDC system was established, and fault diagnosis was studied as a typical case. An intelligent decision-making method based on XGBoost was designed, significantly improving the speed, accuracy, and robustness of fault diagnosis.
Article
Thermodynamics
Changfeng Shi et al.
Summary: This paper studies the carbon peak by analyzing low-carbon economics and deep learning. It uses the STIRPAT model and ridge regression to distinguish and rank the importance of influencing factors on carbon emissions. Additionally, it constructs an innovative GA-LSTM model for prediction. The results show that China's carbon emissions have been increasing, with only technological level having an inhibitory effect. China's carbon peak is projected to occur around 2030, with peak values of 11.82, 11.94, and 11.64 billion tons under different scenarios. The paper emphasizes the importance of focusing on energy consumption structure, industrial structure, and technological level for emission reduction work in China.
Article
Construction & Building Technology
Caiqing Zhang et al.
Summary: This research focuses on carbon peak prediction and path of China's public buildings based on the LEAP model. Various carbon emission scenarios are established, and key findings are obtained. Finally, policy recommendations are provided to support carbon emission reduction goals in public buildings.
ENERGY AND BUILDINGS
(2023)
Article
Green & Sustainable Science & Technology
Haonan Xie et al.
Summary: The decarbonization of electric power systems has been accelerated by the energy and climate crises. The emergence of Carbon-neutral, intelligent systems technologies, coupled with digital transformation, is an important part of this process. These technologies have brought significant changes to the new power systems, including the integration of renewable energy, massive power electronics, market planning changes, policy influence, demand response, and emerging technologies. An IntelliSense framework driven by new power system requirements is proposed, discussing the development status, classification characteristics, application of intelligent sensors, intelligent sensor flexible charging, and big data processing. Critical features of new power systems, uncertainties in power big data, wireless power transfer technologies, edge-fog-cloud collaborative computing, and intelligent algorithms are also discussed. Finally, ten core IntelliSense technology challenges and five major future opportunities are summarized as a reference for low-carbon power system development.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Environmental Sciences
Caiquan Bai et al.
Summary: Effectively reducing transportation carbon emissions is crucial for China to achieve its carbon peaking and neutral goals. This study analyzes the carbon emission performance and reduction potential of the transportation sector in China, considering regional technology heterogeneity. The results show that the potential for carbon emission reductions from the transportation sector is 12.3 million tons, accounting for 8.4% of annual transportation carbon emissions. Filling technology gaps and removing management inefficiencies are the major contributors to the potential emission reductions, with the eastern regions having a higher focus on management inefficiencies and the central and western regions on technology gaps. Provincial-specific emission mitigation strategies are provided to facilitate low-carbon development in the transportation sector.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Green & Sustainable Science & Technology
Jinghan Zhou et al.
Summary: This paper proposes a new hierarchy of electricity demand influencing factors for the industrial sector in western China under the carbon peaking and carbon neutral strategies. It constructs feedback equations based on CO2 emission intensity and establishes a long-term electricity forecast model using system dynamics. By predicting the electricity demand and carbon emissions of the industrial sector in Ningxia Province under different policy constraint scenarios, the model shows improved accuracy and provides valuable reference for energy transition planning.
ENERGY FOR SUSTAINABLE DEVELOPMENT
(2023)
Article
Thermodynamics
Tengfei Huo et al.
Summary: This study constructs a STIRPAT-PLS model framework to examine the impact of key factors on building carbon emissions. A dynamic scenario simulation model is applied in China to explore the evolutionary paths and formulate the timetable and roadmap. The results show that building sector will peak at 2.99 Gt CO2 in 2036. Rural residential buildings will peak earliest in 2026, followed by urban residential and commercial buildings: in 2036 and 2038. Achieving carbon neutrality will require the building sector to peak its carbon emissions in 2026 with 2.16-2.40 Gt CO2. The remaining 0.56-0.81 Gt CO2 by 2060 will be offset by negative carbon technologies. Dynamic sensitivity analysis reveals that building floor space per capita and energy intensity significantly promote the emission peaks, and population and building floor space per capita markedly impact the peaking times.
Article
Green & Sustainable Science & Technology
Yongpei Wang et al.
Summary: The fundamental way for China to achieve carbon peak and carbon neutrality is to continuously improve the penetration of renewable energy in the power system and establish an electricity mix dominated by renewable energy power. The impact of the increase in share of renewable energy power on carbon emissions of the electricity sector remains to be estimated. The paper aims to capture the nonlinear characteristics of renewable energy on electricity-related carbon emissions using panel smooth transition regression (PSTR) model and provincial panel data.
Article
Computer Science, Artificial Intelligence
Linfei Yin et al.
Summary: With the increasing demand for energy, wind energy has become an attractive alternative due to its clean and easily accessible nature. However, accurately predicting wind power is challenging due to its uncertainty and instability. This study proposes an Inception-embedded attention memory fully-connected network model for short-term wind power prediction, which shows reliable predictions and outperforms other algorithms by more than 40% in all evaluation metrics.
APPLIED SOFT COMPUTING
(2023)
Article
Energy & Fuels
Sumei Liu et al.
Summary: This paper presents a fault current calculation model for photovoltaic power stations and proposes a novel algorithm to accurately describe the fault current contribution from a PV station, which has been verified to be effective.
Review
Engineering, Multidisciplinary
Yi-Ming Wei et al.
Summary: This study comprehensively collates and investigates 1105 published research studies on carbon peaking and carbon neutrality, and summarizes the priorities and standpoints of key industries. The study also identifies the scientific concerns and strategic demands for achieving these two goals, providing theoretical insights and practical measures for China's carbon-neutral future. This research is crucial for policy formulation related to carbon peaking and carbon neutrality.
Review
Energy & Fuels
Jiyang Wu et al.
Summary: This paper comprehensively summarizes and analyzes the existing fault diagnosis methods of HVDC systems from three different angles: fault type, fault influence, and fault diagnosis. Traditional fault diagnosis methods can no longer meet the development needs of the new power system with the construction of the digital power grid system. Therefore, this paper proposes a knowledge graph technology-based fault diagnosis framework for HVDC transmission systems.
Article
Engineering, Electrical & Electronic
Jialin Tong et al.
Summary: Under the new power system planning, new energies such as wind and solar power are expected to become the main sources, bringing challenges of power balance and clean energy consumption for power grids. This article elaborates on the new missions of thermal power units in the construction of the new power system, and discusses the development trends and obstacles faced by thermal power units in efficient and clean power generation, ultra-low load peak regulation, mixed biomass, and coupled power-side energy storage.
IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION
(2022)
Article
Engineering, Multidisciplinary
Yuwei Fu et al.
Summary: This study proposed convolutional autoencoder-based sky image prediction models to enhance the accuracy and stability of predicting PV power station output. By utilizing the spatiotemporal feature extraction ability of 2-D and 3-D CAEs, the proposed models outperformed traditional DIPT methods in different scenarios.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2021)
Article
Energy & Fuels
Cevahir Tarhan et al.
Summary: As the demand for energy continues to rise, the search for new energy sources to replace traditional fossil fuels is ongoing. Daily energy needs can be met through the use of renewable energy sources. Globally, there is a gradual reduction in the use of fossil fuels in favor of cleaner energy sources such as hydrogen energy.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Computer Science, Information Systems
Xun Suo et al.
Summary: This paper focuses on maximizing new energy consumption in multi-energy power systems by using complex adaptive system theory to adjust node positions and capacities of different types of power sources. The planning method proves effective through simulation results based on actual meteorological and operational data.
