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Although there are opportunities to reduce electrical energy demand in unit processes of mechanical pulp-based paper and paperboard production, this may not be financially beneficial. This is generally because energy optimization opportunities connected to reduced refiner electricity demand in mechanical pulping systems also results in less steam available for the drying of the paper. As modern high consistency refiner systems produce approximately one ton of steam for each MWh of electricity when producing one ton of pulp, a reduction in electric energy demand leads to increased fuel demand in steam boilers to compensate for the steam shortage. In this study, we investigated what the financial and environmental situation would look like if we were to expand the system border from a paper mill to a larger system consisting of a mechanical pulp-based paper or paperboard mill, a district heating system with an incineration boiler and a chemical pulp mill. Mechanical pulp production has a wood to product yield of >90%, a high electric energy demand to separate woodchips to pulp and is a net producer of heat and steam while chemical pulp-based production has a wood to product yield of 50%, a low electric energy demand and is a net heat and electricity producer due to the combustion of dissolved wood polymers. The aim of this research is to create useful and robust models of how to use excess heat from certain industry sites to cover the steam shortage in other industry sites by means of utilizing and optimizing the district heating systems connecting these sites. For this purpose, we used a simulation tool which dynamically allows us to evaluate different scenarios. Our results shows that there is great potential to reduce both carbon dioxide emissions and production costs for industry sites and society by means of these tools. [ABSTRACT FROM AUTHOR]

Carbon emissions from the Yangtze River Economic Belt are an important element of China's carbon emission endeavor, and a study of its emission reduction pathway can provide a reference for the country's overall management of carbon emission reduction. From the perspective of energy consumption, this paper uses the carbon emission factor method to estimate the carbon emissions of the transportation industry in the Yangtze River Economic Belt during 2006–2020, based on the extended STIRPAT model, considering the influence of seven factors, i.e., population size, urbanization rate, GDP per capita, transportation added value, energy structure, energy intensity, and transportation intensity, on carbon emissions. Based on these factors, a scenario analysis, combined with a forecasting model, is used to predict the peak carbon performance of the transportation industry under different development scenarios. The results show that the overall carbon emissions of transportation in the YEB from 2006 to 2020 show a fluctuating upward trend, and the downstream carbon emissions are significantly higher than those in other regions. The main factors influencing carbon emissions from transportation in different upstream, midstream, and downstream regions vary, with both population and economic factors contributing to carbon emissions, while technical factors affect them differently. There are significant differences in the peak carbon performance of transportation under different development scenarios, and the government should take effective measures to work towards achieving the goals of the low-carbon or enhanced low-carbon scenarios. [ABSTRACT FROM AUTHOR]

The building sector contributes to 40% of the total final energy consumption and 36% of CO2 emissions in Europe, and these are set to increase in the coming years. International directives are pushing towards a decarbonisation roadmap to improve the quality of cities and the health of citizens. Buildings have a potentially central role in terms of energy transition as a means to produce and save energy. Photovoltaic shading devices (PVSDs) protect buildings from direct solar radiation and overheating while producing renewable electricity onsite and increasing the users' thermal comfort. Even though the potential of the PVSD is considerable, the sector is still unexplored, and few studies on the topic are available in the literature. This systematic review aims to present an exhaustive overview of the current literature on state-of-the-art PVSDs by analysing the scientific framework in terms of the status of the research. It presents a performance-based approach focusing on innovative products, PVSD design strategies, and energetic performance in distinct climate conditions and configurations. In particular, 75 articles and about 250 keywords were identified, selected, and analysed. The literature review serves as a basis for further R&D activities led by both the industrial and the academic sectors. [ABSTRACT FROM AUTHOR]

Transitioning to clean cooking fuels is not only part of achieving SDG7 but also makes a significant contribution to mitigating climate change by reducing carbon emissions. Research projects and pilots across a number of countries in Africa and South Asia have been exploring the suitability and energy performance of different cooking appliances and fuels. The paper presents the first statistical analysis across these multiple datasets to determine the range of energy required to cook dishes using different technologies and fuels. The paper draws out distinctions between African and Asian dishes, notably the impact of energy-intensive dishes prepared mostly in Africa. The paper demonstrates that the standard efficiency-based approaches to comparing the performance of stoves are not appropriate to modern electric cooking devices, so a novel alternative approach based on specific energy consumption and termed energy ratios is developed. Charcoal stoves are shown to use 15 times as much energy as electric pressure cookers (EPCs) to cook African dishes, and a detailed review of how the EPC works explains why this should be. Energy ratios provide a basis for estimating carbon emission reductions associated with transitioning to modern cooking fuels and also for estimating household cooking costs. Fuel and electricity prices from studies show that the cost of cooking with an EPC can be only 20% of the cost of cooking with charcoal, which highlights the potential for modern, energy-efficient electric cooking devices to defy the conventional wisdom of the energy ladder. [ABSTRACT FROM AUTHOR]

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

In the context of rapid growth in renewable energy installations and increasingly severe consumption issues, this paper designs a 100% green electricity supplied zero-carbon integrated energy station. It aims to analyze its configuration focusing on the following three core features: zero carbon emissions, 100% green electricity supply, and a centralized–distributed system structure. It discusses equipment selection and provides models for configuring upstream green electricity resources, power generation, energy storage, transformer, and energy conversion. The study examines the synergy between lithium-ion battery storage and modular molten salt thermal storage, along with the virtual energy storage characteristics formed by thermal load inertia, supported by mathematical models. Based on the data from a green electricity system in an Eastern Chinese city and typical load profiles, the paper validates a specific configuration for a 100% green electricity supplied zero-carbon integrated energy station, confirming model accuracy and calculating the required scale of upstream green electricity resources. It proves that establishing an electro-thermal storage synergy system is crucial for addressing the significant fluctuations in renewable energy output. It also argues that leveraging thermal load inertia to create virtual storage can reduce the investment in energy storage system construction. [ABSTRACT FROM AUTHOR]

As the main source of energy supply and carbon emissions, the oil and gas industry has entered the comprehensive low-carbon transition stage driven by various factors. Since different oil companies possess distinct understandings of transition paths, the effect of low carbon transition varies greatly. Obviously, it is necessary to evaluate the performance of low-carbon transitions within the oil and gas industry. Therefore, in this paper, 10 major international oil companies are taken as examples, and a super-efficiency slack-based measurement (super-SBM) model is applied in the present study to analyze the efficiency of low-carbon transitions. Furthermore, the logarithmic mean Divisia index (LMDI) is used to decompose the driving factors of carbon emissions and analyze their impact on the low-carbon transition of international oil companies. The obtained results reveal that although major oil companies have taken different measures in low-carbon transition and achieved a year-on-year reduction in carbon emissions, from the perspective of the efficiency of the entire production and operation process, these oil companies are inefficient in carbon emissions and need to adopt more effective low-carbon transition strategies; Moreover, after the further decomposition of the carbon emission driving factors of the 10 companies, it is found that improving the energy consumption intensity and development level of oil companies can effectively improve the effect of low-carbon transition of international oil companies. Drawing on the above findings, this paper puts forward suggestions for the low-carbon transition of energy companies, thus providing theoretical support and guidance for energy companies in different countries to implement low-carbon transition and green development strategies. [ABSTRACT FROM AUTHOR]

The reactive power optimization of an active distribution network can effectively deal with the problem of voltage overflows at some nodes caused by the integration of a high proportion of distributed sources into the distribution network. Aiming to address the limitations in previous studies of dynamic reactive power optimization using the cluster partitioning method, a three-stage dynamic reactive power optimization decoupling strategy for active distribution networks considering carbon emissions is proposed in this paper. First, a carbon emission index is proposed based on the carbon emission intensity, and a dynamic reactive power optimization mathematical model of an active distribution network is established with the minimum active power network loss, voltage deviation, and carbon emissions as the satisfaction objective functions. Second, in order to satisfy the requirement for the all-day motion times of discrete devices, a three-stage dynamic reactive power optimization decoupling strategy based on the partitioning around a medoids clustering algorithm is proposed. Finally, taking the improved IEEE33 and PG&E69-node distribution network systems as examples, the proposed linear decreasing mutation particle swarm optimization algorithm was used to solve the mathematical model. The results show that all the indicators of the proposed strategy and algorithm throughout the day are lower than those of other methods, which verifies the effectiveness of the proposed strategy and algorithm. [ABSTRACT FROM AUTHOR]

Due to the serious problems with energy efficiency, carbon emissions, and thermal comfort of rural residences in northern China, an optimization of active and passive heating technologies for rural residences is necessary. In this paper, an optimization for rural residences in northern China is conducted with four objectives: the whole life cycle carbon emission; the annual energy consumption through heating, ventilation, and air conditioning systems; the annual cost; and thermal comfort. In addition, the optimization model with active–passive heating technology synergy is resolved by NSGA-II genetic algorithm. The active and passive design variables, including the type of air source heat pump, orientation, the type and thickness of envelope insulation, the layer of window glass, the window-to-wall area ratio, as well as sunspace parameters are preferred to obtain the optimal solution. The results indicate that the optimal solution obtained by the ideal point method gives the most outstanding performance. Compared with the prototype, the optimized carbon emissions in severe cold and cold regions decreased by 56.1% and 54.6%, respectively. The annual energy consumption decreased by 59.7% and 62.2%. Finally, the roof insulation thickness is the most sensitive design variable in Pareto-optimal solution sets. This paper offers significant guidance in the application of the optimization method of active–passive technology synergy to the energy-saving design of buildings. [ABSTRACT FROM AUTHOR]

Low or even zero carbon dioxide emissions will be an essential requirement for energy supplies in the near future. Besides transport and electricity generation, industry is another large carbon emitter. Hydrogen produced by renewable energy provides a flexible way of utilizing that energy. Hydrogen, as an energy carrier, could be stored in a large capacity compared to electricity. In Sweden, hydrogen will be used to replace coal for steel production. This paper discusses how the need for electricity to produce hydrogen will affect the electricity supply and power flow in the Swedish power grid, and whether it will result in increased emissions in other regions. Data of the Swedish system will be used to study the feasibility of implementing the hydrogen system from the power system viewpoint, and discuss the electricity price and emission issues caused by the hydrogen production in different scenarios. This paper concludes that the Swedish power grid is feasible for accommodating the additional electricity capacity requirement of producing green hydrogen for the steel industry. The obtained results could be references for decision makers, investors, and power system operators. [ABSTRACT FROM AUTHOR]

With the update of the power transaction mode and the access of increasing electric vehicles with high randomness to the power grid, the existing carbon emission flow calculation method cannot consider the influence of carbon emission due to the fluctuation in electric vehicle charging and various transaction modes. Given the above shortcomings, this paper proposes an improved carbon emission flow model considering electric vehicle charging fluctuations and hybrid power transactions. The model first considers different transaction modes, allocates the network loss to both sides of power generation, and forms a lossless network, realizing the decoupling of the bilateral transaction mode, pool transaction mode, and network loss and then calculating the day-ahead network's carbon emission. Then, the changes in different transaction modes caused by the fluctuation in electric vehicle charging under different transaction modes are analyzed and the nodes of 'spontaneous change' are found to form a day-ahead intra-day deviation network and calculate its carbon emission flow. Finally, the calculation results are combined to obtain an improved power system carbon emission flow considering electric vehicle charging fluctuations and transaction modes. In this paper, the 33-node system is used for verification. [ABSTRACT FROM AUTHOR]

Increasing sales of conventional fuel-based vehicles are leading to an increase in carbon emissions, which are dangerous to the environment. To reduce these, conventional fuel-based vehicles must be replaced with alternative fuel vehicles such as hydrogen-fueled. Hydrogen can fuel vehicles with near-zero greenhouse gas emissions. However, to increase the penetration of such alternative fuel vehicles, there needs to be adequate infrastructure, specifically, refueling infrastructure, in place. This paper presents a comprehensive review of the different optimization strategies and methods used in the location of hydrogen refueling stations. The findings of the review in this paper show that there are various methods which can be used to optimally locate refueling stations, the most popular being the p-median and flow-capture location models. It is also evident from the review that there are limited studies that consider location strategies of hydrogen refueling stations within a rural setting; most studies are focused on urban locations due to the high probability of penetration into these areas. Furthermore, it is apparent that there is still a need to incorporate factors such as the safety elements of hydrogen refueling station construction, and for risk assessments to provide more robust, realistic solutions for the optimal location of hydrogen refueling stations. Hence, the methods reviewed in this paper can be used and expanded upon to create useful and accurate models for a hydrogen refueling network. Furthermore, this paper will assist future studies to achieve an understanding of the extant studies on hydrogen refueling station and their optimal location strategies. [ABSTRACT FROM AUTHOR]

This paper explores the role of electricity in the transition to renewable energy to mitigate climate change. A systematic literature review with the Scopus database identified 92 papers relevant to the renewable electricity transition. A PESTLE (Political, Economic, Sociological, Technological, Legal, and Environmental) review of the papers provided a multidisciplinary analysis. The Paris Agreement created a global movement for carbon neutrality to address the threats of climate change, calling for a transition to renewable electricity to lead the way and expand into new sectors and regions. Although smaller renewable technologies are ramping up, complexities thwarting the transition include locked-in assets, high upfront costs, variability of solar and wind energy, infrastructure, difficulty in decarbonizing transportation and industry, material resource constraints, and fossil fuel support. This research found that renewables are not replacing fossil fuels to date but adding further energy demands, so that greenhouse gas emissions rose in 2021 despite an increased renewable electricity share. Without a major shift in the trillions of dollars of subsidies and investment away from fossil fuels to renewables, catastrophic climate change is predicted. This paper found that the Paris Agreement's commitment to net-zero carbon and the transition to renewable electricity are undermined by record-high levels of subsidies and financing for fossil fuel industry expansion. Transitioning to a climate-neutral economy requires an investment away from fossil fuels into renewable energy ecosystems. Renewable electricity provides possibilities to realize sustainable development goals, climate stabilization, job creation, a green economy, and energy security with careful planning. [ABSTRACT FROM AUTHOR]

Analyzing and investigating the impact of implementing an environmental policy mix on carbon emission from private cars and social welfare holds significant reference value. Firstly, based on vehicle trajectory big data, this paper employs reverse geocoding and artificial neural network models to predict carbon emissions from private cars in various provinces and cities in China. Secondly, by simulating different scenarios of carbon tax, carbon trading, and their policy mix, the propensity score matching model is constructed to explore the effects of the policy mix on carbon emission reduction from private cars and social welfare while conducting regional heterogeneity analysis. Finally, policy proposals are proposed to promote carbon emission reduction from private cars and enhance social welfare in China. The results indicate that the environmental policy mix has a significant positive impact on carbon emission reduction from private cars and social welfare. Furthermore, in the regional heterogeneity analysis, the implementation of the policy mix in eastern regions has a significant positive effect on both carbon emission reduction from private cars and social welfare, while in central and western regions, it shows a significant positive impact on social welfare but has no significant effect on carbon emission reduction in the private car sector. [ABSTRACT FROM AUTHOR]

Mining production, being one of the most energy-intensive industries globally, consumes substantial amounts of fossil fuels and contributes to extensive carbon emissions worldwide. The trend toward electrification and advanced developments in battery technology have shifted attention from diesel power to battery alternatives. These alternatives are appealing, as they contribute to decarbonisation efforts when compared to conventional diesel trucks. This paper presents a comprehensive review of recent technological advancements in powertrains for Mining Haulage Truck (MHT). It also compares these configurations based on mining system-level considerations to assess their future potential. The evaluated configurations include Diesel-Electric Truck (DET), Trolley Assist Truck (TAT), Battery-only Truck (BOT), Battery Trolley with Dynamic charging truck (BT-D), and Battery Trolley with Stationary charging truck (BT-S). According to the analysis, the energy demand for on-board diesel or battery power (excluding trolley power) in these alternative options is as follows: DET—681 kWh, BOT—645 kWh, TAT—511 kWh, BT-S—471 kWh, and BT-D—466 kWh. The paper also illustrates the theory of battery size design based on the current battery technology, battery material selection, battery package design, and battery size selection methods. In the case of tailored battery size selection, BOT, BT-D, and BT-S configurations require LiFePO4 (LFP) battery masses of 25 tonnes, 18 tonnes, and 18 tonnes, respectively. Based on a techno-economic assessment of battery MHT alternatives with a future perspective, it has been determined that BT-D requires the lowest amount of on-board battery energy. Furthermore, over a span of 20 years, BT-S has demonstrated the lowest on-board battery cost. [ABSTRACT FROM AUTHOR]

Cities play a pivotal role in achieving worldwide carbon neutrality due to their significant contribution to global energy consumption and carbon emissions. Therefore, planning effective strategies and guiding evidence-based policymaking at the city scale becomes even more crucial. Composite indices serve as a valuable tool for monitoring urban energy transition trends. This paper aims to present a novel approach, robust and flexible even under conditions of data scarcity, for tracking the energy transition trend of a city by means of a composite index (UETI). The Turin case study is introduced to test the applicability of the proposed approach. Additionally, to demonstrate the robustness of the composite index framework, the paper includes the findings of correlation and sensitivity analyses. This study reveals a significant improvement in Turin's environmental and energy domains, while the socio-economic domain shows more modest improvement. Furthermore, the study highlights the need to address the shortage of urban data to enhance the accuracy and reliability of metric-based frameworks and to extend the assessment to a larger sample of cities. [ABSTRACT FROM AUTHOR]

A major goal of the "14th Five-Year Plan" phase is to promote the green transformation of industrial enterprises to address the 'dual carbon' challenge. Utilizing the China Industrial Enterprises Database and the Polluting Enterprises Database, this paper calculates the carbon emissions of Chinese industrial enterprises from 2001 to 2010 at the micro level. It presents an analysis of the heterogeneity of carbon emission efficiency (TPI) in industrial enterprises, as well as the factors influencing corporate TPI. This study finds that enterprises within a subdivided industry exhibit heterogeneous levels of TPI, with carbon emissions largely affected by the structure of energy consumption. The researchers suggest accelerating the transition of industrial enterprises to green technology and argue that carbon emission policies should shift from controlling direct total targets to strengthening market-oriented policy tools. Carbon reduction targets should be more stringent for enterprises with lower TPI, considering the heterogeneity among enterprises. To meet the challenges of emission reduction, industrial enterprises are encouraged to actively reform their energy consumption structure. Government policies should aim to reduce clean energy costs and encourage the use of clean energy by industrial enterprises. [ABSTRACT FROM AUTHOR]

The EU Carbon Border Adjustment Mechanism (CBAM), which is regarded as the EU's key policy tool to address carbon leakage, might have a non-negligible impact on China's exports, as China is an important trading partner for the EU's carbon-intensive products. This paper uses the GTAP-E model to simulate the impact of the EU CBAM on China's exports to the EU from four aspects, export price, trade structure, trade value and terms of trade, by setting up multiple scenarios. The results show that the EU CBAM reduces the export prices of China's taxed sectors to the EU, and that the export prices of other sectors show the same change characteristics. The export volume of China's taxed sectors decreases differently with the export transfer effect and export inhibition effect. In terms of trade value, the EU carbon tariffs not only reduce China's export value but also lead to a reduction in EU exports. The implementation of the EU CBAM improves the terms of trade of the EU and worsens the terms of trade of China. An expansion of the scope of taxation and a change in the calculation method of carbon emissions would aggravate the change in the terms of trade. The results suggest that feasible measures should be taken to strengthen international cooperation, promote the construction of a unified national carbon market and export diversification, and establish a firm carbon emission accounting system in order to mitigate the negative impact of the EU CBAM. [ABSTRACT FROM AUTHOR]

As part of the intergovernmental and public interventions to reduce carbon dioxide emissions, there are no existing regulations to ban the sale of petrol motorcycles (PM), but it is expected that motorcycle regulations will follow car regulations with several years of delay. There is an emerging trend in motorcycle uptake, which will lead to new development projects with existing brands, and new brands, and will clearly increase the need for development tools that satisfies design challenges specific to electric motorcycles (EM) and electric powertrains. There is significant importance in motorcycle design to quantify the vehicle-level performance indicators and specifications, which are not limited to total vehicle mass, range, acceleration performance, and top speed. Those performance indicators should be quantified for different powertrain configurations and component selections to identify the most suitable configuration for the specific motorcycle development. In this paper, an innovative powertrain sizing approach is proposed to provide solutions for EMs against the design challenges specific to electric motorcycles. The innovative approach is to apply the practice of design space exploration (DSE) in resilient system design (RSD) to EM development. As a proof of concept, a case study of battery sizing is presented, in which a powertrain sizing tool is used to identify battery pack sizing requirements using requirement-based design (RBD), sensitivity analysis and DSE. The case study shows that the RBD approach allows EM product developers to identify a single solution, while DSE clearly demonstrates the trade-off between different configurations, taking multiple design variables into account. The tool prioritises high accessibility and high confidence with limited information at the early phases of electric motorcycle powertrain component sizing and selection. [ABSTRACT FROM AUTHOR]

With the objectives of achieving "peak carbon" and "carbon neutrality", accurately quantifying the carbon emissions of road transportation becomes crucial. It is challenging to accurately describe the energy consumption of vehicles at both temporal and spatial scales from a macro perspective. Therefore, focusing on the quantitative model of vehicle micro energy consumption and road meso energy consumption, this paper reviewed and summarized the energy consumption model of road traffic in terms of data collection, quantification accuracy, and scope of application. Based on this analysis, this paper identifies the challenges of the current road traffic energy consumption model. Finally, we look forward to future research directions for studying quantitative models of energy consumption from road transportation. [ABSTRACT FROM AUTHOR]

The growing demand for personal mobility is leading to an increase in vehicle use, which is in turn contributing to higher carbon emissions. It is widely acknowledged that emission-free electric vehicles (EVs) will play a pivotal role in the decarbonization process, particularly in the decarbonization of transport systems. The objective of this paper was to present the trends in demand for electric vehicles (EVs) in Poland, together with the identification of market shocks and an assessment of the programs supporting electromobility. The number of imported and domestically purchased new and used electric vehicle (BEV) registrations was analyzed using the TRAMO-SEATS and ARIMA-X-12 seasonal adjustment methods. The rise in sales of electric vehicles in Poland was driven by the government's electromobility support programs and alterations to tax legislation, with no discernible seasonal impact. The number of registrations in Poland increased significantly, exhibiting an upward trajectory. However, this growth is constrained by the inadequate number of charging stations, which are primarily powered by electricity derived from coal. Consequently, while the development of electromobility in Poland is evident, the decarbonization process remains a challenge. [ABSTRACT FROM AUTHOR]

In order to reduce carbon emissions from the power grid, photovoltaic (PV) generation units and controllable nonlinear loads based on power electronic devices are gradually becoming more prevalent in the power system. In a PV grid-connected system featuring controllable nonlinear loads, the interplay among PV grid-connected inverters, the loads, and the grid can potentially lead to voltage oscillations. To tackle this challenge, this paper introduces an optimization-based method for suppressing oscillations, which carefully balances system stability with response performance. Firstly, an impedance model of the system is established by applying the harmonic linearization method, and system stability is analyzed using the "logarithmic frequency stability criterion". Subsequently, impedance relative sensitivity is used to identify key parameters that affect system stability, and the interaction between key parameters is considered to analyze the stability range for these parameters. On this basis, a parameter optimization method based on the particle swarm optimization algorithm is proposed to balance system stability and response performance. The effectiveness and robustness of this method are verified through a simulation analysis. [ABSTRACT FROM AUTHOR]

The construction industry plays a pivotal role in China's achievement of its "dual carbon" goals. This study conducts a decomposition analysis of the carbon emissions from the construction industry (CECI) at both national and provincial levels for the period 2010–2020 and employs the ARIMA model to predict the short-term peak trends at the provincial level. The findings are as follows. (1) Inner Mongolia, Shandong, Sichuan, and Chongqing exhibit an N-shaped trend in CECI, while the northeast region shows an inverted U-shaped trend. (2) Labor productivity and energy intensity are identified as the largest and smallest drivers of national CECI growth, respectively, with the driving force of the study's identified factors fluctuating between 1% and 60%. (3) Energy intensity significantly contributes to the growth of CECI in Tianjin and Zhejiang, while it aids in reducing CECI in western provinces. The "rebound effect" of building energy efficiency is particularly pronounced in provinces with strong resource endowments, such as Ningxia. (4) Between 2021 and 2025, CECI is predicted to decrease in the northern and economically developed provinces, while it is expected to increase in central and western provinces, with Heilongjiang, Shandong, Guangdong, Shanghai, and Shaanxi potentially reaching their peaks within the forecast period. The paper concludes with several recommendations. [ABSTRACT FROM AUTHOR]

In the current literature, there exists a lack of analysis regarding the coordination of the spinning reserve and time-shift characteristics of hydrogen storage systems (HSS) and flexible carbon capture systems (FCCS) in terms of low-carbon economic operation. They are presently used solely as a tool to capture carbon dioxide, without fully utilizing the advantages of their flexible operation. The coordination and complementarity of the FCCS and HSS can ensure stable power supply and improve renewable energy (RE) consumption. Combined with demand side response (DSR), these factors can maximize the RE consumption capacity, reduce carbon emissions, and improve revenue. In this paper, a source-storage-load flexible scheduling strategy is proposed by considering the complementary nature of FCCS and HSS in terms of rotating standby and time-shift characteristics. First, the operational mechanisms of FCCS, HSS, and demand side response (DSR) are analyzed, and their mathematical models are constructed to improve flexibility in grid operation and regulation. Next, deficiencies in FCCS and HSS operation under rotating reserve requirements are analyzed to design a coordinated operation framework for the FCCS and HSS. This operational framework aims to enable the complementarity of the rotating reserve and time-shift characteristics of FCCS and HSS. Finally, based on the carbon emission trading mechanism, a three-stage ladder carbon emission trading cost model is constructed, and a source-storage-load flexible scheduling strategy is established to achieve an effective balance between low carbon emissions and economic performance. The simulation results demonstrate that the strategy reduces the overall cost by 8.57%, reduces the carbon emissions by 35.33%, and improves the renewable energy consumption by 3.5% compared with the unoptimized scheme. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) aggregate a large number of distributed energy resources (DERs) through IoT technology to provide flexibility to the grid. It is an effective means to promote the utilization of renewable energy, and enable carbon neutrality for future power systems. This paper addresses the evaluation issue of DERs' low-carbon benefits, proposes a flexibility assessment model for self-organized VPP to quantify the low-carbon value of DERs' response behavior in different time periods. Firstly, we introduce the definition of zero-carbon index based on the curve simultaneous rate of renewable energy and load demand. Then, we establish a multi-level self-organized aggregation method for virtual power plants, define the basic rules of DER, and characterize its self-organized aggregation as a Markov game process. Moreover, we use QMIX to achieve a bottom-up, hierarchical construction of VPP from simple to complex. Experimental results show that when users track the zero-carbon curve, they can achieve zero carbon emissions without reducing the overall load, significantly enhancing the grid's regulation capabilities and the consumption of renewable energy. Additionally, self-organized algorithms can optimize the combinations of DERs to improve the coordination efficiency of VPPs in complex environments. [ABSTRACT FROM AUTHOR]

The paper addresses the overlooked interaction between power-to-gas (P2G) devices and carbon capture and storage (CCS) equipment, along with the stepwise carbon trading mechanism in the context of current multi-park integrated energy microgrids (IEMGs). Additionally, it covers the economic and coordinated low-carbon operation issues in multi-park IEMGs under the carbon trading system. It proposes a multi-park IEMG low-carbon operation strategy based on the synchronous Alternating Direction Method of Multipliers (ADMM) algorithm. The algorithm first enables the distribution of cost relationships among multi-park IEMGs. Then, using a method that combines a CCS device with a P2G unit in line with the tiered carbon trading scheme, it expands on the model of single IEMGs managing thermal, electrical, and refrigeration energy. Finally, the comparison of simulation cases proves that the proposed strategy significantly reduces the external energy dependence while keeping the total cost of the users unchanged, and the cost of interaction with the external grid is reduced by 56.64%, the gas cost is reduced by 27.78%, and the carbon emission cost is reduced by 29.54% by joining the stepped carbon trading mechanism. [ABSTRACT FROM AUTHOR]

Liquefied natural gas (LNG), recognized as the fossil fuel with the lowest carbon emission intensity, is a crucial transitional energy source in the global shift towards low-carbon energy. As the natural gas industry undergoes rapid expansion, the complexity of investment business models has increased significantly. Optimizing the combination of various segments within the value chain has become standard practice, making it essential to control risks and enhance economic benefits in these multifaceted scenarios. This paper introduces an integrated economic model encompassing upstream, liquefaction, shipping, regasification, and consumption, suitable for both upstream and downstream integration. The model offers a comprehensive analysis of the primary business models and key factors across each segment of the value chain. By constructing a robust economic evaluation framework, the study aims to provide a holistic approach to understanding the economic feasibility of LNG projects. Two detailed case studies are conducted to demonstrate the application and effectiveness of the proposed model, highlighting its capability to guide investment decisions, support risk management, and optimize asset portfolios. The integrated economic model developed in this study serves as a valuable tool for stakeholders in the LNG industry. It not only facilitates informed investment decision-making but also enhances the strategic management of risks and resources. By leveraging this model, investors and managers can better navigate the complexities of the LNG business, ensuring sustainable and economically viable operations. [ABSTRACT FROM AUTHOR]

The LDR-50 low-temperature nuclear reactor is designed for the Finnish and European district heating markets, as an environmentally sustainable heating option for the 2030s. While the carbon footprint of conventional electricity-producing reactors is known to be small, there have been no comprehensive studies on the emission reduction potential when the technology is applied to the heating sector. This paper aims to fill this knowledge gap by means of life cycle assessment (LCA) analysis. The carbon footprint of the LDR-50 heating plant is evaluated, and compared to conventional heating fuels, direct electric heating, and heat pumps. The results of the analysis show that the life cycle CO2 emissions are low, although there are still significant uncertainties related to the construction phase, due to missing data. In addition to carbon footprint, the analysis is also extended to other adverse environmental impacts. It is concluded that significant reductions in CO2 emissions can be achieved by replacing fossil heating fuels with nuclear energy. The technology is considered a viable option alongside biofuels and heat pumps. The overall environmental impacts are low, and the production does not compete for low-carbon electricity or scarce natural resources. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative cooperative model for energy efficiency retrofitting that incorporates carbon emission rights, addressing critical financial constraints in Energy Performance Contracting (EPC). By employing the fuzzy analytic hierarchy process (F-AHP) to evaluate risk assessment indicators and stakeholder contributions and utilizing the enhanced Shapley method for equitable benefit distribution, the model demonstrates significant improvements in financing and efficiency for energy conservation projects. The findings are as follows: (1) the energy efficiency retrofit model, which integrates carbon emission rights, effectively alleviates the financial constraints and fosters energy conservation and emission reduction in guaranteed-savings EPC projects; (2) the enhanced Shapley method is deemed appropriate for the equitable distribution of energy-saving benefits among stakeholders; (3) when compared with the traditional model and the benefit allocation-absent carbon rights, the energy-saving benefits of the energy efficiency retrofit model incorporating carbon emission rights are higher in individual and overall terms. The findings of this study offer a viable solution to financing challenges faced by stakeholders in such projects and delineate a pragmatic approach for enterprises to enhance energy efficiency and reduce emissions. [ABSTRACT FROM AUTHOR]

This paper reviews and assesses India's energy policy in the context of its commitment to achieve the target of net-zero carbon emissions by 2070. It emphasizes the central role of green electrification, particularly through the expansion of solar power capacity. It discusses policies outside the energy sector that need to be part of a strategy of achieving this target, including the use of information technology, infrastructure development, and transportation. Furthermore, it examines possible policy options for accelerating the target date to 2050, especially with the use of carbon capture to manage the transition from the current heavy use of coal. The paper also discusses the possible financial and growth implications of various strategy options, arguing that feasible external financing commitments can allow India to achieve net-zero goals without sacrificing economic growth. [ABSTRACT FROM AUTHOR]

China aims to reduce carbon dioxide emissions and achieve peak carbon and carbon neutrality goals. Natural gas, as a high-quality fossil fuel energy, is an important transition resource for China in the process of carbon reduction, so it is necessary to predict China's natural gas demand. In this paper, a novel natural gas demand combination forecasting model is constructed to accurately predict the future natural gas demand. The Lasso model and the polynomial model are used to build a combinatorial model, which overcomes the shortcomings of traditional models, which have low data dimensions and poor prediction abilities. In the modeling process, the cross-validation method is used to adjust the modeling parameters. By comparing the performance of the combinatorial forecasting model, the single forecasting model and other commonly used forecasting models, the results show that the error (2.99%) of the combinatorial forecasting model is the smallest, which verifies the high accuracy and good stability advantages of the combinatorial forecasting model. Finally, the paper analyzes the relevant data from 1999 to 2022 and predicts China's natural gas demand in the next 10 years. The results show that the annual growth rate of China's natural gas demand in the next 10 years will reach 13.33%, at 8.3 × 1011 m3 in 2033, which proves that China urgently needs to rapidly develop the gas supply capacity of gas supply enterprises. This study integrates the impact of multiple factors on the natural gas demand, predicts China's natural gas demand from 2023 to 2033, and provides decision-making support for China's energy structure adjustment and natural gas import trade. [ABSTRACT FROM AUTHOR]

Conventional generation maintenance scheduling (GMS) is a solution to increase the reliability of power systems and minimize the operation and maintenance costs paid by generation companies (GenCos). Nonetheless, environmental aspects, such as zero carbon emissions, have attracted global attention, leading to emission costs being paid by electricity generators. Therefore, to obtain GMS plans that consider these factors, this paper proposes multi-objective GMS models to minimize operation, maintenance, and emission costs by using lexicographic optimization as a mathematical tool. A demand response program (DRP) is also adapted to decrease emission generation and operational expenditures. The probability that no generation unit (GU) fails unexpectedly and the average net reserve value, comprising the system reliability with and without considering the GU failure rate, are demonstrated. Numerical examples are implemented for the IEEE 24-bus reliability test system. A GMS algorithm presented in a published work is run and compared to verify the robustness of the proposed GMS models. Our results indicate that this paper provides comprehensive approaches to the multi-objective GMS problem focusing on operation, maintenance, carbon, and DRP costs in consideration of technical and environmental aspects. The use of lexicographic optimization allows for the systematic and hierarchical consideration of these objectives, leading to significant benefits for GenCos. [ABSTRACT FROM AUTHOR]

This paper presents a thorough review and analysis of solar photovoltaic (PV) home systems in Malaysia, offering a comprehensive exploration of their implementation, challenges, benefits, and future potential. As a nation striving to embrace sustainable and renewable energy solutions, Malaysia's adoption of solar PV systems at the residential level is of paramount importance. The study delves into the current state of solar PV deployment, government initiatives, and policy frameworks that influence adoption trends. It examines the economic, environmental, and societal advantages of solar PV home systems, outlining their contribution to reducing electricity costs, carbon emissions, and energy dependence. Addressing barriers to wider acceptance, the paper scrutinizes challenges encompassing cost, awareness, intermittency, and regulatory constraints. Furthermore, the study evaluates the socio-economic implications of solar PV home systems, including potential job creation and energy independence. Technological advancements, such as enhanced efficiency and smart grid integration, are also explored for their role in surmounting obstacles. Drawing insights from practical case studies, the paper underscores successful installations and the lessons they offer. In examining policy and regulatory frameworks, it analyzes existing incentives while suggesting improvements to accelerate adoption. Finally, the paper offers a visionary perspective on the future trajectory of solar PV home systems in Malaysia, envisioning increased affordability, advanced energy storage solutions, and seamless integration with emerging technologies. This holistic analysis contributes valuable insights to propel Malaysia's sustainable energy transition and inform strategic decision making for stakeholders across sectors. [ABSTRACT FROM AUTHOR]

The ageing of coal-fired power stations in South Africa has led to regular power outages. Therefore, the country will need to urgently increase its electricity capacity to meet further energy demand from growing urbanization and population growth. This challenge has increased interest in alternative energy sources, such as renewable energy (RE). South Africa is gradually implementing appropriate renewable energy practices, reducing carbon emissions, cleansing the air, and assuring a more sustainable future. This paper summarizes the availability, current state, and future potential of renewable energy choices in South Africa. This paper also evaluates specific policy measures and government actions aimed at eliminating barriers and increasing renewable energy deployment in the future. It also considers the South African network's specialized techno-economic analysis. The findings show that South Africa is still heavily reliant on coal, with 78% of the current installed capacity coming from coal power in 2022, compared to 9.3% for solar and wind energy. [ABSTRACT FROM AUTHOR]

Global climate change imposes significant challenges on the ecological environment and human sustainability. Industrial parks, in line with the national climate change mitigation strategy, are key targets for low-carbon revolution within the industrial sector. To predict the carbon emission of industrial parks and formulate the strategic path of emission reduction, this paper amalgamates the benefits of the "top-down" and "bottom-up" prediction methodologies, incorporating the logarithmic mean divisia index (LMDI) decomposition method and long-range energy alternatives planning (LEAP) model, and integrates the Tapio decoupling theory to predict the carbon emissions of an industrial park cluster of an economic development zone in Yancheng from 2020 to 2035 under baseline (BAS) and low-carbon scenarios (LC1, LC2, and LC3). The findings suggest that, in comparison to the BAS scenario, the carbon emissions in the LC1, LC2, and LC3 scenarios decreased by 30.4%, 38.4%, and 46.2%, respectively, with LC3 being the most suitable pathway for the park's development. Finally, the paper explores carbon emission sources, and analyzes emission reduction potential and optimization measures of the energy structure, thus providing a reference for the formulation of emission reduction strategies for industrial parks. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, China has become the world's largest carbon emitter. China not only has an obvious growth rate of industrial carbon emissions but also the intensity of agricultural carbon emissions is hovering at a high level. The development of China's agricultural economy has largely come at the expense of high emissions. Currently, under the background of global warming and difficulty in controlling greenhouse gas emissions, the development of low-carbon agriculture is an important way to realize the harmonious development of the ecological environment and economic growth and to promote the sustainable development of agriculture. The agricultural production efficiency is the main factor affecting the intensity of agricultural carbon emissions. Based on provincial panel data of China from 2010 to 2019, this paper establishes an indicator system and uses the super-efficiency SBM model to measure agricultural production efficiency. The regional agricultural carbon emissions were estimated using carbon-emission-related agricultural production activities. In order to study the nonlinear relationship between agricultural production efficiency and agricultural carbon emission intensity in the narrow sense, this paper uses a threshold regression model with agricultural carbon emissions as the threshold variable. Based on the analysis of China's agricultural production efficiency and agricultural carbon emissions from 2010 to 2019, an empirical test is conducted through a threshold regression model. The results show an "inverted U-shaped" relationship between agricultural production efficiency and agricultural carbon emission intensity. In areas with high agricultural production efficiency, the improvement of production efficiency can suppress the intensity of agricultural carbon emissions; in areas with low agricultural production efficiency, the improvement of production efficiency increases the intensity of agricultural carbon emissions. Finally, based on the research conclusions, this paper provides feasible suggestions and countermeasures for China's agricultural carbon emission reduction and improvement of agricultural production efficiency. [ABSTRACT FROM AUTHOR]

The income gap and global warming have always been topics of common concern to scholars worldwide. Internationally, there is no consensus yet about the impact of the income gap on carbon emissions, and there are few studies about that in China. To explore the effect of the income gap on carbon emissions at the provincial level in China, this paper first theoretically and qualitatively analyzes the non-linear impact of the income gap on carbon emissions. Then, the Gini coefficient of the resident income of different regions in China from 2010 to 2019 is calculated. Finally, a threshold regression model is used to quantitatively test the existence of a threshold effect between the income gap and carbon emission intensity in China. The threshold value is the per capita disposable income of residents. The results show that the income gap is positively related to carbon emission intensity in poor regions. In high-income areas, the widening income gap inhibits the increase in carbon emission intensity. Based on this, this paper proposes policy recommendations to narrow the income gap and reduce the intensity of carbon emissions. [ABSTRACT FROM AUTHOR]

As the world becomes more concerned about carbon emissions, the Chinese government, which is a large contributor to carbon emissions, has also begun to pay attention to the issue of carbon emissions. Environmental regulatory policies have been implemented to improve the environment, but are these policies really conducive to improving firms' eco-innovation performance? This paper empirically investigates the relationship between environmental regulation policies and firms' eco-innovation performance in China and finds that: firstly, environmental regulation in China is inadequate and that manufacturing eco-innovation performance is generally low; secondly, there is a U-shaped relationship between environmental regulation policies and firms' eco-innovation performance; thirdly, there is significant industry and regional heterogeneity in the induced effects of environmental regulation tools; and fourthly, there is a mediating effect of industrial agglomeration on the promotion of firms' eco-innovation performance. The conclusions of this paper are: firstly, that the Chinese government should continue to improve environmental regulations and strictly enforce them so that green becomes the colour of 'economic recovery'; secondly, that the Chinese government should develop scientific and reasonable environmental regulatory policies according to local conditions; thirdly, that Chinese companies should increase their spending on research and development; and fourthly, that the Chinese government needs to optimise the industrial layout and support mechanisms. The Chinese government should play an active role in industrial agglomeration in technological innovation. [ABSTRACT FROM AUTHOR]

Reducing CO 2 emissions from coal-fired power plants is an urgent global issue. Effective and precise monitoring of CO 2 emissions is a prerequisite for optimizing electricity production processes and achieving such reductions. To obtain the high temporal resolution emissions status of power plants, a lot of research has been done. Currently, typical solutions are utilizing Continuous Emission Monitoring System (CEMS) to measure CO 2 emissions. However, these methods are too expensive and complicated because they require the installation of a large number of devices and require periodic maintenance to obtain accurate measurements. According to this limitation, this paper attempts to provide a novel data-driven method using net power generation to achieve near-real-time monitoring. First, we study the key elements of CO 2 emissions from coal-fired power plants (CFPPs) in depth and design a regression and physical variable model-based emission simulator. We then present Emission Estimation Network (EEN), a heterogeneous network-based deep learning model, to estimate CO 2 emissions from CFPPs in near-real-time. We use artificial data generated by the simulator to train it and apply a few real-world datasets to complete the adaptation. The experimental results show that our proposal is a competitive approach that not only has accurate measurements but is also easy to implement. [ABSTRACT FROM AUTHOR]

The main problem confronting the world is human-caused climate change, which is intrinsically linked to the need for energy both now and in the future. Renewable (green) energy has been proposed as a future solution, and many renewable energy technologies have been developed for different purposes. However, progress toward net zero carbon emissions by 2050 and the role of renewable energy in 2050 are not well known. This paper reviews different renewable energy technologies developed by different researchers and their potential and challenges to date, and it derives lessons for world and especially African policymakers. According to recent research results, the mean global capabilities for solar, wind, biogas, geothermal, hydrogen, and ocean power are 325 W, 900 W, 300 W, 434 W, 150 W, and 2.75 MWh, respectively, and their capacities for generating electricity are 1.5 KWh, 1182.5 KWh, 1.7 KWh, 1.5 KWh, 1.55 KWh, and 3.6 MWh, respectively. Securing global energy leads to strong hope for meeting the Sustainable Development Goals (SDGs), such as those for hunger, health, education, gender equality, climate change, and sustainable development. Therefore, renewable energy can be a considerable contributor to future fuels. [ABSTRACT FROM AUTHOR]

This study focuses on the carbon emissions of key industries in Henan Province, employing techniques of seasonal adjustment, frequency transformation, and statistical modeling to construct an industry-level "Electricity–Energy–Carbon" model to aid in the high-frequency monitoring of carbon emissions in the province's industries. Based on relevant data, this research performs high-frequency calculations of carbon emissions from energy consumption in 34 typical industries and from the production processes of 53 typical sub-categories in the industrial sector of Henan. The findings reveal the following: Firstly, industrial energy consumption in Henan accounts for over half of the total provincial energy consumption, with most months seeing proportions around 60%. Industries such as energy, non-ferrous metals, building materials, steel, chemicals, petrochemicals, and paper making contribute to over 80% of the industrial energy consumption's carbon emissions, often nearing 90% in most months. Secondly, among the major industries, such as non-ferrous metals, chemicals, building materials, and steel, there is a dual challenge of being restricted under the "high energy consumption and high emissions" project while also being required to build key industrial bases, leading to fluctuating trends in historical annual carbon emissions data. Thirdly, six sub-categories, namely plastic products, cement, flat glass, steel, ten types of non-ferrous metals, and alumina, have significant carbon emissions in their production processes, accounting for about 72.3% of the total production-related emissions. [ABSTRACT FROM AUTHOR]

In the current context of fossil energy depletion and the requirement for low carbon emissions, the efficient use of energy and a diversified energy mix have become increasingly important. The use of cleaner and low-carbon alternative fuels is rapidly growing. However, corrosion remains a key issue limiting the large-scale application of alternative fuels. This paper describes the corrosion characteristics of different alternative fuels. Also, the mechanisms of fuel corrosion, corrosion measurement methods, and the future of corrosion inhibitor applications are discussed. Corrosion causes changes in material weight and surface morphology and generates electrical signals as it progresses. Although there are well-established methods to characterize corrosion by recognizing these changes, there is still a need to identify a universal standard signal for their detailed description. For the foreseeable future, corrosion in fuels will continue to be mitigated by the addition of corrosion inhibitors. The research on corrosion inhibitors focuses on green corrosion inhibitors and multifunctional corrosion inhibitors. However, further analysis is needed to understand the active ingredients in green corrosion inhibitors, and the mechanism of corrosion inhibition for different types of corrosion inhibitors needs further research. [ABSTRACT FROM AUTHOR]

The chemical looping reforming and combustion of methane have attracted increasing interest as processes for clean energy and syngas production, with potential to reduce carbon dioxide emissions. Previous literature on the development of oxygen carriers evidenced the effects that oxygen availability exerts on the selectivity of the oxidation reaction. In the present paper, we evaluate the performance of chromite sand (Chro), cerium dioxide (CeO2), and mixed cerium–copper oxide (Ce–Cu) as oxygen carriers for either reforming or combustion according to their oxygen availability. The oxides are tested in 2 to 5 min reduction intervals in a CH4/N2 mixture (5, 10 and 20% vol.) followed by regeneration in O2/N2 (3, 5, or 21% vol.), with redox cycles conducted either at 850 °C or 950 °C. The obtained rank of selectivity towards complete CH4 combustion is Ce–Cu > CeO2 > Chro. Another relevant finding is the role of the degree of carrier conversion in promoting partial or total oxidation. In particular, the selectivity towards CO2 markedly decreases at increasing carrier conversion, disclosing new strategies for process design and optimization by controlling the carrier conversion degree. [ABSTRACT FROM AUTHOR]

In order to reduce carbon emissions, which are currently a problem in the shipping and offshore plant sectors, the international community is strengthening regulations such as the Energy Efficiency Design Index (EEDI) and Energy Efficiency Existing Ship Index (EEXI). To cope with this, eco-friendly fuel propulsion technology is being developed, and the development of an ammonia fuel supply system is in progress. Among them, fuel valve train (FVT) technology was researched for the final supply and cutoff of fuel and purging through nitrogen for ammonia engines. In this paper, we analyzed the change in ammonia supply due to FVT opening and the change in nitrogen supply due to closure. In addition, a plan to minimize risk factors was presented by applying a control method to remove residual fuel in FVT. According to the presented FVT model, the difference in the flow rate of supplied fuel was as much as 17.8 kg/s. Additionally, by opening the gas bleed valve at intervals during the closing process and purging about 0.28 kg of nitrogen, the internal fuel could be completely discharged. This is expected to have an impact on improving the marine environment through the application of eco-friendly fuels and the development of fuel supply system technology. [ABSTRACT FROM AUTHOR]

The deeper penetration of renewables in the energy mix is an intense requirement in order to reduce global carbon dioxide emissions. In addition, new technologies are being developed, such as electric mobility and Distributed Generation (DG) in urban areas. However, the unpredictable fluctuations in energy generation from roof-installed PVs and the switching operation of their inverters greatly aggravate the already-present grid quality problems. In this paper, the Smart Boiler (SB) concept for grid quality improvement is presented. Furthermore, its experimental verification is implemented on a flexible testbed that accurately emulates several realistic scenarios for the low voltage distribution grid, under complex operating conditions. The proposed low-cost electronic kit, which contains a converter of fairly simple topology and requires connection to the internet, is used to upgrade conventional domestic boilers to smart devices. The SB automatically regulate the local reactive power flow, helping to stabilize the voltage level and suppress the grid current harmonic content, with both services provided in a matter of seconds. The higher the active power consumed and the denser the SB cluster, the wider the beneficial impact on the affected network area. While this service is provided, excess energy generated by PVs is temporarily stored as heat in the boiler tanks, given the users' hot water consumption habits. The whole application, as a powerful demand-side management tool, proves beneficial for both the network operator and the end-user, especially when self-consumption is desirable in order to achieve a Nearly Zero Energy Building. [ABSTRACT FROM AUTHOR]

From powering our homes to driving our economies, energy lies at the heart of humanity's complex challenges in the modern era. This paper reviews the evolution of smart energy systems, examining their technological advancements and societal implications while proposing a future design framework emphasizing four key pillars: holistic resource optimization, adaptive intelligence, environmental harmony, and human-centered design. While they offer numerous benefits, such as enhanced energy efficiency and reduced carbon emissions, smart energy systems also face challenges. These include cybersecurity risks, the complexity of integrating diverse energy sources seamlessly, high upfront costs, and potential compatibility issues arising from evolving technologies. Overcoming these challenges will be crucial for unleashing the full potential of smart energy systems and facilitating their global adoption. Abundant opportunities for further research and development exist in this domain, awaiting exploration and advancement. [ABSTRACT FROM AUTHOR]

Urban carbon emissions are an important area for addressing climate change, and it is necessary to establish scientific and effective carbon emission prediction models to formulate reasonable emission reduction policies and measures. In this paper, a novel model based on Lasso regression, an ARIMA model, and a BPNN is proposed. Lasso regression is used to screen the key factors affecting carbon emissions, and the ARIMA model is used to extract the linear components of the carbon emission sequences, while the BPNN is used to predict the residuals of the ARIMA model. The final result is the sum of that from the ARIMA model and the BPNN. The carbon peak, carbon neutralization time, and emissions were analyzed under different scenarios. Taking Suzhou City as an example, the results show that the electricity consumption of the whole population is one of the key drivers of carbon emissions; the carbon emission prediction accuracy and stability of the ARIMA-BPNN combined model are better than those of the single model, which improves the reliability as well as the accuracy of the model's prediction. However, under the constraints of the current policies, the goal of achieving carbon peaking by 2030 in Suzhou City may not be realized as scheduled. This novel carbon emission prediction model built was validated to provide a scientific basis for low-carbon urban development. This study presents an important reference value for predicting carbon emissions and formulating emission reduction measures in other cities. [ABSTRACT FROM AUTHOR]

Hydrogen is an emerging technology changing the context of heating with cleaner combustion than traditional fossil fuels. Studies indicate the potential to repurpose the existing natural gas infrastructure, offering consumers a sustainable, economically viable option in the future. The integration of hydrogen in combined heat and power systems could provide residential energy demand and reduce environmental emissions. However, the widespread adoption of hydrogen will face several challenges, such as carbon dioxide emissions from the current production methods and the need for infrastructure modification for transport and safety. Researchers indicated the viability of hydrogen in decarbonizing heat, while some studies also challenged its long-term role in the future of heating. In this paper, a comprehensive literature review is carried out by identifying the following key aspects, which could impact the conclusion on the overall role of hydrogen in heat decarbonization: (i) a holistic view of the energy system, considering factors such as renewable integration and system balancing; (ii) consumer-oriented approaches often overlook the broader benefits of hydrogen in emission reduction and grid stability; (iii) carbon capture and storage scalability is a key factor for large-scale production of low-emission blue hydrogen; (iv) technological improvements could increase the cost-effectiveness of hydrogen; (v) the role of hydrogen in enhancing resilience, especially during extreme weather conditions, raises the potential of hydrogen as a flexible asset in the energy infrastructure for future energy supply; and finally, when considering the UK as a basis case, (vi) incorporating factors such as the extensive gas network and unique climate conditions, necessitates specific strategies. [ABSTRACT FROM AUTHOR]

Predictive modeling is important for assessing and reducing energy consumption and CO2 emissions of light-duty vehicles (LDVs). However, LDV emission datasets have not been fully analyzed, and the rich features of the data pose challenges in prediction. This study aims to conduct a comprehensive analysis of the CO2 emission data for LDVs and investigate key prediction model characteristics for the data. Vehicle features in the data are analyzed for their correlations and impact on emissions and fuel consumption. Linear and non-linear models with feature selection are assessed for accuracy and consistency in prediction. The main behaviors of the predictive models are analyzed with respect to vehicle data. The results show that the linear models can achieve good prediction performance comparable to that of nonlinear models and provide superior interpretability and reliability. The non-linear generalized additive models exhibit enhanced accuracy but display varying performance with model and parameter choices. The results verify the strong impact of fuel consumption and powertrain attributes on emissions and their substantial influence on the prediction models. The paper uncovers crucial relationships between vehicle features and CO2 emissions from LDVs. These findings provide insights for model and parameter selections for effective and reliable prediction of vehicle emissions and fuel consumption. [ABSTRACT FROM AUTHOR]

Wave energy, as a significant renewable and clean energy source with vast global reserves, exhibits no greenhouse gas or other pollution during real-sea operational conditions. However, throughout the entire lifecycle, wave energy convertors can produce additional CO2 emissions due to the use of raw materials and emissions during transportation. Based on laboratory test data from a wave energy convertor model, this study ensures consistency between the model and the actual sea-deployed wave energy convertors in terms of performance, materials, and geometric shapes using similarity criteria. Carbon emission factors from China, the European Union, Brazil, and Japan are selected to predict the carbon emissions of wave energy convertors in real-sea conditions. The research indicates: (1) The predicted carbon emission coefficient for unit electricity generation ( E F co 2 ) of wave energy is 0.008–0.057 kg CO2/kWh; when the traditional steel production mode is adopted, the E F co 2 in this paper is 0.014–0.059 kg CO2/kWh, similar to existing research conclusions for the emission factor of CO2 for wave energy convertor (0.012–0.050 kg CO2/kWh). The predicted data on carbon emissions in the lifecycle of wave energy convertors aligns closely with actual operational data. (2) The main source of carbon emissions in the life cycle of a wave energy converter, excluding the recycling of manufacturing metal materials, is the manufacturing stage, which accounts for 90% of the total carbon emissions. When the recycling of manufacturing metal materials is considered, the carbon emissions in the manufacturing stage are reduced, and the carbon emissions in the transport stage are increased, from about 7% to about 20%. (3) Under the most ideal conditions, the carbon payback period for a wave energy convertor ranges from 0.28 to 2.06 years, and the carbon reduction during the design lifespan (20 years) varies from 238.33 t CO2 (minimum) to 261.80 t CO2 (maximum). [ABSTRACT FROM AUTHOR]