Current Issue https://www.hdpower.net EN-US https://www.hdpower.net/EN/2097-0706/current.shtml https://www.hdpower.net 2097-0706 https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.001 To realize the sustainable development of high-energy-consuming enterprises锛� and promote carbon emission reduction and energy efficiency锛� an energy-saving and carbon-reduction evaluation index system for aluminum processing is establish. The system takes energy efficiency锛� carbon emission and environment indicators into considerations锛� so as to ensure the comprehensiveness and accuracy of the evaluation. The analytic hierarchy process is used to evaluate the efficiency锛� carbon emission level and environmental impact of each processing section in aluminum processing. In a case study锛� the energy-saving and carbon-reduction potential of each processing section was evaluated锛� and the sensitivity analysis on the energy-saving and carbon-reduction evaluation index system was carried out to ensure the universality of the established index system. The results show that aluminum processing enterprises can improve their energy-saving and carbon-reduction capabilities from updating the casting process. Based on user profiling锛� optimizing suggestions for production process are proposed to reduce energy consumption and environmental pollutants锛宎chieving sustainable development goals.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.002 In view that petrochemical industry is a typical industry of high carbon emissions锛� studying the variation law and influencing factors of its carbon emissions can facilitate the implement of China's "dual carbon" strategy. Based on the data from the nine carbon emission sources which include raw coal锛� clean coal锛� coke锛� gasoline锛� diesel and crude oil in five sub industries of petrochemical industry in Jilin Province from 2002 to 2021锛� the temporal evolution characteristics and composition of the carbon emissions are studied. Six indicators affecting the carbon emissions from petrochemical industry in Jilin Province锛� including economic value added锛� are selected锛� and their impacts and mechanisms are deeply studied based on the expanded STIRPAT model and ridge regression parameter estimation. According to empirical analysis results锛� three suggestions are proposed to promote the low-carbon development and carbon reduction of petrochemical industry in Jilin Province锛� improving energy efficiency and energy consumption structure锛� selecting valuable investment projects and low-carbon projects锛� adopting circular economy and conducting environmental impact assessments.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.003 In order to achieve China's "double carbon" target锛� reducing the carbon emissions from automobile industry has become an important measure锛� and studying the main factors affecting the carbon emissions is of great significance for formulating low-carbon development strategies. To analyzed the changes of the total carbon emissions from automobile industry in Jilin Province from 2012 to 2021锛� a Vector Auto Regression锛圴AR锛� model is applied in exploring the driving factors for the emissions. It is found out that there are four main factors impacting the carbon emissions from automobile industry in Jilin Province锛� and the degree of impacts is as follows in descending order锛� the level of household consumption锛� the retain number of family cars锛� the carbon emissions from transportation industry and the carbon emissions of automobile manufacturing. Based on the analytic results above锛� following measures are proposed to promote the realization of emission reduction of automobile industry in Jilin Province锛� taking intelligent and clean technologies and new energy-saving measures in vehicle production锛� providing subsidies for car purchase and building charging facilities锛� developing public transportation and optimizing route layout锛� recycling waste parts and forming a cycling economy.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.004 Scientific and effective carbon asset assessment is a major boost for enterprises to achieve their efficient carbon management and the prosperity and development of the national carbon emission trading market.In order to improve the assessment efficiency of enterprises' carbon assets and enhance their enthusiasm to participate in the national carbon emission rights trading market锛宼he characteristics of enterprises' carbon assets are analyzed on the basis of fully studying the trading and compliance processes of enterprises' participation in the market. Based on the real option theory and fuzzy mathematics theory锛宎 comprehensive enterprise carbon asset valuation model is constructed to solve the inaccurate evaluation results resulting from sharp fluctuations of carbon prices and the neglect of the correlation between two carbon assets.The effectiveness and stability of the model are fully verified by numerical examples.The results show that the carbon asset valuation model proposed based on the fuzzy real option theory can be used as a basis for judging the enterprises' carbon reduction performances锛宎n assistance to realize efficient carbon asset management and a boost for enterprises to participate in the carbon market. It is a methodology exploration of enterprises' low-carbon transformation.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.005 With the continuous access of flexible energy sources such as distributed new energy and electric vehicles锛宼he potential of building energy systems in energy conservation and carbon reduction gets inspired.It is of great significance to clarify the development trend of building energy systems for achieving the goals of carbon peak and carbon neutrality in urban areas.Since the building energy system whole process includes system construction锛宱peration and management锛宼he new system structure锛宔nergy supply mode锛宻ystem operation mode锛宒igital management锛宒emand response and control mechanism should be analyzed comprehensively.Based on the analysis results锛宼he development trend of building energy systems towards production and marketing integration锛宭ow carbonization锛宖lexibility锛宒igitization and standardization are prospected锛寃hich provides reference for the high-quality development of urban building energy systems.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.006 Hydrolysis process limits the anaerobic digestion 锛圓D锛� rate of sludge. Supplementing exogenous biochar 锛圔C锛� can effectively boost methane production by overcoming the limitation in hydrolysis. The iron-manganese modified biochar 锛團e-Mn-BC锛� derived from the residual shells of woody oil crops锛� specifically Camellia oleifera shells锛� is studied. SEM锛� FTIR锛� XPS and XRD are employed to characterize the material锛� and its impacts on sludge AD performance锛� methane yield and microbial community structure are explored. The study results demonstrate that since Fe-Mn-BC possesses a porous structure锛� iron and manganese particles can load onto the BC surface in various forms of oxides. The addition of Fe-Mn-BC elevates methane production. When the total solid mass fraction of Fe-Mn-BC reaches 80 mg/g锛� cumulative gas production peaks at 301.59 mL/g锛� marking a 45.27% increase compared to that of the control group. Microbial community analysis reveals that Fe-Mn-BC enriches the abundance of archaeal communities锛� including Crenarchaeota锛� Candidatus_Methanomethylicus and Candidatus_Methanofastidiosum. These communities play crucial roles in promoting the hydrolysis of organic matters and enhancing the methane production锛� indicating that Fe-Mn-BC not only enriches functional microbial communities such as methanogenic bacteria锛� but also effectively improves the efficiency of sludge AD. Furthermore锛� this method presents a resource utilization solution for Camellia oleifera shells.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.007 Taking a 660 MW opposed firing boiler as the study object锛宼he combustion features and distribution of alkali metals in the furnace during co-combustion with dehydrated sludge are studied by numerical simulation锛宎nd the influence factors including the blending layer锛� excess air coefficient and different Cl content in sludge are analyzed. The co-combustion with dehydrated sludge will increase the alkali metal mass concentration on the furnace side wall. The study indicates that blending sludge on the middle and upper layer of the burner can reduce the emission rate of alkali metals and lower the wall temperature near OFA nozzles. Increasing excess air coefficient can improve the burnout rate of pulverized coal and reduce the alkali metal mass concentration on the side wall. And decline of the Cl content in sludge can effectively reduce the concentration of alkali metals in flue gas and conversion rate of alkali metal compounds to NaCl. Blending sludges on the middle and upper layers of a co-combustion burner can reduce the excess air coefficient and alleviate the fouling锛� slagging and alkali metal high temperature corrosion in the furnace.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.008 The furnace temperature of a multi-pass circulating fluidized bed锛圕FD锛� is higher than that of a traditional CFD锛� which advances the miniaturization of CFDs. The gas-olid flows and combustion of a multi-pass CFD were numerically stimulated by computational particle fluid dynamics method. The simulation results fitted well with the results of the pilot-scale experiment. The results indicate that volume fractions of particle phase show core-annulus structure锛� ranking from high to low in the main combustion chamber锛� auxiliary combustion chamber锛� and burnout chamber. The furnace temperature is from 1 000 to 1 200 K. The temperature of the main chamber is higher larger than that of the auxiliary chamber锛� and the temperature of the auxiliary chamber is higher than that of the burnout chamber and the cyclone separator. Increasing the oxygen content in the dense phase zone of the furnace by enlarging the proportion of primary air to secondary air can intensify the combustion and increase the bed temperature. Pre-classification of fuel at the secondary chamber inlet is beneficial for coke reduction reactions锛� which is favorable to the reductions of NO concentration and nitrogen oxide emissions.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.009 As an important component of an integrated energy system锛� a CHP unit not only provides electric and thermal power锛宐ut also lays a foundation for renewable energy consumption. The fan and coal mill are significant devices for a cogeneration unit and play vital roles in its operation. In the research on fault diagnosis technologies锛宖aults in fans and coal mills are summarized锛宎nd subsequently锛� based on artificial intelligence algorithms锛宼he fault diagnosis technologies are categorized into three technical approaches锛� machine learning锛� deep learning锛� and hybrid models. The development trends and core issues of each technology are analysed. Finally锛� the prospects of fault diagnosis technologies applying in integrated energy systems are discussed.

]]> https://www.hdpower.net/EN/10.3969/j.issn.2097-0706.2024.08.010 Making reliability evaluations on selective catalytic reduction锛圫CR锛� denitrification systems in thermal power plants is significance for the safe operation of denitrification systems. Based on the classification on failure causes of denitrification systems锛宎 fault tree analysis锛團TA锛� taking abnormal ammonia/nitrogen molar ratio as its main indicator is applied on the evaluation. Then锛� Boolean algebra is used to analyze the path set of the FTA fault indicator锛寃ith a total of 11 minimum cut sets and a total of 5 minimum path sets. Considering the combination modes and propagation paths of impacts of elementary events on top events锛宎n evaluation method for system safety hazards according to confidence degree is proposed. Based on the operational data of a denitrification system in a 300 MW unit boiler锛宎 failure probability analysis was carried out on a specific fault of the reactor锛宎nd the conclusion was reached that the relative error between the confidence degree of the minimum cut set K7 and the confidence degree of the reliability evaluation method was only 0.694%. And the relative errors of other 20 fault events were all within 1%. The results show that the proposed evaluation method based on the minimum cut set confidence is accurate and feasible.

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