Energy Conversion and Management最新文献

{"title":"Multi-energy cooperative optimal scheduling of rural virtual power plant considering flexible dual-response of supply and demand and wind-photovoltaic uncertainty","authors":"","doi":"10.1016/j.enconman.2024.118990","DOIUrl":"10.1016/j.enconman.2024.118990","url":null,"abstract":"<div><p>With the vast land areas and abundant biomass resources, rural areas have significant potential for the development of distributed energy system. To mitigate the current rural energy use conflict, this paper formulates a novel virtual power plant framework based on the unique resource endowment of rural areas. Firstly, a more practical method of wind-photovoltaic output scenario generation is proposed by using time-varying copula. Subsequently, refine the utilization of hydrogen energy in the power-to-gas process to increase the energy efficiency of the system. On this basis, considering the variable power operation of the internal energy supply units and the demand response of various loads, a flexible dual-response mechanism for supply and demand is proposed. Ultimately, a ladder-type trading mechanism is used to guide the system for low-carbon operation. Simulation results indicate that 1) the time-varying copula function possesses better accuracy in measuring the correlation between wind and photovoltaic output. 2) power-to-gas with refined utilization of hydrogen improves system energy efficiency by 3.52%. 3) the dual-response mechanism for supply and demand can significantly lower the total cost and carbon emissions by 11.68% and 7.63%, respectively. 4) The ladder-type trading mechanism can equilibrate the carbon emissions and economics of the system.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of phenol yield by machine learning based on biomass characteristics, pyrolysis conditions, and catalyst properties","authors":"","doi":"10.1016/j.enconman.2024.119001","DOIUrl":"10.1016/j.enconman.2024.119001","url":null,"abstract":"<div><p>Phenol is one of the most valuable chemicals from biomass pyrolysis. The study of phenol production is time-consuming and uneconomical by traditional experiments. In this study, random forest (RF) and extreme gradient boosting (XGB) were used to predict phenol yield based on biomass characteristics, pyrolysis conditions, and catalyst properties. The results indicated the XGB model had a better prediction performance (optimal test R² = 0.93). The Shapley additional exploration showed that the lignin content (Lig) and the ratio of catalyst to biomass (C/B) had more impact on phenol yield. The one-dimensional partial dependency plots suggested that phenol yield first increased with the increase of Lig (Lig &lt; 35 wt%) and C/B (C/B &lt; 1), and then decreased with the rise of Lig (Lig &gt; 35 wt%) and C/B (C/B &gt; 1). The two-dimensional partial dependency plots indicated that the highest phenol yield could reach 66 mg/g (Lig ≈ 43 wt% and PT ≈ 570 °C). Moreover, the predictive performance of the model was verified by experiments. All prediction errors were within ± 10 %, achieving higher accuracy. This study provides a convenient and economical way to evaluate and optimize pyrolysis experiments to improve phenol yield and provides a scientific reference for efficient utilization of biomass and bio-oil production.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An interpretable machine learning-based optimization framework for the optimal design of carbon dioxide to methane process","authors":"","doi":"10.1016/j.enconman.2024.119010","DOIUrl":"10.1016/j.enconman.2024.119010","url":null,"abstract":"<div><p>The conversion of carbon dioxide into methane is widely recognized as an effective approach to address the challenges caused by climate change and carbon emissions. However, this process is highly intricate and susceptible to multiple influencing factors, making it challenging to optimize and determine through conventional trial-and-error methods simultaneously. Therefore, an interpretable machine learning-based optimization framework, which integrates the merits of process simulation, exergy analysis, and artificial intelligence approaches and tools, is developed for the optimal design of this process. The bottleneck analysis is conducted through exergy analysis based on the simulated material and energy results of the entire carbon dioxide (CO₂) to methane process, revealing that its exergy efficiency is about 80.29 %. Furthermore, it is found that the CO₂ methanation reactor exhibits the highest exergy destruction ratio, accounting for 60.57 % of the total destructions. Therefore, this study develops three types of machine learning models for enhancing the performance of the reaction process effectively. Compared with the random forest and deep neural network algorithms, the extreme gradient boosting model has the highest prediction accuracy on the CO₂ conversion ratio, methane selectivity, and exergy efficiency of the reactor (with a coefficient of determination &gt; 0.916). The Shapley additive explanations and partial dependence plots analysis are conducted to further identify the most important parameters for improving performance and analyze their impact mechanisms. The comparison with other input parameters highlights that the performance of CO₂ methanation systems is primarily influenced by reaction conditions (accounting for 56.3 %) and catalyst conditions, particularly temperature. Finally, the CO₂ conversion ratio, methane yield, and exergy efficiency of the CO₂ to methane process are improved by 3.97 %, 3.06 %, and 1.46 % through multi-objective optimization.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental investigation of a splitting organic Rankine cycle for dual waste heat recovery","authors":"","doi":"10.1016/j.enconman.2024.119005","DOIUrl":"10.1016/j.enconman.2024.119005","url":null,"abstract":"<div><p>The organic Rankine cycle (ORC) is an effective method for internal combustion engines’ waste heat recovery. The waste heat from internal combustion engines primarily includes exhaust gas and engine cooling water. However, single-loop preheating and dual-loop ORC configurations are difficult to balance the recovery efficiency of the dual heat sources and the complexity of the equipment. The splitting ORC, as an effective method for enhancing the utilization of waste heat sources, has been proposed.</p><p>This study developed for the first time a test bench for a splitting ORC with a recuperator (SR-ORC) for internal combustion engines’ waste heat recovery, aiming to verify the enhancement effect of the system’s performance by splitting the working fluid into two branches to recover the engine cooling water and exhaust gas waste heat respectively.</p><p>The research results indicate that there exists an optimal working fluid pump speed and splitting ratio to maximize the net output power and efficiency of the system. Moreover, under the engine condition of rotating speed of 1100 rpm and torque of 600 N·m, the system achieves a maximum net power output of 2.81 kW, a maximum internal combustion engine efficiency improvement of 1.6 %, and a maximum thermal efficiency of 10.1 % at the maximum heat source safety operating range. Compared to the non-splitting mode of this test bench with the same engine and heat source condition, these values represent a relative improvement of 8.3 %, 9.6 %, and 27.9 %, respectively.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the relationship between catalytic pyrolysis conditions and hydrogen production by aqueous phase reforming of the water-soluble fractions of bio-oils","authors":"","doi":"10.1016/j.enconman.2024.118999","DOIUrl":"10.1016/j.enconman.2024.118999","url":null,"abstract":"<div><p>The valorization to H₂ of real aqueous fractions of bio-oil (AFBs) from catalytic pyrolysis of woodchips was carried out by aqueous phase reforming (APR). Notable gas yield (23 mmol/gTOC_o) and H₂ concentration (46 mol%) were achieved, with values among the best published for the APR of real biorefinery streams. The reforming of AFBs was favoured by a high concentration of levoglucosan and low proportion of acids and ketones, with acetone and acetic acid being the most refractory compounds to APR. Relationships between the pyrolysis conditions and the H₂ production obtained by APR were assessed, with more favourable results when the pyrolysis was carried out under the most severe conditions of those studied, i.e. 0.30 catalyst/biomass ratio and 500 °C in the catalytic step. H₂ production increased to 32 mmol/gTOC_o when 0.04 wt% formic acid was added to the reaction medium, showing that this strategy can overcome the low reforming ability of some AFB components. The Pt catalyst showed good stability after 3 consecutive reaction cycles, displaying only a slight decrease in TOC conversion and CCgas, but a moderate decrease in H₂ production and gas concentration. The loss of activity was ascribed to cumulative adsorption of high molecular weight compounds and oligomers on the catalyst surface.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0196890424009403/pdfft?md5=8440ec1cadd8351b70d74da35b59a691&pid=1-s2.0-S0196890424009403-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and simulated evaluation of inter-seasonal power-to-heat and power-to-cool with underground thermal storage for self-consumption of surplus solar energy in buildings","authors":"","doi":"10.1016/j.enconman.2024.119013","DOIUrl":"10.1016/j.enconman.2024.119013","url":null,"abstract":"<div><p>The adoption of renewable energy, such as solar, to meet the energy demand in buildings has become one of the keys to achieving the global target for net-zero emissions. As a result, solar photovoltaic installations have increased tremendously, giving rise to an enormous surplus of electricity generation, which has become an issue requiring alternative ways to be addressed. Underground thermal energy storage for power-to-heat operations has gained interest in this area due to its reliability, cost-effectiveness, and carbon-free nature. This study presents a novel system configuration with an operational strategy guided by a simple control method that uses surplus photovoltaic electricity to power an inter-seasonal heating and cooling system coupled with seasonal underground thermal energy storage. Two cases were developed, modeled, and simulated in the TRNSYS 18 simulation tool. Case 1 involves an air-source water-load heat pump and 1.5 m-shallow underground thermal storage with power-to-heat and power-to-cool operations. Case 2 features an air-source water-load heat pump and vertical 150 m-deep underground thermal storage with power-to-heat and power-to-cool operations. The base case involving an air-source water-load heat pump without power-to-heat and power-to-cool operations was modeled for their evaluation. In Case 1, energy savings and power-to-heat and power-to-cool efficiency of 14 % and 39 % were obtained, respectively. Similarly, energy savings and power-to-heat and power-to-cool efficiency of 13 % and 36 % were obtained, respectively, from Case 2. Both study cases displayed a self-consumption ratio of approximately 81 % compared to the base case, which had 76 %. Similarly, the surplus energy utilization ratio of about 26 % was obtained from both cases. Furthermore, 60 % and 52 % thermal efficiencies were obtained for study cases 1 and 2, respectively, for the underground thermal storage. The results demonstrate that the configuration and operational strategy implemented can seasonally utilize the available photovoltaic power and enhance the performance of the heat pumps.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0196890424009543/pdfft?md5=6f48310e961c24f6d2448afdd60fb3a7&pid=1-s2.0-S0196890424009543-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards various occupants with different thermal comfort requirements: A deep reinforcement learning approach combined with a dynamic PMV model for HVAC control in buildings","authors":"","doi":"10.1016/j.enconman.2024.118995","DOIUrl":"10.1016/j.enconman.2024.118995","url":null,"abstract":"<div><p>Reinforcement learning (RL) has great potential in achieving energy-efficient, comfortable and intelligent control of heating, ventilation and air conditioning (HVAC) systems. Although research on RL-based HVAC control has attracted increasing interest, current studies generally use simple building simulation as the environment to train agents, and the definition of thermal comfort is limited to a wide temperature range, which cannot meet the different thermal comfort requirements of various occupants. This study proposes a deep reinforcement learning (DRL) control framework based on the Dueling Deep Q-network (DQN) algorithm, combined with a self-designed environmental model and reward function, for HVAC control meeting different thermal comfort requirements. Specifically, based on the theory of building thermal dynamics, a nonlinear equation modified by experimental data is used for the environmental model that reflects the actual thermal change of building. Different thermal comfort requirements are considered and analysed through a dynamic predicted mean vote (PMV) model that focuses on the metabolic rate and clothing level of occupants. By systematically exploring different heating modes for occupants and control time intervals, the proposed framework demonstrates that heating energy consumption can be reduced by 4.8%-39.58% under various conditions compared to rule-based control. In addition, the study found that the HVAC control based on DRL has greater potential in saving energy when the heating demand of building is higher. Our study is helpful for researchers to make HVAC control more energy-efficient and user-friendly with the help of artificial intelligence.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How torrefaction impacts minimal fluidization velocity from different biomasses and their mixtures","authors":"","doi":"10.1016/j.enconman.2024.119002","DOIUrl":"10.1016/j.enconman.2024.119002","url":null,"abstract":"<div><p>Torrefaction has emerged as a promising technology for optimizing the efficiency of thermochemical processes. However, many challenges still need to be addressed regarding its integration with other processes, such as gasification. This work investigates the potential of torrefaction to transform the properties of biomass mixtures, improving operations in fluidized bed reactors. Experimentally, hazelnut shells and olive pit mixtures were torrefied at 280 °C for 45 min to analyze how torrefaction affected the minimum fluidization velocity as a bulk density function. The results were compared to other biomasses from the literature. Our findings show that torrefaction can stabilize minimum fluidization velocity at 0,45 m/s for mixtures of biomasses with bulk densities below 700 kg/m³ and particle size range (T) of 1,7 &lt; T &lt; 2,36 × 10⁻³ m. These findings collectively emphasize the potential of torrefaction as an effective technology for utilizing agro-industrial residues in energy generation processes not only for the improvement of conversion efficiency but also for operation stability.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative pressurized diesel reforming for sustainable hydrogen production using advanced PtRu-CGO catalyst","authors":"","doi":"10.1016/j.enconman.2024.118973","DOIUrl":"10.1016/j.enconman.2024.118973","url":null,"abstract":"<div><p>This study suggests a novel approach for producing hydrogen through the pressurized reforming of commercial diesel, leveraging the PtRu-CGO catalyst. Foundational experiments were performed with PtRu-CGO powder catalysts at conditions up to 9 bar and 800 °C, achieving complete fuel conversion and stable performance with an average hydrogen concentration of approximately 58.7 mol%. Additionally, the structured catalysts developed herein also could maintain high efficiency and durability under a gas hourly space velocity (GHSV) of 10,000 h⁻¹. Notably, at 6 bar, the system exhibited an extraordinary efficiency of around 75 % over 300 h of continuous operation. These results underscore the practicality of pressurized diesel reforming for hydrogen production with the PtRu-CGO catalyst, highlighting its potential in the development and optimization of hydrogen energy systems and aiding the shift towards a hydrogen-based economy.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142128978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance investigation of a novel photovoltaic-thermal vapor injection heat pump based on 4E analysis","authors":"","doi":"10.1016/j.enconman.2024.118994","DOIUrl":"10.1016/j.enconman.2024.118994","url":null,"abstract":"<div><p>A novel photovoltaic-thermal vapor injection heat pump (PVHP) is proposed and analyzed in this paper, which owns remarkably superior performance by realizing cogeneration of electricity and thermal energy from solar energy. The operation characteristics of PVHP are evaluated based on built simulation model. It indicates that the solar assisted mode is suitable for extremely low or no solar radiation conditions, while the vapor injection mode is preferable to other conditions. There exists optimal combination of intermediate pressure and split ratio for PVHP to achieve the maximal comprehensive COP (coefficient of performance). The energy, exergy, economic and environmental performance of PVHP and traditional economized vapor injection heat pump (VIHP) are compared based on genetic algorithm. Thereinto, the heating COP and comprehensive COP of PVHP respectively exceed the heating COP of VIHP by averages of 18.4 % and 4.1 % under evaporating temperature range of −20 ∼ 5 °C. Moreover, PVHP can produce 4.2 % more heat exergy output with 12.2 % less net electricity consumption compared with VIHP. PVHP yields about 8.5 years payback periods in four northern China cities when adopted to replace VIHP in the considered application scenario, and significantly reduces the pollutant emissions. In addition, the optimal combination of comprehensive COP and levelized cost of energy is located at [5.55, 0.132 $ kWh⁻¹] by multi-objective optimization.</p></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}