Pub Date : 2023-08-01DOI: 10.1061/jleed9.eyeng-4850
Hua Jing, Chunhui Zhao
Monitoring wind turbines is essential for their safe operation on wind farms. However, the majority of data-driven monitoring strategies do not consider expert knowledge. Consequently, they cannot simultaneously monitor statistical and physical characteristics and have poor monitoring results. This study proposes a knowledge-aided adaptive parallel monitoring strategy to monitor the process by evaluating the physical and statistical characteristics using two submodels. First, we propose a novel knowledge-aided monitoring statistic to characterize energy conversion efficiency, thus monitoring both the conversion efficiency using one of the submodels and the physical performance of the wind turbine. Subsequently, the process characteristics covering both steady and varying states can be monitored with another submodel using two monitoring statistics, which can accurately detect unusual behaviors from a statistical perspective. Generally, we can use three statistics to monitor the process from two perspectives. With the physical and statistical characteristics captured, we propose a novel adaptive monitoring strategy to adjust the model performance and accurately detect fault conditions. Real-world experiments demonstrate the effectiveness of the proposed method. Among the four monitoring methods, the monitoring strategy aided by knowledge showed the highest detection accuracy.
{"title":"A Novel Adaptive Parallel Model with Knowledge-Aided Conversion Efficiency Assessment for Wind Turbine Condition Monitoring","authors":"Hua Jing, Chunhui Zhao","doi":"10.1061/jleed9.eyeng-4850","DOIUrl":"https://doi.org/10.1061/jleed9.eyeng-4850","url":null,"abstract":"Monitoring wind turbines is essential for their safe operation on wind farms. However, the majority of data-driven monitoring strategies do not consider expert knowledge. Consequently, they cannot simultaneously monitor statistical and physical characteristics and have poor monitoring results. This study proposes a knowledge-aided adaptive parallel monitoring strategy to monitor the process by evaluating the physical and statistical characteristics using two submodels. First, we propose a novel knowledge-aided monitoring statistic to characterize energy conversion efficiency, thus monitoring both the conversion efficiency using one of the submodels and the physical performance of the wind turbine. Subsequently, the process characteristics covering both steady and varying states can be monitored with another submodel using two monitoring statistics, which can accurately detect unusual behaviors from a statistical perspective. Generally, we can use three statistics to monitor the process from two perspectives. With the physical and statistical characteristics captured, we propose a novel adaptive monitoring strategy to adjust the model performance and accurately detect fault conditions. Real-world experiments demonstrate the effectiveness of the proposed method. Among the four monitoring methods, the monitoring strategy aided by knowledge showed the highest detection accuracy.","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135717278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1061/jleed9.eyeng-4734
Cheng Li, Hao Jing, Jianyao Hu, Guangdi Hu, Yuxiang Deng
This paper proposes a novel approach to control the output power of a proton-exchange membrane fuel-cell (PEMFC) system by the current rate of change. First, a 70-kW PEMFC system model is established, which is validated by the experimental data with the maximum error of the output voltage being 3.68%. Then, a multi-input multi-output (MIMO) sliding mode controller (SMC) is designed based on the PEMFC model to maintain the excess oxygen ratio, the pressure difference between the cathode and anode, the stack temperature, and the output power at expectations. Finally, the simulation results show that the designed MIMO SMC performs better than the conventional proportional integral (PI) controller. When the PEMFC system responds to the dynamically changing power demand, the maximum power tracking error is 4.79%, the temperature fluctuation is about 0.06 K, and the pressure difference is maintained within 10 Pa.
{"title":"Sliding Mode Control for Power Tracking of Proton-Exchange Membrane Fuel-Cell System","authors":"Cheng Li, Hao Jing, Jianyao Hu, Guangdi Hu, Yuxiang Deng","doi":"10.1061/jleed9.eyeng-4734","DOIUrl":"https://doi.org/10.1061/jleed9.eyeng-4734","url":null,"abstract":"This paper proposes a novel approach to control the output power of a proton-exchange membrane fuel-cell (PEMFC) system by the current rate of change. First, a 70-kW PEMFC system model is established, which is validated by the experimental data with the maximum error of the output voltage being 3.68%. Then, a multi-input multi-output (MIMO) sliding mode controller (SMC) is designed based on the PEMFC model to maintain the excess oxygen ratio, the pressure difference between the cathode and anode, the stack temperature, and the output power at expectations. Finally, the simulation results show that the designed MIMO SMC performs better than the conventional proportional integral (PI) controller. When the PEMFC system responds to the dynamically changing power demand, the maximum power tracking error is 4.79%, the temperature fluctuation is about 0.06 K, and the pressure difference is maintained within 10 Pa.","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135465232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1061/jleed9.eyeng-4559
Yan Sun, Changgao Xia, Jiangyi Han
For a fuel cell range-extended electric vehicle (FC-REEV), the fuel cell system can work at a fixed output power point, and it has high durability. However, the differences in output power and start–stop threshold can lead to a significant difference in energy loss and degradation of power sources. Based on the thermostat control strategy (TCS), the state of charge (SOC) of the battery is stabilized within a reasonable range. To obtain the lowest hydrogen consumption rate, the vehicle’s fuel economy is considered in the evaluation function. The artificial bee colony (ABC) optimization algorithm is then used to increase the driving range, and the conventional ABC-TCS (CABC-TCS) is proposed. However, the CABC-TCS leads to many start–stop times for fuel cells. To enhance the durability of the fuel cells, a penalty factor was added to the evaluation function, and a novel optimized ABC-TCS (OABC-TCS) is proposed. Different strategies were tested under federal test procedure (FTP)-72 and worldwide light-duty test procedure (WLTC) driving cycles. The results show that, compared with TCS, the optimized driving range of OABC-TCS in FTP-72 and WLTC conditions increased almost 10.59% and 10.3%. Compared with CABC-TCS, the start–stop times of OABC-TCS in FTP-72 and WLTC conditions decreased by 27.55 and 46.47 times/h, respectively.
{"title":"Optimization of Energy Saving and Fuel-Cell Durability for Range-Extended Electric Vehicle","authors":"Yan Sun, Changgao Xia, Jiangyi Han","doi":"10.1061/jleed9.eyeng-4559","DOIUrl":"https://doi.org/10.1061/jleed9.eyeng-4559","url":null,"abstract":"For a fuel cell range-extended electric vehicle (FC-REEV), the fuel cell system can work at a fixed output power point, and it has high durability. However, the differences in output power and start–stop threshold can lead to a significant difference in energy loss and degradation of power sources. Based on the thermostat control strategy (TCS), the state of charge (SOC) of the battery is stabilized within a reasonable range. To obtain the lowest hydrogen consumption rate, the vehicle’s fuel economy is considered in the evaluation function. The artificial bee colony (ABC) optimization algorithm is then used to increase the driving range, and the conventional ABC-TCS (CABC-TCS) is proposed. However, the CABC-TCS leads to many start–stop times for fuel cells. To enhance the durability of the fuel cells, a penalty factor was added to the evaluation function, and a novel optimized ABC-TCS (OABC-TCS) is proposed. Different strategies were tested under federal test procedure (FTP)-72 and worldwide light-duty test procedure (WLTC) driving cycles. The results show that, compared with TCS, the optimized driving range of OABC-TCS in FTP-72 and WLTC conditions increased almost 10.59% and 10.3%. Compared with CABC-TCS, the start–stop times of OABC-TCS in FTP-72 and WLTC conditions decreased by 27.55 and 46.47 times/h, respectively.","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136097248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1061/jleed9.eyeng-4586
Mohammad Hossein Oboudi, Mohammad Mohammadi, Dimitris N. Trakas, Nikos D. Hatziargyriou
Earthquakes and other natural disasters have caused significant damages to power systems, indicating the necessity to enhance power system resilience. This paper proposes a risk-based resilience enhancement framework against earthquakes that considers their stochastic nature. The proposed framework supports the decision-making of distribution system operators (DSOs) for retrofitting substation components and underground cables to enhance distribution system resilience. The framework consists of four phases, namely earthquake modeling, vulnerability assessment, risk assessment, and resilience enhancement. An attenuation relationship is used to model the earthquake characteristics. Vulnerability assessment includes the failure probability calculation of substation components and a fault-tree method application to examine the seismic vulnerability of the substation. Conditional value at risk (CVaR) is used to assess the seismic risk, and includes the estimation of repair cost and customer interruption cost due to the damage caused by the earthquake, as well as the power generation cost of the distributed energy resources (DERs) used to meet the demand locally. A modified risk reduction worth (RRW) metric is adopted to determine the optimal retrofitting strategy to enhance resilience. The proposed framework was applied to a real distribution substation to examine the effectiveness of substation component retrofitting for resilience enhancement.
{"title":"A Risk-Based Framework to Improve a Distribution System’s Resilience against Earthquakes","authors":"Mohammad Hossein Oboudi, Mohammad Mohammadi, Dimitris N. Trakas, Nikos D. Hatziargyriou","doi":"10.1061/jleed9.eyeng-4586","DOIUrl":"https://doi.org/10.1061/jleed9.eyeng-4586","url":null,"abstract":"Earthquakes and other natural disasters have caused significant damages to power systems, indicating the necessity to enhance power system resilience. This paper proposes a risk-based resilience enhancement framework against earthquakes that considers their stochastic nature. The proposed framework supports the decision-making of distribution system operators (DSOs) for retrofitting substation components and underground cables to enhance distribution system resilience. The framework consists of four phases, namely earthquake modeling, vulnerability assessment, risk assessment, and resilience enhancement. An attenuation relationship is used to model the earthquake characteristics. Vulnerability assessment includes the failure probability calculation of substation components and a fault-tree method application to examine the seismic vulnerability of the substation. Conditional value at risk (CVaR) is used to assess the seismic risk, and includes the estimation of repair cost and customer interruption cost due to the damage caused by the earthquake, as well as the power generation cost of the distributed energy resources (DERs) used to meet the demand locally. A modified risk reduction worth (RRW) metric is adopted to determine the optimal retrofitting strategy to enhance resilience. The proposed framework was applied to a real distribution substation to examine the effectiveness of substation component retrofitting for resilience enhancement.","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135803519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1061/(asce)ey.1943-7897.0000878
{"title":"Reviewers","authors":"","doi":"10.1061/(asce)ey.1943-7897.0000878","DOIUrl":"https://doi.org/10.1061/(asce)ey.1943-7897.0000878","url":null,"abstract":"","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136062391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AbstractThe high-pressure injection strategy for di-n-butyl ether (DBE)-diesel fuel blends reduces particulate matter emissions. Exhaust gas recirculation (EGR) technology was used to decrease NOx ...
{"title":"Potential of Di-n-Butyl Ether as an Alternative Fuel for Compression Ignition Engines with Different EGR Rates and Injection Pressure","authors":"Changkun Wu, Yuke Wang, Hailang Sang, Haozhong Huang, Qiwei Wang, Mingzhang Pan","doi":"10.1061/(ASCE)EY.1943-7897.0000790","DOIUrl":"https://doi.org/10.1061/(ASCE)EY.1943-7897.0000790","url":null,"abstract":"AbstractThe high-pressure injection strategy for di-n-butyl ether (DBE)-diesel fuel blends reduces particulate matter emissions. Exhaust gas recirculation (EGR) technology was used to decrease NOx ...","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"3 1","pages":"04021042"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90308355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1061/(ASCE)EY.1943-7897.0000791
M. Lun, Xinke Chen, Qingyan Fang, Cheng Zhang, Gang Chen, Ji Xia
AbstractThe combustion interactions during blended coal combustion affect their combustion characteristics, and the combustion interactions under air–fuel conditions have been well studied. However...
{"title":"Combustion Interactions of Blended Chars under Oxidation and Gasification Competition in Oxy–Fuel Condition","authors":"M. Lun, Xinke Chen, Qingyan Fang, Cheng Zhang, Gang Chen, Ji Xia","doi":"10.1061/(ASCE)EY.1943-7897.0000791","DOIUrl":"https://doi.org/10.1061/(ASCE)EY.1943-7897.0000791","url":null,"abstract":"AbstractThe combustion interactions during blended coal combustion affect their combustion characteristics, and the combustion interactions under air–fuel conditions have been well studied. However...","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"279 1","pages":"04021041"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76421144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1061/(ASCE)EY.1943-7897.0000785
Lin Wei, Qulan Zhou, Zhuhan Liu, Na Li, Lian Li, Qinlan Luo
AbstractTo study the operational problems of an opposed firing boiler in continuously changing working conditions, the temperature, strain, and thermal stress of water walls were measured to analyz...
{"title":"Experimental Study on the Distribution of Temperature and Deformation in the Water Walls of an Opposed Firing Boiler under Variable Load Conditions","authors":"Lin Wei, Qulan Zhou, Zhuhan Liu, Na Li, Lian Li, Qinlan Luo","doi":"10.1061/(ASCE)EY.1943-7897.0000785","DOIUrl":"https://doi.org/10.1061/(ASCE)EY.1943-7897.0000785","url":null,"abstract":"AbstractTo study the operational problems of an opposed firing boiler in continuously changing working conditions, the temperature, strain, and thermal stress of water walls were measured to analyz...","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"15 1","pages":"04021040"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84461512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-01DOI: 10.1061/(ASCE)EY.1943-7897.0000787
T. Yalcinoz
AbstractRecently, light electric vehicles such as pedelecs, electric bicycles, and electric scooters have shown excellent potential for short distances. It is essential to control the power require...
{"title":"Hybrid System of Air-Breathing PEM Fuel Cells/Supercapacitors for Light Electric Vehicles: Modeling and Simulation","authors":"T. Yalcinoz","doi":"10.1061/(ASCE)EY.1943-7897.0000787","DOIUrl":"https://doi.org/10.1061/(ASCE)EY.1943-7897.0000787","url":null,"abstract":"AbstractRecently, light electric vehicles such as pedelecs, electric bicycles, and electric scooters have shown excellent potential for short distances. It is essential to control the power require...","PeriodicalId":15695,"journal":{"name":"Journal of Energy Engineering-asce","volume":"16 1","pages":"04021034"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81904724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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