As a pillar industry of national economy, China’s construction industry is still facing the status of substantial energy consumption and high CO2 emissions, which is a key field of energy conservation and emission reduction. In CO2 emissions research, it is essential to focus on analyzing the present and future trends of CO2 emissions in China’s construction industry. This article introduces a novel prediction model, in which the weighted algorithm is combined with Elman neural network (ENN) optimized by Adaptive Boosting algorithm (Adaboost) for evaluating future CO2 emissions in China’s construction industry. Firstly, logarithmic mean Divisia index (LMDI) is used to decompose CO2 emissions into economy, structural, intensity, and population indicators, posing as inputs to the weighted Adaboost-ENN model. Then, through comparison with other three models based on the data of total CO2 emissions in China’s construction industry during 2004-2016, there is evidence that the proposed model makes a favorable prediction performance. On this basis, we employ scenario analysis to predict future trend of CO2 emissions in China’s construction industry. It can be found that the peak of CO2 emissions in China’s construction industry will be achieved before 2030 in high carbon scenario (HS) and baseline carbon scenario (BS), whereas it will not be realized in low carbon scenario (LS). Finally, the specific policy recommendations related to energy conservation and emission reduction in China’s construction industry are proposed.
{"title":"Forecasting CO2 Emissions in China’s Construction Industry Based on the Weighted Adaboost-ENN Model and Scenario Analysis","authors":"Jianguo Zhou, Xiaolei Xu, Wei Li, Fengtao Guang, Xuechao Yu, Baoling Jin","doi":"10.1155/2019/8275491","DOIUrl":"https://doi.org/10.1155/2019/8275491","url":null,"abstract":"As a pillar industry of national economy, China’s construction industry is still facing the status of substantial energy consumption and high CO2 emissions, which is a key field of energy conservation and emission reduction. In CO2 emissions research, it is essential to focus on analyzing the present and future trends of CO2 emissions in China’s construction industry. This article introduces a novel prediction model, in which the weighted algorithm is combined with Elman neural network (ENN) optimized by Adaptive Boosting algorithm (Adaboost) for evaluating future CO2 emissions in China’s construction industry. Firstly, logarithmic mean Divisia index (LMDI) is used to decompose CO2 emissions into economy, structural, intensity, and population indicators, posing as inputs to the weighted Adaboost-ENN model. Then, through comparison with other three models based on the data of total CO2 emissions in China’s construction industry during 2004-2016, there is evidence that the proposed model makes a favorable prediction performance. On this basis, we employ scenario analysis to predict future trend of CO2 emissions in China’s construction industry. It can be found that the peak of CO2 emissions in China’s construction industry will be achieved before 2030 in high carbon scenario (HS) and baseline carbon scenario (BS), whereas it will not be realized in low carbon scenario (LS). Finally, the specific policy recommendations related to energy conservation and emission reduction in China’s construction industry are proposed.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87734449","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}
China has over the past thirty years experienced unprecedented economic growth averaging over 10% per year (“China GDP Annual Growth Rate ∣ 1989-2018 ∣ Data ∣ Chart ∣ Calendar” n.d.). For this reason, the relationship between China and Africa is often characterized as a case of China colonizing Africa to own natural resources and their associated infrastructure to feed its industrialization. Despite this postulation, Africa sees the cooperation as based on mutual interests in areas such as energy. The two regions could leverage their cooperation with the help of the international community to significantly advance access to electricity in Africa by improving energy efficiency, deploying cookstove programs to reduce health hazards and deaths from smoke inhalation, diversifying energy portfolio, and creating power pools that countries experiencing hiccups in their systems could tap into to meet their electricity needs. The two regions could also formulate energy policies to support these programs. Additionally, the energy infrastructure in Africa is still in infancy presenting an excellent opportunity to utilize emerging technologies and new power systems that are more efficient, resilient, and clean.
{"title":"China’s Contribution to the African Power Sector: Policy Implications for African Countries","authors":"Luka Powanga, Irene Giner-Reichl","doi":"10.1155/2019/7013594","DOIUrl":"https://doi.org/10.1155/2019/7013594","url":null,"abstract":"China has over the past thirty years experienced unprecedented economic growth averaging over 10% per year (“China GDP Annual Growth Rate ∣ 1989-2018 ∣ Data ∣ Chart ∣ Calendar” n.d.). For this reason, the relationship between China and Africa is often characterized as a case of China colonizing Africa to own natural resources and their associated infrastructure to feed its industrialization. Despite this postulation, Africa sees the cooperation as based on mutual interests in areas such as energy. The two regions could leverage their cooperation with the help of the international community to significantly advance access to electricity in Africa by improving energy efficiency, deploying cookstove programs to reduce health hazards and deaths from smoke inhalation, diversifying energy portfolio, and creating power pools that countries experiencing hiccups in their systems could tap into to meet their electricity needs. The two regions could also formulate energy policies to support these programs. Additionally, the energy infrastructure in Africa is still in infancy presenting an excellent opportunity to utilize emerging technologies and new power systems that are more efficient, resilient, and clean.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"113 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79573831","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}
Background. The demand for diesel fuel is constantly increasing, requiring its alternate that could be sustainable, technically feasible, price competitive, and ecologically acceptable. Biodiesel is one of ecologically acceptable substitute for the conventional fuels. Methods. Sufficient lime fleshing waste was collected from Addis Ababa tannery share company. The limed fleshing waste in the wet condition was delimed using boric acid, dried, chopped, and subjected to Soxhlet extraction using petroleum ether solvent. The oil was treated by orthophosphoric acid and distilled water to remove gums. The pretreated oil was subjected to homogeneous base catalyzed transesterification. Response surface was used to optimize the process variables. GC-MS was used to see composition of the biodiesel produced. Result. The oil yield of the goat, hide, and sheep delimed fleshing wastes were 23.08%, 12.05%, and 26.7%, respectively. The conversion to biodiesel by KOH-catalyzed transesterification was achieved above 96% under optimum conditions: a methanol-to-oil molar ratio of 6:1, catalyst amount of 1 % w/w, and reaction temperature of 60°C for an hour reaction time. Conclusion. It was proven that fleshing wastes from tanneries whose storage and disposal are both troublesome and costly could be transformed to a fuel with low emission values and a performance close to diesel fuel.
{"title":"Waste to Energy: Response Surface Methodology for Optimization of Biodiesel Production from Leather Fleshing Waste","authors":"H. Dagne, R. Karthikeyan, S. Feleke","doi":"10.1155/2019/7329269","DOIUrl":"https://doi.org/10.1155/2019/7329269","url":null,"abstract":"Background. The demand for diesel fuel is constantly increasing, requiring its alternate that could be sustainable, technically feasible, price competitive, and ecologically acceptable. Biodiesel is one of ecologically acceptable substitute for the conventional fuels. Methods. Sufficient lime fleshing waste was collected from Addis Ababa tannery share company. The limed fleshing waste in the wet condition was delimed using boric acid, dried, chopped, and subjected to Soxhlet extraction using petroleum ether solvent. The oil was treated by orthophosphoric acid and distilled water to remove gums. The pretreated oil was subjected to homogeneous base catalyzed transesterification. Response surface was used to optimize the process variables. GC-MS was used to see composition of the biodiesel produced. Result. The oil yield of the goat, hide, and sheep delimed fleshing wastes were 23.08%, 12.05%, and 26.7%, respectively. The conversion to biodiesel by KOH-catalyzed transesterification was achieved above 96% under optimum conditions: a methanol-to-oil molar ratio of 6:1, catalyst amount of 1 % w/w, and reaction temperature of 60°C for an hour reaction time. Conclusion. It was proven that fleshing wastes from tanneries whose storage and disposal are both troublesome and costly could be transformed to a fuel with low emission values and a performance close to diesel fuel.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"30 8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88715307","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}
Tapobrata Dey, Jaydeep Deshpande, D. Singdeo, P. Ghosh
A fuel cell stack is configured to power any load ranging from watts to megawatt by varying cells connected in series. During stack assembly, major emphasis must be placed on application of adequate external pressure for reducing the ohmic losses, the purpose of which is to achieve proper contact between the cell components and minimize the contact resistance. Present work aims to study the influence of geometry of the cell, bolt configuration, gasket thickness mismatch, and material properties of different components of average and distribution contact pressure. The geometries are evaluated for end plate designs with a view to understand the pressure distribution and contact resistance in each case. Among different designs, extruded hexagon is found to perform well with an average contact pressure of 0.13 MPa and contact resistance of 28 Ω-cm2. Greater gasket thickness requires higher forces to be applied before the GDL makes contact with BPP. The effect of gasket thickness mismatch is evaluated for different values to identify its appropriate value. The pressure is applied using bolts and position and number of bolts is determined for homogeneous contact pressure on the active area. This study provides a framework for future end plate design of fuel cells.
{"title":"Study of PEM Fuel Cell End Plate Design by Structural Analysis Based on Contact Pressure","authors":"Tapobrata Dey, Jaydeep Deshpande, D. Singdeo, P. Ghosh","doi":"10.1155/2019/3821082","DOIUrl":"https://doi.org/10.1155/2019/3821082","url":null,"abstract":"A fuel cell stack is configured to power any load ranging from watts to megawatt by varying cells connected in series. During stack assembly, major emphasis must be placed on application of adequate external pressure for reducing the ohmic losses, the purpose of which is to achieve proper contact between the cell components and minimize the contact resistance. Present work aims to study the influence of geometry of the cell, bolt configuration, gasket thickness mismatch, and material properties of different components of average and distribution contact pressure. The geometries are evaluated for end plate designs with a view to understand the pressure distribution and contact resistance in each case. Among different designs, extruded hexagon is found to perform well with an average contact pressure of 0.13 MPa and contact resistance of 28 Ω-cm2. Greater gasket thickness requires higher forces to be applied before the GDL makes contact with BPP. The effect of gasket thickness mismatch is evaluated for different values to identify its appropriate value. The pressure is applied using bolts and position and number of bolts is determined for homogeneous contact pressure on the active area. This study provides a framework for future end plate design of fuel cells.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84404098","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}
In this paper, we applied the Wavelet Transform Coherence (WTC) and phase analysis to analyze the relationship between the daily electricity demand (DED) and weather variables such as temperature, relative humidity, wind speed, and radiation. The DED data presents both seasonal fluctuations and increasing trend while the weather variables depict only seasonal variation. The results obtained from the WTC and phase analysis permit us to detect the period of time when the DED significantly correlates with the weather variables. We found a strong seasonal interdependence between the air temperature and DED for a periodicity of 256-512 days and 128-256 days. The relationship between the humidity and DED also shows a significant interdependence for a periodicity of 256-512 days with average coherence equal to 0.8. Regarding the radiation and wind speed, the correlation is low with average coherence less than 0.5. These results provide an insight into the properties of the impacts of weather variables on electricity demand on the basis of which power planners can rely to improve their forecasting and planning of electricity demand.
{"title":"Wavelet Analysis of Daily Energy Demand and Weather Variables","authors":"A. Bonkaney, I. Seidou Sanda, A. Balogun","doi":"10.1155/2019/4974107","DOIUrl":"https://doi.org/10.1155/2019/4974107","url":null,"abstract":"In this paper, we applied the Wavelet Transform Coherence (WTC) and phase analysis to analyze the relationship between the daily electricity demand (DED) and weather variables such as temperature, relative humidity, wind speed, and radiation. The DED data presents both seasonal fluctuations and increasing trend while the weather variables depict only seasonal variation. The results obtained from the WTC and phase analysis permit us to detect the period of time when the DED significantly correlates with the weather variables. We found a strong seasonal interdependence between the air temperature and DED for a periodicity of 256-512 days and 128-256 days. The relationship between the humidity and DED also shows a significant interdependence for a periodicity of 256-512 days with average coherence equal to 0.8. Regarding the radiation and wind speed, the correlation is low with average coherence less than 0.5. These results provide an insight into the properties of the impacts of weather variables on electricity demand on the basis of which power planners can rely to improve their forecasting and planning of electricity demand.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85673487","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}
Energy poverty affects physical health, well-being, and ability to prosper. A large proportion of Kenyan population lack access to electricity because they are located far from the national grid where it is uneconomical to extend electricity. This paper assesses energy poverty situation in Kirinyaga and reviews its implication on standard of living. Kirinyaga is a rural county with the main economic activity being agriculture and a few agroprocessing factories. Most rural households in Kirinyaga rely on fuel wood to meet their basic energy requirements and lack access to electricity. Tea factories and educational institutions rely on fuel wood to minimize cost of electricity. Kirinyaga residents, therefore, experience energy poverty as indicated by low electricity access and reliance on traditional cooking fuels. Energy poverty in Kirinyaga has negative impact on indicators of standards of living, calorific intake, life expectancy, and literacy levels.
{"title":"Energy Poverty and Its Implication on Standard of Living in Kirinyaga, Kenya","authors":"C. Njiru, S. Letema","doi":"10.1155/2018/3196567","DOIUrl":"https://doi.org/10.1155/2018/3196567","url":null,"abstract":"Energy poverty affects physical health, well-being, and ability to prosper. A large proportion of Kenyan population lack access to electricity because they are located far from the national grid where it is uneconomical to extend electricity. This paper assesses energy poverty situation in Kirinyaga and reviews its implication on standard of living. Kirinyaga is a rural county with the main economic activity being agriculture and a few agroprocessing factories. Most rural households in Kirinyaga rely on fuel wood to meet their basic energy requirements and lack access to electricity. Tea factories and educational institutions rely on fuel wood to minimize cost of electricity. Kirinyaga residents, therefore, experience energy poverty as indicated by low electricity access and reliance on traditional cooking fuels. Energy poverty in Kirinyaga has negative impact on indicators of standards of living, calorific intake, life expectancy, and literacy levels.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83381822","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}
{"title":"Corrigendum to “How Households Adopt Sustainable Innovations? A Free Decision Enforced by Others”","authors":"I. Kastner, Sebastian Bobeth","doi":"10.1155/2018/8501621","DOIUrl":"https://doi.org/10.1155/2018/8501621","url":null,"abstract":"","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"88 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84717530","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}
Nigeria has not been able to provide enough electric power to her about 200 million people. The last effort by the federal government to generate 6000 MW power by the end of 2009 failed. Even with the available less than 6000 MW of electricity generated in the country, only about 40% of the population have access to the electricity from the National Grid, out of which, urban centers have more than 80% accessibility while rural areas, which constitute about 70% of the total population, have less than 20% of accessibility to electricity. This paper addresses the possibility of meeting the energy demand in Nigeria through biomass gasification technology. The techno-economic analysis of biomass energy is demonstrated and the advantages of the biomass gasification technology are presented. Following the technical analysis, Nigeria is projected to have total potential of biomass of about 5.5 EJ in 2020 which has been forecast to increase to about 29.8 EJ by 2050. Based on a planned selling price of $0.727/kWh, the net present value of the project was found to be positive, the cost benefit ratio is greater than 1, and the payback period of the project is 10.14 years. These economic indicators established the economic viability of the project at the given cost. However, economic analysis shows a selling price of $0.727/kWh. Therefore, the capital investment cost, operation and maintenance cost, and fuel cost can be reduced through the development of the gasification system using local materials, purposeful and efficient plantation of biomass for the energy generation, giving out of financial incentives by the government to the investors, and locating the power plant very close to the source of feedstock generation.
{"title":"Techno-Economic Analysis of Biomass Energy Utilization through Gasification Technology for Sustainable Energy Production and Economic Development in Nigeria","authors":"G. Sobamowo, S. J. Ojolo","doi":"10.1155/2018/4860252","DOIUrl":"https://doi.org/10.1155/2018/4860252","url":null,"abstract":"Nigeria has not been able to provide enough electric power to her about 200 million people. The last effort by the federal government to generate 6000 MW power by the end of 2009 failed. Even with the available less than 6000 MW of electricity generated in the country, only about 40% of the population have access to the electricity from the National Grid, out of which, urban centers have more than 80% accessibility while rural areas, which constitute about 70% of the total population, have less than 20% of accessibility to electricity. This paper addresses the possibility of meeting the energy demand in Nigeria through biomass gasification technology. The techno-economic analysis of biomass energy is demonstrated and the advantages of the biomass gasification technology are presented. Following the technical analysis, Nigeria is projected to have total potential of biomass of about 5.5 EJ in 2020 which has been forecast to increase to about 29.8 EJ by 2050. Based on a planned selling price of $0.727/kWh, the net present value of the project was found to be positive, the cost benefit ratio is greater than 1, and the payback period of the project is 10.14 years. These economic indicators established the economic viability of the project at the given cost. However, economic analysis shows a selling price of $0.727/kWh. Therefore, the capital investment cost, operation and maintenance cost, and fuel cost can be reduced through the development of the gasification system using local materials, purposeful and efficient plantation of biomass for the energy generation, giving out of financial incentives by the government to the investors, and locating the power plant very close to the source of feedstock generation.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91062882","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 : 2018-10-12DOI: 10.20944/preprints201810.0256.v1
Laban N. Ongaki, C. Maghanga, J. Kerongo
Background. Global warming is a growing threat in the world today mainly due to the emission of CO2 caused by the burning of fossil fuel. Consequently, countries are being forced to seek potential alternative sources of energy such as wind, solar, and photovoltaic among many others. However, the realization of their benefits is faced with challenges. Though wind stands a chance to solve this problem, the lack of adequate site profiles, long-term behavioural information, and specific data information that enables informed choice on site selection, turbine selection, and expected power output has remained a challenge to its exploitation. In this research, Weibull and Rayleigh models are adopted. Wind speeds were analyzed and characterized in the short term and then simulated for a long-term measured hourly series data of daily wind speeds at a height of 10 m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent the mean wind speed, diurnal variations, daily variations, and monthly variations. To verify the models, statistical tools of Chi square, RMSE, MBE, and correlational coefficient were applied. Also, the method of measure, correlate, and predict was adopted to check for the reliability of the data used. The wind speed frequency distribution at the height of 10 m was found to be 2.9 ms-1 with a standard deviation of 1.5. From the six months’ experiments, averages of wind speeds at hub heights of 10 m were calculated and found to be 1.7 m/s, 2.4 m/s, and 1.3 m/s, for Ikobe, Kisii University, and Nyamecheo stations, respectively. The wind power density of the region was found to be 29 W/m2. By a narrow margin, Rayleigh proves to be a better method over Weibull in predicting wind power density in the region. Wind speeds at the site are noted to be decreasing over the years. The region is shown as marginal on extrapolation to 30 m for wind energy generation hence adequate for nongrid connected electrical and mechanical applications. The strong correlation between the site wind profiles proves data reliability. The gradual decrease of wind power over the years calls for attention.
{"title":"Evaluation of the Technical Wind Energy Potential of Kisii Region Based on the Weibull and Rayleigh Distribution Models","authors":"Laban N. Ongaki, C. Maghanga, J. Kerongo","doi":"10.20944/preprints201810.0256.v1","DOIUrl":"https://doi.org/10.20944/preprints201810.0256.v1","url":null,"abstract":"Background. Global warming is a growing threat in the world today mainly due to the emission of CO2 caused by the burning of fossil fuel. Consequently, countries are being forced to seek potential alternative sources of energy such as wind, solar, and photovoltaic among many others. However, the realization of their benefits is faced with challenges. Though wind stands a chance to solve this problem, the lack of adequate site profiles, long-term behavioural information, and specific data information that enables informed choice on site selection, turbine selection, and expected power output has remained a challenge to its exploitation. In this research, Weibull and Rayleigh models are adopted. Wind speeds were analyzed and characterized in the short term and then simulated for a long-term measured hourly series data of daily wind speeds at a height of 10 m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent the mean wind speed, diurnal variations, daily variations, and monthly variations. To verify the models, statistical tools of Chi square, RMSE, MBE, and correlational coefficient were applied. Also, the method of measure, correlate, and predict was adopted to check for the reliability of the data used. The wind speed frequency distribution at the height of 10 m was found to be 2.9 ms-1 with a standard deviation of 1.5. From the six months’ experiments, averages of wind speeds at hub heights of 10 m were calculated and found to be 1.7 m/s, 2.4 m/s, and 1.3 m/s, for Ikobe, Kisii University, and Nyamecheo stations, respectively. The wind power density of the region was found to be 29 W/m2. By a narrow margin, Rayleigh proves to be a better method over Weibull in predicting wind power density in the region. Wind speeds at the site are noted to be decreasing over the years. The region is shown as marginal on extrapolation to 30 m for wind energy generation hence adequate for nongrid connected electrical and mechanical applications. The strong correlation between the site wind profiles proves data reliability. The gradual decrease of wind power over the years calls for attention.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"128 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78843823","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}
Use of multilevel inverters with induction machines has become popular in most energy conversion and management systems. The present paper discusses the behavior of the dual stator-winding induction machine (DSIM) for the power source, which is a power supply with Neutral Point Clamped (NPC). Multilevel inverter with PWM technique control is analyzed. The DSIM control is obtained by the PWM technique to multicarrier PWM technique and after a comparative study of various characteristics of the DSIM taking into account the different electrical offsets between the two stars (0°, 30°, 60°). The gap between the two stars was considered, and it is impacted on torque and rates harmonic distortion of circulation currents.
{"title":"Behavior of a Dual Stator Induction Machine Fed by Neutral Point Clamped Multilevel Inverter","authors":"M. Khlifi","doi":"10.1155/2018/6968023","DOIUrl":"https://doi.org/10.1155/2018/6968023","url":null,"abstract":"Use of multilevel inverters with induction machines has become popular in most energy conversion and management systems. The present paper discusses the behavior of the dual stator-winding induction machine (DSIM) for the power source, which is a power supply with Neutral Point Clamped (NPC). Multilevel inverter with PWM technique control is analyzed. The DSIM control is obtained by the PWM technique to multicarrier PWM technique and after a comparative study of various characteristics of the DSIM taking into account the different electrical offsets between the two stars (0°, 30°, 60°). The gap between the two stars was considered, and it is impacted on torque and rates harmonic distortion of circulation currents.","PeriodicalId":30572,"journal":{"name":"Journal of Energy","volume":"124 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2018/6968023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72407798","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}