R&P Entries
Articles in Journals
Dotche, K. A., Banuenumah, W. & Ofosu, W. K. (2016). Non Regenerative Fiber Backbone Power Loss Budget,. Transactions on Networks and Communications,, 4,
Abstract
The most important stage in the design of a Wavelength Division Multiplexing (WDM) fiber optic system is about the choice of the correct optical transmitter, and receiver combination. This depends on the signal to be transmitted over the channel. By adopting the WDM two (2) signals at two (2) different wavelengths of 1310nm and 1550nm, can conveniently be carried on the same fiber. The WDM fiber link can carry 32,256 channels and the throughput too is high (>=2.5Gbps). Many television channels can be accommodated. The amplification along the fiber backhaul remains a bottleneck due to the non-linearity effects that could be additive. In order to minimize the non-linearity effect of the amplifiers, non-regenerative solutions are nowadays used. This paper develops a power loss budget for an optical sparse WDM long haul without inserting any regenerator along the transmission line. The study gives details of establishing a 200 km fiber optic link, operating at 2.5Gbps and supporting a digital signal of Synchronous Transport Signal-48/ Synchronous Transport Module 16 (STS-48/STM-16), where the link is assumed to carry 8 (WDM). In the dimensioning, the optical interfaces were chosen in agreement with the ITU-TG 654 applicable values. The system power deficit was not satisfactory in the first attempt, and so the Erbium Doped-Fiber Amplifiers (EDFAs) were inserted at the light source, and a preamplifier at the optical detector side. The system power deficit was still negative but not much. The transmitting system should have a positive value of the system power deficit so that the link budget can be suggested for the required transmission. Finally the change of the detector sensitivity gave the best estimation in the design process for the required link budget.
The most important stage in the design of a Wavelength Division Multiplexing (WDM) fiber optic system is about the choice of the correct optical transmitter, and receiver combination. This depends on the signal to be transmitted over the channel. By adopting the WDM two (2) signals at two (2) different wavelengths of 1310nm and 1550nm, can conveniently be carried on the same fiber. The WDM fiber link can carry 32,256 channels and the throughput too is high (>=2.5Gbps). Many television channels can be accommodated. The amplification along the fiber backhaul remains a bottleneck due to the non-linearity effects that could be additive. In order to minimize the non-linearity effect of the amplifiers, non-regenerative solutions are nowadays used. This paper develops a power loss budget for an optical sparse WDM long haul without inserting any regenerator along the transmission line. The study gives details of establishing a 200 km fiber optic link, operating at 2.5Gbps and supporting a digital signal of Synchronous Transport Signal-48/ Synchronous Transport Module 16 (STS-48/STM-16), where the link is assumed to carry 8 (WDM). In the dimensioning, the optical interfaces were chosen in agreement with the ITU-TG 654 applicable values. The system power deficit was not satisfactory in the first attempt, and so the Erbium Doped-Fiber Amplifiers (EDFAs) were inserted at the light source, and a preamplifier at the optical detector side. The system power deficit was still negative but not much. The transmitting system should have a positive value of the system power deficit so that the link budget can be suggested for the required transmission. Finally the change of the detector sensitivity gave the best estimation in the design process for the required link budget.
Awopone, A. K., Zobaa, A. F. & Banuenumah, W. (2017). Assessment of Optimal pathways for power generation system in Ghana.. Cogent Engineering, 4,
Abstract
This study applied the Open Source Energy Modelling System (OSeMOSYS), an optimisation model for long term energy planning, which is integrated in Long-range Energy Alternatives Planning (LEAP) to develop optimal generation pathways and dispatch scheduling of selected generating technologies for power generation in Ghana. Simulating conventional and non-conventional energy technologies, the study examines the technological, economic and environmental implications of renewable energy policies from 2010 to 2040. Sensitivity analyses were undertaken to determine the effect of varied development in non-conventional renewable energy technologies investment cost as well as fuel prices. The findings suggest that, with a comprehensive implementation of energy efficiency and other strategies, renewable energy technologies can contribute more than 70% of the generation requirement in Ghana by 2040. This will result in significant economic and environmental benefits as well as sustainability of the energy sector.
This study applied the Open Source Energy Modelling System (OSeMOSYS), an optimisation model for long term energy planning, which is integrated in Long-range Energy Alternatives Planning (LEAP) to develop optimal generation pathways and dispatch scheduling of selected generating technologies for power generation in Ghana. Simulating conventional and non-conventional energy technologies, the study examines the technological, economic and environmental implications of renewable energy policies from 2010 to 2040. Sensitivity analyses were undertaken to determine the effect of varied development in non-conventional renewable energy technologies investment cost as well as fuel prices. The findings suggest that, with a comprehensive implementation of energy efficiency and other strategies, renewable energy technologies can contribute more than 70% of the generation requirement in Ghana by 2040. This will result in significant economic and environmental benefits as well as sustainability of the energy sector.
Awopone, A. K. & Zobaa, A. F. (2017). Analyses of optimum generation scenarios for sustainable power generation in Ghana. AIMS Energy, 5,
Abstract
This study examines optimum generation scenarios for Ghana from 2010 to 2040. The Open Source Energy Modelling System (OSeMOSYS), an optimisation model for long term energy planning, which is integrated in Long-range Energy Alternatives Planning (LEAP) tool, was applied to model the generation system. The developed model was applied to the case study of the reference scenario (OPT) which examines the least cost development of the system without any shift in policy. Three groups of policy scenario were developed based on the future possible energy policy direction in Ghana: energy emission targets, carbon taxes and transmission and distribution losses improvements. The model was then used to simulate the development of technologies in each scenario up to 2040 and the level of renewable generation examined. Finally, cost benefit analysis of the policy scenarios, as well as their greenhouse gas mitigation potential were also discussed. The results show that: suitable policies for clean power generation have an important role in CO2 mitigation in Ghana. The introduction of carbon minimisation policies will also promote diversification of the generation mix with higher penetration of renewable energy technologies, thus reducing the overall fossil fuel generation in Ghana. It further indicated that, significant greenhouse emissions savings is achieved with improvement in transmission and distribution losses.
This study examines optimum generation scenarios for Ghana from 2010 to 2040. The Open Source Energy Modelling System (OSeMOSYS), an optimisation model for long term energy planning, which is integrated in Long-range Energy Alternatives Planning (LEAP) tool, was applied to model the generation system. The developed model was applied to the case study of the reference scenario (OPT) which examines the least cost development of the system without any shift in policy. Three groups of policy scenario were developed based on the future possible energy policy direction in Ghana: energy emission targets, carbon taxes and transmission and distribution losses improvements. The model was then used to simulate the development of technologies in each scenario up to 2040 and the level of renewable generation examined. Finally, cost benefit analysis of the policy scenarios, as well as their greenhouse gas mitigation potential were also discussed. The results show that: suitable policies for clean power generation have an important role in CO2 mitigation in Ghana. The introduction of carbon minimisation policies will also promote diversification of the generation mix with higher penetration of renewable energy technologies, thus reducing the overall fossil fuel generation in Ghana. It further indicated that, significant greenhouse emissions savings is achieved with improvement in transmission and distribution losses.
Awopone, A. K., Zobaa, A. F. & Banuenumah, W. (2017). Techno-economic and environmental analysis of power generation expansion plan of Ghana.. Energy Policy, 104,
Abstract
This paper examines the current electrical generation expansion plan of Ghana and compares it with proposed expansion pathways with higher penetration of Renewable Energy Technologies. An adaptation of Schwartz's Scenario Methodology was used to develop the scenarios which were then analysed using the Long-range Alternatives Planning (LEAP) model. Each of the scenarios represents policy options for generation expansion in Ghana up to 2040. Energy, economic and environmental analysis of the three alternative scenarios compared to the base scenarios was undertaken. Sensitivity results show that, if the country were to follow the generation expansion path described in the renewable energy scenarios, it could reap economic benefits of 0.5–13.23% depending on the developments in fuel prices and renewable technology capital cost. The analysis further quantifies benefits to be derived from a reduction in Greenhouse gases of the scenarios. Policy implications for the generation system of Ghana based on the results are also discussed
This paper examines the current electrical generation expansion plan of Ghana and compares it with proposed expansion pathways with higher penetration of Renewable Energy Technologies. An adaptation of Schwartz's Scenario Methodology was used to develop the scenarios which were then analysed using the Long-range Alternatives Planning (LEAP) model. Each of the scenarios represents policy options for generation expansion in Ghana up to 2040. Energy, economic and environmental analysis of the three alternative scenarios compared to the base scenarios was undertaken. Sensitivity results show that, if the country were to follow the generation expansion path described in the renewable energy scenarios, it could reap economic benefits of 0.5–13.23% depending on the developments in fuel prices and renewable technology capital cost. The analysis further quantifies benefits to be derived from a reduction in Greenhouse gases of the scenarios. Policy implications for the generation system of Ghana based on the results are also discussed
Dotche, K.A., Sekyere, F. and Banuenumah, W. (2016). LPC for Signal Analysis in Cellular Network Coverage.. Open Access Library Journal, 3,
Abstract
This paper introduces a novelty method of using a Linear Prediction Coefficient (LPC) filter, a digital signal processing (DSP) tool to get accurate signal measurement in noisy mobile environment. By measuring the received power of a mobile radio, it also measures the coverage of an area served by several base stations. For results’ validation, the mobile received power at user end of two Code Division Multiple Acccess-2000 (CDMA2000) cellular networks operating at different frequency (450 MHz and 800 MHz) in the same environment, Lome in Togo, was considered. Our analysis has consistently shown that within the problem areas in the coverage, the filter response does not match with the measured data. These mismatching areas may likely result from poor soft-handoff process or some dead zones. The study has proven the significant help of this novelty method in problem areas identification. Consequently, such a filter can be embedded to current firmware for Radio Frequency coverage optimization, and for an effective spectrum efficiency.
This paper introduces a novelty method of using a Linear Prediction Coefficient (LPC) filter, a digital signal processing (DSP) tool to get accurate signal measurement in noisy mobile environment. By measuring the received power of a mobile radio, it also measures the coverage of an area served by several base stations. For results’ validation, the mobile received power at user end of two Code Division Multiple Acccess-2000 (CDMA2000) cellular networks operating at different frequency (450 MHz and 800 MHz) in the same environment, Lome in Togo, was considered. Our analysis has consistently shown that within the problem areas in the coverage, the filter response does not match with the measured data. These mismatching areas may likely result from poor soft-handoff process or some dead zones. The study has proven the significant help of this novelty method in problem areas identification. Consequently, such a filter can be embedded to current firmware for Radio Frequency coverage optimization, and for an effective spectrum efficiency.
Banuenumah, W., Sekyere, F. & Donkor, E. (2016). Impact of Solar Photovoltaic as an Alternative Source of Power for Rural Electrication in Ghana.. International Journal of Scientific & Engineering Research, 7,
Abstract
The dynamics of solar photovoltaic (PV) technology’s impact as an alternative source of power for rural electrification has taken centre stage in recent years. Solar PV is seen as a panacea to the energy problems of rural populations in developing countries, aiming partly to address prevailing rampant poor energy levels in households. This study seeks to evaluate the social impact, examine the economic benefits and identify challenges; financial, technical and maintenance of solar PV systems in rural electrification. The study purposively sampled 200 solar PV household heads (120 from JICA PV and 80 from Government PV), in Pungu-Navorongo in the Kassena – Nankana District in the Upper East Region of Ghana, which has one of the lowest levels of electricity access and highest poverty levels among the inhabitants. The study reveals the dynamics of rural electrification and energy needs as well as the livelihood assets such as social, economic and technical aspects. It was found that, the overall impact of solar PV on the quality of life of the local beneficiaries was positively marginal. Challenges were identified, including limited wattage capacity, malfunction of some basic components, high cost of installation and low technical know-how. The findings further indicated that satisfaction derived from solar PV electricity supply among local households was high, social as well as economic impact were enhanced and justifies concessions on fee-for-service and government subsidy for the rural poor. For a decisive enhancement of rural livelihoods, it is strongly recommended that the PV systems be scaled up to include different energy dynamics such as cooking, irrigation, heating and to explore the extent to which technical know-how can affect utilization and sustainability of solar PV systems in rural electrification.
The dynamics of solar photovoltaic (PV) technology’s impact as an alternative source of power for rural electrification has taken centre stage in recent years. Solar PV is seen as a panacea to the energy problems of rural populations in developing countries, aiming partly to address prevailing rampant poor energy levels in households. This study seeks to evaluate the social impact, examine the economic benefits and identify challenges; financial, technical and maintenance of solar PV systems in rural electrification. The study purposively sampled 200 solar PV household heads (120 from JICA PV and 80 from Government PV), in Pungu-Navorongo in the Kassena – Nankana District in the Upper East Region of Ghana, which has one of the lowest levels of electricity access and highest poverty levels among the inhabitants. The study reveals the dynamics of rural electrification and energy needs as well as the livelihood assets such as social, economic and technical aspects. It was found that, the overall impact of solar PV on the quality of life of the local beneficiaries was positively marginal. Challenges were identified, including limited wattage capacity, malfunction of some basic components, high cost of installation and low technical know-how. The findings further indicated that satisfaction derived from solar PV electricity supply among local households was high, social as well as economic impact were enhanced and justifies concessions on fee-for-service and government subsidy for the rural poor. For a decisive enhancement of rural livelihoods, it is strongly recommended that the PV systems be scaled up to include different energy dynamics such as cooking, irrigation, heating and to explore the extent to which technical know-how can affect utilization and sustainability of solar PV systems in rural electrification.
Oduro, S.D., Metia, S., Duc, H., & Ha, Q.P. (2016). Inverse Air Pollution Emission and Prediction using Extended Fractional Kalman Filtering. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9,
Abstract
It is essential to maintain air-quality standards and to take necessary measures when air-pollutant concentrations exceed permissible limits. Pollutants such as ground-level ozone (O3), nitrogen oxides (NOX), and volatile organic compounds (VOCs) emitted from various sources can be estimated at a particular location through integration of observation data obtained from measurement sites and effective air-quality models, using emission inventory data as input. However, there are always uncertainties associated with the emission inventory data as well as uncertainties generated by a meteorological model. This paper addresses the problem of improving the inverse air pollution emission and prediction over the urban and suburban areas using the air-pollution model with chemical transport model (TAPM-CTM) coupled with the extended fractional Kalman filter (EFKF) based on a Matérn covariance function. Here, nitrogen oxide (NO), nitrogen dioxide (NO2), and O3 concentrations are predicted by TAPM-CTM in the airshed of Sydney and surrounding areas. For improvement of the emission inventory, and hence the airquality prediction, the fractional order of the EFKF is tuned using a genetic algorithm (GA). The proposed methodology is verified with measurements at monitoring stations and is then applied to obtain a better spatial distribution of O3 over the region.
It is essential to maintain air-quality standards and to take necessary measures when air-pollutant concentrations exceed permissible limits. Pollutants such as ground-level ozone (O3), nitrogen oxides (NOX), and volatile organic compounds (VOCs) emitted from various sources can be estimated at a particular location through integration of observation data obtained from measurement sites and effective air-quality models, using emission inventory data as input. However, there are always uncertainties associated with the emission inventory data as well as uncertainties generated by a meteorological model. This paper addresses the problem of improving the inverse air pollution emission and prediction over the urban and suburban areas using the air-pollution model with chemical transport model (TAPM-CTM) coupled with the extended fractional Kalman filter (EFKF) based on a Matérn covariance function. Here, nitrogen oxide (NO), nitrogen dioxide (NO2), and O3 concentrations are predicted by TAPM-CTM in the airshed of Sydney and surrounding areas. For improvement of the emission inventory, and hence the airquality prediction, the fractional order of the EFKF is tuned using a genetic algorithm (GA). The proposed methodology is verified with measurements at monitoring stations and is then applied to obtain a better spatial distribution of O3 over the region.
2. Oduro, S.D., Metia, S., Hong, H., Duc, H., & Ha, Q.P. (2015). Multivariate Adaptive Regression Splines Models for Vehicular Emission Prediction. Visualization in Engineering, 3,
Abstract
Background: Rate models for predicting vehicular emissions of nitrogen oxides (NOX ) are insensitive to the vehicle modes of operation, such as cruise, acceleration, deceleration and idle, because these models are usually based on the average trip speed. This study demonstrates the feasibility of using other variables such as vehicle speed, acceleration, load, power and ambient temperature to predict (NOX ) emissions to ensure that the emission inventory is accurate and hence the air quality modelling and management plans are designed and implemented appropriately. Methods: We propose to use the non-parametric Boosting-Multivariate Adaptive Regression Splines (B-MARS) algorithm to improve the accuracy of the Multivariate Adaptive Regression Splines (MARS) modelling to effectively predict NOX emissions of vehicles in accordance with on-board measurements and the chassis dynamometer testing. The B-MARS methodology is then applied to the NOX emission estimation. Results: The model approach provides more reliable results of the estimation and offers better predictions of NOX emissions. Conclusion: The results therefore suggest that the B-MARS methodology is a useful and fairly accurate tool for predicting NOX emissions and it may be adopted by regulatory agencies.
Background: Rate models for predicting vehicular emissions of nitrogen oxides (NOX ) are insensitive to the vehicle modes of operation, such as cruise, acceleration, deceleration and idle, because these models are usually based on the average trip speed. This study demonstrates the feasibility of using other variables such as vehicle speed, acceleration, load, power and ambient temperature to predict (NOX ) emissions to ensure that the emission inventory is accurate and hence the air quality modelling and management plans are designed and implemented appropriately. Methods: We propose to use the non-parametric Boosting-Multivariate Adaptive Regression Splines (B-MARS) algorithm to improve the accuracy of the Multivariate Adaptive Regression Splines (MARS) modelling to effectively predict NOX emissions of vehicles in accordance with on-board measurements and the chassis dynamometer testing. The B-MARS methodology is then applied to the NOX emission estimation. Results: The model approach provides more reliable results of the estimation and offers better predictions of NOX emissions. Conclusion: The results therefore suggest that the B-MARS methodology is a useful and fairly accurate tool for predicting NOX emissions and it may be adopted by regulatory agencies.
Oduro, S.D., Ha, Q.P. & Duc, H. (2016). Vehicular emissions prediction with CART-BMARS hybrid models. Elsevier Transportation Research Part D, 49,
Abstract
Vehicular emission models play a key role in the development of reliable air quality modeling systems. To minimize uncertainties associated with these models, it is essential to match the high-resolution requirements of emission models with up-to-date information. However, these models are usually based on average trip speed, not on environmental parameters like ambient temperature, and vehicle’s motion characteristics, such as speed, acceleration, load and power. This contributes to the degradation of its predictive performance. In this paper, we propose to use the non-parametric Classification and Regression Trees (CART), the Boosting Multivariate Adaptive Regression Splines (BMARS) algorithm and a combination of them in hybrid models to improve the accuracy of vehicular emission prediction using on-board measurements and the chassis dynamometer testing. The experimental comparison between the proposed CART-BMARS hybrid model with the BMARS and artificial neural networks (ANNs) algorithms demonstrates its effectiveness and efficiency in estimating vehicular emissions.
Vehicular emission models play a key role in the development of reliable air quality modeling systems. To minimize uncertainties associated with these models, it is essential to match the high-resolution requirements of emission models with up-to-date information. However, these models are usually based on average trip speed, not on environmental parameters like ambient temperature, and vehicle’s motion characteristics, such as speed, acceleration, load and power. This contributes to the degradation of its predictive performance. In this paper, we propose to use the non-parametric Classification and Regression Trees (CART), the Boosting Multivariate Adaptive Regression Splines (BMARS) algorithm and a combination of them in hybrid models to improve the accuracy of vehicular emission prediction using on-board measurements and the chassis dynamometer testing. The experimental comparison between the proposed CART-BMARS hybrid model with the BMARS and artificial neural networks (ANNs) algorithms demonstrates its effectiveness and efficiency in estimating vehicular emissions.
Cobbold, C., & Boateng, P. (2016). How Confident are Kindergarten Teachers in Their Ability to Keep Order in the Classroom? A Study of Teacher Efficacy in Classroom Management. Journal of Education and Practice, 7,
Abstract
The objective of the study was to investigate kindergarten teachers’ efficacy beliefs in classroom management. The sample size was 299 teachers drawn from both public and private kindergarten schools in the Kumasi Metropolis of Ghana. The efficacy beliefs of the teachers with respect to their classroom management practices were measured on a six-point Likert agreement survey questionnaire. Findings from the study indicated that kindergarten teachers in the study area had high efficacy beliefs in classroom management practices. No statistically significant difference was found in the efficacy beliefs in classroom management practices of trained and untrained kindergarten teachers, and of public and private kindergarten teachers. The study drew the conclusion that the professional status of the teachers (i.e. whether they were trained or untrained) and their institutional placement (i.e. whether they taught in a public or private school) were not important influential factors in the teachers’ efficacy beliefs in classroom management. Recommendations for early childhood teacher education programme and research are made.
The objective of the study was to investigate kindergarten teachers’ efficacy beliefs in classroom management. The sample size was 299 teachers drawn from both public and private kindergarten schools in the Kumasi Metropolis of Ghana. The efficacy beliefs of the teachers with respect to their classroom management practices were measured on a six-point Likert agreement survey questionnaire. Findings from the study indicated that kindergarten teachers in the study area had high efficacy beliefs in classroom management practices. No statistically significant difference was found in the efficacy beliefs in classroom management practices of trained and untrained kindergarten teachers, and of public and private kindergarten teachers. The study drew the conclusion that the professional status of the teachers (i.e. whether they were trained or untrained) and their institutional placement (i.e. whether they taught in a public or private school) were not important influential factors in the teachers’ efficacy beliefs in classroom management. Recommendations for early childhood teacher education programme and research are made.
