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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.
Danso, H.
3rd International Conference on Natural Fibers - Advanced Materials for a Greener World. Braga, Portugal June 21-23, 2017
Paper presented:
Properties of coconut, oil pa lm and bagasse fibres: As potential building materials
Abstract
The use of natural fibres in composite materials is attracting research interest worldwide due to the fibres ability to increase the strength, reduce environmental impact and reduce cost of the material. In this study the properties of coconut husk fibre, oil palm fruit fibre and sugarcane bagasse fibre have been investigated. Experiments on length and diameter, specific weight, tensile strength, modulus of elasticity, moisture content and water absorption tests on the fibres have been conducted to determine their properties for possible use as reinforcement in composite. It was found that different fibres have different properties and behave similarly in wet and damp conditions. The study concludes that all the fibres possess the properties that are acceptable as natural fibres to be used as reinforcement in soil blocks.
The use of natural fibres in composite materials is attracting research interest worldwide due to the fibres ability to increase the strength, reduce environmental impact and reduce cost of the material. In this study the properties of coconut husk fibre, oil palm fruit fibre and sugarcane bagasse fibre have been investigated. Experiments on length and diameter, specific weight, tensile strength, modulus of elasticity, moisture content and water absorption tests on the fibres have been conducted to determine their properties for possible use as reinforcement in composite. It was found that different fibres have different properties and behave similarly in wet and damp conditions. The study concludes that all the fibres possess the properties that are acceptable as natural fibres to be used as reinforcement in soil blocks.
Danso, H. (2016). Influence of Compacting Rate on the Properties of Compressed Earth Blocks. Advances in Materials Science and Engineering, 2016,
Abstract
Compaction of blocks contributes significantly to the strength properties of compressed earth blocks. This paper investigates the influence of compacting rates on the properties of compressed earth blocks. Experiments were conducted to determine the density, compressive strength, splitting tensile strength, and erosion properties of compressed earth blocks produced with different rates of compacting speed. The study concludes that although the low rate of compaction achieved slightly better performance characteristics, there is no statistically significant difference between the soil blocks produced with low compacting rate and high compacting rate. The study demonstrates that there is not much influence on the properties of compressed earth blocks produced with low and high compacting rates. It was further found that there are strong linear correlations between the compressive strength test and density, and density and the erosion. However, a weak linear correlation was found between tensile strength and compressive strength, and tensile strength and density.
Compaction of blocks contributes significantly to the strength properties of compressed earth blocks. This paper investigates the influence of compacting rates on the properties of compressed earth blocks. Experiments were conducted to determine the density, compressive strength, splitting tensile strength, and erosion properties of compressed earth blocks produced with different rates of compacting speed. The study concludes that although the low rate of compaction achieved slightly better performance characteristics, there is no statistically significant difference between the soil blocks produced with low compacting rate and high compacting rate. The study demonstrates that there is not much influence on the properties of compressed earth blocks produced with low and high compacting rates. It was further found that there are strong linear correlations between the compressive strength test and density, and density and the erosion. However, a weak linear correlation was found between tensile strength and compressive strength, and tensile strength and density.
Danso, H., Martinson, D. B., Ali, M. & Williams, J. B. (2017). Mechanisms by which the inclusion of natural fibres enhance the properties of soil blocks for construction. Journal of Composite Materials, ,
Abstract
Soil blocks are widely used for construction, especially in less economically developed countries. Addition of agricultural waste fibres has been shown to improve the properties of these blocks, however unlike most composites the fibres are not bound to the soil matrix. Therefore, the reinforcement mechanisms are different and not well characterised. This article investigates these mechanisms through a series of experimental studies to inform the development of better guidance for practitioners, and hence improve housing for low-income communities. The microstructural characteristics were investigated using scanning electron microscopy, computerised tomography scan, optical microscope analysis and pull out testing. It was established that fibres in the soil matrix are randomly distributed with gaps between the fibres and soil matrix due to fibre shrinkage during drying of the blocks. It also found that natural fibres in soil matrix can either be pulled-out or rupture under load depending on the depth of fibres embedment in the soil matrix.
Soil blocks are widely used for construction, especially in less economically developed countries. Addition of agricultural waste fibres has been shown to improve the properties of these blocks, however unlike most composites the fibres are not bound to the soil matrix. Therefore, the reinforcement mechanisms are different and not well characterised. This article investigates these mechanisms through a series of experimental studies to inform the development of better guidance for practitioners, and hence improve housing for low-income communities. The microstructural characteristics were investigated using scanning electron microscopy, computerised tomography scan, optical microscope analysis and pull out testing. It was established that fibres in the soil matrix are randomly distributed with gaps between the fibres and soil matrix due to fibre shrinkage during drying of the blocks. It also found that natural fibres in soil matrix can either be pulled-out or rupture under load depending on the depth of fibres embedment in the soil matrix.
Current Research in Combustion: A Forum for Young Researchers and Early Career Researchers*S.K. Amedorme*Lecturer*IOP Institute of Physics, Combustion Physics Group*Loughborough University, UK*9 September, 2015*9 September, 2015
