Browsing by Author "Attalage, R. A"

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Open Access
Achieving near-zero carbon dioxide emissions from energy use: The case of Sri Lanka
(Elsevier, 2023-07-04) Fernando, G.L; Liyanage, M.H; Anandarajah, G; Attalage, R. A; Karunaratne, S
Signatories to the Paris Agreement are to achieve net zero Green House Gas (GHG) emissions during the half-century to pursue the efforts limiting global average temperature increase by 2 °C compared to pre-industrial levels. This study models ambitious to challenging scenarios involving energy demand and supply side actions for energy system transition toward net-zero for Sri Lanka. To analyze these scenarios a least cost optimization-based bottom-up type energy system model was developed from 2015 to 2050. A Business-as-usual (BAU) scenario and four countermeasure (CM) scenarios termed Plausible, Ambitious, Challenging, and Stringent were developed. Four different carbon tax rates were used to fathom the level of carbon tax needed to achieve net-zero emissions. The CM scenarios were formulated considering different technology options and policy measures such as the diffusion of efficient technologies, availability of renewable energy sources, use of cleaner fuels, the introduction of nuclear and carbon capture and storage technologies, and green hydrogen for power generation. The result of this study reveals that the stringent scenario which includes aggressive policy measures in both the energy supply and demand sectors, such as nuclear, and renewable energy for power generation, diffusion of efficient Enduse devices, fuel switching, including the introduction of electric cars, and increased share for public transport achieves the near carbon-neutral scenario at a carbon tax trajectory of 32 US$/tCO2 in 2020 and 562US$/tCO2 in 2050. The Net Energy Import Dependency (NEID) of the country decreases to 13 % in 2050 compared to that of the BAU scenario (65 %) under the near carbon neutral scenario, which is a positive sign from the energy security perspective.
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Analysis of household cooking energy demand and its environmental impact in Sri Lanka
(Pergamon, 2002-11-01) Attalage, R. A; Wijayatunga, Priyantha DC
This paper presents the results and analysis of a study conducted with the objective of investigating the cooking energy requirements in the Sri Lanka domestic sector and the environmental emissions associated with it. The study was conducted out through a sample and showed that the main household energy supply sources were biomass, liquefied petroleum gas (LPG), electricity and kerosene with electricity being used largely for water boiling in all subsectors. It was observed that the urban sector cooking is largely dominated by LPG (95% of urban households) while the rural sector cooking is confined mainly to biomass (95% of rural households). The suburban sector consists of a mixture of all the sources (LPG-70% and biomass-85% of suburban households). Similarly, LPG dominates in electrified households (76.4% of electrified households), while biomass dominates in all non-electrified households. It was found in the analysis that the highest level of gaseous emissions due to cooking activity occurs in the rural areas, mainly due to the relatively large use of biomass, while the lowest level of emissions is recorded in a typical suburban household. Also, the analysis shows that fuel switching in domestic cooking activities from biomass to LPG and kerosene can be used as a measure to reduce emissions due to higher stove efficiencies and lower emission factors associated with these fuels. Substitution of 50% of biomass usage by kerosene in the rural households will result in 39–50% reduction in emissions within the rural sector. Further, substitution of 50% of biomass usage in urban and suburban sectors by LPG results in 4–49% reduction in emissions within these sectors.
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Analysis of rural household energy supplies in Sri Lanka: energy efficiency, fuel switching and barriers to expansion
(Pergamon, 2003-05-01) Attalage, R. A; Wijayatunga, Priyantha DC
A majority of the households in Sri Lanka, as in the case of many developing countries, is concentrated in the rural areas of the country. Unfortunately, very little attention has been paid until recently to analyse and address various issues associated with rural energy supplies, particularly those issues regarding barriers to penetration of clean and convenient sources of energy. This paper presents the results and analysis of a study conducted through a sample study on domestic energy supplies in rural Sri Lanka with emphasis on cooking and lighting energy requirements. The paper has attempted to highlight policy issues associated with rural energy supplies and possible solutions to them in the context of the country’s overall picture of the energy sector.
Open Access
Artificial intelligence based smart building automation controller for energy efficiency improvements in existing buildings
(2015-08-01) Basnayake, B. A. D.J.C.K; Amarasinghe, Y.W.R; Attalage, R. A; Udayanga, T.D.I; Jayasekara, A.G.B.P
This paper presents the design and implementation details of an Artificial Intelligent based smart building automation controller (AIBSBAC). It has the capability to perform intelligently adaptive to user preferences, which are focused on improved user comfort, safety and enhanced energy performance. The design of AIBSBAC consists of subsystems of smart user identification, internal and external environment observation subsystems, an artificial intelligent decision making subsystem and also a universal infrared communication system. Furthermore, the design architecture of AIBSBAC facilitates quick install flexible plug and play concept for most of the residential and buildings automation applications without a barrier to infrastructure modifications in installation.
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Co-production of fucoxanthin, docosahexaenoic acid (DHA) and bioethanol from the marine microalga Tisochrysis lutea
(Elsevier, 2021-12-01) Premaratne, M; Liyanaarachchi, V. C; Nimarshana, P. H. V; Ariyadasa, T. U; Malik, A; Attalage, R. A
The marine microalga Tisochrysis lutea is renowned for its ability to synthesize fucoxanthin and docosahexaenoic acid (DHA), which are nutritionally valuable high-value compounds. Although numerous studies in literature have assessed fucoxanthin and DHA production by T. lutea, very few studies have evaluated the feasibility of comprehensively utilizing biomass for co-production of these metabolites within the framework of biorefineries. To this end, the current study focused on the synthesis of fucoxanthin and DHA by cultivation of T. lutea under two different initial nitrate concentrations (1x: 882 µM, 3x: 2,646 µM) and three different light intensities (LL: 50 µmol/m2/s; ML: 100 µmol/m2/s; HL: 150 µmol/m2/s). The maximum fucoxanthin yield of 8.80 ± 0.30 mg/L (14.43 ± 0.52 mg/g) and DHA yield of 7.08 ± 0.02 mg/L (11.90 ± 0.14 mg/g) were achieved in the 3x HL culture at the end of 16 days of cultivation. Thereafter, a novel process of biphasic solvent extraction using ethanol/n-hexane/water (10:9:1 v/v/v) was utilized for co-extraction 97.96 ± 0.54% fucoxanthin and 74.11 ± 1.49% DHA from 3x HL biomass, and products were separated into two fractions. Fermentation of the residual biomass obtained from co-extraction resulted in a bioethanol yield of 48.49 ± 0.58 mg/g. Accordingly, the current study demonstrated the potential of T. lutea as a feedstock for biorefineries.
Open Access
Comparative assessment on the extraction of carotenoids from microalgal sources: Astaxanthin from H. pluvialis and β-carotene from D. salina
(Elsevier, 2019-03-20) Rammuni, M N; Ariyadasa, Thilini U; Nimarshana, P. H. V; Attalage, R. A
Astaxanthin and β-carotene are important carotenoids used in numerous pharmaceutical and nutraceutical applications, owing to their vigorous antioxidant properties. The microalgal strains Haematococcus pluvialis and Dunaliella salina accumulate the highest quantities of astaxanthin and β-carotene (up to 7% and 13% dry weight respectively) and are therefore considered as sustainable feedstock for the commercial production of carotenoids. Thus, from an economical perspective, it becomes desirable to optimize recovery of carotenoids from microalgal cells. To this end, here, we have summarized the conventional and modern extraction techniques generally used for the recovery of astaxanthin from Haematococcus pluvialis and β-carotene from Dunaliella salina. Furthermore, we have also discussed the optimum process conditions employed for numerous extraction protocols including solvent extraction, ultrasonic-assisted extraction (UAE), microwave-assisted extraction (MAE) and supercritical fluid extraction (SFE). Overall, our study highlights the sustainability of integrated co-production of biofuels and carotenoids in a biorefinery framework.
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Converting existing Internal Combustion Generator (ICG) systems into HESs in standalone applications
(Pergamon, 2013-10-01) Perera, A.T. D; Attalage, R. A; Perera, K.K.C.K; Dassanayake, V. P. C
Expanding existing Internal Combustion Generator (ICG) systems by combining renewable energy sources is getting popular due to global concern on emission of green house gases (GHG) and increasing fossil fuel costs. Life cycle cost, initial capital cost (ICC), power supply reliability of the system, and GHG emission by ICG are factors to be considered in this process. Pareto front of Levelized Energy Cost (LEC)–Unmet Load Fraction (ULF)–GHG emission was taken in this study for four different expansion scenarios. Furthermore, Pareto front of ICC–LE–ULF was taken for three different expansion scenarios in order to analyze the impact of renewable energy integration. The results clearly depict that characteristics of the Pareto front varies with the scale of expansion and objectives taken for the optimization. A detailed analysis was conducted for a scale up problem with a 4 kVA ICG by using the Pareto fronts obtained.
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Designing standalone hybrid energy systems minimizing initial investment, life cycle cost and pollutant emission
(Pergamon, 2013-06-01) Perera, A. T. D; Attalage, R. A; Perera, K. K. C. K; Dassanayake, V. P. C
HES (hybrid energy system)s are becoming energy systems of choice for standalone applications due to ever increasing fuel costs and global concern on GHG (Green House Gas) emissions. However, it is difficult to justify the higher ICC (Initial Capital Cost) of renewable energy components, especially for rural electrification projects in developing countries. This paper illustrates the modeling and simulation of HESs, and multi-objective optimization carried out in order to support decision-making in such instances. LEC (Levelized Energy Cost), ICC and GHG emission were taken as objective functions in the optimization and the sensitivity of market prices and power supply reliability was further evaluated. Results depict that Pareto front of LEC, ICC and GHG emission can be simplified as a combination of ICC–LEC and LEC–GHG emission Pareto fronts making the decision-making process simpler. Gradual integration of renewable energy sources in a number of design stages is proposed for instances where it is difficult to bear the higher ICC. Finally, importance of planning integration of renewable energy sources at early design stages of the project is highlighted in order to overcome the difficulties that need to be faced when coming up with the optimum design.
Open Access
Designing standalone hybrid energy systems minimizing initial investment, life cycle cost and pollutant emission
(Pergamon, 2013-06-01) Perera, A. T. D; Attalage, R. A; Perera, K. K. C. K; Dassanayake, V. P. C
HES (hybrid energy system)s are becoming energy systems of choice for standalone applications due to ever increasing fuel costs and global concern on GHG (Green House Gas) emissions. However, it is difficult to justify the higher ICC (Initial Capital Cost) of renewable energy components, especially for rural electrification projects in developing countries. This paper illustrates the modeling and simulation of HESs, and multi-objective optimization carried out in order to support decision-making in such instances. LEC (Levelized Energy Cost), ICC and GHG emission were taken as objective functions in the optimization and the sensitivity of market prices and power supply reliability was further evaluated. Results depict that Pareto front of LEC, ICC and GHG emission can be simplified as a combination of ICC–LEC and LEC–GHG emission Pareto fronts making the decision-making process simpler. Gradual integration of renewable energy sources in a number of design stages is proposed for instances where it is difficult to bear the higher ICC. Finally, importance of planning integration of renewable energy sources at early design stages of the project is highlighted in order to overcome the difficulties that need to be faced when coming up with the optimum design.
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Development of an artificial neural network model to simulate the growth of microalga Chlorella vulgaris incorporating the effect of micronutrients
(Elsevier, 2020-03-20) Liyanaarachchi, V. C; Nishshanka, G. K. S. H; Nimarshana, P. H.V; Ariyadasa, T. U; Attalage, R. A
Artificial neural network (ANN) models can be trained to simulate the dynamic behavior of biological systems. In the present study, an ANN model was developed upon multilayer perceptron neural network architecture with 23-20-1 configuration to predict the cell concentration of microalga Chlorella vulgaris at a given time. Irradiance level, photoperiod, temperature, air flow rate, CO2 percentage of the air stream, initial cell concentration, cultivation time and the nutrient concentrations of the media were considered as the input variables of the model. Resilient backpropagation learning algorithm was used to train the model by means of 484 experimental data belonging to four studies. Bias and accuracy factors of the developed model fall into the range of 0.95–1.11 indicating the model has an excellent prediction ability. Parity plot showed a good agreement between the predicted and experimental values with R2 = 0.98. Relative importance of the inputs was evaluated using Garson’s algorithm. The results of the study indicated that CO2 supply had the highest impact on the growth of C. vulgaris within the selected range of input parameters. Among macronutrients and micronutrients, highest influence was demonstrated by nitrogen and copper respectively.
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Development of multi-sensory feedback system for building automation systems
(IEEE, 2017-10) Basnayake, B. A. D. J. C. K; Amarasinghe, Y. W. R; Attalage, R. A; Jayasekara, A. G. B. P; Devinda, M. G. K
Under this research, the multi-sensory feedback system has been developed utilizing commercially available MEMS based and miniaturized sensors for building automation systems. This system consist of non-contact infrared thermal array sensor based occupancy identification / localization system and self-floor locations categorization system with an environmental monitoring system. Further, it has smart realtime energy monitoring system which capable to identify the load devices and their status while operation. The entire system is capable of obtaining quantitative values of this sensory information and applied for the development of more convenient and energy efficient automation in building premises. The implemented system was tested and validated using fuzzy logic based building automation controller via the wireless network.
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Economy wide emission impacts of carbon and energy tax in electricity supply industry: A case study on Sri Lanka
(Pergamon, 2007-07-01) Siriwardena, K; Wijayatunga, P. D.C; Fernando, W.J.L.S; Shrestha, R. M; Attalage, R. A
This paper presents the results and analysis of a study conducted with the objective of investigating the impact on economy wide emissions due to carbon and energy taxes levied within the electricity generation sector of Sri Lanka. This exercise is mainly based on the input–output table developed by the national planning department. An input–output decomposition technique is used to analyze four types of effects that contribute to the overall reduction in equivalent carbon, NOx and SO2 emissions. These four effects are: fuel mix effect (i.e. the change in emissions due to variation I fuel mix), structural effect (i.e. change in emissions due to changes in technological coefficients with taxes compared to that without taxes), final demand effect (i.e. the change in emissions associated with changes in final demand) and joint effect (i.e. the interactive effect between or among the fuel mix, structural and final demand effects). The polluting fuel sources and low energy efficiency generation technologies are less preferred under these tax regimes. Of the four effects, a change in fuel mix in thermal electricity generation and a change final demand for electricity were found to be the main contributors in achieving economy wide emission reductions. It was found in the analysis that a minimum of US$ 50/tC tax or US$ 1.0/MBtu of energy tax is required to have a significant impact on economy wide emissions in the Sri Lankan context. This translates into an overall increase in electricity generation cost of approximately USCts 0.9 kW−1 h−1 and USCts 0.6 kW−1 h−1 under the carbon and energy tax regimes, respectively. The reduction in emissions is also strongly coupled with the value of the price elasticity of electricity.
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A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems
(Elsevier, 2013-07-01) Amarasinghage, T; Perera, D; Attalage, R. A; Perera, K. K. C. K; Dassanayake, Vishwanath P C
Hybrid energy systems (HESs) are becoming popular for standalone applications due to global concern regarding green house gas (GHG) emissions and depletion of fossil fuel resources. Research in the optimal design of HESs is ongoing, with numerous optimization techniques giving special emphasis to Pareto optimization, incorporating conflicting objectives. The subsequent decision-making process including the non-dominant set of solutions has yet to be addressed. This work focuses on combining multi-objective optimization with a multi-criterion decision making (MCDM) technique to support decision makers in the process of designing HESs. Four different objectives, i.e., levelized energy cost (LEC), unmet load fraction, wasted renewable energy (WRE) and fuel consumption are used to obtain the Pareto front. A decision support tool based on Fuzzy TOPSIS and level diagrams is proposed to analyze the Pareto front and support the subsequent decision-making activity. A case study is used to illustrate the applicability of the proposed method. The study shows that the novel method is useful when determining the relative weights of objectives, providing a detailed picture of the objective space to the designer when coming up with the optimum system. The technique proposed in this study can be further extended to analyze similar problems in energy system design where MCDM is necessary after multi-objective optimization.
Open Access
A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems
(Elsevier, 2013-07-01) Amarasinghage, T; Perera, D; Attalage, R. A; Perera, K. K. C. K; Dassanayake, V. P. C
Hybrid energy systems (HESs) are becoming popular for standalone applications due to global concern regarding green house gas (GHG) emissions and depletion of fossil fuel resources. Research in the optimal design of HESs is ongoing, with numerous optimization techniques giving special emphasis to Pareto optimization, incorporating conflicting objectives. The subsequent decision-making process including the non-dominant set of solutions has yet to be addressed. This work focuses on combining multi-objective optimization with a multi-criterion decision making (MCDM) technique to support decision makers in the process of designing HESs. Four different objectives, i.e., levelized energy cost (LEC), unmet load fraction, wasted renewable energy (WRE) and fuel consumption are used to obtain the Pareto front. A decision support tool based on Fuzzy TOPSIS and level diagrams is proposed to analyze the Pareto front and support the subsequent decision-making activity. A case study is used to illustrate the applicability of the proposed method. The study shows that the novel method is useful when determining the relative weights of objectives, providing a detailed picture of the objective space to the designer when coming up with the optimum system. The technique proposed in this study can be further extended to analyze similar problems in energy system design where MCDM is necessary after multi-objective optimization.
Open Access
Making Realistic Predictions on Building Energy Performance through Coupled Energy Simulation and Computational Fluid Dynamics
(National Energy Symposium, 2015-11-20) Bandara, R. M. P. S; Attalage, R. A; Fernando, W. C. D. K
Buildings account for nearly 40% of the global energy consumption and hence presently high emphasize is made on improving the energy performance of buildings. Energy Simulation (ES) is the most widely used method in predicting the energy performance of buildings during the conceptual stage. However, it is observed that Energy Simulation tools show certain inherent deficiencies in predicting the energy performance of buildings. The said tools do not have the capacity to model air circulation through the building space explicitly. Energy Simulation tools mainly rely on the simplifying assumption that air within a thermal zone of a building is well-mixed. Furthermore, convective heat transfer coefficients of building surfaces are calculated using set empirical correlations. Hence, ES tools often find it difficult to make realistic predictions on energy performance of buildings. The literature also reveals that most Energy Simulation tools under-predict energy consumption in buildings, especially under sunny conditions. On the other hand, Computational Fluid Dynamics (CFD) tools are capable of predicting the indoor flow field comprehensively. However, CFD simulations need to be provided with the corresponding boundary conditions of the computational domain, which are readily available in the Energy Simulation approach. On this basis, the paper explains how Energy Simulation can be coupled with Computational Fluid Dynamics in predicting the energy performance of an actual building design more accurately through complementary data exchange between the tools. The analysis uses EnergyPlus 8.0 and Ansys Fluent 6.3 as the tools for conducting Energy Simulation and Computational Fluid Dynamics respectively. MATLAB R2012a establishes the coupling platform. The study shows that the coupled scheme predicts considerably higher energy consumption for the building design compared to that given by the conventional Energy Simulation using EnergyPlus.
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A model for analyzing the thermal performance of roof configurations with flat inclined surfaces
(Elsevier, 2016-03-15) Sirimanna, M. P. G; Attalage, R. A
The development of a thermal model, followed by a generalized computational tool that analyses thermal performance of roofs with four inclined surfaces and a ceiling by considering dynamic environmental and operating conditions, changes of roof geometry and materials is presented here. Roof elements are analyzed based on finite-volume method with implicit formulation. View factors of roof enclosures are calculated numerically. Experimental results, obtained for six actual building roofs under tropical climatic conditions of Sri Lanka, indicated that the thermal model is capable of replicating the actual temperature profiles with an average accuracy of 1.1 °C. Ceiling temperature of common roofs were found to be 10 °C above the ambient temperature, which could even rise up to15 °C in hot days. The model was successfully used to compare roofs and quantify the thermal effects of different parameters. For instance, changes in geometrical parameters led ceiling temperature to change by 5 °C, highlighting the importance of roof geometry. Out of the widely used three roofing materials in Sri Lanka, clay tile roofing has showed the best thermal performance. Compared to clay tiles, asbestos and steel roofing can have a maximum ceiling temperature rise of 4 °C and 6 °C, respectively.
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A multi criterion analysis for renewable energy integration process of a standalone hybrid energy system with internal combustion generator
(AIP Publishing LLC, 2015-07-18) Perera, A. T. D; Attalage, R. A; Perera, K.K.C.K; Madusanka, A. N
Integrating renewable energy into standalone Internal Combustion Generator (ICG) systems is an economical and eco-friendly option. However, previous studies demonstrate the difficulties in replacing the ICGs completely by using Solar PV (SPV) and wind energy with a dispatchable energy storage. This makes it interesting to analyze the limitations in integrating the SPV and wind energy into Hybrid Energy System. A multi criterion analysis is presented in this study, considering Levelized Energy Cost, Loss of Load Probability, and Fuel Consumption varying the scale of the ICG capacity to attain aforementioned objective. Changes in the system design with the integration of the SPV and wind energy were analyzed using Pareto multi-objective optimization considering Renewable Energy Capacity as an objective function. Sensitivity of the ICG capacity on optimum Renewable Energy Technology, role of the ICG in improving system reliability, etc., were subsequently analyzed. The results depict that the ICG capacity notably influence to the balance between wind and SPV capacity. An increase in the ICG capacity does increase the contribution from dispatchable energy source in most of the scenarios. Furthermore, it facilitates to amalgamate highly fluctuating renewable energy sources at a relatively low cost. This makes it inevitable to replace ICG with non-dispatchable renewable energy sources and energy storage
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Multi Objective Optimization of Lifecycle Cost, Unmet Load, and Renewable Energy Capacity for an Expansion of Existing Standalone Internal Combustion Generator (ICG) Systems
(Elsevier, 2011-01-01) Perera, A. T. D; Attalage, R. A
This paper presents, for the first time, the application of the strength Pareto evolutionary algorithm to the multi-objective design of isolated hybrid systems, minimising both the total cost throughout the useful life of the installation and the unmet load. For this task, a multi-objective evolutionary algorithm (MOEA) and a genetic algorithm (GA) have been used in order to find the best combinations of components for the hybrid system and control strategy. Also, a novel control strategy has been developed and it will be expounded in this article. As an example of application, a PV–wind–diesel system has been designed, obtaining a set of possible solutions (Pareto set) from which the designer can choose those which he/she prefers considering the costs and unmet load of each. The results obtained demonstrate the practical utility of the design method used.
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Occupancy identification based energy efficient Illuminance controller with improved visual comfort in buildings
(IEEE, 2017-05-29) Basnayake, B. A. D. J. C. K; Amarasinghe, Y. W. R; Attalage, R. A; Jayasekara, A. G. B. P
Under this research Smart energy efficient and visual comfort lighting system has been developed based on the presence of occupancy and occupancy localization information. The developed system consist of non-contact occupancy identification system, wireless sensor network, and wireless light intensity control device. The controller is constructed on a fuzzy logic based closed loop controller developed on a single board computer powered by 900MHz quad-core ARM Cortex-A7 CPU. Lighting is an important factor in maintaining the visual comfort in a living premise. According to literature, the lighting consumes about 40% of total electricity consumption in a building. Since lighting energy requirement contains a larger share of energy demand any saving from that demand will result in a reduction in areas of energy wastage, negative impact to the environment and the cost to the consumers and so on. The results of the experiment indicate that the improvement of visual comfort and enhanced energy performance by avoiding of unwanted visual comfort level in a living premise.
Open Access
Optimization Methodologies for Building Performance Modelling and Optimization
(FACULTY OF ENGINEERING, UNIVERSITY OF MORATUWA, 2013) Bandara, R. M. P. S; Attalage, R. A
Buildings account for approximately 40% of the global energy consumption and 36% of total carbon dioxide emissions. At present, high emphasis is given on the reduction of energy consumption and carbon footprint by optimizing the performance and resource utilization of buildings to achieve sustainable development. Building performance is analyzed in terms of energy performance, indoor environment for human comfort & health, environmental degradation and economic aspects. As for the energy performance analysis, this can be best modeled and optimized by a whole building energy simulation tool coupled with an appropriate optimization algorithm. Building performance optimization problems are inherently multivariate and multi-criteria. Optimization methodologies with different characteristics that are broadly classified as Adaptive, Non-adaptive and Pareto Algorithms can be applied in this regard. The paper discusses the applicability of the aforementioned optimization methodologies in building performance optimization for achieving realistic results.