Showing papers in "Energy in 2014"
TL;DR: In this article, the concept of 4th Generation District Heating (4GDH) was defined, including the relations to district cooling and the concepts of smart energy and smart thermal grids.
Abstract: This paper defines the concept of 4th Generation District Heating (4GDH) including the relations to District Cooling and the concepts of smart energy and smart thermal grids. The motive is to ident ...
TL;DR: In this paper, the authors provide a comprehensive and critical overview of the latest models and assessment techniques that are currently available to analyze MES and in particular DMG systems, including for instance energy hubs, microgrids, and VPPs (virtual power plants), as well as various approaches and criteria for energy, environmental, and technoeconomic assessment.
Abstract: MES (multi-energy systems) whereby electricity, heat, cooling, fuels, transport, and so on optimally interact with each other at various levels (for instance, within a district, city or region) represent an important opportunity to increase technical, economic and environmental performance relative to “classical” energy systems whose sectors are treated “separately” or “independently”. This performance improvement can take place at both the operational and the planning stage. While such systems and in particular systems with distributed generation of multiple energy vectors (DMG (distributed multi-generation)) can be a key option to decarbonize the energy sector, the approaches needed to model and relevant tools to analyze them are often of great complexity. Likewise, it is not straightforward to identify performance metrics that are capable to properly capture costs and benefits that are relating to various types of MES according to different criteria. The aim of this invited paper is thus to provide the reader with a comprehensive and critical overview of the latest models and assessment techniques that are currently available to analyze MES and in particular DMG systems, including for instance concepts such as energy hubs, microgrids, and VPPs (virtual power plants), as well as various approaches and criteria for energy, environmental, and techno-economic assessment.
TL;DR: In this article, a review of the application of the ASP flooding process in oil recovery in the petroleum industry and its limitations in maximizing oil recovery from onshore and offshore reservoirs is presented.
Abstract: Owing to the inefficiency of the conventional primary and secondary recovery methods to yield above 20–40% of the OOIP (original oil in place) as incremental oil, the need for EOR (Enhanced Oil Recovery) techniques to recover a higher proportion of the OOIP has become imperative. ASP (Alkaline/Surfactant/Polymer) is one of such techniques that has proven successful due to its ability to improve displacement and sweep efficiency. Alkaline–surfactant–polymer (ASP) flooding is a combination process in which alkali, surfactant and polymer are injected at the same slug. Because of the synergy of these three components, ASP is widely practiced in both pilot and field operations with the objective of achieving optimum chemistry at large injection volumes for minimum cost. Despite its popularity as a potentially cost-effective chemical flooding method, it is not without its limitations. This paper therefore focuses on the reviews of the application of ASP flooding process in oil recovery in the petroleum industry and its limitations in maximizing oil recovery from onshore and offshore reservoirs. Also discussed are technical solutions to some of these challenges.
TL;DR: In this article, the authors quantify the flexibility requirements at the operational timescale of 1-12 hours and different spatial scales across Europe and find that the flexibility requirement of a geographically large, transnational power system is significantly lower than of smaller regional systems, especially at high wind penetration.
Abstract: Flexibility is the ability of a power system to respond to changes in power demand and generation. Integrating large shares of variable renewable energy sources, in particular wind and solar, can lead to a strong increase of flexibility requirements for the complementary system, traditionally hydrothermal, which has to balance the fluctuations of variable generation. We quantify these flexibility requirements at the operational timescale of 1–12 hours and different spatial scales across Europe. Our results indicate that three major factors determine the ramping flexibility needed in future power systems: the penetration of variable renewables, their mix and the geographic system size. Compared to the variability of load, flexibility requirements increase strongly in systems with combined wind and PV (photovoltaics) contribution of more than 30% of total energy and a share of PV in the renewables mix above 20–30%. In terms of extreme ramps, the flexibility requirements of a geographically large, transnational power system are significantly lower than of smaller regional systems, especially at high wind penetration.
TL;DR: In this article, the causal links between CO2 (carbon dioxide) emissions, energy consumption, economic development and FDI (foreign direct investment) in six Sub Saharan African countries were investigated.
Abstract: This study investigates the causal links between CO2 (carbon dioxide) emissions, energy consumption, economic development and FDI (foreign direct investment) in six Sub Saharan African countries: the Republic of the Congo, the DRC (Democratic Republic of the Congo), Kenya, South Africa, Zambia and Zimbabwe The results based on an autoregressive distributed lag model imply that the variables move together in the long run (cointegration) in all of the countries The results also support the environmental Kuznets curve hypothesis in the cases of DRC, Kenya and Zimbabwe Moreover, FDI appears to increase CO2 emissions in some of the countries, while the opposite impact can be observed in others The most common unidirectional Granger causality relationships run from the other variables to CO2 emissions, with different variables Granger causing CO2 emissions in different countries, and from GDP (gross domestic product) to FDI Granger causality running to CO2 emissions appears more likely in the countries where the evidence supports the environmental Kuznets curve hypothesis Otherwise, the causality relationships vary greatly between the countries, making it impossible to give any universal policy recommendations
TL;DR: In this paper, the influence of an external magnetic field on ferrofluid flow and heat transfer in a semi annulus enclosure with sinusoidal hot wall is investigated and the governing equations which are derived by considering the both effects of FHD and MHD (Magnetohydrodynamic) are solved via CVFEM (Control Volume based Finite Element Method).
Abstract: In this paper, influence of an external magnetic field on ferrofluid flow and heat transfer in a semi annulus enclosure with sinusoidal hot wall is investigated. The governing equations which are derived by considering the both effects of FHD (Ferrohydrodynamic) and MHD (Magnetohydrodynamic) are solved via CVFEM (Control Volume based Finite Element Method). The effects of Rayleigh number, nanoparticle volume fraction, Magnetic number arising from FHD and Hartmann number arising from MHD on the flow and heat transfer characteristics have been examined. Results show that Nusselt number increases with augment of Rayleigh number and nanoparticle volume fraction but it decreases with increase of Hartmann number. Magnetic number has different effect on Nusselt number corresponding to Rayleigh number. Also it can be found that for low Rayleigh number, enhancement in heat transfer is an increasing function of Hartmann number and decreasing function of Magnetic number while opposite trend is observed for high Rayleigh number.
TL;DR: In this paper, the effects of using nanofluid as a coolant on the thermal and electrical efficiencies of a PV/T (photovoltaic thermal unit) are experimentally studied.
Abstract: In this research, the effects of using nanofluid as a coolant on the thermal and electrical efficiencies of a PV/T (photovoltaic thermal unit) are experimentally studied. Coolant fluids in the experiments are pure water and silica (SiO2)/water nanofluid 1% and 3% by weight (wt%). A brief uncertainty analysis is performed which shows that the measurements are sufficiently accurate. By converting the output electrical energy of the PV/T system into an equivalent thermal energy, it is found that the overall energy efficiency for the case with a silica/water nanofluid of 1 wt% is increased by 3.6% compared to the case with pure water. When using the silica/water nanofluid of 3 wt%, however, the increase is 7.9%. The thermal efficiency of the PV/T collector for the two cases of 1 wt% and 3 wt% of silica/water nanofluids are increased by 7.6% and 12.8%, respectively. The total exergy of the PV/T system, with and without nanofluids, is also compared with that of the PV system with no collector. It is observed that by adding a thermal collector to a PV system, the total exergy for the three cases with pure water, 1 wt% silica/water nanofluid, and 3 wt% silica/water nanofluid is increased by 19.36%, 22.61% and 24.31%, respectively.
TL;DR: In this paper, an assessment of the theoretical demand response potential in Europe is presented, with special attention given to temporal availability and geographic distribution of flexible loads, based on industrial production and electricity consumption statistics, as well as periodic and temperature-dependent load profiles.
Abstract: DR (Demand response) measures typically aim at an improved utilization of power plant and grid capacities. In energy systems mainly relying on photovoltaic and wind power, DR may furthermore contribute to system stability and increase the renewable energy share. In this paper, an assessment of the theoretical DR potential in Europe is presented. Special attention is given to temporal availability and geographic distribution of flexible loads. Based on industrial production and electricity consumption statistics, as well as periodic and temperature-dependent load profiles, possible load reduction and increase is estimated for each hour of the year. The analysis identifies substantial DR potentials in all consumer sectors. They add up to a minimum load reduction of 61 GW and a minimum load increase of 68 GW, available in every hour of the year. The overall potential features significant variations during the year, which are characteristic for specific consumers and countries.
TL;DR: In this paper, the authors present some applications and future expected development in the field of sub and supercritical fluids, and present a short overview of the current and future potential applications in this field.
Abstract: High pressure technologies involving sub and supercritical fluids offer the possibility to obtain new products with special characteristics or to design new processes, which are environmentally friendly and sustainable. By using high pressure as a processing tool one can also avoid the legal limitations for solvent residues and restrictions on use of conventional solvents in chemical processes. Supercritical fluids are already applied in several processes developed to commercial scale in pharmaceutical, food and textile industries. Extraction of valuable compounds from plant materials and their “in situ” formulation in products with specific properties is one of the very promising applications of high pressure technology. Particle formation using supercritical fluids may overcome the drawbacks of conventional particle size reduction processes. Because of their unique thermo-dynamic and fluid-dynamic properties, dense gases can also be used for impregnation of solid particles, particle coating, foaming etc. Some biochemical and chemical reactions performed in supercritical fluids have already been implemented at industrial scale to obtain products with high added value, while the use of supercritical fluids as heat carriers is a newly emerging field. In our short overview we present some applications and future expected development in the field of sub and supercritical fluids.
TL;DR: In this paper, the EKC hypothesis was investigated with regards to the relationship between carbon emissions, income and energy consumption in 16 EU (European Union) countries, and the results showed that the inverted U-shape relationship does not hold for carbon emissions in the 16 EU countries.
Abstract: Recently a great number of empirical research studies have been conducted on the relationship between certain indicators of environmental degradation and income. The EKC (Environmental Kuznets Curve) hypothesis has been tested for various types of environmental degradation. The EKC hypothesis states that the relationship between environmental degradation and income per capita takes the form of an inverted U shape. In this paper the EKC hypothesis was investigated with regards to the relationship between carbon emissions, income and energy consumption in 16 EU (European Union) countries. We conducted panel data analysis for the period of 1990–2008 by fixing the multicollinearity problem between the explanatory variables using their centered values. The main contribution of this paper is that the EKC hypothesis has been investigated by separating final energy consumption into renewable and fossil fuel energy consumption. Unfortunately, the inverted U-shape relationship (EKC) does not hold for carbon emissions in the 16 EU countries. The other important finding is that renewable energy consumption contributes around 1/2 less per unit of energy consumed than fossil energy consumption in terms of GHG (greenhouse gas) emissions in EU countries. This implies that a shift in energy consumption mix towards alternative renewable energy technologies might decrease the GHG emissions.
TL;DR: The ABC (artificial bee colony) algorithm is proposed, an evolutionary method inspired by the intelligent foraging behavior of honey bees, which exhibits a better search capacity to face multi-modal objective functions in comparison with other evolutionary algorithms.
Abstract: In order to improve the performance of solar energy systems, accurate modeling of current vs. voltage ( I – V ) characteristics of solar cells has attracted the attention of various researches. The main drawback in accurate modeling is the lack of information about the precise parameter values which indeed characterize the solar cell. Since such parameters cannot be extracted from the datasheet specifications, an optimization technique is necessary to adjust experimental data to the solar cell model. Considering the I – V characteristics of solar cells, the optimization task involves the solution of complex non-linear and multi-modal objective functions. Several optimization approaches have been proposed to identify the parameters of solar cells. However, most of them obtain sub-optimal solutions due to their premature convergence and their difficulty to overcome local minima in multi-modal problems. This paper proposes the use of the ABC (artificial bee colony) algorithm to accurately identify the solar cells' parameters. The ABC algorithm is an evolutionary method inspired by the intelligent foraging behavior of honey bees. In comparison with other evolutionary algorithms, ABC exhibits a better search capacity to face multi-modal objective functions. In order to illustrate the proficiency of the proposed approach, it is compared to other well-known optimization methods. Experimental results demonstrate the high performance of the proposed method in terms of robustness and accuracy.
TL;DR: In this article, the authors reviewed the selection, production and accumulation of target bioenergy carrier's strains and their advantages as well as the technological development for oil, biodiesel, ethanol, methanol, biogas production and GHG mitigation.
Abstract: The extensive use of fossil fuels is increasingly recognized as unsustainable as a consequence of depletion of supplies and the contribution of these fuels to climate change by GHG (greenhouse gas) emissions into the atmosphere. Microalgae indicate alternative renewable sustainable energy sources as they have a high potential for producing large amounts of biomass which in turn can be used for production of different third-generation biofuels at large scale. Microalgae transform the solar energy into the carbon storage products, leads to lipid accumulation, including TAG (triacylglycerols), which then can be transformed into biodiesel, bioethanol and biomethanol. This paper reviews the selection, production and accumulation of target bioenergy carrier's strains and their advantages as well as the technological development for oil, biodiesel, ethanol, methanol, biogas production and GHG mitigation. The feedstock of promising algal strain exhibits the suitable biofuel production. The current progress of hybrid-technologies (biomass production, wastewater treatment, GHG mitigation) for production of prime-products as biofuels offer atmospheric pollution control such as the reduction of GHG (CO2 fixation) coupling wastewater treatment with microalgae growth. The selection of efficient strain, microbial metabolism, cultivation systems, biomass production are key parameters of viable technology for microalgae-based biodiesel-production.
TL;DR: In this paper, the AHP and ANP are applied to help the managing board of an important Spanish solar power investment company to decide whether to invest in a particular solar-thermal power plant project and, if so, to determine the order of priority of the projects in the company's portfolio.
Abstract: In this paper the AHP (Analytic Hierarchy Process) and the ANP (Analytic Network Process) are applied to help the managing board of an important Spanish solar power investment company to decide whether to invest in a particular solar-thermal power plant project and, if so, to determine the order of priority of the projects in the company's portfolio. Project management goes through a long process, from obtaining the required construction permits and authorizations, negotiating with different stakeholders, complying with complex legal regulations, to solving the technical problems associated with plant construction and distribution of the energy generated. The whole process involves high engineering costs. The decision approach proposed in this paper consists of three phases. In the first two phases, the managing board must decide whether to accept or reject a project according to a set of criteria previously identified by the technical team. The third phase consists of establishing a priority order among the projects that have proven to be economically profitable based on project risk levels and execution time delays. This work analyzes the criteria that should be taken into account to accept or reject proposals for investment, as well as the risks used to prioritize some projects over others.
TL;DR: In this paper, a global panel consisting of 64 countries over the period 1990-2011 by using a dynamic system-GMM panel model was used to investigate the determinants of renewable energy consumption.
Abstract: Over recent years, renewable energy sources have emerged as an important component of world energy consumption. Little is however known about the determinants of renewable energy consumption. This article tackles this issue for a global panel consisting of 64 countries over the period 1990–2011 by using a dynamic system-GMM panel model. We also consider three homogenous subpanels which are constructed based on the income level of sample countries (high-, middle-, and low-income subpanels). We mainly find that the increases in CO2 emissions and trade openness are the major drivers of renewable energy consumption. Oil price increases have a smaller but negative impact on renewable energy consumption in the middle-income and global panels. Policy implications of our results are also discussed.
TL;DR: In this article, the influence of properties of various common bio-fuels on the combustion, performance and exhaust emissions of an experimental, single-cylinder, four-stroke, high-speed, DI (direct injection) ‘Hydra’ diesel engine operated at three different loads was evaluated.
Abstract: This work evaluates the influence of properties of various common bio-fuels on the combustion, performance and exhaust emissions of an experimental, single-cylinder, four-stroke, high-speed, DI (direct injection) ‘Hydra’ diesel engine operated at three different loads. Various blends of diesel fuel with either vegetable oil of cottonseed or its derived (methyl ester) bio-diesel, or ethanol, or n -butanol, or diethyl ether were investigated. Fuel consumption, exhaust gas temperature, and exhaust smoke, NO x (nitrogen oxides), CO (carbon monoxide) and total unburned HC (hydrocarbons) were measured. The differences in combustion, performance and exhaust emissions of those bio-fuels blends from the baseline operation of the diesel engine (with neat diesel fuel) and among themselves are compared. Fuel injection, combustion chamber pressure, and HRR (heat release rate) diagrams reveal interesting features of the combustion mechanisms. These results and the different physical and chemical properties of those bio-fuels are used to aid the interpretation of the observed engine behavior. With increasing percentage of all bio-fuels in the blends, significant reduction of smoke opacity is observed with the exception of the vegetable oil case, reduction of NO x , and mixed behavior for the CO and HC emissions against the corresponding neat diesel fuel case.
TL;DR: In this paper, the potential of ORC (Organic Rankine Cycles) for the exploitation of low-medium enthalpy geothermal brines is investigated. And an economic model was defined and implemented in the Matlab® code previously developed.
Abstract: This two-part paper investigates the potential of ORC (Organic Rankine Cycles) for the exploitation of low-medium enthalpy geothermal brines. Part A deals with thermodynamic analysis and optimization, while Part B focuses on economic optimization. In this part, an economic model was defined and implemented in the Matlab® code previously developed. A routine was also implemented to estimate the design of the turbine (number of stages, rotational speed, mean diameter), allowing to estimate turbine efficiency and cost. The tool developed allowed performing an extensive techno-economic analysis of many cycles exploiting geothermal brines with temperatures between 120 °C and 180 °C. By means of an optimization routine, the cycles and the fluids leading to the minimum cost of the electricity are found for each geothermal source considered. Cycle parameters found from the techno-economic optimization are compared with those assumed and found from the thermodynamic optimization. Quite relevant differences show the necessity to perform optimization on the basis of specific plant cost. As a general trend, it is however confirmed that configurations based on supercritical cycles, employing fluids with a critical temperature slightly lower than the temperature of the geothermal source, lead to the lowest electricity cost for most of the investigated cases.
TL;DR: In this article, a guided tour on NZEB evaluation through literature-research is presented, which includes an overview about definitions and energy-efficient measures of NZEBs, and a summary of widely-used research method, tool and performance indicator in evaluation.
Abstract: NZEB (Net zero energy building) is regarded as an integrated solution to address problems of energy-saving, environmental protection, and CO2 emission reduction in the building section. NZEB could be even possible with electricity production if enough renewable energy could be used. Moreover, various building-service systems with renewable energy sources have been widely considered for potential applications in NZEB. All of these new features extend the technical boundary of the conventional energy-efficient buildings, attach a more profound implication to the sustainable development of building technology, and therefore pose a challenge to evaluation works on NZEB performance. This paper presents a guided tour on NZEB evaluation through literature-research. An overview about definitions and energy-efficient measures of NZEB is presented so that the research object and technology boundary can be clarified for NZEB evaluation. Then, a summary of widely-used research method, tool and performance indicator in evaluation is provided for the methodology part. This part also includes a discussion on the application of LCA (life cycle assessment) in NZEB evaluation and LCA's role in promoting a well-defined NZEB. Finally, potential progress in NZEB evaluation with possible development trends is highlighted in terms of energy storage, load match and smart grid.
TL;DR: In this paper, the authors presented an economy-energy-environment model based on system dynamics which integrates all those aspects: the physical restrictions (with peak estimations for oil, gas, coal and uranium), the techno-sustainable potential of renewable energy estimated by a novel top-down methodology, the socio-economic energy demands, the development of alternative technologies and the net CO 2 emissions.
Abstract: The progressive reduction of high-quality-easy-to-extract energy is a widely recognized and already ongoing process. Although depletion studies for individual fuels are relatively abundant, few of them offer a global perspective of all energy sources and their potential future developments, and even fewer include the demand of the socio-economic system. This paper presents an Economy-Energy-Environment model based on System Dynamics which integrates all those aspects: the physical restrictions (with peak estimations for oil, gas, coal and uranium), the techno-sustainable potential of renewable energy estimated by a novel top-down methodology, the socio-economic energy demands, the development of alternative technologies and the net CO 2 emissions. We confront our model with the basic assumptions of previous Global Environmental Assessment (GEA) studies. The results show that demand-driven evolution, as performed in the past, might be unfeasible: strong energy-supply scarcity is found in the next two decades, especially in the transportation sector before 2020. Electricity generation is unable to fulfill its demand in 2025–2040, and a large expansion of electric renewable energies move us close to their limits. In order to find achievable scenarios, we are obliged to set hypotheses which are hardly used in GEA scenarios, such as zero or negative economic growth.
TL;DR: In this article, the authors examined the empirical relationship between economic growth, energy consumption and carbon dioxide emissions, calculated the trend of decoupling effects and analyzed the evolution of inequality in CO2 emissions in GCC (Gulf Cooperation Council countries) countries.
Abstract: This study examines the empirical relationship between economic growth, energy consumption and carbon dioxide emissions, calculates the trend of decoupling effects and finally analyzes the evolution of inequality in CO2 emissions in GCC (Gulf Cooperation Council countries) countries. Results indicate a positive and significant association between energy consumption and CO2 emissions and between economic growth and energy consumption both in the short- and the long-run. No significant relationship is found between economic growth and CO2 emissions. Energy consumption and CO2 emissions Granger cause each other while unidirectional causal link running from economic growth to energy consumption is also found to exist. Both absolute and relative decoupling occurred in all the GCC countries except Saudi Arabia during the study period. Divergences in the Gini index values contributed towards different levels of emissions inequality in the region. CO2 emissions inequality significantly declined both in energy carriers as well as in the economic sectors over time. Despite some optimistic findings, the GCC countries are still significant contributors to CO2 emissions and as such, the study recommends pursuing favorable regulatory policies that would promote various initiatives to reduce emissions. The overall findings will help GCC countries assess its position better in future climate change negotiations.
TL;DR: The effectiveness of the proposed method is presented in terms of reduction in power system losses, maximization of system loadability and voltage quality improvement and HPSO (hybrid particle swarm optimization) algorithm is proposed in this paper.
Abstract: This paper presents a new approach for optimum simultaneous multi-DG (distributed generation) placement and sizing based on maximization of system loadability without violating the system constraints. DG penetration level, line limit and voltage magnitudes are considered as system constraints. HPSO (hybrid particle swarm optimization) algorithm is also proposed in this paper to find the optimum solution considering maximization of system loadability and the corresponding minimum power losses. The proposed method is tested on standard 16-bus, 33-bus and 69-bus radial distribution test systems. This paper will also compare the proposed method with existing Ettehadi method and present the effectiveness of the proposed method in terms of reduction in power system losses, maximization of system loadability and voltage quality improvement.
TL;DR: In this article, the engine performance and emissions testing was conducted using biodiesel blends 10%, 20%, 30%, 30% and 50% in a diesel engine at full throttle load.
Abstract: Biodiesel is a recognized replacement for diesel fuel in compressed ignition engines due to its significant environmental benefits. The purpose of this study is to investigate the engine performance and emis- sions produced from Jatropha curcas, Ceiba pentandra and Calophyllum inophyllum biodiesel in com- pressed ignition engine. The biodiesel production process and properties are discussed and a comparison of the three biodiesels as well as diesel fuel is undertaken. After that, engine performance and emissions testing was conducted using biodiesel blends 10%, 20%, 30% and 50% in a diesel engine at full throttle load. The engine performance shows that those biodiesel blends are suitable for use in diesel engines. A 10% biodiesel blend shows the best engine performance in terms of engine torque, engine power, fuel consumption and brake thermal efficiency among the all blending ratios for the three biodiesel blends. Biodiesel blends have also shown a significant reduction in CO 2, CO and smoke opacity with a slight increase in NOx emissions.
TL;DR: A system that uses supervised machine learning techniques to automatically estimate specific “characteristics” of a household from its electricity consumption, which paves the way for targeted energy efficiency programs and other services that benefit from improved customer insights is developed.
Abstract: Utilities are currently deploying smart electricity meters in millions of households worldwide to collect fine-grained electricity consumption data. We present an approach to automatically analyzing this data to enable personalized and scalable energy efficiency programs for private households. In particular, we develop and evaluate a system that uses supervised machine learning techniques to automatically estimate specific “characteristics” of a household from its electricity consumption. The characteristics are related to a household's socio-economic status, its dwelling, or its appliance stock. We evaluate our approach by analyzing smart meter data collected from 4232 households in Ireland at a 30-min granularity over a period of 1.5 years. Our analysis shows that revealing characteristics from smart meter data is feasible, as our method achieves an accuracy of more than 70% over all households for many of the characteristics and even exceeds 80% for some of the characteristics. The findings are applicable to all smart metering systems without making changes to the measurement infrastructure. The inferred knowledge paves the way for targeted energy efficiency programs and other services that benefit from improved customer insights. On the basis of these promising results, the paper discusses the potential for utilities as well as policy and privacy implications.
TL;DR: In this article, a modified GA (genetic algorithm) was proposed to increase the energy harvesting capability of the photovoltaic system by embedding a simple MPPT algorithm (P&O) inside the structure of the GA, thus finding the maximum power point in a shorter time.
Abstract: This article presents a novel MPPT (maximum power point tracking) algorithm, based on a modified GA (genetic algorithm). When photovoltaic systems are affected by partial shading, a GMPPT (global maximum power point tracking) algorithm is required to increase the energy harvesting capability of the system. A new GMPPT algorithm is proposed in this article: a P&O (perturb and observe) algorithm is integrated inside the GA function and creates a single algorithm. By embedding a simple MPPT algorithm (P&O) inside the structure of the GA, the population size and the number of iterations are decreased, thus finding the MPP (maximum power point) in a shorter time. The algorithm parameters (population size, number of genes, and number of iterations) are optimized and the final solution is provided. A macromodel is used to average the real DC–DC converter and reduce the computation burden of the simulator, thus reducing the simulation time. The control part and the GMPPT algorithm were implemented on a DSP (digital signal processor) and tested on an experimental small scale photovoltaic system. A description of this algorithm and its performances are detailed in this article, verified through simulation and experimental results.
TL;DR: In this paper, the authors used Grey Modeling (1,1) to forecast the total electric energy demand of Turkey for the 2013-2025 period by using an optimized grey modeling (1-1) forecasting technique, which is implemented both in direct and iterative manners.
Abstract: Energy demand forecasting is an important issue for governments, energy sector investors and other related corporations. Although there are several forecasting techniques, selection of the most appropriate technique is of vital importance. One of the forecasting techniques which has proved successful in prediction is Grey Modeling (1,1). Grey Modeling (1,1) does not need any prior knowledge and it can be used when the amount of input data is limited. However, the basic form of Grey Modeling (1,1) still needs to be improved to obtain better forecasts. In this study, total electric energy demand of Turkey is predicted for the 2013–2025 period by using an optimized Grey Modeling (1,1) forecasting technique called Optimized Grey Modeling (1,1). The Optimized Grey Modeling (1,1) technique is implemented both in direct and iterative manners. The results show the superiority of Optimized Grey Modeling (1,1) when compared with the results from literature. Another finding of the study is that the direct forecasting approach results in better predictions than the iterative forecasting approach in forecasting Turkey's electricity consumption. The supply values of primary energy resources in order to produce electricity have calculated for 2015, 2020 and 2025 by using the outputs of Optimized Grey Modeling (1,1).
TL;DR: In this paper, the authors explored the bi-directional long-run relationship between energy consumption in the road transport sector with CO2 emissions and economic growth in OECD countries using time series data from 1960 to 2008.
Abstract: This paper explores the bi-directional long-run relationship between energy consumption in the road transport sector with CO2 emissions and economic growth in OECD countries. Using time series data from 1960 to 2008 and employing the Fully Modified Ordinary Least Squares cointegration approach, the paper shows positive significant long-run bi-directional relationship between CO2 emissions and economic growth, road sector energy consumption and economic growth and CO2 emissions and road sector energy consumption in all the OECD countries. To examine the response of each of the variables to shocks in the value of other variables, the generalized impulse response approach is employed. The response of CO2 emissions to economic growth is initially positive in most cases but it is relatively shorter when compared to its initial response to the road transport sector energy consumption. Moreover, in most cases, the response of carbon emissions to the road transport sector energy consumption lasts longer than its response to economic growth. This implies that most of the CO2 emissions from transport come from energy consumption, thus long-run policies related to the efficient use of energy and shifting to biofuel, renewable and nuclear energy can bring major benefits in mitigating GHG (Greenhouse Gas) emissions.
TL;DR: In this article, a conceptual definition of social acceptance for renewable energy systems is proposed, which is both explicit and allows for quantitative assessment, and this definition will aid future literature by clearly defining the goal of Social acceptance research from the outset.
Abstract: One of the key issues in adopting a sustainable and renewable energy system is gaining social acceptance for technological change. Many technological changes can adversely affect residents and lead to opposition. Extensive development of electricity infrastructure has been met with especially strong resistance from local stakeholders. An abundance of research has been conducted to study the process and driving factors of social acceptance in the context of these infrastructural developments. This paper develops a conceptual definition of social acceptance that is both explicit and allows for quantitative assessment. This definition will aid future literature by clearly defining the goal of social acceptance research from the outset. As examples of the problems faced in electricity system change, factors of discontent surrounding the social acceptance of wind farms, transmission lines, and pump hydro-storage facilities are identified and synthesized. Policy relevant conclusions from previous research are summarized for these three infrastructure types. It is concluded that while research has done well in understanding the causes of opposition, more work is needed to grasp the efficacy and implementation of acceptance improving strategies. Future research should be focused on devising procedures to facilitate quick and efficient negotiations between infrastructure developers and local groups.
TL;DR: In this article, a detailed optimization model for planning the short-term operation of combined cooling, heat and power (CCHP) energy systems is presented, which considers the simultaneous use of different prime movers (generating electricity and heat), boilers, compression heat pumps and chillers, and absorption chillers.
Abstract: A detailed optimization model is presented for planning the short-term operation of combined cooling, heat and power (CCHP) energy systems. The purpose is, given the design of a cogeneration system, to determine an operating schedule that minimizes the total operating and maintenance costs minus the revenue due to the electricity sold to the grid, while taking into account time-varying loads, tariffs and ambient conditions. The model considers the simultaneous use of different prime movers (generating electricity and heat), boilers, compression heat pumps and chillers, and absorption chillers to satisfy given electricity, heat and cooling demands. Heat and cooling load can be stored in storage tanks. Units can have one or two operative variables, highly nonlinear performance curves describing their off-design behavior, and limitations or penalizations affecting their start-up/shut-down operations. To exploit the effectiveness of state-of-the-art Mixed Integer Linear Program (MILP) solvers, the resulting Mixed Integer Nonlinear Programming (MINLP) model is converted into a MILP by appropriate piecewise linear approximation of the nonlinear performance curves. The model, written in the AMPL modeling language, has been tested on several plant test cases. The computational results are discussed in terms of the quality of the solutions, the linearization accuracy and the computational time.
TL;DR: In this paper, a review summarizes recent researches and developments on novel solid desiccant materials that can be adopted in SDC systems, including composite desiccants, nanoporous inorganic materials and polymeric desciccants.
Abstract: SDC (Solid desiccant cooling) systems have gained increasing interest as an alternative air conditioning technology. Performance of desiccant plays a crucial role in overall performance of the whole system, especially in terms of dehumidification and regeneration capacity. It is desirable to explore desiccant possessing high adsorption capacity and good regeneration ability. Thus, this review summarizes recent researches and developments on novel solid desiccant materials that can be adopted in SDC systems. The materials include composite desiccants, nanoporous inorganic materials and polymeric desiccants. Adsorption isotherms are concluded and compared. Regeneration ability is also considered for full use of low grade thermal energy. Results show that by proper selection of host matrix and immersed salts, composite desiccants have improved capacity of dehumidification and regeneration. Besides, a good balance can be reached between regeneration and adsorption capacity by tailoring textural properties of nanoporous inorganic materials. For polymeric desiccants, especially MIL type (materials of Institute Lavoisier Frameworks), further progress in adsorptive dehumidification will be anticipated. Though some novel materials approach requirements for SDC systems, no material currently available can perfectly satisfy all the required demands. In this case, more intensive researches in the field of development and evaluation of advanced materials are still required.
TL;DR: In this article, a new combined SCRB/ORC (supercritical CO2 recompression Brayton/organic Rankine cycle) for generating electricity is reported, in which the waste heat from SCRB and ORC is utilized by an organic Rankine Cycle (ORC) for power generation.
Abstract: Exergoeconomic analysis is reported for a new combined SCRB/ORC (supercritical CO2 recompression Brayton/organic Rankine cycle) in which the waste heat from SCRBC (supercritical CO2 recompression Brayton cycle) is utilized by an organic Rankine cycle (ORC) for generating electricity. The analysis is also performed for the SCRBC for comparison purposes. Considering eight different working fluids for the ORC, thermodynamic and exergoeconomic models are developed for the cycles through applying mass and energy conservations, exergy balance and exergy cost equations to systems' components. Influences on the SCRB/ORC and SCRBC performances are investigated of the pinch point temperature difference in pre-cooler1 and in condenser, the compressor pressure ratio and the ORC turbine inlet temperature. Using the EES (Engineering Equation Solver) software, the SCRB/ORC performance is optimized thermodynamically and economically. It is concluded that the exergy efficiency of SCRB/ORC is higher than that of the SCRBC by up to 11.7% and that, the total product unit cost of SCRB/ORC is lower than that of the SCRBC by up to 5.7%. The results also indicate that the highest exergy efficiency and the lowest product unit cost for the SCRB/ORC are obtained when Isobutane and RC318 are considered as the ORC working fluid, respectively.
TL;DR: In this article, the effect of using a mixture of diesel and n-pentanol, which is one of the second-generation biofuels with comparable properties to diesel fuel, as fuel on the combustion, performance, and gaseous and particulate emissions of a naturally-aspirated, four-cylinder, direct-injection diesel engine was examined.
Abstract: In this study, experiments were conducted to examine the effect of using a mixture of diesel and n-pentanol, which is one of the second-generation biofuels with comparable properties to diesel fuel, as fuel on the combustion, performance, and gaseous and particulate emissions of a naturally-aspirated, four-cylinder, direct-injection diesel engine. Three n-pentanol fractions in the fuel mixture were selected: 10, 20 and 30% by volume. Results show that, the addition of n-pentanol leads to longer ignition delay and increases the peak heat release rate in the premixed combustion phase. The brake specific fuel consumption increases with increase of n-pentanol, while the brake thermal efficiency is not affected. Regarding the gaseous emissions, n-pentanol addition results in the following consequence: (a) HC (hydrocarbon) and CO (carbon monoxide) emissions increase for 30% n-pentanol in the blended fuel at low engine load but decrease at high engine load; (b) a slight increase (maximum 8%) in NOx emissions but noticeable increase in NO2 emissions. Regarding the particulate emissions, n-pentanol is found to be very promising in terms of reducing both the mass concentration and the particulate number concentration simultaneously.