Showing papers in "Energies in 2013"

Effects of Environmental Factors and Nutrient Availability on the Biochemical Composition of Algae for Biofuels Production: A Review

Abstract: Due to significant lipid and carbohydrate production as well as other useful properties such as high production of useful biomolecular substrates (e.g., lipids) and the ability to grow using non-potable water sources, algae are being explored as a potential high-yield feedstock for biofuels production. In both natural and engineered systems, algae can be exposed to a variety of environmental conditions that affect growth rate and cellular composition. With respect to the latter, the amount of carbon fixed in lipids and carbohydrates (e.g., starch) is highly influenced by environmental factors and nutrient availability. Understanding synergistic interactions between multiple environmental variables and nutritional factors is required to develop sustainable high productivity bioalgae systems, which are essential for commercial biofuel production. This article reviews the effects of environmental factors (i.e., temperature, light and pH) and nutrient availability (e.g., carbon, nitrogen, phosphorus, potassium, and trace metals) as well as cross-interactions on the biochemical composition of algae with a special focus on carbon fixation and partitioning of carbon from a biofuels perspective.

Catalytic Fast Pyrolysis: A Review

Abstract: Catalytic pyrolysis is a promising thermochemical conversion route for lignocellulosic biomass that produces chemicals and fuels compatible with current, petrochemical infrastructure. Catalytic modifications to pyrolysis bio-oils are geared towards the elimination and substitution of oxygen and oxygen-containing functionalities in addition to increasing the hydrogen to carbon ratio of the final products. Recent progress has focused on both hydrodeoxygenation and hydrogenation of bio-oil using a variety of metal catalysts and the production of aromatics from bio-oil using cracking zeolites. Research is currently focused on developing multi-functional catalysts used in situ that benefit from the advantages of both hydrodeoxygenation and zeolite cracking. Development of robust, highly selective catalysts will help achieve the goal of producing drop-in fuels and petrochemical commodities from wood and other lignocellulosic biomass streams. The current paper will examine these developments by means of a review of existing literature.

Microalgal Species Selection for Biodiesel Production Based on Fuel Properties Derived from Fatty Acid Profiles

Abstract: Physical and chemical properties of biodiesel are influenced by structural features of the fatty acids, such as chain length, degree of unsaturation and branching of the carbon chain. This study investigated if microalgal fatty acid profiles are suitable for biodiesel characterization and species selection through Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis. Fatty acid methyl ester (FAME) profiles were used to calculate the likely key chemical and physical properties of the biodiesel [cetane number (CN), iodine value (IV), cold filter plugging point, density, kinematic viscosity, higher heating value] of nine microalgal species (this study) and twelve species from the literature, selected for their suitability for cultivation in subtropical climates. An equal-parameter weighted (PROMETHEE-GAIA) ranked Nannochloropsis oculata, Extubocellulus sp. and Biddulphia sp. highest; the only species meeting the EN14214 and ASTM D6751-02 biodiesel standards, except for the double bond limit in the EN14214. Chlorella vulgaris outranked N. oculata when the twelve microalgae were included. Culture growth phase (stationary) and, to a lesser extent, nutrient provision affected CN and IV values of N. oculata due to lower eicosapentaenoic acid (EPA) contents. Application of a polyunsaturated fatty acid (PUFA) weighting to saturation led to a lower ranking of species exceeding the double bond EN14214 thresholds. In summary, CN, IV, C18:3 and double bond limits were the strongest drivers in equal biodiesel parameter-weighted PROMETHEE analysis.

Microalgae for Biofuels and Animal Feeds

Abstract: The potential of microalgae biomass production for low-cost commodities—biofuels and animal feeds—using sunlight and CO2 is reviewed. Microalgae are currently cultivated in relatively small-scale systems, mainly for high value human nutritional products. For commodities, production costs must be decreased by an order of magnitude, and high productivity algal strains must be developed that can be stably cultivated in large open ponds and harvested by low-cost processes. For animal feeds, the algal biomass must be high in digestible protein and long-chain omega-3 fatty acids that can substitute for fish meal and fish oils. Biofuels will require a high content of vegetable oils (preferably triglycerides), hydrocarbons or fermentable carbohydrates. Many different cultivation systems, algal species, harvesting methods, and biomass processing technologies are being developed worldwide. However, only raceway-type open pond systems are suitable for the production of low-cost commodities.

A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm

Abstract: In this study, large-eddy simulations (LESs) were performed to investigate the effects of changing wind direction on the turbine wakes and associated power losses in the Horns Rev offshore wind farm. In the LES framework, the turbulent subgrid-scale stresses are parameterized using a tuning-free Lagrangian scale-dependent dynamic model, and the turbine-induced forces are computed using a dynamic actuator-disk model with rotation (ADM-R). This dynamic ADM-R couples blade-element theory with a turbine-specific relation between the blade angular velocity and the shaft torque to compute simultaneously turbine angular velocity and power output. A total of 67 simulations were performed for a wide range of wind direction angles. Results from the simulations show a strong impact of wind direction on the spatial distribution of turbine-wake characteristics, such as velocity deficit and turbulence intensity. This can be explained by the fact that changing the wind angle can be viewed as changing the wind farm layout relative to the incoming wind, while keeping the same wind turbine density. Of particular importance is the effect of wind direction on the distance available for the wakes to recover and expand before encountering other downwind turbines (in full-wake or partial-wake interactions), which affects the power losses from those turbines. As a result, even small changes in wind direction angle can have strong impacts on the total wind farm power output. For example, a change in wind direction of just 10° from the worst-case full-wake condition is found to increase the total power output by as much as 43%. This has important implications for the design of wind farms and the management of the temporal variability of their power output.

Lessons Learned from the 787 Dreamliner Issue on Lithium-Ion Battery Reliability

Abstract: On 16 January 2013, all Boeing 787 Dreamliners were indefinitely grounded due to lithium-ion battery failures that had occurred in two planes. Subsequent investigations into the battery failures released through the National Transportation Safety Board (NTSB) factual report, the March 15th Boeing press conference in Japan, and the NTSB hearings in Washington D.C., never identified the root causes of the failures—a major concern for ensuring safety and meeting reliability expectations. This paper discusses the challenges to lithium-ion battery qualification, reliability assessment, and safety in light of the Boeing 787 battery failures. New assessment methods and control techniques that can improve battery reliability and safety in avionic systems are then presented.

Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle

Abstract: This paper compares two optimal energy management methods for parallel hybrid electric vehicles using an Automatic Manual Transmission (AMT). A control-oriented model of the powertrain and vehicle dynamics is built first. The energy management is formulated as a typical optimal control problem to trade off the fuel consumption and gear shifting frequency under admissible constraints. The Dynamic Programming (DP) and Pontryagin’s Minimum Principle (PMP) are applied to obtain the optimal solutions. Tuning with the appropriate co-states, the PMP solution is found to be very close to that from DP. The solution for the gear shifting in PMP has an algebraic expression associated with the vehicular velocity and can be implemented more efficiently in the control algorithm. The computation time of PMP is significantly less than DP.

Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns

Abstract: Forecasting and modeling building energy profiles require tools able to discover patterns within large amounts of collected information. Clustering is the main technique used to partition data into groups based on internal and a priori unknown schemes inherent of the data. The adjustment and parameterization of the whole clustering task is complex and submitted to several uncertainties, being the similarity metric one of the first decisions to be made in order to establish how the distance between two independent vectors must be measured. The present paper checks the effect of similarity measures in the application of clustering for discovering representatives in cases where correlation is supposed to be an important factor to consider, e.g., time series. This is a necessary step for the optimized design and development of efficient clustering-based models, predictors and controllers of time-dependent processes, e.g., building energy consumption patterns. In addition, clustered-vector balance is proposed as a validation technique to compare clustering performances.

Evaluation of Various Technologies for Wave Energy Conversion in the Portuguese Nearshore

Abstract: The objective of the present work is to perform an evaluation of the performance provided by various technologies for wave energy conversion in the Portuguese continental coastal environment. The wave climate in the target area is first analyzed using the results from three years of simulations with a wave prediction system based on numerical models. Based on the above data, diagrams for the bivariate distributions of the sea states occurrences, defined by the significant wave height and the energy period, are designed for both winters and whole years. On this basis, the output of five different technologies for the conversion of wave energy is assessed in some relevant locations from the Portuguese nearshore. According to the results obtained, the Portuguese continental coastal environment appears to be appropriate for the wave energy extraction. At the same time, the present work shows that the output of the wave energy conversion devices does not depend only on the average wave energy but is also dependent on the distribution of the wave energy among the sea states of different periods. For this reason, a good agreement between the characteristics of the power matrices of the wave energy converters operating in a certain place and the diagrams for the bivariate distributions of the sea states occurrences corresponding to the considered location represents a key issue in selecting the most appropriate technology for wave energy conversion.

Green-Roof Effects on Neighborhood Microclimate and Human Thermal Sensation

Abstract: Green roofs have been recognized as an effective sustainable design tool to mitigate urban heat island (UHI) effects. Previous studies have identified green-roof benefits in cooling and energy-conservation at the building scale, with limited exploration of the wider influence on neighborhood microclimate and human thermal comfort (HTC). This paper investigated the impacts of community-scale green-roof installation on air temperature and HTC in five typical residential neighborhoods of subtropical Hong Kong. The microclimate models ENVI-met and RayMan permitted studies of two main green-roof scenarios, namely extensive (EGR) and intensive (IGR). Microclimatic monitoring data from a local experimental green-roof site validated the modeling methods. The results verified that green-roof cooling effects were not restricted to rooftops, but extended to the ground to improve neighborhood microclimate. EGR reduced pedestrian-level air temperature by 0.4-0.7 °C, and IGR by 0.5-1.7 °C, with maximum effect in open-set low rise sites. Coverage by building footprints and building height dampened lateral and vertical advection of cool air generated by green roofs. Roof greening also improved notably the rooftop-podium level HTC. Diurnal duration of high heat stress was reduced by 6-9 h for EGR scenarios, and 9-11 h for IGR. The findings indicated that large-scale green-roof installation could bring neighborhood-wide cooling, mitigate urban heat island effect, and furnish more comfortable thermal environment for urban residents.

Analytical modeling of partially shaded photovoltaic systems

Abstract: As of today, the considerable influence of select environmental variables, especially irradiance intensity, must still be accounted for whenever discussing the performance of a solar system. Therefore, an extensive, dependable modeling method is required in investigating the most suitable Maximum Power Point Tracking (MPPT) method under different conditions. Following these requirements, MATLAB-programmed modeling and simulation of photovoltaic systems is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) systems. End results prove the reliability of the proposed model in replicating the aforementioned output characteristics in the prescribed setting. The proposed model is chosen because it can, conveniently, simulate the behavior of different ranges of PV systems from a single PV module through the multidimensional PV structure.

Effects of Biomass Feedstocks and Gasification Conditions on the Physiochemical Properties of Char

Abstract: Char is a low-value byproduct of biomass gasification and pyrolysis with many potential applications, such as soil amendment and the synthesis of activated carbon and carbon-based catalysts. Considering these high-value applications, char could provide economic benefits to a biorefinery utilizing gasification or pyrolysis technologies. However, the properties of char depend heavily on biomass feedstock, gasifier design and operating conditions. This paper reports the effects of biomass type (switchgrass, sorghum straw and red cedar) and equivalence ratio (0.20, 0.25 and 0.28), i.e., the ratio of air supply relative to the air that is required for stoichiometric combustion of biomass, on the physiochemical properties of char derived from gasification. Results show that the Brunauer-Emmett-Teller (BET) surface areas of most of the char were 1–10 m2/g and increased as the equivalence ratio increased. Char moisture and fixed carbon contents decreased while ash content increased as equivalence ratio increased. The corresponding Fourier Transform Infrared spectra showed that the surface functional groups of char differed between biomass types but remained similar with change in equivalence ratio.

Bioethanol Production by Carbohydrate-Enriched Biomass of Arthrospira (Spirulina) platensis

Abstract: In the present study the potential of bioethanol production using carbohydrate-enriched biomass of the cyanobacterium Arthrospira platensis was studied. For the saccharification of the carbohydrate-enriched biomass, four acids (H2SO4, HNO3, HCl and H3PO4) were investigated. Each acid were used at four concentrations, 2.5 N, 1 N, 0.5 N and 0.25 N, and for each acid concentration the saccharification was conducted under four temperatures (40 °C, 60 °C, 80 °C and 100 °C). Higher acid concentrations gave in general higher reducing sugars (RS) yields (%, gRS/gTotal sugars) with higher rates, while the increase in temperature lead to higher rates at lower acid concentration. The hydrolysates then were used as substrate for ethanolic fermentation by a salt stress-adapted Saccharomyces cerevisiae strain. The bioethanol yield (%, gEtOH/gBiomass) was significantly affected by the acid concentration used for the saccharification of the carbohydrates. The highest bioethanol yields of 16.32% ± 0.90% (gEtOH/gBiomass) and 16.27% ± 0.97% (gEtOH/gBiomass) were obtained in hydrolysates produced with HNO3 0.5 N and H2SO4 0.5 N, respectively.

Satellite Lithium-Ion Battery Remaining Cycle Life Prediction with Novel Indirect Health Indicator Extraction

Abstract: Prognostics and remaining useful life (RUL) estimation for lithium-ion batteries play an important role in intelligent battery management systems (BMS). The capacity is often used as the fade indicator for estimating the remaining cycle life of a lithium-ion battery. For spacecraft requiring high reliability and long lifetime, in-orbit RUL estimation and reliability verification on ground should be carefully addressed. However, it is quite challenging to monitor and estimate the capacity of a lithium-ion battery on-line in satellite applications. In this work, a novel health indicator (HI) is extracted from the operating parameters of a lithium-ion battery to quantify battery degradation. Moreover, the Grey Correlation Analysis (GCA) is utilized to evaluate the similarities between the extracted HI and the battery’s capacity. The result illustrates the effectiveness of using this new HI for fading indication. Furthermore, we propose an optimized ensemble monotonic echo state networks (En_MONESN) algorithm, in which the monotonic constraint is introduced to improve the adaptivity of degradation trend estimation, and ensemble learning is integrated to achieve high stability and precision of RUL prediction. Experiments with actual testing data show the efficiency of our proposed method in RUL estimation and degradation modeling for the satellite lithium-ion battery application.

PAT Design Strategy for Energy Recovery in Water Distribution Networks by Electrical Regulation

Abstract: In the management of water distribution networks, large energy savings can be yielded by exploiting the head drop due to the network pressure control strategy, i.e., for leak reductions. Hydropower in small streams is already exploited, but technical solutions combining efficiency and economic convenience are still required. In water distribution networks, an additional design problem comes out from the necessity of ensuring a required head drop under variable operating conditions, i.e., head and discharge variations. Both a hydraulic regulation (HR)—via a series-parallel hydraulic circuit- and an electrical regulation (ER)—via inverter- are feasible solutions. A design procedure for the selection of a production device in a series-parallel hydraulic circuit has been recently proposed. The procedure, named VOS (Variable Operating Strategy), is based on the overall plant efficiency criteria and is applied to a water distribution network where a PAT (pump as a turbine) is used in order to produce energy. In the present paper the VOS design procedure has been extended to the electrical regulation and a comparison between HR and ER efficiency and flexibility within a water distribution network is shown: HR was found more flexible than ER and more efficient. Finally a preliminary economic study has been carried out in order to show the viability of both systems, and a shorter payback period of the electromechanical equipment was found for HR mode.

A Two-Stage Continuous Fermentation System for Conversion of Syngas into Ethanol

Abstract: We have established a two-stage continuous fermentation process for production of ethanol from synthesis gas (syngas) with Clostridium ljungdahlii. The system consists of a 1-L continuously stirred tank reactor as a growth stage and a 4-L bubble column equipped with a cell recycle module as an ethanol production stage. Operating conditions in both stages were optimized for the respective purpose (growth in stage one and alcohol formation in stage two). The system was fed with an artificial syngas mixture, mimicking the composition of syngas derived from lignocellulosic biomass (60% CO, 35% H2, and 5% CO2). Gas recycling was used to increase the contact area and retention time of gas in the liquid phase, improving mass transfer and metabolic rates. In stage two, the biocatalyst was maintained at high cell densities of up to 10 g DW/L. Ethanol was continuously produced at concentrations of up to 450 mM (2.1%) and ethanol production rates of up to 0.37 g/(L·h). Foam control was essential to maintain reactor stability. A stoichiometric evaluation of the optimized process revealed that the recovery of carbon and hydrogen from the provided carbon monoxide and hydrogen in the produced ethanol was 28% and 74%, respectively.

State of Charge Estimation Using the Extended Kalman Filter for Battery Management Systems Based on the ARX Battery Model

Abstract: State of charge (SOC) is a critical factor to guarantee that a battery system is operating in a safe and reliable manner. Many uncertainties and noises, such as fluctuating current, sensor measurement accuracy and bias, temperature effects, calibration errors or even sensor failure, etc. pose a challenge to the accurate estimation of SOC in real applications. This paper adds two contributions to the existing literature. First, the auto regressive exogenous (ARX) model is proposed here to simulate the battery nonlinear dynamics. Due to its discrete form and ease of implemention, this straightforward approach could be more suitable for real applications. Second, its order selection principle and parameter identification method is illustrated in detail in this paper. The hybrid pulse power characterization (HPPC) cycles are implemented on the 60AH LiFePO4 battery module for the model identification and validation. Based on the proposed ARX model, SOC estimation is pursued using the extended Kalman filter. Evaluation of the adaptability of the battery models and robustness of the SOC estimation algorithm are also verified. The results indicate that the SOC estimation method using the Kalman filter based on the ARX model shows great performance. It increases the model output voltage accuracy, thereby having the potential to be used in real applications, such as EVs and HEVs.

Review of microalgae harvesting via co-Pelletization with filamentous fungus.

Abstract: Cultivation of microalgae to utilize CO2 and nutrients in the wastewater to generate biofuel products is a promising research objective. However, the process faces tremendous technical difficulties, especially the harvest of microalgae cells, an economically challenging step. Several researchers recently reported co-culturing of filamentous fungi with microalgae so that microalgae cells can be co-pelletized in order to facilitate the cell harvest. This algae pelletization via the filamentous fungi represents an innovative approach to address both the cost and sustainability issues in algae biofuel production and also has potential with direct commercial applications. This paper reviews the current research status in this area and some possible drawbacks of this method in order to provide some possible directions for the future research.

Discrete Displacement Hydraulic Power Take-Off System for the Wavestar Wave Energy Converter

Abstract: The Wavestar Wave Energy Converter (WEC) is a multiple absorber concept, consisting of 20 hemisphere shaped floats attached to a single platform. The heart of the Wavestar WEC is the Power Take-Off (PTO) system, converting the wave induced motion of the floats into a steady power output to the grid. In the present work, a PTO based on a novel discrete displacement fluid power technology is explored for the Wavestar WEC. Absorption of power from the floats is performed by hydraulic cylinders, supplying power to a common fixed pressure system with accumulators for energy smoothing. The stored pressure energy is converted into electricity at a steady pace by hydraulic motors and generators. The storage, thereby, decouples the complicated process of wave power absorption from power generation. The core for enabling this PTO technology is implementing a near loss-free force control of the energy absorbing cylinders. This is achieved by using special multi-chambered cylinders, where the different chambers may be connected to the available system pressures using fast on/off valves. Resultantly, a Discrete Displacement Cylinder (DDC) is created, allowing near loss free discrete force control. This paper presents a complete PTO system for a 20 float Wavestar based on the DDC. The WEC and PTO is rigorously modeled from incident waves to the electric output to the grid. The resulting model of +600 states is simulated in different irregular seas, showing that power conversion efficiencies above 70% from input power to electrical power is achievable for all relevant sea conditions.

Slag Behavior in Gasifiers. Part I: Influence of Coal Properties and Gasification Conditions

Abstract: In the entrained-flow gasifiers used in integrated gasification combined cycle (IGCC) plants, the majority of mineral matter transforms to liquid slag on the wall of the gasifier and flows out the bottom. However, a small fraction of the mineral matter is entrained (as fly ash) with the raw syngas out of the gasifier to downstream processing. This molten/sticky fly ash could cause fouling of the syngas cooler. To improve gasification availability through better design and operation of the gasification process, a better understanding of slag behavior and the characteristics of the slagging process is needed. Char/ash properties, gas compositions in the gasifier, the gasifier wall structure, fluid dynamics, and plant operating conditions (mainly temperature and oxygen/carbon ratio) all affect slagging behavior. Because coal has varying ash content and composition, different operating conditions are required to maintain the slag flow and limit problems downstream. In Part I, we review the main types and the operating conditions of entrained-flow gasifiers and coal properties used in IGCC plants; we identify and discuss the key coal ash properties and the operating conditions impacting slag behavior; finally, we summarize the coal quality criteria and the operating conditions in entrained-flow gasifiers. In Part II, we discuss the constitutive modeling related to the rheological studies of slag flow.

Banki-Michell Optimal Design by Computational Fluid Dynamics Testing and Hydrodynamic Analysis

Abstract: In hydropower, the exploitation of small power sources requires the use of small turbines that combine efficiency and economy. Banki-Michell turbines represent a possible choice for their simplicity and for their good efficiency under variable load conditions. Several experimental and numerical tests have already been designed for examining the best geometry and optimal design of cross-flow type machines, but a theoretical framework for a sequential design of the turbine parameters, taking full advantage of recently expanded computational capabilities, is still missing. To this aim, after a review of the available criteria for Banki-Michell parameter design, a novel two-step procedure is described. In the first step, the initial and final blade angles, the outer impeller diameter and the shape of the nozzle are selected using a simple hydrodynamic analysis, based on a very strong simplification of reality. In the second step, the inner diameter, as well as the number of blades and their shape, are selected by testing single options using computational fluid dynamics (CFD) simulations, starting from the suggested literature values. Good efficiency is attained not only for the design discharge, but also for a large range of variability around the design value.

A Bayesian Method for Short-Term Probabilistic Forecasting of Photovoltaic Generation in Smart Grid Operation and Control

Abstract: A new short-term probabilistic forecasting method is proposed to predict the probability density function of the hourly active power generated by a photovoltaic system. Firstly, the probability density function of the hourly clearness index is forecasted making use of a Bayesian auto regressive time series model; the model takes into account the dependence of the solar radiation on some meteorological variables, such as the cloud cover and humidity. Then, a Monte Carlo simulation procedure is used to evaluate the predictive probability density function of the hourly active power by applying the photovoltaic system model to the random sampling of the clearness index distribution. A numerical application demonstrates the effectiveness and advantages of the proposed forecasting method.

Short-Term Load Forecasting for Microgrids Based on Artificial Neural Networks

Abstract: Electricity is indispensable and of strategic importance to national economies. Consequently, electric utilities make an effort to balance power generation and demand in order to offer a good service at a competitive price. For this purpose, these utilities need electric load forecasts to be as accurate as possible. However, electric load depends on many factors (day of the week, month of the year, etc.), which makes load forecasting quite a complex process requiring something other than statistical methods. This study presents an electric load forecast architectural model based on an Artificial Neural Network (ANN) that performs Short-Term Load Forecasting (STLF). In this study, we present the excellent results obtained, and highlight the simplicity of the proposed model. Load forecasting was performed in a geographic location of the size of a potential microgrid, as microgrids appear to be the future of electric power supply.

Support Vector Regression Model Based on Empirical Mode Decomposition and Auto Regression for Electric Load Forecasting

Abstract: Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR), this paper presents a SVR model hybridized with the empirical mode decomposition (EMD) method and auto regression (AR) for electric load forecasting. The electric load data of the New South Wales (Australia) market are employed for comparing the forecasting performances of different forecasting models. The results confirm the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability.

Pareto Optimal Reconfiguration of Power Distribution Systems Using a Genetic Algorithm Based on NSGA-II

Abstract: Reconfiguration, by exchanging the functional links between the elements of the system, represents one of the most important measures which can improve the operational performance of a distribution system. The authors propose an original method, aiming at achieving such optimization through the reconfiguration of distribution systems taking into account various criteria in a flexible and robust approach. The novelty of the method consists in: the criteria for optimization are evaluated on active power distribution systems (containing distributed generators connected directly to the main distribution system and microgrids operated in grid-connected mode); the original formulation (Pareto optimality) of the optimization problem and an original genetic algorithm (based on NSGA-II) to solve the problem in a non-prohibitive execution time. The comparative tests performed on test systems have demonstrated the accuracy and promptness of the proposed algorithm.

Infrared Screening of Residential Buildings for Energy Audit Purposes: Results of a Field Test

Abstract: In the European Union (EU), the building sector is responsible for approximately 40% of total energy consumption. The existing building stock is inefficient and can, and indeed must be retrofitted to address this issue. The practical implementation of the European strategies requires knowledge of the energy performance of existing buildings through energy audit techniques. Application of thermography in the fields of energy are very widespread, since, through such a non-invasive investigation, and through correct interpretation of infrared images, it is possible to highlight inefficiencies in buildings and related facilities. The paper shows and discusses the results of an infrared audit campaign on 14 existing buildings located in Milan Province (Italy) made in different construction periods and characterised, therefore, by different building technologies. The U-values obtained in an indirect way through the thermography of the opaque walls of the buildings investigated, were compared with the actual known values in order to verify the reliability of the method and the possible margin of error. The study indicated that the category of buildings in which the application of this method is sufficiently reliable is that of solid-mass structure buildings, the most widespread in Italy, whereas in the case of buildings whose external walls are insulated, the percentage of deviation is very high.

The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms

Abstract: Large-eddy simulation is used to study the influence of free-atmosphere stratification on the structure of atmospheric boundary-layer flow inside and above very large wind farms, as well as the power extracted by the wind turbines. In the simulations, tuning-free Lagrangian scale-dependent dynamic models are used to model the subgrid-scale turbulent fluxes, while the turbine-induced forces are parameterized with an actuator-disk model. It is shown that for a given surface cover (with and without turbines) thermal stratification of the free atmosphere reduces the entrainment from the flow above compared with the unstratified case, leading to lower boundary-layer depth. Due to the fact that in very large wind farms vertical energy transport associated with turbulence is the only source of kinetic energy, lower entrainment leads to lower power production by the wind turbines. In particular, for the wind-turbine arrangements considered in the present work, the power output from the wind farms is reduced by about 35% when the potential temperature lapse rate in the free atmosphere increases from 1 to 10 K/km (within the range of values typically observed in the atmosphere). Moreover, it is shown that the presence of the turbines has significant effect on the growth of the boundary layer. Inspired by the obtained results, a simple one-dimensional model is developed to account for the effect of free-atmosphere stability on the mean flow and the power output from very large wind farms.

Recycling of Waste Engine Oils Using a New Washing Agent

Abstract: This paper addresses recycling of waste engine oils treated using acetic acid. A recycling process was developed which eventually led to comparable results with some of the conventional methods. This gives the recycled oil the potential to be reused in cars’ engines after adding the required additives. The advantage of using the acetic acid is that it does not react or only reacts slightly with base oils. The recycling process takes place at room temperature. It has been shown that base oils and oils’ additives are slightly affected by the acetic acid. Upon adding 0.8 vol% of acetic acid to the used oil, two layers were separated, a transparent dark red colored oil and a black dark sludge at the bottom of the container. The base oils resulting from other recycling methods were compared to the results of this paper. The comparison showed that the recycled oil produced by acetic acid treatment is comparable to those recycled by the other conventional methods.

A Combined Fuzzy-AHP and Fuzzy-GRA Methodology for Hydrogen Energy Storage Method Selection in Turkey

Abstract: In this paper, we aim to select the most appropriate Hydrogen Energy Storage (HES) method for Turkey from among the alternatives of tank, metal hydride and chemical storage, which are determined based on expert opinions and literature review. Thus, we propose a Buckley extension based fuzzy Analytical Hierarchical Process (Fuzzy-AHP) and linear normalization based fuzzy Grey Relational Analysis (Fuzzy-GRA) combined Multi Criteria Decision Making (MCDM) methodology. This combined approach can be applied to a complex decision process, which often makes sense with subjective data or vague information; and used to solve to solve HES selection problem with different defuzzification methods. The proposed approach is unique both in the HES literature and the MCDM literature.

A Materials Life Cycle Assessment of a Net-Zero Energy Building

Abstract: This study analyzed the environmental impacts of the materials phase of a net-zero energy building. The Center for Sustainable Landscapes (CSL) is a three-story, 24,350 square foot educational, research, and administrative office in Pittsburgh, PA, USA. This net-zero energy building is designed to meet Living Building Challenge criteria. The largest environmental impacts from the production of building materials is from concrete, structural steel, photovoltaic (PV) panels, inverters, and gravel. Comparing the LCA results of the CSL to standard commercial structures reveals a 10% larger global warming potential and a nearly equal embodied energy per square feet, largely due to the CSL’s PV system. As a net-zero energy building, the environmental impacts associated with the use phase are expected to be very low relative to standard structures. Future studies will incorporate the construction and use phases of the CSL for a more comprehensive life cycle perspective.