International Science Index

International Journal of Energy and Power Engineering

Thermal Energy Storage Based on Molten Salts Containing Nano-Particles: Dispersion Stability and Thermal Conductivity Using Multi-Scale Computational Modelling
New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.
Effective Scheduling of Hybrid Reconfigurable Microgrids Considering High Penetration of Renewable Sources
This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.
Assessment of On-Site Solar and Wind Energy at a Manufacturing Facility in Ireland
The feasibility of on-site electricity production from solar and wind and the resulting load management for a specific manufacturing plant in Ireland are assessed. The industry sector accounts directly and indirectly for a high percentage of electricity consumption and global greenhouse gas emissions; therefore, it will play a key role in emission reduction and control. Manufacturing plants, in particular, are often located in non-residential areas since they require open spaces for production machinery, parking facilities for the employees, appropriate routes for supply and delivery, special connections to the national grid and other environmental impacts. Since they have larger spaces compared to commercial sites in urban areas, they represent an appropriate case study for evaluating the technical and economic viability of energy system integration with low power density technologies, such as solar and wind, for on-site electricity generation. The available open space surrounding the analysed manufacturing plant can be efficiently used to produce a discrete quantity of energy, instantaneously and locally consumed. Therefore, transmission and distribution losses can be reduced. The usage of storage is not required due to the high and almost constant electricity consumption profile. The energy load of the plant is identified through the analysis of gas and electricity consumption, both internally monitored and reported on the bills. These data are not often recorded and available to third parties since manufacturing companies usually keep track only of the overall energy expenditures. The solar potential is modelled for a period of 21 years based on global horizontal irradiation data; the hourly direct and diffuse radiation and the energy produced by the system at the optimum pitch angle are calculated. The model is validated using PVWatts and SAM tools. Wind speed data are available for the same period within one-hour step at a height of 10m. Since the hub of a typical wind turbine reaches a higher altitude, complementary data for a different location at 50m have been compared, and a model for the estimate of wind speed at the required height in the right location is defined. Weibull Statistical Distribution is used to evaluate the wind energy potential of the site. The results show that solar and wind energy are, as expected, generally decoupled. Based on the real case study, the percentage of load covered every hour by on-site generation (Level of Autonomy LA) and the resulting electricity bought from the grid (Expected Energy Not Supplied EENS) are calculated. The economic viability of the project is assessed through Net Present Value, and the influence the main technical and economic parameters have on NPV is presented. Since the results show that the analysed renewable sources can not provide enough electricity, the integration with a cogeneration technology is studied. Finally, the benefit to energy system integration of wind, solar and a cogeneration technology is evaluated and discussed.
Advanced Bio-Fuels for Biorefineries: Incorporation of Waste Tires and Calcium-Based Catalysts to the Pyrolysis of Biomass
The appropriate use of renewable sources emerges as a decisive point to minimize the environmental impact caused by fossil fuels use. Particularly, the use of lignocellulosic biomass becomes one of the best promising alternatives since it is the only carbon-containing renewable source that can produce bioproducts similar to fossil fuels and it does not compete with food market. Among all the processes that can valorize lignocellulosic biomass, pyrolysis is an attractive alternative because it is the only thermochemical process that can produce a liquid biofuel (bio-oil) in a simple way and solid and gas fractions that can be used as energy sources to support the process. However, in order to incorporate bio-oils in current infrastructures and further process in future biorefineries, their quality needs to be improved. Introducing different low-cost catalysts and/or incorporating different polymer residues to the process are some of the new, simple and low-cost strategies that allow the user to directly obtain advanced bio-oils to be used in future biorefineries in an economic way. In this manner, from previous thermogravimetric analyses, local agricultural wastes such as grape seeds (GS) were selected as lignocellulosic biomass while, waste tires (WT) were selected as polymer residue. On the other hand, CaO was selected as low-cost catalyst based on previous experiences by the group. To reach this aim, a specially-designed fixed bed reactor using N₂ as a carrier gas was used. This reactor has the peculiarity to incorporate a vertical mobile liner that allows the user to introduce the feedstock in the oven once the selected temperature (550 ºC) is reached, ensuring higher heating rates needed for the process. Obtaining a well-defined phase distribution in the resulting bio-oil is crucial to ensure the viability to the process. Thus, once experiments were carried out, not only a well-defined two layers was observed introducing several mixtures (reaching values up to 40 wt.% of WT) but also, an upgraded organic phase, which is the one considered to be processed in further biorefineries. Radical interactions between GS and WT released during the pyrolysis process and dehydration reactions enhanced by CaO can promote the formation of better-quality bio-oils. The latter was reflected in a reduction of water and oxygen content of bio-oil and hence, a substantial increase of its heating value and its stability. Moreover, not only sulphur content was reduced from solely WT pyrolysis but also potential and negative issues related to a strong acidic environment of conventional bio-oils were minimized due to its basic pH and lower total acid numbers. Therefore, acidic compounds obtained in the pyrolysis such as CO₂-like substances can react with the CaO and minimize acidic problems related to lignocellulosic bio-oils. Moreover, this CO₂ capture promotes H₂ production from water gas shift reaction favoring hydrogen-transfer reactions, improving the final quality of the bio-oil. These results show the great potential of grapes seeds to carry out the catalytic co-pyrolysis process with different plastic residues in order to produce a liquid bio-oil that can be considered as a high-quality renewable vector.
Safety Considerations of Furanics for Sustainable Applications in Advanced Biorefineries
Production of bio-based chemicals and materials from lignocellulosic biomass is gaining tremendous importance in advanced bio-refineries while aiming towards progressive replacement of petroleum based chemicals in transportation fuels and commodity polymers. One such attempt has resulted in the production of key furan derivatives (FD) such as furfural, HMF, MMF etc., via acid catalyzed dehydration (ACD) of C6 and C5 sugars, which are further converted into key chemicals or intermediates (such as Furandicarboxylic acid, Furfuryl alcohol etc.,). In subsequent processes, many high potential FD are produced, that can be converted into high added value polymers or high energy density biofuels. During ACD, an unavoidable polyfuranic byproduct is generated which is called humins. The family of FD is very large with varying chemical structures and diverse physicochemical properties. Accordingly, the associated risk profiles may largely vary. Hazardous Material (Haz-mat) classification systems such as GHS (CLP in the EU) and the UN TDG Model Regulations for transport of dangerous goods are one of the preliminary requirements for all chemicals for their appropriate classification, labelling, packaging, safe storage, and transportation. Considering the growing application routes of FD, it becomes important to notice the limited access to safety related information (safety data sheets available only for famous compounds such as HMF, furfural etc.,) in these internationally recognized haz-mat classification systems. However, these classifications do not necessarily provide information about the extent of risk involved when the chemical is used in any specific application. Factors such as thermal stability, speed of combustion, chemical incompatibilities, etc., can equally influence the safety profile of a compound, that are clearly out of the scope of any haz-mat classification system. Irrespective of the bio-based origin, FD has so far received inconsistent remarks concerning their toxicity profiles. With such inconsistencies, there is a fear that, a large family of FD may also follow extreme judgmental scenarios like ionic liquids, by ranking some compounds as extremely thermally stable, non-flammable, etc., Unless clarified, these messages could lead to misleading judgements while ranking the chemical based on its hazard rating. Safety is a key aspect in any sustainable biorefinery operation/facility, which is often underscored or neglected. To fill up these existing data gaps and to address ambiguities and discrepancies, the current study focuses on giving preliminary insights on safety assessment of FD and their potential targeted by-products. With the available information in the literature and obtained experimental results, physicochemical safety, environmental safety as well as (a scenario based) fire safety profiles of key FD, as well as side streams such as humins and levulinic acid, will be considered. With this, the study focuses on defining patterns and trends that gives coherent safety related information for existing and newly synthesized FD in the market for better functionality and sustainable applications.
Humins: From Industrial By-Product to High Value Polymers
During the last decades renewable and low-cost resources have attracted increasingly interest. Carbohydrates can be derived by lignocellulosic biomasses, which is an attractive option since they represent the most abundant carbon source available in nature. Carbohydrates can be converted in a plethora of industrially relevant compounds, such as 5-hydroxymethylfurfural (HMF) and levulinic acid (LA), within acid catalyzed dehydration of sugars with mineral acids. Unfortunately, these acid catalyzed conversions suffer of the unavoidable formation of highly viscous heterogeneous poly-disperse carbon based materials known as humins. This black colored low value by-product is made by a complex mixture of macromolecules built by covalent random condensations of the several compounds present during the acid catalyzed conversion. Humins molecular structure is still under investigation but seems based on furanic rings network linked by aliphatic chains and decorated by several reactive moieties (ketones, aldehydes, hydroxyls, …). Despite decades of research, currently there is no way to avoid humins formation. The key parameter for enhance the economic viability of carbohydrate conversion processes is, therefore, increasing the economic value of the humins by-product. Herein are presented new humins based polymeric materials that can be prepared starting from the raw by-product by thermal treatment, without any step of purification or pretreatment. Humins foams can be produced with the control of reaction key parameters, obtaining polymeric porous materials with designed porosity, density, thermal and electrical conductivity, chemical and electrical stability, carbon amount and mechanical properties. Physico chemical properties can be enhanced by modifications on the starting raw material or adding different species during the polymerization. A comparisons on the properties of different compositions will be presented, along with tested applications. The authors gratefully acknowledge the European Community for financial support through Marie-Curie H2020-MSCA-ITN-2015 "HUGS" Project.
Achieving High Renewable Energy Penetration in Western Australia Using Data Digitisation and Machine Learning
The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.
Modeling and Benchmarking the Thermal Energy Performance of Palm Oil Production Plant
Thermal energy consumption in palm oil production plant comprises mainly of steam, hot water and hot air. In most efficient plants, hot water and air are generated from the steam supply system. Research has shown that thermal energy utilize in palm oil production plants is about 70 percent of the total energy consumption of the plant. In order to manage the plants’ energy efficiently, the energy systems are modelled and optimized. This paper aimed to present the model of steam supply systems of a typical palm oil production plant in Ghana. The models include exergy and energy models of steam boiler, steam turbine and the palm oil mill. The paper further simulates the virtual plant model to obtain the thermal energy performance of the plant under study. The simulation results show that, under normal operating condition, the boiler energy performance is considerably below the expected level as a result of several factors including intermittent biomass fuel supply, significant moisture content of the biomass fuel and significant heat losses. The total thermal energy performance of the virtual plant is set as a baseline. The study finally recommends number of energy efficiency measures to improve the plant’s energy performance.
Benchmarking Energy Challenges in Palm Oil Production Industry in Ghana
The current energy crisis in Ghana has affected significant number of industries which have direct impact on the country’s economy. Amongst the affected industries are palm oil production industries even though the impact is less as compared to fully relied national grid industries. Most of the large and medium palm oil production industries are partially grid reliance, however, the unavailability and the high cost palm biomass poses huge challenge. This paper aimed to identify and analyse the energy challenges associated with the palm oil production industries in Ghana. The study is conducted on the nine largest palm oil production plants in Ghana. Data is obtained by the use of questionnaire and observation. Since the study aimed to compare the respective energy challenges associated with nine industrial plants under study and establish a benchmark that represents a common problem of all the nine plants under study, the study uses percentile analysis and Analysis of Variance (ANOVA) as the statistical tools to validate the benchmark. The results indicate that lack of sustainability of palm biomass supply chain is the key energy challenge in the palm oil production industries in Ghana. Other problems include intermittent power supply from the grid and the low boiler efficiency due to outmoded conversion technology of the boilers. The result also demonstrates that there are statistically significant differences between the technologies in different age groups in relation to technology conversion efficiency.
Validation of a Fast Model of the Levenmouth Wind Turbine
This paper describes the process adopted to generate a FAST (Fatigue, Aerodynamics, Structures, and Turbulence) model to produce some relevant design load cases (DLCs) for the Levenmouth demonstration foreshore wind turbine owned by Offshore Renewable Energy Catapult (ORE Catapult). FAST is an open-source aero-hydro-servo-elastic dynamic modelling tool developed by the National Renewable Energy Laboratory (NREL). Although there are a few published FAST models, all of them belong to reference turbines (e.g. NREL-5MW, NTU-10MW). Even though the Levenmouth wind turbine is not a commercial one, the fact of shedding results of a real engine will be highly appreciated to the industry and the academic community. Moreover, the Levenmouth wind turbine exhibits a new generation of extremely flexible blades that conflicts with the previous approaches used by most common aero-elastic codes. The study is divided into four stages. It starts by building the model and fine-tunes it until it matches the natural frequencies of blades and tower. The second stage encompasses the comparison of the commissioning results with the relevant FAST simulations to match the dynamic behaviour of the turbine. The next phase comprises a load’s comparison for the interface between tower and transition piece to validate the new aero-servo-elastic model with commissioning loads. Finally, a comparison with SCADA outputs has been performed. The results of the study show good agreement in the natural frequencies, the dynamic performance and the loads between the aero-servo-elastic model and the commissioning results. The present study is framed into an EngD project and a wider turbine virtualization project. We anticipate our work to be the initial point for more sophisticated aero-elastic models, adapted the unique properties of the Levenmouth demonstration wind turbine.
State of Charge Estimation of High Capacity Sodium Ion Battery Using Cascade Forward Backpropagation Network Algorithm
Sodium ion battery (SIB) technology is a promising battery technology for energy storage systems. Due to its abundancy in nature and lower cost, it can be a good alternative for current Lithium ion battery (LIB) technology. The Sodium ion layered transition metal oxide battery was synthesized using sol-gel method. The maximum capacity of the fabricated battery is 140 mAh/gm. The battery is charged and discharged at different current to different voltage window. To the best of our knowledge, State of Charge (SOC) estimation for the SIB battery using the Cascaded Forward Backpropagation Network Algorithm (CFBN) has not been reported. The estimated result of SOC using CFBN was compared with SOC calculated using Coulomb counting method and highlighted the good accuracy of the estimation technique.
Employing Systems Engineering Tools to Analyze Green Microgrids for Remote Islands
Microgrids (small scale power systems optimizing variable generation and loads) that serve a remote island’s load requirements demonstrate both the extreme challenges and opportunities in providing reliable power in remote locations. Microgrids, which provide the entire power requirements with on-island resources, can be considered complex systems. These complex systems can be modeled using a variety of tools. This paper provides an overview of different tools used to characterize different aspects of microgrids’ behavior in order to improve their overall efficiency. These tools include agent-based modeling as one of a class of computational models commonly used in Systems Engineering, as well as specialized software packages specifically developed to address energy performance modeling, like EnergyPlan. A broad overview of the used methods is followed by illustration of how these tools could be applied to the analysis of a green microgrid of a remote island. The paper ends with conclusions on advantages and disadvantages of employing different tools to investigate the dynamics of remote island microgrids.
Central Energy Management for Optimizing Utility Grid Power Exchange with a Network of Smart Homes
Smart homes are small energy systems which may be equipped with renewable energy sources, storage devices, and loads. Energy management strategy plays a main role in the efficient operation of smart homes. Effective energy scheduling of the renewable energy sources and storage devices guarantees efficient energy management in households while reducing the energy imports from the grid. Nevertheless, despite such strategies, independently day ahead energy schedules for multiple households can cause undesired effects such as high power exchange with the grid at certain times of the day. Therefore, the interactions between multiple smart home day ahead energy projections is a challenging issue in a smart grid system and if not managed appropriately, the imported energy from the power network can impose additional burden on the distribution grid. In this paper, a central energy management strategy for a network consisting of multiple households each equipped with renewable energy sources, storage devices, and Plug-in Electric Vehicles (PEV) is proposed. The decision-making strategy alongside the smart home energy management system, minimizes the energy purchase cost of the end users, while at the same time reducing the stress on the utility grid. In this approach, the smart home energy management system determines different operating scenarios based on the forecasted household daily load and the components connected to the household with the objective of minimizing the end user overall cost. Then, selected projections for each household that are within the same cost range are sent to the central decision-making system. The central controller then organizes the schedules to reduce the overall peak to average ratio of the total imported energy from the grid. To validate this approach simulations are carried out for a network of five smart homes with different load requirements and the results confirm that by applying the proposed central energy management strategy, the overall power demand from the grid can be significantly flattened. This is an effective approach to alleviate the stress on the network by distributing its energy to a network of multiple households over a 24- hour period.
A Study on Cleaning Mirror Technology with Reduced Water Consumption in a Solar Thermal Power Plant
In our study, traditional cleaning mirror technology with reduced consumption of water in solar thermal power plants is investigated. In developed countries, a significant increase of growth and innovation in solar thermal power sector is evident since over the last decade. These power plants required higher water consumption, however, there are some complications to construct and operate such power plants under severe drought-inflicted areas like deserts where high water-deficit can be seen but sufficient solar energy is available. Designing new experimental equipments is the most important advantage of this study. These equipments can estimate various types of measurements at the mean time. In this study, Glasses were placed for 10 and 20 days at certain positions to deposit dusts on glass surface by using a common method. Dust deposited on glass surface was washed by experimental equipment and measured dust deposition on each glass. After that, experimental results were analyzed and concluded.
Lifetime Monitoring of Boiler Components and Piping Systems in Conventional Thermal Power Plants at High Temperatures
Lifetime monitoring of power plant components used in the boiler area as well as in high pressure/high temperature piping to the turbine plays an important role in conventional thermal power plants. The currently new power plants utilize significantly high steam parameters and thus a lower design reserve. At the same time, especially in Germany, a higher flexibility due the modulation of the power grid is required so in the future start-up and shut-down processes are expected more frequently associated with the energy turnaround. Accordingly, a continuous online monitoring of the actual piping behavior is an important precondition to maintain the operation reliability, establishing maintenance and inspection intervals and ensure a safe long-term operation. The need for this kind of monitoring arises from the limited lifetime of these components. The limiting factors to components’ life are creep damage which occurs as a result of mechanical loading at high temperature and low cycle fatigue caused by thermal stresses in the walls during start-up and shut-down processes. The lifetime calculation is conducted based on the Tresca equivalent stress (maximum shear stress hypothesis) and consider both effects, creep and fatigue, by the degree of exhaustion. It is assumed, that there is no influence by additional system loads. The verification of this boundary condition can be attained through the monitoring of the piping system. Thus, in addition to standard measurements of pressure and temperature, the basis of the monitoring system is the capturing of data on piping movements and hanger loads at selected locations. Knowledge from movement and force measurements allow early reactions to eliminate malfunctions in the hanger system and thus contribute to an optimization of the lifetime of the piping. The experience with this kind of monitoring systems and the obtained results are shown by several case studies from recorded operational data.
Calculation Model for Heat Transfer Processes in Dry Ash Conveyors
In recent years, the demand for a dry handling of bottom ash from coal-fired power plants has significantly increased. The reasons are manifold, such as lacks of water availability at the location of power plants, the requirement to reduce operational costs or environmental reasons. Thereby it is crucial, that a sufficient cooling of the bottom ash is achieved by the dry cooling air. The cooling air is ambient air, which enters the dry ash conveyor through several inlets. It is in a countercurrent flow with respect to the ash and finally enters the combustion chamber of the boiler as leakage air through an ash hopper. On the way, a variety of heat-exchanging mechanisms between ash and cooling air takes place. Within this contribution, a model for the simulation of heat transfer processes in dry ash conveyors is developed. A numerical example taking into account geometrical and operational data of an existing plant is considered and conservatism of the calculation model is shown by comparison to measurement data. The developed model can be applied in future designs and projections of dry ash handling facilities.
Cloud Induced Photovoltaic Transient Analysis for Smart Microgrids in the Mediterranean Area
Integration of Renewable Energy Resources (RER) into power systems has been popular topic for a long time, and will be more popular in the future since it is free and environment friendly energy source. Particularly, solar energy is the one of the sources which get the greatest attention among other sources since it is easy to install them on the roof. Due to government policy and incentives solar energy will be the most important energy sources that can be invested for meeting the energy needs. Besides its advantages, due to intermittent nature of solar energy, photovoltaic (PV) generation causes some serious problems to the grid. One of the primary concern regarding PV energy production is intermittent nature especially in cloudy weather conditions. Since PV generation directly depends on the solar irradiance, speed of clouds, cloud width, number and time interval between clear and cloudy weather can greatly influence the grid where PV is the main source of production. PV sources are main source of energy when microgrid is islanded from main grid. Sudden changes in PV generation due to intermittent cloud movements can cause some severe issues on the system such as voltage violations, reverse power flow, voltage fluctuations, and power quality problems. These types of issues complicate to maintain voltage within compulsory levels at customer sides. When the system has very high penetration rates, these negative effects can play more important role on the grid. Thus, cloud induced transients in photovoltaic (PV) in grid are seen as a potential handicap for the future expansion of Renewable Energy Resources. This study investigates the impact of cloud induced PV transient to the microgrid that will be implemented in the Malta College of Arts Science and Technology (MCAST) campus. The solar irradiance and clouds data used for the analysis in this work are specific to the Mediterranean region. The results in this work are based on the project called 3DMicroGrid that is ERANETMED funded project.
Design of Dynamic and Stochastic Optimization Models Integration with Agent Technology Infrastructure for Smart Microgrids in the Mediterranean Area
Microgrid has become a key topic in recent years especially due to increased energy demand, which is consist of a cluster of distributed generators, energy storage systems and loads. One of the unique features of microgrid is that it is able to work in two operation modes, grid-connected mode or islanded mode. There are many benefits inherent to microgrids such as improving power quality, reducing transmission losses and carbon emissions, localizing operation and control, robustness and resilience owing to diverse energy sources, optimal load scheduling, possibility to incorporate energy management systems, better use of renewable energy sources and less dependency on external suppliers of energy and fuel. Microgrids are generally characterized by very low inertia when in islanded operation mode. This means that a more appropriate approach in dealing with the optimal allocation of resources would involve the dynamic behavior of the system. A state-of-the-art time dependent hybrid dynamic optimization will be advanced to give the possibility of optimum use of generation resources and optimal allocation. Integration of renewable energy resources (RES) into smart micro grids gives rise to complexity and challenges to its modeling, control, and optimization because of the intermittency and volatility in renewable power generation. The intermittency indicates that the generation is not always available and the volatility indicates that the generation is fluctuating in different time scales. Since renewable power generation depends upon weather conditions (sunlight or wind), predicting the weather is a highly probabilistic activity. The amount of load is also probabilistic, particularly predictions related to demand response and the corresponding allocation of power generation and energy storage. This study will present an approach in order to derive stochastic optimization models for active smart micro-grids within the context of 3DMicroGrid project, which is an ERANETMED funded project aiming towards designing and developing a microgrid framework. This project will be deployed as a pilot proof of concept implementation at a university campus in Malta or Jordan with collaboration of partners from Jordan, Malta, Germany, Turkey, Spain, Cyprus, Algeria, and Greece. The stochastic optimization models based on the dynamic optimization models together with the other microgrid elements will be integrated into a multi-agent technology infrastructure.
Comparison of Electrical Parameters of Oil- Immersed and Dry-Type Transformer Using Finite Element Method
The choice evaluation between oil-immersed and dry-type transformers is often controlled by cost, location, and application. This paper compares the electrical performance of liquid- filled and dry-type transformers, which will assist the customer to choose the right and efficient ones for particular applications. An accurate assessment of the time-average flux density, electric field intensity and voltage distribution in an oil-insulated and a dry-type transformer have been computed and investigated. The detailed transformer modeling and analysis has been carried out to determine electrical parameter distributions. The models of oil-immersed and dry-type transformers are developed and solved by using the finite element method (FEM) to compare the electrical parameters. The effects of non-uniform and non-coherent voltage gradient, flux density and electric field distribution on the power losses and insulation properties of transformers are studied in detail. The results show that for the same voltage and kilo-volt-ampere (kVA) rating oil-immersed transformers have better insulation properties and less hysteresis losses than the dry-type.
Optimization of Solar Tracking Systems
In this paper, an intelligent approach is proposed to optimize the orientation of continuous solar tracking systems on cloudy days. Considering the weather case, the direct sunlight is more important than the diffuse radiation in case of clear sky. Thus the panel is always pointed towards the sun. In case of an overcast sky, the solar beam is close to zero, and the panel is placed horizontally to receive the maximum of diffuse radiation. Under partly covered conditions, the panel must be pointed towards the source that emits the maximum of solar energy and it may be anywhere in the sky dome. Thus, the idea of our approach is to analyze the images, captured by ground-based sky camera system, in order to detect the zone in the sky dome which is considered as the optimal source of energy under cloudy conditions. The proposed approach is implemented using experimental set-up developed at PROMES-CNRS laboratory in Perpignan city (France). Under overcast conditions, the results were very satisfactory and the intelligent approach has provided efficiency gains of up to 9% relative to conventional continuous sun tracking systems.
The SynchroniCity Methodological Framework for Smart Cities in the European Union to Implement Co-Creation
Co-creation is an effective process to generate ideas by sharing knowledge and experiences, connecting products and services to the real users. In Smart Cities projects, citizens should be engaged since the beginning, in a continuous process to effectively transform ideas into action and contribute to the co-creation activities. The analysis of co-creation strategies in Smart Cities is still scarce in the literature, and a common methodological approach for supporting the implementation of real use cases is needed. The purpose of this paper is to establish first a solid framework on co-creation approaches within the Smart Cities environment; secondly, to provide guidance to the SynchroniCity project, to concretely identify which methodologies should be implemented by the cities; thirdly, to validate the results achieved in terms of citizens’ engagement in co-creation activities. The background of the study is based on literature review on the topic, and the framework is validated through an online questionnaire and in-depth interviews with the Smart Cities part of the project. The research found that co-creation is required to improve innovation capabilities and the sustainability of new and already existing products, especially during the co-design phase, by increasing the number of people, not only citizens but also industries and actors from the utility sector, participating in this process. Co-creation is also necessary in Smart Cities to improve the governance framework within their municipalities.
A Co-Creation Methodology for Smart Cities: Insights from Multiple Case Studies
Today, as city governments struggle to meet the demands for improvement in public service delivery and the quality of urban life - while facing ever-diminishing resources – an examination is warranted of how we understand current dynamics between smart city (governance) and citizens in public service delivery. This paper seeks to yield insight into how products and services can be co-created between city and citizens, to benefit both the city and everyday urban life. The concept of co-creation - associated with a participatory turn in digital development practices reflected in the claimed democratization of digital technologies - may, arguably, offer a solution towards delivering sustainable long-term benefits for public service providers and users. It highlights what has been termed the smart city’ as an opportunity for promoting citizen participation and bottom-up innovation approaches. This is also reflected in the concept of ‘Smart Citizenship’ as defined in the literature, where citizens are co-creators of urban design and technology. The underlying, fundamental shift in relationships between public administrations, citizens and stakeholders is, however, easier said than done. Value co-creation has been applied in marketing as a way to strengthen the relationship between company and customers. Also in the public sector, particularly within the Smart City one, the relevance of value co-creation has become increasingly clear in theory and practice. Less clear is how cities can collaborate with citizens in co-creating services and products. Even public administrations that are keen to apply this approach often struggle in identifying the best way to approach it in a sustainable fashion. This is due to changes in practices that are required to integrate the complex co-creation process in organizational design, as well as diffuse understandings of co-creation as a means. This paper realizes and addresses the evident need for a systematic framework that supports Smart Cities and their administrations in understanding how to develop and implement co-creation to ultimately become more participatory. It aims to support cities in applying a clear-cut user-driven approach to co-creation. This paper is therefore designed to enhance our understanding and offer a systematic approach by deploying the results of several case studies, for which a co-creation methodology for Smart Cities has been defined and tried. By drawing upon European projects the reasoning behind the methodology and its implementation can be illustrated. The methodology rests on three pillars; First, it guides the reader through the overall co-creation process including problem analysis via stakeholder identification to evaluation; Second, it helps to identify specific and appropriate means to achieve the set objectives, i.e. co-creation methods and tools to implement; Third, it provides guidelines to put them into action. In addition to the presentation of the methodology, the paper discusses feedback from users, how the guidance and structure it provides, helps to co-create services and products, to demonstrate the value and feasibility of co-creation, and to promote and strengthen the participatory Smart City.
Hardware-in-the-Loop Test for Automatic Voltage Regulator of Synchronous Condenser
Automatic voltage regulator (AVR) plays an important role in volt/var control of synchronous condenser (SC) in power systems. Test AVR performance in steady-state and dynamic conditions in real grid is expensive, low efficiency, and hard to achieve. To address this issue, we implement hardware-in-the-loop (HiL) test for the AVR of SC to test the steady-state and dynamic performances of AVR in different operating conditions. Startup procedure of the system and voltage set point changes are studied to evaluate the AVR hardware response. Overexcitation, underexcitation, and AVR set point loss are tested to compare the performance of SC with the AVR hardware and that of simulation. The comparative results demonstrate how AVR will work in a real system. The results show HiL test is an effective approach for testing devices before deployment and is able to parameterize the controller with lower cost, higher efficiency, and more flexibility.
Superordinated Control for Increasing Feed-in Capacity and Improving Power Quality in Low Voltage Distribution Grids
The ever increasing amount of distributed generation in low voltage distribution grids (mainly PV and micro-CHP) can lead to reverse load flows from low to medium/high voltage levels at times of high feed-in. Reverse load flow leads to rising voltages that may even exceed the limits specified in the grid codes. Furthermore, the share of electrical loads connected to low voltage distribution grids via switched power supplies continuously increases. In combination with inverter-based feed-in, this results in high harmonic levels reducing overall power quality. Especially high levels of third-order harmonic currents can lead to neutral conductor overload, which is even more critical if lines with reduced neutral conductor section areas are used. This paper illustrates a possible concept for smart grids in order to increase the feed-in capacity, improve power quality and to ensure safe operation of low voltage distribution grids at all times. The key feature of the concept is a hierarchically structured control strategy that is run on a superordinated controller, which is connected to several distributed grid analyzers and inverters via broad band powerline (BPL). The strategy is devised to ensure both quick response time as well as the technically and economically reasonable use of the available inverters in the grid (PV-inverters, batteries, stepless line voltage regulators). These inverters are provided with standard features for voltage control, e.g. voltage dependent reactive power control. In addition they can receive reactive power set points transmitted by the superordinated controller. To further improve power quality, the inverters are capable of active harmonic filtering, as well as voltage balancing, whereas the latter is primarily done by the stepless line voltage regulators. By additionally connecting the superordinated controller to the control center of the grid operator, supervisory control and data acquisition capabilities for the low voltage distribution grid are enabled, which allows easy monitoring and manual input. Such a low voltage distribution grid can also be used as a virtual power plant.
Development of Vertically Integrated 2D Lake Victoria Flow Models in COMSOL Multiphysics
Lake Victoria is the second largest fresh water body in the world, located in East Africa with a catchment area of 250,000 km², of which 68,800 km² is the actual lake surface. The hydrodynamic processes of the shallow (40–80 m deep) water system are unique due to its location at the equator, which makes Coriolis effects weak. The paper describes a St.Venant shallow water model of Lake Victoria developed in COMSOL Multiphysics software, a general purpose finite element tool for solving partial differential equations. Depth soundings taken in smaller parts of the lake were combined with recent more extensive data to resolve the discrepancies of the lake shore coordinates. The topography model must have continuous gradients, and Delaunay triangulation with Gaussian smoothing was used to produce the lake depth model. The model shows large-scale flow patterns, passive tracer concentration and water level variations in response to river and tracer inflow, rain and evaporation, and wind stress. Actual data of precipitation, evaporation, in- and outflows were applied in a fifty-year simulation model. It should be noted that the water balance is dominated by rain and evaporation and model simulations are validated by Matlab and COMSOL. The model conserves water volume, the celerity gradients are very small, and the volume flow is very slow and irrotational except at river mouths. Numerical experiments show that the single outflow can be modelled by a simple linear control law responding only to mean water level, except for a few instances. Experiments with tracer input in rivers show very slow dispersion of the tracer, a result of the slow mean velocities, in turn, caused by the near-balance of rain with evaporation. The numerical and hydrodynamical model can evaluate the effects of wind stress which is exerted by the wind on the lake surface that will impact on lake water level. Also, model can evaluate the effects of the expected climate change, as manifest in changes to rainfall over the catchment area of Lake Victoria in the future.
Efficiency of Pre-Treatment Methods for Biodiesel Production from Mixed Culture of Microalgae
The rapid depletion of fossil fuel supplies and the emission of carbon dioxide by their continued combustion have paved the way for increased production of carbon-neutral biodiesel from naturally occurring oil sources. The high biomass growth rate and lipid production of microalgae make it a viable source for biodiesel production compared to conventional feedstock. In Sri Lanka, the production of biodiesel by employing indigenous microalgae species is at its emerging stage. This work was an attempt to compare the various pre-treatment methods before extracting lipids such as autoclaving, microwaving and sonication. A mixed culture of microalgae predominantly consisting of Chlorella sp. was obtained from Beire Lake which is an algae rich, organically polluted water body located in Colombo, Sri Lanka. After each pre-treatment method, a standard solvent extraction using Bligh and Dyer’s method was used to compare the total lipid content in percentage dry weight (% dwt). The fatty acid profiles of the oils extracted with each pretreatment method were analyzed using gas chromatography-mass spectrometry (GC-MS). The properties of the biodiesels were predicted by Biodiesel Analyzer© Version 1.1, in order to compare with ASTM 6751-08 biodiesel standard.
Wet Processing of Algae for Protein and Carbohydrate Recovery as Co-Product of Algal Oil
Historically, lipid extraction from dried algal biomass remained a focus area of the algal research. It has been realized over the past few years that the lipid-centric approach and conversion technologies that require dry algal biomass have several challenges. Algal culture in cultivation systems contains more than 99% water, with algal concentrations of just a few hundred milligrams per liter ( < 0.05 wt%), which makes harvesting and drying energy intensive. Drying the algal biomass followed by extraction also entails the loss of water and nutrients. In view of these challenges, focus has shifted toward developing processes that will enable oil production from wet algal biomass without drying. Hydrothermal liquefaction (HTL), an emerging technology, is a thermo-chemical conversion process that converts wet biomass to oil and gas using water as a solvent at high temperature and high pressure. HTL processes wet algal slurry containing more than 80% water and significantly reduces the adverse cost impact owing to drying the algal biomass. HTL, being inherently feedstock agnostic, i.e., can convert carbohydrates and proteins also to fuels and recovers water and nutrients. It is most effective with low-lipid (10--30%) algal biomass, and bio-crude yield is two to four times higher than the lipid content in the feedstock. In the early 2010s, research remained focused on increasing the oil yield by optimizing the process conditions of HTL. However, various techno-economic studies showed that simply converting algal biomass to only oil does not make economic sense, particularly in view of low crude oil prices. Making the best use of every component of algae is a key for economic viability of algal to oil process. On investigation of HTL reactions at the molecular level, it has been observed that sequential HTL has the potential to recover value-added products along with biocrude and improve the overall economics of the process. This potential of sequential HTL makes it a most promising technology for converting wet waste to wealth. In this presentation, we will share our experience on the techno-economic and engineering aspects of sequential HTL for conversion of algal biomass to algal bio-oil and co-products.
Solar Photovoltaic Foundation Design
Solar Photovoltaic (PV) development is reliant on the sunlight hours available in a particular region to generate electricity. A potential area is assessed through its inherent solar radiation intensity measured in watts per square meter. Solar energy development involves the feasibility, design, construction, operation and maintenance of the relevant infrastructure, but this paper will focus on the design and construction aspects. Africa and Australasia have the longest sunlight hours per day and the highest solar radiation per square meter, 7 sunlight hours/day and 5 kWh/day respectively. Solar PV support configurations consist of fixed-tilt support and tracker system structures, the differentiation being that the latter was introduced to improve the power generation efficiency of the former due to the sun tracking movement capabilities. The installation of Solar PV foundations involves rammed piles, drilling/grout piles and shallow raft reinforced concrete structures. This paper presents a case study of 2 solar PV projects in Africa and Australia, discussing the foundation design consideration and associated construction cost implications of the selected foundations systems. Solar PV foundations represent up to one fifth of the civil works costs in a project. Therefore, the selection of the most structurally sound and feasible foundation for the prevailing ground conditions is critical towards solar PV development. The design wind speed measured by anemometers govern the pile embedment depth for rammed and drill/grout foundation systems. The lateral pile deflection and vertical pull out resistance of piles increase proportionally with the embedment depth for uniform pile geometry and geology. The pile driving rate may also be used to anticipate the lateral resistance and skin friction restraining the pile. Rammed pile foundations are the most structurally suitable due to the pile skin friction and ease of installation in various geological conditions. The competitiveness of solar PV projects within the renewable energy mix is governed by lowering capital expenditure, improving power generation efficiency and power storage technological advances. The power generation reliability and efficiency are areas for further research within the renewable energy niche.
Studying the Effect of Rooftop Photovoltaic Panels Shading on Dwellings Thermal Performance
Thermal performance considered to be a key measure in building sustainability. The major factors affecting this measure are quite well known and they are specifically related to building architecture design such as roof type or shading from adjacent objects, and building materials such as type of walls, insulation, and windows. In some climate zones, shading has significant impact on building thermal performance due to its effect on heating and/or cooling load. In cold weather zones shading the roof may reduce heat gain of the building and thus increase the heating load, on the other side in hot or warm weather zones shading the roof may increase building thermal performance due to the reduction of its cooling load. One of the vital shading components of the current building sustainable design is the rooftop solar PV panel technology. The application of this type of technology has expanded vastly during the last 5 years in many countries; however, not many comprehensive works were carried out to analyze the impact of shading developed by these panels on building thermal performance. This paper studies the effect of shading and power generation developed by the solar PV rooftop panels on dwellings thermal performance. A typical dwelling with conventional roof design, as well as standard PV panel configurations, were adopted. The analysis is performed by using two types of packages: 'AccuRate Sustainability' for rating the energy efficiency of residential building design, and 'PVSYST' for the solar PV power system design. The former package is used to calculate the heating and cooling load of a dwelling at different roof shading ratios, and the later package is used to evaluate the power production from the PV system at a certain design condition. The analysis correlates the power generated from the PV panels to the heating and cooling load associated with the corresponding shaded area of the roof to optimize the solar PV panels area. Different roof orientation, roof inclination, roof insulation, as well as PV panel area are considered in this study in different major cities in Australia. The analysis shows that the PV rooftop in some flat roof designs has significant effect on overall energy balance of a dwelling. However, in other designs that have roof space, the loss in thermal performance due to shaded area of the roof by PV panels is negligible compared to the energy generated by these panels. The results of this work help building sustainability designer to maximize the thermal performance and improve energy efficiency of the dwellings.
Comparative Study on Subcritical and Supercritical Organic Rankine Cycle Applications for Exhaust Waste Heat Recovery
Waste heat recovery by means of Organic Rankine Cycle is a promising technology for the recovery of engine exhaust heat. However, it is complex to find out the optimum cycle conditions with appropriate working fluids to match exhaust gas waste heat due to its high temperature. Hence, this paper focuses on comparing subcritical and supercritical ORC conditions with eight working fluids on a combined diesel engine-ORC system. The model employs two ORC designs, Regenerative-ORC and Pre-Heating-Regenerative-ORC respectively. The thermodynamic calculations rely on the first and second law of thermodynamics, thermal efficiency and exergy destruction factors are the fundamental parameters evaluated. Additionally, in this study, environmental and safety, GWP (Global Warming Potential) and ODP (Ozone Depletion Potential), characteristic of the refrigerants are taken into consideration as evaluation criteria to define the optimal ORC configuration and conditions. Consequently, the study’s outcomes reveal that supercritical ORCs with alkane and siloxane are more suitable for high-temperature exhaust waste heat recovery in contrast to subcritical conditions.