Capturing the tidal energy is one of the ways of tapping natural and renewable energy which do not involve the cost of working fluid/ fuel. The present work focuses on some of the feasibility aspects of setting up of major tidal power plants along the seacoast. Besides, the present study synergizes on methods of estimating the power-producing capacities in regions along the seacoast. Estimation of power-producing capacities, calendar month-wise, and lunar month-wise gave handy information. Also, the estimation of power-producing capacities of different regions along a location gave clarity on the probable regions of interest for producing power simultaneously. A comparison of the estimates with the details of the literature authenticated the study. A discussion of producing more tidal power in specific locations gave insights into the aspects that may have been ignored in the literature. Geographic restrictions along the local seacoast like identifying the security-sensitive regions rationalized the estimating procedures. The paper includes a discussion of various factors that address the feasibility concerns. The study supposedly helps space exploration too.

In this study, an islanded microgrid system is proposed that integrates identical stacks of solid oxide fuel cell and electrolyzer to achieve a thermally self-sustained energy storage system. Thermal management of the SOEC is achieved by use of heat from the SOFC with a heat exchanger network and control strategies. While the SOFC meets the building electricity demand and heat from its electrochemical reactions is transferred to the SOEC for endothermic heat and standby demands. Each component is physically modelled in Simulink and ultimately integrated at the system level for dynamic analyses. The current work simulates a system comprised of a wind farm in Palm Springs, CA coupled with the SOEC (for H 2 generation), and an industrial building powered by the SOFC. Results from two-weeks of operation using measured building and wind data showed that despite fluctuating power profiles, average temperature and local temperature gradients of both the SOEC and SOFC were within desired tolerances. However, for severe conditions of wind power deficit, H 2 had to be supplied from previous windy days’ storage or imported.

This research, a part of more extensive research, presents pre-feasibility and unit sizing analysis of a hybrid system equipped with renewable energy resources in Tabriz, Iran (46°26/E, 38°06/N). This case study examines a GSM telecommunication station as a stand-alone load system. Renewable energy resources include photovoltaic (PV), a wind turbine as primary resources and fuel cell, and a battery stack as backup and energy storage systems, while an electrolyzer is used to provide the required hydrogen in the fuel cell system. Feasibility analysis and unit sizing are conducted based on climatic data such as solar irradiance and wind speed to derive an optimal model during the study. HOMER software is used to simulate the feasibility analysis, measure the size, and optimize the system. The results showed that the hybrid system performs cost-effectively. According to wind energy data and fuel-cell costs, sensitivity analysis is conducted. The load is a stand-alone GSM station that consumes 60kW per day with a maximum of 3.8kW per hour. This analysis showed that wind, PV, electrolyzer, battery, and fuel cells are not currently the best solutions. Shortly, according to improved prediction in fuel-cell technology, it is expected that this source as a backup will be the best option because it has decreased fuel-cell costs up to 65 percent. Some criteria such as size, application, and cost, have been mainly examined. These results provide excellent opportunities for this hybrid system. The result shows using fuel cells in a hybrid system is not affordable by considering current fuel cell price, and the main suggestion hybrid system configuration is PV, wind turbine, and battery, while for the nearby location of Tabriz by decreasing wind speed, using wind turbines is not feasible and more PV array should be added to the system.

Health condition monitoring in wind turbine motor plays an extremely important role, as these devices are highly in demand in the energy sector, especially in renewable energy and are vulnerable to both mechanical and electrical failures, more often. As such, timely identification of internal faults in these electrical devices goes a long way in productive operations by reducing the maintenance time and costs, i.e. such internal faults, if identified at an early stage, repaired or replaced timely will aid in reliable renewable energy supply. Taking this into consideration, automated continuous monitoring of wind turbine machine is a key to making this process more effective. A web application is built in the proposed research enabling quick monitoring of faults in wind turbine motor from a remote access workstation, like a control room. An experimental setup of wind turbine motor is made and data set of stator currents from both healthy and faulty conditions as well as the power spectral density from the motors were used for condition monitoring with a web interface application. Insulation failure in stator winding is a most commonly occurring electrical failure in machines. As such in the current research stator current features from the experimental machine are used for requirement analysis under both healthy and faulty operating conditions. Among the stator insulation failure most commonly occurring stator turn-to-turn faults are taken into consideration in the current research with percentage of insulation failure varying between 25% to 75%. Fault identification is done with the help of wavelet based artificial neural network analysis at the back end and the interface displays the details in the form of dashboards, with the program mainly featuring three dashboards for the unit, stator, rotor, and components in total. Using interactive visualizations, the user will be able to obtain more in-depth knowledge about the suspected faults in the system and its components, and help to take the necessary action. i.e. whether the wind turbine motor needed to be repaired or replaced depending on the vulnerability of the fault. The application also has been experimented with handheld devices by hosting the application on local host and tunneling it over the web. Interactive visualization also includes information about the working conditions of the electrical machine, such as balanced, unbalanced, and failure conditions. Thus internal electrical fault in a wind turbine induction machine can be remotely analyzed, checked and cure can be suggested with a proper online health condition monitoring system.

Conventional Fault Tree Analysis (FTA) suffers from a variety of shortcomings which must be considered in critical analysis. The main disadvantage of FTA is its inability to model the dynamic failure behaviors of the components. Accordingly, Dynamic Fault Tree Analysis (DFTA) has been proposed to overcome such limitation. In this study, first, Monte Carlo simulation (MSC) approach is used to handle internal calculations of dynamic gates. The second main weakness of common FTA is about handling the different types of uncertainties. Hence, in the second step of this study, a combined of fuzzy numbers and MCS has been proposed to overcome the limitation of FTA in dealing with uncertainties. The main purpose of this paper is a comparative study on differences between MCS and Fuzzy-Monte Carlo simulation (FMCS) approaches for solving DFTA of a typical mechanical system. From available literatures, our proposed approaches have been demonstrated on different renewable energy systems, as case studies, and results are discussed. A comparison between MCS and FMCS shows that the results of FMCS method are reasonable and more realistic. Finally, in the last section, conclusions and some of the future wok are proposed.

The purpose of this project was to explore the feasibility of powering a climate control system solely from a renewable energy source. The off-the-shelf cooling system components were taken from a ca. 1986 R-12 residential refrigerator and then reassembled onto a custom enclosure which was constructed to serve as the climate-controlled compartment. The enclosure design was purposefully simple: a rectangular shaped box constructed out of plywood and mounted on wheels together with a plexiglass door which was substituted for the front face. The overall design provided for enhanced mobility while also allowing for easy observation of the interior temperature via an interior-mounted, digital, commercial residential thermostat integrated into the control system. The system, nominally, is triggered by incident solar radiation; the initial set-point temperature was 21 °C. Compressor power was derived solely from renewable energy. Specifically, a pair of 100W 12V monocrystalline silicon photovoltaic solar panels was used to generate electricity which was subsequently stored in a deep-cycle battery. Under steady-state AC operation, the compressor draws approximately 2.1A. Due to system inefficiencies, the corresponding DC current draw is necessarily higher and approaches 22.3A. For a compressor duty cycle ranging from 50–100%, the current draw over a model 9 hr day would range from between 100.1–200.3 A-H. The lower limit is within the energy storage capacity for the fully-charged system, as currently designed.

Thermoelectric generator technology can be utilized as a renewable energy source and has untapped potential. Thermoelectric generators (TEGs) have been used by industry experts to make some thermodynamic processes slightly more efficient. However, TEGs can be operated in a manner that allows for greater energy production at a higher efficiency and in a stand-alone setting. This paper presents design and analysis of an innovative portable water-cooled thermoelectric generator apparatus. The apparatus can create clean energy using optimal heat transfer through the device. To reduce the amount of power lost to internal heat resistance, the device is cooled by a large body of water. Solar irradiation is the primary heat source for the TEGs and is absorbed using copper foil and high emissive paint. The temperature differential predicted during device operation was modeled using ANSYS. The ANSYS heat transfer model revealed that heat absorption and subsequent transfer to a body of water was possible without exceeding the operating parameters of the TEGs. Experimental results revealed that a 120°C temperature difference across the TEGs produced 12.5 V of electricity. Analysis of the water-cooled TEG prototype performance revealed that power production is possible, and the design has numerous applications.

In this study, we develop a load estimation method and an optimization tool for community-driven planning of rural electricity systems which aims to encourage stakeholder involvement in planning processes and reinforce the sustainability of small-scale electrification projects. Electricity demand is estimated through the bottom-up construction of load profiles based on devices used in three common rural end-use sectors. A cost minimization model is then implemented to determine the least-cost capacity composition that can be installed based on the load profile and energy availability. The energy sources modeled are small-scale wind, hydro, solar (photovoltaic), diesel, and battery. In the base case, which includes the three sectors equally, most of the optimal capacity (77%) is provided by renewable energy at an average levelized cost of electricity (LCOE) of $0.05/kWh for a notional village with 500 houses. The base case results are compared to the results when each sector is respectively favored. The results show that backup dispatchable generation and batteries can both be solutions to intermittent renewables, and the choice between the two appears to depend on the load shape. We also find that the base case results are not very sensitive to the CO 2 tax, suggesting that not only are renewables cost-competitive with or without the tax, but they also benefit economically from coupling with cheap fossil fuel generators.

Kuwait’s oil reserves include approximately 13 bn barrels of heavy oil, primarily located in the northern region of the country. The Lower Fars (LF) heavy oil development project aims to extract heavy oil from the Ratqa oil field. The US$7 bn project is being developed in phases, with the first phase expected to start in 2019 with a production rate of 60,000 Barrel of Oil Per Day (BOPD). This amount is planned to ramp up to 270,000 BOPD by 2030. The steam required for the Enhanced Heavy Oil Recovery (EHOR) process can be either generated by using conventional fuels or renewable energy resources, such as solar energy. The amount of steam required to recover a certain quantity of heavy oil depends on the value of Steam to Oil Ratio (SOR). The aim of this work was to determine the specifications of a parabolic trough collector field required to produce steam with the right properties to recover 270,000 BOPD from Lower Fars reservoir. The Industrial Process Heat (IPH) model of the System Advisor Model (SAM) software, developed by the National Renewable Energy Laboratory (NREL), was used for this purpose. The capital cost and the running cost of the project, as well as the Levelized Cost of Heat (LCOH), were also determined. The simulation was implemented on EuroTrough ET150 trough collectors and Schott PTR 70 receiving tubes. Different plant designs with different types of heat transfer fluids (HTF) including Therminol VP-1, Therminol 59, Therminol 66, Dowtherm Q, Dowtherm RP, and Caloria HT43 have been investigated.

Despite the potential for limitless clean energy, nuclear fusion is seldom discussed in conjunction with other alternative energy sources. Nonetheless, there is a small but strong amateur community dedicated to the research of nuclear fusion. If grown, this community may help facilitate more conversation, interest, and eventual research into nuclear fusion. An often-large barrier in independent fusion research is detection and quantification of reactions. This research outlines the common methods currently used for fusion detection in inertial electrostatic confinement (IEC) reactors and suggests an experiment to explore indirect methods of detection using Matlab code written for light emission analysis. Current indirect, or theoretical, methods of determining reaction rate are unreliable, as they do not consider all construction variables of the reactor. By measuring characteristics of the plasma to determine reaction rate, a more accurate indirect measurement method may be developed, allowing for a larger number of individuals to participate in nuclear fusion research.

Renewable energy sources and related conversion technologies are considered as the main solution for resolving the current issues related to global warming and environmental protection. Salinity gradient energy (SGE) is a source of renewable energy which can be defined as the Gibbs Energy of mixing when two solutions with different salinities mix together. The difference in the salinity of salt solutions is the main driving force of energy production by the SGE conversion technologies. One of the main conversion technologies of SGE is reverse electrodialysis (RED). In this technology the gradient between the concentrated and diluted salt solutions, the ions with a negative charge (anion) and positive charge (cation) pass through selective ion exchange membranes known as anion exchange membrane and cation exchange membrane. The driving force for diffusion of the ions is a function of the concentration gradient. The chemical potential of the salt solution is a function of the concentration of the salt solution and plays an important role in the Gibbs energy of mixing. The chemical potential of the salt solution is a thermodynamic property which is a function of the concentration and activity coefficient of the salt solution. The activity coefficient of the salt solution is a unique parameter which depends on the ionic strength of the solution and the type of ions in the salt solution. The salts with higher activity coefficient have a higher potential to be used in the SGE conversion process due to higher released Gibbs Energy during the mixing process. In this paper the thermodynamic model presented by Bromley [1], is used to calculate activity coefficient of 20 salts at different concentrations (0.01–6 molal). Two dimensionless parameters, Φ and Ψ, are defined as the ratio of activity coefficient and concentration between the concentrated and diluted solutions in 6 and 0.5 molal respectively. Using the dimensionless parameters, the theoretical open circuit voltage (OCV) of salt solutions in a RED cell is calculated. The salts are screened and ranked based on the activity coefficients and the theoretical open circuit voltage (OCV). The best salts are selected for use in a RED cell based on the activity coefficients and theoretical OCV. These alts could have potential for developing SGE storage systems in combination with renewable energy devices.

Enhancing the thermal conductivity of phase change materials (PCMs) is attracting attention for renewable energy applications such as solar, geothermal and wind energy. The use of energy storage can significantly improve the efficiency of renewable energy systems due to their intermittent nature. Latent heat thermal energy storage is a particularly attractive technique due to its high capacity can store energy at near constant temperature corresponding to the phase transition temperature of the PCMs. The present work aims to overcome this undesirable property of low thermal conductivity by manipulating metal fillers including nickel (Ni) nanoparticles/nanowires within the paraffin wax to improve its thermal property. In present work, a finite element method (FEM) was developed to obtain a fundamental understanding of the behavior of the Ni particles/wires under a uniform magnetic field by predefined magnetic pads. In the model, the Navier-Stokes equations were introduced as governing equations for the fluid field and the magnetic field was simulated by Maxwell’s equations. Then the motion of single Ni wire was modeled and the translation and rotational movements of the wire was studied in this paper.

In recent years, there has been a lot of interest in clean energy especially in solar energy leading to the construction of numerous photovoltaic (PV) panels around the world. These panels need to be inspected to make sure they produce the desired amount of electricity. There are many methods to inspect which are manual, semi-autonomous and fully autonomous. The manual and semi-autonomous already exist but the process is tedious and requires a lot of time and resources. In this paper, we propose a fully autonomous solution where the drone will be preprogrammed to follow certain waypoints inputted via GPS data. The drone is equipped with a thermal camera where the video is recorded for postprocessing. The video is processed offline in order to detect the panels using image processing techniques such as thresholding, binary, canny edge, hough transform, and others. The novelty of this paper is on proposing a fully integrated solution for PV panel detection using a drone; it paves a way for future applications involving machine and deep learning.

Norwegian industries are constantly assessing new technologies and methods for more efficient and safer maintenance in the aqua cultural, renewable energy, and oil and gas industries. These Norwegian offshore industries share a common challenge: to install new equipment and transport personnel in a safe and controllable way between ships, farms and platforms. This paper deploys the Moving Frame Method (MFM) to analyze ship stability moderated by a dual gyroscopic inertial device. The MFM describes the dynamics of the system using modern mathematics. Lie group theory and Cartan’s moving frames are the foundation of this new approach to engineering dynamics. This, together with a restriction on the variation of the angular velocity used in Hamilton’s principle, enables an effective way of extracting the equations of motion. This project extends previous work. It accounts for the dual effect of two inertial disk devices, it accounts for the prescribed spin of the disks. It separates out the prescribed variables. This work displays the results in 3D on cell phones. It represents a prelude to testing in a wave tank.

Renewable energy and natural gas are displacing coal and nuclear power in many parts of the world as sources of electricity. While, the environmental benefits of such changes seem clear, the impact on worker safety, especially in developed nations is less clear. Coal mining is a relatively dangerous occupation, though one that has grown significantly safer in recent decades. Manufacturing and installation of solar photovoltaic (PV) power may pose less risk to workers on a per hour basis, but the number of worker hours necessary to generate a Megawatt-hour of electricity is currently higher for solar PV than it is for coal-generated power. The implications for the overall occupational burden of accidental deaths and injuries has not been previously detailed. This paper presents the results of a Monte Carlo sensitivity analysis for changes in total worker injuries and injury rates under different assumptions for the future energy mix in developed nations. Projections from the Energy Information Agency (EIA) and other organizations together with documented productivity gains for the various energy industries provide test cases for this analysis. The analysis indicates that future occupational fatality and injury burden of the energy sector is highly dependent on improvements in safety in the expanding industries, while specific projections on the share of specific technologies is less critical. This result highlights the need to invest in occupational risk mitigation in these industries.

Using data series obtained by experiments at the Marine Renewable Energy Laboratory of the University of Michigan, a Data-Driven Model is constructed for further investigation of the Process Dynamics and Control System Design and Configuration. This will enable advances in hydrokinetic energy harvesting using Vortex Induced Vibrations (VIV) and galloping, or more generally, Flow Induced Oscillations (FIO). Typically in such energy converters, one or more multiple bluff bodies, such as cylinders are suspended on springs in a water flow (currents, tides, rivers). In commonly encountered flows, oscillations are induced to the bluff rigid bodies due to vortex shedding in their wake, or due to lift instabilities in galloping, or both. These phenomena are dependent on stiffness, damping, mass ratio and the resulting vortex shedding frequency. The experiments in the cases investigated generated position signal recordings for one or two cylinders used as bluff bodies in FIO in a cross-flow. The position signals are used to set up a dynamic model. The model equation helps in gaining insight into the dynamics and underlying physics of the modeled FIO and can be used for Control System Tuning and Verification.

A concept for an innovative wind turbine blade with an actively transformable twist distribution is presented. A simulation model demonstrates that adapting the blade twist distribution can increase the aerodynamic efficiency during partial-load operation. A blade concept consisting of a rigid spar that is surrounded by deformable modular shells is also proposed. The outer shells are assumed to be produced using additive manufacturing (AM) technology. Integrated features enabled by the AM process tune the stiffness, and thus the degree of flexibility for each surrounding segment. The unique local stiffness and the placement of actuators establishes a nonlinear twist angle distribution (TAD). An optimal design procedure is devised for setting the stiffness and actuator locations. It maximizes the aerodynamic efficiency for a discrete range of wind speed. The blade performance is quantified using data acquired from the National Renewable Energy Laboratory (NREL) Aerodyn software. A computer cluster is used to facilitate this process. It must consider the TAD for the range of wind speed that corresponds to the partial-load operation. The design procedure first establishes the TAD geometry based on the theoretical aerodynamic modeling. The TAD geometry is then passed to a mechanical design algorithm. At this point, the actuator positions are set, and the stiffness ratios of the adaptable shells are defined using the objective function. It minimizes the amount of deviation between the actual TAD and that found in the aerodynamic analysis. The free-shape TAD is determined in the final step. This is the shape of the blade when no actuation force is applied to the shells. This shape is then selected to minimize the amount of deflection needed to shape the TAD between its extreme positions. A case study demonstrates the ability of the blade and the proposed design process. The study indicates that a blade with five actuators can achieve the full range of TAD motion. The final solution shows that the adaptive TAD can increase the efficiency by 3.8 and 3.3%, respectively, at the cut-in and rated speeds.

Norway has an opportunity to harvest ocean wave energy through gyroscopic precession as an alternative source of renewable energy, within practical limitations. This research assesses the energy extracted by gyroscopic wave energy generators and their use to provide supplementary power to fish farms and lighting on oilrigs. This project implements the Moving Frame Method (MFM) in dynamics to model the extracted power from a gyroscopic wave energy generator. The MFM leverages Lie Group Theory, Cartan’s moving frames and a new notation from the discipline of geometrical physics. Continuing, the Principle of Virtual Work extracts the equations of motion from the structure of the Special Orthogonal Group. However, the MFM supplements its analysis with a novel application of the restriction on the variations of the angular velocities. This research extends previous work as follows: it accounts for motor torques, it opens a placeholder for buoyancy, and it solves the full 3D set of equations (without assuming negligible yaw). After showing how to obtain the suite of descriptive equations of motion, this project integrates them, however with a relatively simple integration scheme. To complete each step in the analysis, the rotation matrix is updated using the Cayley Hamilton Theorem and the Rodriguez formula. Finally, the results are displayed using the Web Graphics Library such that the actual numerical analysis and display happens on cell phones.

Tidal ocean power is a dependable and dense form of renewable energy which is a relatively underdeveloped field. This study optimizes a tidal turbine with respect to performance and economics, and then optimizes a farm to be economically feasible. It was determined that the southeastern portion of the Gulf Stream, Florida current, would be used for the tidal turbine system as it has some of the world’s fastest velocities and is relatively close to shore. The vertical axis designs were ruled out from extended research on turbine design for their lower efficiency in general. Only horizontal axis designs were tested in simulated environments. Using SolidWorks Flow Simulation and SolidWorks Simulation, turbine models were optimized and selected as having the potential for the greatest energy extraction. Static and fatigue analyses were conducted on the optimized models in order to prevent premature failure. Cost analysis was also performed on the turbine models and the model that had the lowest initial cost as well as the highest power generation was chosen for farm development. The optimized design produced reasonable amount of power considering varying velocities throughout the day having a diameter of about 30 m. Through fatigue analysis the optimized design also showed long enough lifetime so that a good return on investment can be acquired. The single optimized turbine was then placed in a farm, and the farm’s shape and arrangement were tested and optimized so that the best arrangement and distances between units could be found. It was found that a farm 1.25 kilometers by 20 kilometers consisting of 800 turbines would be optimal. The farm would produce an average of 249.33 megawatts for a profit of $294.88 million dollars annually. The farm would pay for itself in 7.12 years and have an expected life span of 26.1 years which was obtained through fatigue analysis.

This review focuses on modern energy attributes and to identify alternative energy source and technology that satisfy energy trilemma requirements. The results and findings of the study show that photovoltaic (PV) solar cells technologies have the potentials of satisfying the global energy quest if deployed more. This study x-rays the different PV cells technologies in terms of generation chronology, power conversion efficiencies (PCE), (EPBT), present status and outlook. This study harmonises many photovoltaic performance indexes from review as follow: PV module power conversion efficiencies (PCE) of solar cells: lab -mono-Si (26.7%), multi-Si (22.3%), CIGS (21.7%), for and CdTe (21.0%); commercial - mono-Si (17%), CdTe (16.0%); energy payback time (EPBT) in Europe, 1–1.5 years and 1.5–3.5 years for thin film and crystalline silicon PV systems, respectively, 3 months and 8 months for perovskite (PSC) and CdTe solar cells respectively. The price of PV has drastically declined from $76/W in 1997 to $0.3/W in 2015. By 2050 and 2100, PV solar technology is expected to provide 20% and over 60% of the world’s energy supply, respectively. This will account for 50% CO2 emissions reduction globally. The projections depend on further improvement on the performance indexes and lifetime, series resistance, and optical properties. CdTe technology performs better than other technologies at elevated temperature, hence, recommended for tropical regions.