Maximum Energy Extraction Research Articles

Recent Progress and Challenges in Plasmon‐Mediated Reduction of CO2 to Chemicals and Fuels

AbstractThe realization of the strong interaction of plasmonic nanostructures with electromagnetic radiation, subdiffraction‐limit field localization, and unusually high field enhancement enables immense opportunities to harness visible light in the field of photocatalysis. Plasmon‐induced energetic charge carriers allow the metal nanostructures to catalyze surface reactions with selective pathways that are rather a holy grail of thermal catalysis. An intriguing application of plasmonic photocatalysis includes sequestration of atmospheric CO2 by its conversion into value‐added chemical fuels, thus mimicking the process of natural photosynthesis and addressing the problem of rising global warming and energy demands. In this regard, plasmonic photocatalysts circumvent the fallacy of conventional semiconductor photocatalysts to harvest visible light and modulate the CO2 reduction reaction pathways to attain selectivity. This review discusses the primary concepts of plasmonic catalysis, emphasizing the recent developments to tackle the obstacles present in achieving efficient and selective CO2 reduction by exploring various multicomponent plasmonic nanostructures that can extract maximum energy to perform a function. Some of the challenges that need more attention to optimize productivity are addressed and an outlook for future avenues in this field is provided.

Numerical investigation of solar energy storage by a salt gradient solar pond in several Moroccan cities

Numerical investigation of solar energy storage by a Salt Gradient Solar Pond (SGSP) in several Moroccan cities (Marrakesh, Ouarzazate, Tangier and Ifrane) is presented in this paper. For this purpose, the SGSP considered is assimilated to an open parallelipedic cavity in which the vertical and bottom walls are thermally insulated. The one-dimensional numerical model developed in Python programming language is based on the energy balance of each SGSP zone in which the heat losses via the SGSP free surface are retained. The numerical results obtained from the model developed are satisfactorily compared and validated against those obtained experimentally and numerically from a literature study. According to the results of one year of the SGSP operation, the storage zone temperature and the energy stored in the SGSP located in Ouarzazate city are the highest and reach maximum values in July (about 128 °C and 146 MJ respectively). Moreover, comparisons between different mass flow rates (0.01 Kg/s, 0.05 Kg/s and 0.09 Kg/s) of heat exchanger placed in the storage zone show that the optimal one is 0.09 Kg/s as it ensures the maximum energy extraction.

Solar PV-Fed Multilevel Inverter With Series Compensator for Power Quality Improvement in Grid-Connected Systems

Power quality difficulties arise as a result of Renewable Energy Sources (RES) integrating with the grid. Voltage swell, sag, and harmonic distortion occur on the grid due to power quality issues, which have an impact on customers. An inexpensive series compensator, like the Dynamic Voltage Restorer (DVR), is the best solution for overcoming the aforementioned problems. In this article, a solar PV integrated DVR with a novel multilevel inverter is introduced to address the power quality issues in the grid. The main objective of the proposed work is to develop a DVR integrated with a 23-level multilevel inverter to enhance the power quality. In addition, an improved INC-MPPT technique is designed for the boost converter for maximum energy extraction from the solar PV modules. Despite numerous benefits of multilevel inverters, there exist several reliability challenges such as fewer component counts and reduced THD. The suggested topology can able to generate 23 levels of output voltage with asymmetrical DC sources. The MLI has several advantages such as a reduction in the overall component count, cost and size of the inverter. Additionally, a detailed mathematical analysis is presented for the rotating dq reference frame control. The dynamic performance of the DVR is evaluated with a balanced load and implemented experimentally. Simulation results of the proposed system are carried out using MATLAB/Simulink. The proposed system is implemented using a dSPACE controller with a laboratory hardware prototype and OPAL-RT real-time simulator setup as well. The results show that the design of the proposed system is more effective at compensating for voltage sag and improves the power quality significantly. The THD obtained at the grid side is lower, which is under IEEE standards.

A bound on energy extraction (and hairiness) from superradiance

The possibility of mining the rotational energy from black holes has far–reaching implications. Such energy extraction could occur even for isolated black holes, if hypothetical ultralight bosonic particles exist in Nature, leading to a new equilibrium state – a black hole with synchronised bosonic hair – whose lifetime could exceed the age of the Universe. A natural question is then: for an isolated black hole and at maximal efficiency, how large is the energy fraction ϵ that can be extracted from a Kerr black hole by the superradiant growth of the dominant mode? In other words, how hairy can the resulting black hole become? A thermodynamical bound for the total superradiance efficiency, ϵ≲0.29 (as a fraction of the initial black hole mass), has long been known, from the area law. However, numerical simulations exhibiting the growth of the dominant mode only reached about one third of this value. We show that if the development of superradiant instabilities is approximately conservative (as suggest by the numerical evolutions), this efficiency is limited to ϵ≲0.10, regardless of the spin of the bosonic field. This is in agreement with the maximum energy extraction obtained in numerical simulations for a vector field and predicts the result of similar simulations with a scalar field, yet to be performed.

Single-phase grid-connected PV system with golden section search-based MPPT algorithm

Maximum power point tracking (MPPT) is a technique employed for with variable-power sources, such as solar, wind, and ocean, to maximize energy extraction under all conditions. The commonly used perturb and observe (P&O) and incremental conductance (INC) methods have advantages such as ease of implementation, but they also have the challenge of selecting the most optimized perturbation step or increment size while considering the trade-off between convergence time and oscillation. To address these issues, an MPPT solution for grid-connected photovoltaic (PV) systems is proposed that combines the golden section search (GSS), P&O, and INC methods to simultaneously achieve faster convergence and smaller oscillation, converging to the MPP by repeatedly narrowing the width of the interval at the rate of the golden ratio. The proposed MPPT technique was applied to a PV system consisting of a PV array, boost chopper, and inverter. Simulation and experimental results verify the feasibility and effectiveness of the proposed MPPT technique, by which the system is able to locate the MPP in 36 ms and regain a drifting MPP in approximately 30 ms under transient performance. The overall MPPT efficiency is 98.99%.

Design, Analysis, and Fabrication of Water Turbine for Slow-Moving Water

Abstract The energy crisis of the modern era may be overcome by hydrokinetic energy, the most readily and free source of energy available, to provide basic electricity needs to remote and urban areas at a low cost. The kinetic energy of flowing water at low speed could be extracted effectively by designing an appropriate design of the blade, as the turbine’s performance is dependent upon the shape of its blade. In this study, the wind turbine model with some modifications was used to design a blade for the hydrokinetic turbine. The horizontal axis turbine model with propeller type configuration was selected for obtaining higher efficiency. The optimum hydrofoil was selected and designed with an optimal twist angle for the maximum energy extraction process. The model was designed in three-dimensional (3D) modeling software solidworks, and then the power analysis was carried out through numerical simulations using the commercial computational fluid dynamics package ansys fluent. The power output was analyzed with a different number of blades, and performance curves were generated for the most efficient system. The calculations exhibited that for 1.5 m/s rated speed of water with the rotor diameter of 0.6096 m provides the rated power of approximately 150 W at 110 RPMs. The power curve of the turbine was analyzed for the selection of an efficient Permanent Magnet Synchronous Generator, and a direct drive system was preferred to reduce the weight and losses. The turbine model was 3D printed for testing and experimentation. The analytical efficiency calculated was 30.52%, and the experimental efficiency achieved was 28.24%. This study shows that the optimum design of hydrokinetic turbines could be integrated into series to provide energy to remote areas where the construction of dams and other resources are not available.

Enzymatic pretreatment of steam-exploded birch wood for increased biogas production and lignin degradation

Lignocellulose is readily available biomass for biogas production; however, due to its rigid structure, it requires pretreatment to obtain a maximum energy extraction. In this study, steam explosion (SE) (220 °C and 10 minute retention time) has been employed to increase the biogas production potential from birch wood. Although the biogas production increased by over two times after SE, the SE of birch wood negatively affects the structure of C5/C6 sugars and doubled the concentration of non-degradable lignin in all the samples. In this work, SE birch wood has been further pretreated by novel lignin-degrading enzymes cocktail to convert lignin into degradable sugars and increase the biogas production rate. The proposed hybrid pretreatment could increase the biogas production by up to 25% (from 450.5 mL/g VS to 566 mL/g VS), and reduced the lignin concentration by up to 48%.

Nonlinear Predictive Control Method for Maximizing Wind Energy Extraction of Variable Speed Wind Turbines under Turbulence

Generally, wind turbines are controlled by Maximum Power Point Tracking (MPPT) strategies in order to achieve maximum power extraction below its rated value. But it is very difficult to adjust the rotor speed according to the highly fluctuating wind speed accurately and quickly, due to the large inertia of wind turbines, and therefore, the efficiency of wind energy extraction will never reach its theoretical maximum value. To address this problem, a new method has been developed in this paper which is totally different from the known classical methods. In this paper a wind speeds prediction for maximum wind energy extraction (MWEE) of variable-speed wind turbines (VSWTs) is presented. A nonlinear predictive control is developed by solving a nonlinear optimization problem to generate the optimal generator torque sequence and consequently the previewed rotor speeds with maximum wind energy extraction. A detailed explanation has been provided of how this new method works through a detailed block diagram; accurate algorithm and flowchart. The proposed nonlinear predictive method takes full advantage and the MWEE objective is confirmed by the simulation results compared to the classical TSR methods.

Short-Term Nacelle Orientation Forecasting Using Bilinear Transformation and ICEEMDAN Framework

To maximize energy extraction, the nacelle of a wind turbine follows the wind direction. Accurate prediction of wind direction is vital for yaw control. A tandem hybrid approach to improve the prediction accuracy of the wind direction data is developed. The proposed approach in this paper includes the bilinear transformation, effective data decomposition techniques, long-short-term-memory recurrent neural networks (LSTM-RNNs), and error decomposition correction methods. In the proposed approach, the angular wind direction data is firstly transformed into time-series to accommodate the full range of yaw motion. Then, the continuous transformed series are decomposed into a group of subseries using a novel decomposition technique. Next, for each subseries, the wind directions are predicted using LSTM-RNNs. In the final step, it decomposed the errors for each predicted subseries to correct the predicted wind direction and then perform inverse bilinear transformation to obtain the final wind direction forecasting. The robustness and effectiveness of the proposed approach are verified using data collected from a wind farm located in Huitengxile, Inner Mongolia, China. Computational results indicate that the proposed hybrid approach outperforms the other single approaches tested to predict the nacelle direction over short-time horizons. The proposed approach can be useful for practical wind farm operations.

Effect of shroud on the energy extraction performance of oscillating foil

A shrouded oscillating-foil turbine is proposed to augment the energy extraction performance. The oscillating foil undergoes combined plunging and pitching motion to convert the flow energy. A diffuser is introduced into the oscillating-foil-based turbine as the shroud. The speed-up and energy extraction performance of the turbine were assessed numerically. The effects of three cost-independent geometrical factors, namely shroud entrance width, shroud angle and streamwise distance between shroud and foil, and shroud sectional shape on energy extraction performance were investigated in detail. The optimal motion parameters for the shrouded oscillating-foil turbine were re-explored due to the altered flow field in the shroud. The results demonstrated that the maximum energy extraction efficiency of bare oscillating foil (0.336) can be augmented by 35.8% to 0.456 by appropriate arrangement of the shroud with a relative chord length of 0.8. The optimal motion parameters for the shrouded foil are slightly different from those of bare foil. The re-tuned motion parameters can further improve the efficiency to 0.47. Considering both the manufacturing cost of the shaped sections and their performance, it is more advantageous and attractive to use a flat plate as the shroud in engineering practices.

Experimental investigation on performance of a light weight solar receiver of a parabolic dish concentrator

The need to extract maximum energy from renewable resources has become quite significant in day-to-day life. Solar energy is an essential source to meet the ever-increasing demand for energy today and the potential ways are to use efficient solar dish concentrators. In the present work, an external type solar receiver in the form of spiral tube is developed with mild steel material and tested with Scheffler type parabolic dish concentrator. The experimental performance analysis is performed in the real atmospheric conditions and the energy efficiency of the receiver in open loop circulation mode is studied for a whole day. Water is used as the heat transferring fluid with 2 LPM as the flow rate. The receiver showed an average thermal energy efficiency of 43.7% with a peak value of 47% during a sunny day with average beam radiation of 743 W/m2 for a HTF flow rate of 2 LPM. The result shows that this receiver has potential to be used in the solar powered process heating application in the temperature range 30°C to 100°C.

Energy‐maximising moment‐based constrained optimal control of ocean wave energy farms

Successful commercialisation of wave energy technology inherently incorporates the concept of an array of wave energy converters (WECs). These devices, which constantly interact via hydrodynamic effects, require optimised control that can guarantee maximum energy extraction from incoming ocean waves while ensuring, at the same time, that any physical limitations associated with device and actuator systems are being consistently respected. This paper presents a moment-based energy-maximising optimal control framework for WECs arrays subject to state and input constraints. The authors develop a framework under which the objective function (and system variables) can be mapped to a finite-dimensional tractable quadratic program (QP), which can be efficiently solved using state-of-the-art solvers. Moreover, the authors show that this QP is always concave, i.e. existence and uniqueness of a globally optimal solution is guaranteed under this moment-based framework. The performance of the proposed strategy is demonstrated through a case study, where (state and input constrained) energy-maximisation for a WEC farm composed of CorPower-like WEC devices is considered.

Numerical Analysis of Wave Energy Extraction Performance According to the Body Shape and Scale of the Breakwater-integrated Sloped OWC

Research on the development of marine renewable energy is actively in progress. Various studies are being conducted on the development of wave energy converters. In this study, a numerical analysis of wave-energy extraction performance was performed according to the body shape and scale of the sloped oscillating water column (OWC) wave energy converter (WEC), which can be connected with the breakwater. The sloped OWC WEC was modeled in the time domain using a two-dimensional fully nonlinear numerical wave tank. The nonlinear free surface condition in the chamber was derived to represent the pneumatic pressure owing to the wave column motion and viscous energy loss at the chamber entrance. The free surface elevations in the sloped chamber were calculated at various incident wave periods. For verification, the results were compared with the 1:20 scaled model test. The maximum wave energy extraction was estimated with a pneumatic damping coefficient. To calculate the energy extraction of the actual size WEC, OWC models approximately 20 times larger than the scale model were calculated, and the viscous damping coefficient according to each size was predicted and applied. It was verified that the energy, owing to the airflow in the chamber, increased as the incident wave period increased, and the maximum efficiency of energy extraction was approximately 40% of the incident wave energy. Under the given incident wave conditions, the maximum extractable wave power at a chamber length of 5 m and a skirt draft of 2 m was approximately 4.59 kW/m.

A multi‐port MMC topology with reduced capacitor size for use in grid‐connected PV systems

AbstractIn this article, a novel multi‐port modular multilevel inverter topology is presented for grid‐connected photovoltaic systems, which feature a smaller capacitor size compared with its counterparts. In the proposed MMC topology, each submodule is an individual input port being fed by an independent PV array through a boost converter. This allows modularity of the proposed topology, easing its maintenance and facilitating its expansion for PV integration. Individual maximum power point tracking controllers are used to operate the boost converters in each submodule to extract maximum energy from their PV arrays under different radiation conditions. A model‐predictive control scheme is designed for regulating the proposed multi‐port MMC topology to inject the harvested solar power to the grid. This controller enables minimized circulating currents in the MMC arms and balanced capacitor voltages in the MMC submodules, while total harmonic distortion (THD) of injected current to the grid is kept within the limits. The proposed multi‐port MMC topology with model‐predictive control is validated under different radiation conditions for a grid‐connected PV system to indicate that the proposed topology has a desirable performance under different radiation conditions.

OPTIMISATION OF SOLAR PHOTOVOLTAIC SYSTEM EMPLOYING DISTRIBUTED MPPT CONTROL

This paper presents simulation and modeling with optimization and analysis in solar photovoltaic systems, as well as the role and potential of maximum power extraction with controller. Matrix calculations for grid inverters with data graphing, their functions, MPPT algorithm applications, user interface design for monitoring PV modules, and interaction with inverter and converter are all aided by simulations of renewable energy systems. It looks at how well they work on a single-phase grid with a PV system. Simulink model for solar energy conversion systems allows you to examine the performance of Photovoltaic cells, modules, arrays, Maximum Power Points and inverters. Controllers are being tracked when the environment and physical variables change. A distributed MPPT scheme, which allows adjustment of each DC-link voltage, may be adopted for PV systems to achieve maximum PV module usage and solar energy extraction. The pattern that has been developed allows for independent management of each DC-link voltage in order to track the MPP for each string of PV panels. For various operating circumstances, simulation results are provided.

Arduino Based Solar Tracking System for Energy Improvement of PV Solar Panel

Solar energy is a clean, easily accessible and abundantly available alternative energy source in nature. Getting solar energy from nature is very beneficial for power generation. Using a fixed Photovoltaic panels extract maximum energy only during 12 noon to 2 PM in Nigeria which results in less energy efficiency. Therefore, the need to improve the energy efficiency of PV solar panel through building a solar tracking system cannot be over-emphasized. Photovoltaic panels must be perpendicular with the sun in order to get maximum energy. The methodology employed in this work includes the implementation of an Arduino based solar tracking system. Light Dependent Resistors (LDRs) are used to sense the intensity of sunlight and hence the PV solar panel is adjusted accordingly to track maximum energy. The mechanism uses servo motor to control the movement of the solar panel. The microcontroller is used to control the servo motor based on signals received from the LDRs. The result of this work has clearly shown that the tracking solar panel produces more energy compared to a fixed panel.

Assessing Hydrokinetic Energy in the Mexican Caribbean: A Case Study in the Cozumel Channel

This paper presents a techno-economic assessment of hydrokinetic energy of Cozumel Island, where ocean currents have been detected, but tourist activities are paramount. The main objective of this research is to identify devices that have been used to harvest hydrokinetic power elsewhere and perform an economic analysis as to their implementation in the Mexican Caribbean. First, the energy potential of the area was evaluated using simulated data available through the HYCOM consortium. Then, for four pre-commercial and commercial turbines, technical and economic analyses of their deployments were performed. Socio-environmental constraints were reviewed and discussed. Three optimal sites were identified, with an average annual hydrokinetic energy density of 3–6 MWh/m2-year. These sites meet the socio-environmental requirements for marine kinetic energy harvesting. Of the turbines considered in the analysis, the best energy price/cost ratio is that of SeaGen device, with a maximum theoretical energy extraction of 1319 MWh/year with a Capacity Factor of 12.5% and a Levelised Cost of Energy (LCOE) of 1148 USD/MWh. Using this device, but assuming a site-specific design that achieves at least 25% of Capacity Factor, 20-year useful life, and a discount rate of 0.125, the LCOE would be 685.6 USD/MWh. The approach presented here can be applied for techno-economic analyses of marine turbines in other regions.

Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia

The peak period of an energy-generating wave is one of the most important parameters that describe the spectral shape of the oceanic wave, as this indicates the duration for which the waves prevail with respect to their maximum extractable energy. In this paper, a half-hourly peak wave energy period (TP) forecast model is constructed using a suite of statistically significant lagged inputs based on the partial auto-correlation function with an extreme learning machine model developed and its predictive utility is benchmarked against deep learning models, i.e., convolutional neural network (CNN/CovNet) and recurrent neural network (RNN) models and other traditional M5tree, Conditional Maximization based Multiple Linear Regression (MLR-ECM) and MLR models. The objective model (ELM) vs. the comparison models (CNN, RNN, M5tree, MLR-ECM, and MLR) were trained and validated independently on the test dataset obtained from coastal zones of eastern Australia that have a high potential for implementation of wave energy generation systems. The outcomes ascertain that the ELM model can generate significantly accurate predictions of the half-hourly peak wave energy period, providing a good level of accuracy relative to deep learning models in selected coastal study zones. The study establishes the practical usefulness of the ELM model as being a noteworthy methodology for the applications in renewable and sustainable energy resource management systems.

Dynamic Modeling and Performance Analysis of PMSG- based Variable Speed WTG: Case Study of Adama Wind Farm I, Ethiopia

In this paper, the performance of Permanent Magnet Synchronous Generator (PMSG) -based Variable Speed Wind Turbine Generator (WTG) at Adama Wind Farm I (WTG), connected to a grid is studied. To study the performance of the WTG, both machine and grid side converters are modeled and analyzed very well. On the machine side, maximum power point tracking (MPPT) for maximum energy extraction is done using the direct speed control (DSC) technique, which is linked with the optimal tip speed ratio for each wind speed value considered. On the grid side, dc-link voltage and reactive power flow to the grid are controlled. For this purpose, first, the simulation model of the system is prepared in MATLAB Simulink considering the dynamic mathematical model of the PMSG, and Wind Turbine Aerodynamic model using the user-defined function blocks. Then, the PI regulators designed for direct speed, torque (current) control, and dc-link voltage are employed in the model. Moreover, to study and analyze the behavior of the system in a variable speed operation, a wind speed starting from cut-in wind speed (3m/s) to the rated wind speed (11m/s) is applied in 4s. The simulation result of the existing system model shows that the actual values of performance variables correspond well with the analytical values of the system. In addition, the chosen control algorithms applied in the control system of the generator-side converter are hence verified.

Adaptive fractional order control of doubly fed induction generator based wind energy conversion system under uncertainty

Conventional fossil fuel sources are being reduced and simultaneously became more and more sources of considerable undesirable influences on the environment. In an attempt to expand renewable energy sources, wind energy is playing a significant role. A doubly fed induction generator as an alternative concept of different prevalent generators in wind power industry has a conspicuous efficiency improvement impact. There are nonlinear dynamics and many uncertainties in wind power plants, such as matched and mismatched disturbances and uncertainties of parameters. Designing a convenient controller to address these nonlinearities and uncertainties is a problematic task and has been the topic of much great research. Sliding mode control is a powerful nonlinear high-frequency switching controller, which has been widely applied. In a more specialized scope, combining fractional order calculus with controllers provides more degrees of freedom for responding to the demands of existing fractional dynamics of systems. To this regard, this paper presents an adaptive fractional-order terminal sliding mode controller to extract maximum energy from a wind turbine based doubly fed induction generator, which as the name of the controller implies is adaptive and robust against uncertainties, improves control accuracy, reduces chattering and mechanical stresses, and speeds up response time. A novel and unique sliding surface has been selected for this controller. Lumped uncertainties and switching control signal parameters have been estimated by adaptation laws. Maximized aerodynamic wind energy has been harvested by utilizing the proposed controller for the rotor side converter. The Lyapunov theorem is applied to guarantee the closed-loop system stability. Under normal conditions and in the presence of uncertainty and disturbance, the proposed method has been compared with SMC and a feedback linearization proportional integral controller.