A Multi-Objective Real-Coded Genetic Algorithm Method for Wave Energy Converter Array Optimization

2016 ◽  
Author(s):  
Chris Sharp ◽  
Bryony DuPont
Keyword(s):  
Genetic Algorithm ◽  
Wave Energy ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Energy Converter ◽  
Algorithm Comparison ◽  
Real Coded Genetic Algorithm ◽  
Array Optimization ◽  
The Many ◽  
Promising Source

For consumers residing near a coastline, and especially for those living or working in remote coastal areas, ocean energy is a promising source of electricity that has the potential to serve as a primary energy source. Over the last decade, many wave energy converter (WEC) designs have been developed for extracting energy from the ocean waves, and with the progression of these devices’ ocean deployment, the industry is looking ahead to the integration of arrays of devices into the grid. Due to the many factors that can potentially influence the configuration of an array (such as device interaction and system cost) optimal positioning of WECs in an array has yet to be well understood. This paper presents the results of a novel real-coded genetic algorithm created to determine ideal array configurations in a non-discretized space such that both power and cost are included in the objective. Power is calculated such that the wave interactions between devices are considered and cost is calculated using an analytical model derived from Sandia National Laboratory’s Reference Model Project. The resulting layouts are compared against previous array optimization results, using the same constraints as previous work to facilitate algorithm comparison. With the development of an algorithm that dictates device placement in a continuous space so that optimal array configurations are achieved, the results presented in this paper demonstrate progression towards an open-source method that the wave energy industry can use to more efficiently extract energy from the ocean’s vast supply through the creation of array designs that consider the many elements of a WEC array.

scholarly journals Techno-Economic Optimisation for a Wave Energy Converter via Genetic Algorithm

2020 ◽  
Vol 8 (7) ◽  
pp. 482 ◽  
Author(s):  
Sergej Antonello Sirigu ◽  
Ludovico Foglietta ◽  
Giuseppe Giorgi ◽  
Mauro Bonfanti ◽  
Giulia Cervelli ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Wave Energy ◽  
Capital Expenditure ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Width Ratio ◽  
Energy Converter ◽  
Essential Condition ◽  
Cost Of Energy ◽  
The Cost

Although sea and ocean waves have been widely acknowledged to have the potential of providing sustainable and renewable energy, the emergence of a self-sufficient and mature industry is still lacking. An essential condition for reaching economic viability is to minimise the cost of electricity, as opposed to simply maximising the converted energy at the early design stages. One of the tools empowering developers to follow such a virtuous design pathway is the techno-economic optimisation. The purpose of this paper is to perform a holistic optimisation of the PeWEC (pendulum wave energy converter), which is a pitching platform converting energy from the oscillation of a pendulum contained in a sealed hull. Optimised parameters comprise shape; dimensions; mass properties and ballast; power take-off control torque and constraints; number and characteristics of the pendulum; and other subcomponents. Cost functions are included and the objective function is the ratio between the delivered power and the capital expenditure. Due to its ability to effectively deal with a large multi-dimensional design space, a genetic algorithm is implemented, with a specific modification to handle unfeasible design candidate and improve convergence. Results show that the device minimising the cost of energy and the one maximising the capture width ratio are substantially different, so the economically-oriented metric should be preferred.

Optimization of a Torus-Shaped Wave Energy Converter Attached to a Hinged Arm

2021 ◽  
Author(s):  
Mojtaba Kamarlouei ◽  
Thiago S. Hallak ◽  
Jose F. Gaspar ◽  
Miguel Calvário ◽  
C. Guedes Soares
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Prime Mover ◽  
Optimal Result ◽  
Energy Converter ◽  
Sea State ◽  
Absorbed Power ◽  
Spring System

Abstract This paper presents the adaptation of a torus wave energy converter prime mover to an onshore or nearshore fixed platform, by a hinged arm. An optimization code is developed to obtain the best torus and arm geometry, as well as the power take-off parameters, taking as objective function the maximization of total wave absorbed power. In this paper, the power take-off system is modelled as a simplified damper and spring system, where the parameters are optimized for the phase control of the wave energy converter in each sea state, whereas the optimization process is performed with a genetic algorithm. Finally, the optimal result for the productive sea state indicates that the absorbed power is relatively considerable while a better survivability performance is expected from a torus wave energy converter compared to a conventional truncated prime mover.

scholarly journals Deep Learning for Wave Energy Converter Modeling Using Long Short Term Memory

2021 ◽  
Author(s):  
Seyed Milad Mousavi ◽  
Majid Ghasemi ◽  
Mahsa Dehghan Manshadi ◽  
Amir Mosavi
Keyword(s):  
Wind Speed ◽  
Output Power ◽  
Wave Energy ◽  
Short Term Memory ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Energy Converter ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory

Accurate forecasts of ocean waves energy can not only reduce costs for investment but it is also essential for management and operation of electrical power. This paper presents an innovative approach based on the Long Short Term Memory (LSTM) to predict the power generation of an economical wave energy converter named “Searaser”. The data for analyzing is provided by collecting the experimental data from another study and the exerted data from numerical simulation of searaser. The simulation is done with Flow-3D software which has high capability in analyzing the fluid solid interactions. The lack of relation between wind speed and output power in previous studies needs to be investigated in this field. Therefore, in this study the wind speed and output power are related with a LSTM method. Moreover, it can be inferred that the LSTM Network is able to predict power in terms of height more accurately and faster than the numerical solution in a field of predicting. The network output figures show a great agreement and the root mean square is 0.49 in the mean value related to the accuracy of LSTM method. Furthermore, the mathematical relation between the generated power and wave height was introduced by curve fitting of the power function to the result of LSTM method.

scholarly journals Kinerja Model Fisik Konverter Energi Ombak Rangkaian Gear Searah pada Periode Ombak yang Bervariasi

2016 ◽  
Vol 22 (2) ◽  
pp. 71 ◽  
Author(s):  
Masjono Muchtar ◽  
Salama Manjang ◽  
Dadang A Suriamiharja ◽  
M Arsyad Thaha
Keyword(s):  
Physical Model ◽  
Wave Energy ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Wave Period ◽  
Physical Model Test ◽  
Energy Converter ◽  
Wave Flume ◽  
Period Variations ◽  
Hydraulics Laboratory

To date there were few research on the effect of non-linearity properties of the ocean waves on the performance of wave energy converter (WEC), which uses a series of unidirectional gear. One such parameter is the variation of wave period. The influence of wave period variations on the performance of physical model of the wave energy converters have been investigated at the Hydraulics Laboratory, Department of Civil Engineering, Hasanuddin University Indonesia. This WEC physical model was fabricated and assembled at Politeknik ATI Makassar Indonesia. The investigation steps consists of physical model development, physical model investigation at wave flume prior to the wave period  variation, measuring input output parameters of the physical model under test and empirical model formulation based on observed data analysis. Physical model test carried out on the wave flume at the Hydraulics Laboratory of the Department of Civil Hasanuddin University, at a water depth of 25 cm, wave height between 5-9 cm and wave period between 1.2 - 2.2 seconds. Investigation result based on flywheel radial speed (RPM) and torque (Nm) indicated that calculated harvested power was inversely proportional with the wave period. The longer the period of the waves, the energy produced is getting smaller. The derived empirical formula was y = -85.598x + 208.53 and R² = 0.8881. Y is energy produced (Watt) and X is the wave period (Second). Formulations generated from this study could be used as a reference for future research in dealing with wave period variations on a design one way gear wave energy converter as a source of renewable energy.

scholarly journals Nonlinear PTO Effect on Performance of Vertical Axisymmetric Wave Energy Converter Using Semi-Analytical Method

2017 ◽  
Vol 24 (s3) ◽  
pp. 49-57 ◽  
Author(s):  
Ming Liu ◽  
Hengxu Liu ◽  
Xiongbo Zheng ◽  
Hailong Chen ◽  
Liquan Wang ◽  
...  
Keyword(s):  
Wave Energy ◽  
Analytical Method ◽  
Renewable Energy Sources ◽  
Single Point ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Energy Converter ◽  
Advantages And Disadvantages ◽  
Axisymmetric Wave ◽  
Efficient Power

Abstract The wave energy, as a clean and non-pollution renewable energy sources, has become a hot research topic at home and abroad and is likely to become a new industry in the future. In this article, to effectively extract and maximize the energy from ocean waves, a vertical axisymmetric wave energy converter (WEC) was presented according to investigating of the advantages and disadvantages of the current WEC. The linear and quadratic equations in frequency-domain for the reactive controlled single-point converter property under regular waves condition are proposed for an efficient power take-off (PTO). A method of damping coefficients, theoretical added mass and exciting force are calculated with the analytical method which is in use of the series expansion of eigen functions. The loads of optimal reactive and resistive, the amplitudes of corresponding oscillation, and the width ratios of energy capture are determined approximately and discussed in numerical results.

scholarly journals Wave-Powered AUV Recharging: A Feasibility Study

2019 ◽  
Author(s):  
Blake P. Driscol ◽  
Andrew Gish ◽  
Ryan G. Coe
Keyword(s):  
Wave Energy ◽  
Autonomous Underwater Vehicles ◽  
Electrical Power ◽  
Ocean Waves ◽  
Underwater Vehicles ◽  
Geographic Region ◽  
Wave Energy Converter ◽  
Energy Converter ◽  
Energy Needs ◽  
The U.S

Abstract The aim of this study is to determine whether multiple U.S. Navy autonomous underwater vehicles (AUVs) could be supported using a small, heaving wave energy converter (WEC). The U.S. Navy operates numerous AUVs that need to be charged periodically onshore or onboard a support ship. Ocean waves provide a vast source of energy that can be converted into electricity using a wave energy converter and stored using a conventional battery. The Navy would benefit from the development of a wave energy converter that could store electrical power and autonomously charge its AUVs offshore. A feasibility analysis is required to ensure that the WEC could support the energy needs of multiple AUVs, remain covert, and offer a strategic military advantage. This paper investigates the Navy’s power demands for AUVs and decides whether or not these demands could be met utilizing various measures of WEC efficiency. Wave data from a potential geographic region is analyzed to determine optimal locations for the converter in order to meet the Navy’s power demands and mission set.

Experimental Investigation of Irregular Wave Cancellation Using a Cycloidal Wave Energy Converter

2012 ◽  
Author(s):  
Stefan G. Siegel ◽  
Casey Fagley ◽  
Marcus Römer ◽  
Thomas McLaughlin
Keyword(s):  
Wave Energy ◽  
Deep Ocean ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Irregular Waves ◽  
Energy Converter ◽  
Irregular Wave ◽  
Wave Measurements ◽  
Wave Heights ◽  
Significant Wave Heights

The ability of a Cycloidal Wave Energy Converter (CycWEC) to cancel irregular deep ocean waves is investigated in a 1:300 scale wave tunnel experiment. A CycWEC consists of one or more hydrofoils attached equidistant to a shaft that is aligned parallel to the incoming waves. The entire device is fully submerged in operation. Wave cancellation requires synchronization of the rotation of the CycWEC with the incoming waves, as well as adjustment of the pitch angle of the blades in proportion to the wave height. The performance of a state estimator and controller that achieve this objective were investigated, using the signal from a resistive wave gage located up-wave of the CycWEC as input. The CycWEC model used for the present investigations features two blades that are adjustable in pitch in real time. The performance of the CycWEC for both a superposition of two harmonic waves, as well as irregular waves following a Bretschneider spectrum is shown. Wave cancellation efficiencies as determined by wave measurements of about 80% for the majority of the cases are achieved, with wave periods varying from 0.4s to 0.75s and significant wave heights of Hs ≈ 20mm. This demonstrates that the CycWEC can efficiently interact with irregular waves, which is in good agreement with earlier results obtained from numerical simulations.

Robotized Stacking of the Uppsala University Wave Energy Converter Generator Stator

2014 ◽  
Author(s):  
Erik Hultman ◽  
Marcus Linder ◽  
Mats Leijon
Keyword(s):  
Wave Energy ◽  
Industrial Robot ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Energy Converter ◽  
Large Wave ◽  
Assembly Method ◽  
Assembly Accuracy ◽  
High Flexibility ◽  
Robot Cell

A technology for renewable energy conversion from ocean waves has been developed at Uppsala University. The concept is intended for large Wave Energy Converter farms and thus requires large series production lines. For this technology to be competitive on the global energy market, it is necessary to keep down the manufacturing costs. Assembly automation will therefore be important, especially if the production should be kept in industrialized countries. Stacking of the stator for the Wave Energy Converter generator is an essential task during the assembly process. The operation is repetitive and time-consuming, requires high precision and large reach and can thus be suitable for industrial robot automation. This paper presents a robot cell design for robotized automation of the stator stacking for an Uppsala University Wave Energy Converter generator. Prototype equipment has been developed and validated in an experimental stacking setup. From these experiments, it has been indicated that the proposed automation solution can substantially reduce the stacking cycle time while assuring sufficient assembly accuracy. The main advantages with the proposed assembly method are the high flexibility, the ability to lift and assemble multiple stator sheets at the same time, the ability to calibrate to the exact position of the stator sheet to be lifted and the high stacking accuracy result. The suggested robot cell is likely to be possible to adjust for stacking of other stator designs as well.

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