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![A cross-flow turbine developed by Ocean Renewable Power Company being prepared for an open-water test [25] (photo from Ocean Renewable Power Company, NREL 24507).](profile/Yi-Hsiang-Yu/publication/280222640/figure/fig8/AS:340126577250318@1458103903428/A-cross-flow-turbine-developed-by-Ocean-Renewable-Power-Company-being-prepared-for-an.png)
A cross-flow turbine developed by Ocean Renewable Power Company being prepared for an open-water test [25] (photo from Ocean Renewable Power Company, NREL 24507).
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Marine hydrokinetic power generation is a relatively new type of renewable generation. Its predecessors, such as wind power generation, hydropower plant generation, geothermal generation, photovoltaic generation, and solar thermal generation, have gained a lot of attention because of their successful implementation. The successful integration of re...
Citations
... The former two are current-based, often referred to as Current Energy Converters (CECs), while the latter, wave-based, is known as Wave Energy Converter (WEC) hydrokinetic power. Both CECs and WECs offer a diverse array of configurations, design sizes, electrical generation capacities, and foundation types [4,5]. Some CEC designs bear a resemblance to conventional small-scale sub-aqueous wind turbines, boasting efficiency levels between 50% and 59%, while certain WEC devices exhibit estimated efficiencies surpassing 70% [6]. ...
Marine hydrokinetic (MHK) devices hold the promise of expanding renewable energy production by tapping into the power of waves and currents for electricity generation. However, these devices remain in the developmental stage, necessitating research to understand their environmental impacts, lower operational costs, and prevent equipment failures. In this study, we investigate various MHK array configurations to gain insights into their effects on wave patterns, water flow, and sediment conditions, considering both short-term and long-term morphodynamic changes under average and extreme conditions in shallow offshore environments. Our objectives encompass understanding the influence of mean and extreme environmental conditions on MHK devices, evaluating their impact on the bathymetry of the ocean floor, and exploring the role of different array configurations in morphodynamic evolution. Our findings, based on modeling these devices as static lumps, reveal that sediment erosion downstream of MHKs increases by 50% after one year of average conditions. When accounting for the absorption of 30% of the energy by MHK devices, downstream sediment deposition surges by almost 125%. Moreover, alterations in MHK arrays, such as spacing, size, and number, result in noticeable changes in sedimentation magnitudes during storm conditions. While long-term mean wave conditions have minimal effects on sedimentation, extreme wave conditions, akin to large storm events, bring about significant alterations in ocean floor bathymetry, potentially leading to costly maintenance of the MHK arrays. Our research provides a valuable framework for site analysis, enabling the estimation of maintenance needs and the optimization of array configurations to minimize sedimentation-related issues.
... The main advantages of underwater turbines over wind turbines are their discretion and the predictability of energy production, which is not subject to seasonal variability. It is also estimated that the specific mass density of water is 1000 times that of the air (Muljadi and Yu, 2015). ...
Payment consequentiality should improve the validity of welfare estimates in stated preference surveys according to a growing body of research. In this paper, we study whether the type of amounts (precision, parity) that composes the cost vector affects payment consequentiality. Our experiment consists in a binary choice survey on renewable energy where the cost amounts range between 0.5 and 25 euros. For small amounts, we find that precision increases payment consequentiality. For larger amounts, even numbers perform better than odd numbers. Our results suggest that the type of cost amount (e.g., even/odd, general/precise) should be carefully considered by the analyst.
... The performance of the power take-off (PTO) depends upon the control topology used. A passive control system is easy to implement but it cannot absorb the maximum power [3]. The reactive control topologies are able to absorb most of the wave power, but the physical limits of the WEC pose a limitation in such control strategies [4]. ...
... where n = [1,2,3] is the branch number and N series shows the total number of series connected cells in a module. As the first branch capacitance is voltage dependent and for a positive applied voltage, the current in that branch can be calculated by (26). ...
The unceasing oscillations of ocean waves have potential energy, which can be converted to useful electrical energy with the help of linear generators. But these oscillating waves have intermittent power, which pose a major challenge for a grid connection. As a solution to this problem, a supercapacitor is proposed for short-term energy storage for smoothing out the fluctuation. A complete grid tied wave-to-wire system is modelled in the MATLAB/Simulink environment, which comprises an Archimedes wave swing wave energy converter, a permanent magnet linear generator, voltage source converters, and a supercapacitor. Converters are controlled to absorb the maximum power from the waves and to minimize the generator losses by controlling the d- and q-axis currents. An improved control strategy is proposed to keep the dc-link and the point of common coupling voltages at a fixed level.
... In this paper, we mainly focused on permanent magnet synchronous generators (PMSG) based MHK generation system [16]. Due to the electro-mechanical coupling between generator and rotating components, the vibrations of the drivetrain induced by an imbalance fault in the blade will modulate the current signals of the generator, considering the transition from current to power (i.e., P=V * I), making it possible to use generator power signals to conduct blade fault prognosis. ...
... p(x k+T |z 1:k ) = p(x k |z 1:k ) k+T g=k+1 p(x g |x g−4:g−1 )dx k (16) When the state of the ith particle at a future time instant k+ m reaches a threshold, the RUL is calculated by the particle to be the time between now and that future time instant, denoted as RU L i k . When all the particle reach the threshold, the PDF of the RUL p(RU L k |z 1:k ) at current time instant k can be obtained by: ...
Marine hydrokinetic (MHK) turbines extract renewable energy from harsh marine environments, where biofouling and corrosion acting on turbine blades will affect system performance and lead to progressively increasing damages. Thus, accurately estimating a blade's remaining useful life (RUL) is important to achieving condition-based maintenance to ensure secure and reliable operations of MHK turbines, and the reduced cost of hydrokinetic power. In this paper, we propose a new RUL estimation method based on adaptive neuro-fuzzy inference system (ANFIS) and particle filtering (PF) approaches, establishing a relationship between blade imbalance faults and the produced power signal. The ANFIS is trained via historical failure data, and it constitutes with a m-order hidden Markov model to describe the fault propagation process. The high-order particle filter uses this Markov model to predict RUL in the form of a probability density function through collected normalized time series data. Results demonstrate the strong potential of the proposed approach for MHK turbine lifetime prediction.
... OSCILLATING WATER COLUMN WAVE EN-ERGY DEVICE[6] ...
Wave energy converters (WECs) are often subject to large displacements during operating conditions. Hence, nonlineari-ties present in numerical methods to estimate the performance of WECs must be considered for realistic predictions. These large displacements occur when the device operates on resonant conditions , which results in maximum energy conversion. The system dynamics are usually simulated via time domain models in order to being able to capture nonlinearities. However, a high computational cost is associated with those simulations. Alternatively, the present work treats the nonlinearities in the frequency domain via Statistical Linearization (SL). The SL results are compared to the Power Spectrum Density (PSD) of time domain simulations to verify the reliability of the proposed method. In this regard, the work initiates with the derivation of the governing equations of the air-chamber and the Oscillating Water Column (OWC). Then, the SL technique is presented and applied. The SL results show a satisfactory agreement for the system dynamics, mean surface elevation, mean pressure, and mean power compared to time domain simulations. Also, the SL technique produces a rapid estimation of the response, which is an effective approach for the evaluation of numerous environmental conditions and design, and further optimization procedures.
... Active power control is one of the main requirements in the daily management of any electrical systems. The aim of this control is to monitor the variation of the active power and to keep it within the limits prescribed by the standards [1][2][3][4]. The problem becomes more complex when dealing with an interconnected system [5][6]. ...
Active power balance and frequency control are important tasks in the daily management of a power system. With the integration of several microgrids in the modern power system, the balancing of sources of energy has become a major concern for electrical power engineers and researchers worldwide. New power systems require more flexibility in optimization and control design to ensure their ability to maintain the balance between generation and load of the system. The present paper discusses an optimal control design for minimization of the power flow in tie-lines and frequency deviations in the microgrid, which will lead to power balance between the generation and load demand of the system. The system being studied consists of two microgrids, each made up of a wind farm, conventional power system (large hydro or thermal plant), photovoltaic system, battery energy storage system and the system load. Optimal control theory is applied to control the power flow between two microgrids. The Matlab environment is used for simulations.
... It is this rotational motion that is used to generate electrical power without the need for dams. Because of their similarity with wind turbines [10], they will not be discussed in detail here. ...
It is well known that wind and hydropower are the most dominant renewable energy sources available. In fact, hydropower is the most dominant but wind is the fastest growing segment of the renewable energy industry. The latter has a consistent double digit growth rate over the past decade. There is also renewable energy from ocean resources including tides, tidal currents, and waves that are considered in this chapter. It is common knowledge that almost all available electrical power in the world is generated with one type of turbine or another. Therefore, there is sufficient space dedicated to analysis of turbines. The goal of the chapter is to provide basic fluid dynamics analyses of common energy converters including turbines used for renewable energy generation such as hydropower and wind sources as well as devices based on vortex induced motions. The chapter also provides a general overview of renewable energy from fluid motion.
... Various types of marine hydrokinetic generators have been explored, and some of have been commercialized. [4][5]. A typical tidal generator can be mounted on the bottom of an estuary, and its shape and structure are similar to that of a Savonius wind turbine generator. ...
... This type of control is often used in variable-speed wind turbine generation and has been proven successful. The control algorithm can be implemented by using a prescribed power-speed lookup table as shown in equations (4)(5). Note that under normal circumstances, the value of K gain is constant at one per unit. ...
This chapter starts by bringing a summary of the analytical dynamics of mechanical systems with mass varying explicitly with time and position. The extended Lagrange’s equations for such systems are re-analysed and simpler forms are derived. Hamiltonian’s formulations for non-material volumes are discussed. Examples are worked out: (i) a two-degrees of freedom variable mass system and (ii) a one-degree of freedom model of an oscillating water column excited by incoming free surface waves or by parametric excitations caused by motions imposed to the pipe. Then, the nonlinear response of the water column oscillator driven by random free surface waves is assessed by statistical methods.
