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Major investment of renewable energy currently focuses on wind and solar, which are commercially mature. However, there is no large commercial application of wave energy, despite more than four decades of continuous development. Previous research has indicated that wave energy could supply a significant portion of world electricity consumption. Therefore, it is critical to incentivize the utilization of wave energy. The hybrid energy farms, combining wave energy with wind energy, have been considered as one of the most viable solutions to promote mature grid integration of wave energy. However, combining wind and wave requires the identification of adequate locations for both resources and development of layout optimization algorithms capable of handling the complexity of wave wakes. Wave wake analysis has been one of the biggest hurdles for the development of recursive wave farm layout optimization algorithms due to the required extremely time consuming computation processes for each wave wake iteration. This research proposes a new approach by preprocessing the wave wakes beforehand the actual execution of the recursive layout optimization algorithm. This proposed preprocessed wave wake model can be integrated with the different optimization algorithms to identify optimal layouts for hybrid wave-wind farms. The new approach was tested in two selected locations in the Gulf of Mexico with over 36 years (1979–2015) of historical meteorological data. It identifies locations capable of sustaining commercially viable levels of wind and wave energy while simultaneously avoiding risk from extreme oceanic conditions that in the past have damaged or destroyed wave energy converters. Although the two locations have different meteorological conditions, the new approach was able to identify layouts with promising results in both locations. Results indicated that the selected locations could produce very good power output with a wave-wind hybrid energy farm, and most wave and wind energy devices generated capacity factor with values higher than commercial threshold limits.
Francisco Haces-Fernandez; Hua Li; David Ramirez. A layout optimization method based on wave wake preprocessing concept for wave-wind hybrid energy farms. Energy Conversion and Management 2021, 244, 114469 .
AMA StyleFrancisco Haces-Fernandez, Hua Li, David Ramirez. A layout optimization method based on wave wake preprocessing concept for wave-wind hybrid energy farms. Energy Conversion and Management. 2021; 244 ():114469.
Chicago/Turabian StyleFrancisco Haces-Fernandez; Hua Li; David Ramirez. 2021. "A layout optimization method based on wave wake preprocessing concept for wave-wind hybrid energy farms." Energy Conversion and Management 244, no. : 114469.
For a heaving point absorber to perform optimally, it has to be designed to resonate to the prevailing ocean wave period. Hence, it is important to make the ocean wave data analysis to be as accurate as possible. In this study, existing wave condition data is used to investigate the effect of the temporal resolution (daily vs. hourly) of wave data on the design of the device and power capture. The temporal resolution effect on the estimation of ocean wave resource theoretical potential is also investigated. Results show that the temporal resolution variation of the ocean wave data affects the design of the device and its power capture, but the theoretical power resource assessment is not significantly affected. The device designed for the Gulf of Mexico is also analyzed with wave condition in Oregon, which has about 40 times the wave resource theoretical potential compared to the Gulf of Mexico. The results confirmed that a device should be designed for a specific location as the device performed better in the Gulf of Mexico, which has much less ocean wave resource theoretical potential. At last, the effect of the design, diameter and season (summer and winter) on the power output of the device is also investigated using statistical hypothesis testing methods. The results show that the power capture of a device is significantly affected by these parameters.
Tunde Aderinto; Hua Li. Effect of Spatial and Temporal Resolution Data on Design and Power Capture of a Heaving Point Absorber. Sustainability 2020, 12, 9532 .
AMA StyleTunde Aderinto, Hua Li. Effect of Spatial and Temporal Resolution Data on Design and Power Capture of a Heaving Point Absorber. Sustainability. 2020; 12 (22):9532.
Chicago/Turabian StyleTunde Aderinto; Hua Li. 2020. "Effect of Spatial and Temporal Resolution Data on Design and Power Capture of a Heaving Point Absorber." Sustainability 12, no. 22: 9532.
Different concepts and methods have been proposed and developed by many researchers to harvest ocean wave energy. In this paper, a new self-adjustable wave energy converter concept is presented, which changes its inertia through ballasting and de-ballasting using sea water. The trigger of ballasting and de-ballasting is controlled by the critical wave period. Therefore, the self-adjustable wave energy converter is able to interact at resonance with the ocean waves at two different resonant bandwidths. Ten years real wave data with hourly resolution from a selected location in Gulf of Mexico was used in this paper to decide the critical wave period and other parameters of the wave energy converter. The annual energy performance of the self-adjustable wave energy converter was also estimated and compared with non-adjustable wave energy converter with similar dimensions. Structural analysis including both static and fatigue analysis was performed on the self-adjustable wave energy converter to determine its survivability with the real ocean wave data. The results show that the self-adjustable wave energy converter is able to capture more energy than non-adjustable wave energy converter, and is able to survive during the hash ocean wave conditions.
Tunde Aderinto; Hua Li. Conceptual Design and Simulation of a Self-Adjustable Heaving Point Absorber Based Wave Energy Converter. Energies 2020, 13, 1997 .
AMA StyleTunde Aderinto, Hua Li. Conceptual Design and Simulation of a Self-Adjustable Heaving Point Absorber Based Wave Energy Converter. Energies. 2020; 13 (8):1997.
Chicago/Turabian StyleTunde Aderinto; Hua Li. 2020. "Conceptual Design and Simulation of a Self-Adjustable Heaving Point Absorber Based Wave Energy Converter." Energies 13, no. 8: 1997.
The level of awareness about ocean wave energy as a viable source of useful energy has been increasing recently. Different concepts and methods have been suggested by many researchers to harvest ocean wave energy. This paper reviews and compares the efficiencies and power performance of different wave energy converters. The types of analyses used in deriving the reported efficiencies are identified, and the stage of the power conversion processes at which the efficiencies were determined is also identified. In order to find a common way to compare the efficiencies of different technologies, the hydrodynamic efficiency in relation to the characteristic width of the wave energy converters and the wave resource potential are chosen in this paper. The results show that the oscillating body systems have the highest ratio in terms of the efficiency per characteristic width, and overtopping devices have the lowest. In addition, with better understanding of the devices’ dynamics, the efficiencies of the newer oscillating water column and body systems would increase as the potential wave energy level increases, which shows that those newer designs could be suitable for more potential locations with large variations in wave energy potentials. At last, discussion about the cost of ocean wave energy is presented as well.
Tunde Aderinto; Hua Li. Review on Power Performance and Efficiency of Wave Energy Converters. Energies 2019, 12, 4329 .
AMA StyleTunde Aderinto, Hua Li. Review on Power Performance and Efficiency of Wave Energy Converters. Energies. 2019; 12 (22):4329.
Chicago/Turabian StyleTunde Aderinto; Hua Li. 2019. "Review on Power Performance and Efficiency of Wave Energy Converters." Energies 12, no. 22: 4329.
Wind energy is becoming the fastest growing and most inexpensive renewable source, even surpassed natural gas. The environmental advantages coupled with the significant financial benefits have created a positive prognosis for wind energy continuously growing. However, the complexity and limited availability of wind resources create challenges that need to be addressed in order to continue improving wind energy harvesting. This paper developed a new concept to modify wind farm’s layout by deactivating selected wind turbines to maximize its total power output under different wind conditions. Different wind conditions create different wake effects, while most wind farms cannot change their layouts to cope with the changing wind conditions. Through deactivating selected wind turbines to effectively reduce or eliminate some turbulent wakes, it is possible to improve a wind farm’s total power output by creating a net gain for the entire wind farm. A new method was developed to identify the best combinations of deactivated wind turbines under different wind conditions to achieve maximum power output. Several case studies with real wind farms and real wind conditions were conducted together with sensitivity analysis. The promising results demonstrated the effectiveness of the new method and the new concept, named layout optimization through selective deactivation. Several factors were identified as influencing factors on the effectiveness of the new concept.
Francisco Haces-Fernandez; Hua Li; David Ramirez. Improving wind farm power output through deactivating selected wind turbines. Energy Conversion and Management 2019, 187, 407 -422.
AMA StyleFrancisco Haces-Fernandez, Hua Li, David Ramirez. Improving wind farm power output through deactivating selected wind turbines. Energy Conversion and Management. 2019; 187 ():407-422.
Chicago/Turabian StyleFrancisco Haces-Fernandez; Hua Li; David Ramirez. 2019. "Improving wind farm power output through deactivating selected wind turbines." Energy Conversion and Management 187, no. : 407-422.
Wave energy is substantial as a resource, and its potential to significantly contribute to the existing energy mix has been identified. However, the commercial utilization of wave energy is still very low. This paper reviewed the background of wave energy harvesting technology, its evolution, and the present status of the industry. By covering the theoretical formulations, wave resource characterization methods, hydrodynamics of wave interaction with the wave energy converter, and the power take-off and electrical systems, different challenges were identified and discussed. Solutions were suggested while discussing the challenges in order to increase awareness and investment in wave energy industry as a whole.
Tunde Aderinto; Hua Li. Ocean Wave Energy Converters: Status and Challenges. Energies 2018, 11, 1250 .
AMA StyleTunde Aderinto, Hua Li. Ocean Wave Energy Converters: Status and Challenges. Energies. 2018; 11 (5):1250.
Chicago/Turabian StyleTunde Aderinto; Hua Li. 2018. "Ocean Wave Energy Converters: Status and Challenges." Energies 11, no. 5: 1250.
Offshore oil platforms operate with independent electrical systems using gas turbines to generate their own electricity. However, gas turbines operate very inefficiently under the variable offshore conditions, increasing fuel costs and air pollutant emissions. This paper focused on investigating the feasibility of implementing a hybrid electricity supply system for offshore oil platforms in the Gulf of Mexico, both for the United States and Mexico Exclusive Economic Zones. Geographic Information Systems methodologies were used to analyze the data from various sources. Three different scenarios were studied, including wind power only, wave power only, and wind and wave power combined. The results showed that all the offshore locations were within accepted feasible distance to the coast for connecting to the onshore grid. Most of the locations had acceptable power levels of either wind or wave energy while the combination of both resources can improve the overall energy harvesting efficiency and reduce the variability in a significant number of locations. The proposed methodology can be applied for specific locations with finer spatial and time resolution, which will allow stakeholders to improve the decision making process, generate important savings on the normal operation, reduce pollution, and potentially increase income by selling surplus energy from renewable sources.
Francisco Haces-Fernandez; Hua Li; David Ramirez. Assessment of the Potential of Energy Extracted from Waves and Wind to Supply Offshore Oil Platforms Operating in the Gulf of Mexico. Energies 2018, 11, 1084 .
AMA StyleFrancisco Haces-Fernandez, Hua Li, David Ramirez. Assessment of the Potential of Energy Extracted from Waves and Wind to Supply Offshore Oil Platforms Operating in the Gulf of Mexico. Energies. 2018; 11 (5):1084.
Chicago/Turabian StyleFrancisco Haces-Fernandez; Hua Li; David Ramirez. 2018. "Assessment of the Potential of Energy Extracted from Waves and Wind to Supply Offshore Oil Platforms Operating in the Gulf of Mexico." Energies 11, no. 5: 1084.
Wave energy is one of the most concentrated ocean renewable energy resources. Although wave energy has been studied extensively for more than four decades, there is no large commercial installation for wave energy production or a consensus framework on how to exploit this resource. Wave energy is a complex resource that directly depends on two meteorological parameters, which produced significant fluctuations of wave energy in both temporal and spatial criteria. This paper presents a new concept called Energy Event, to analyze meteorological data generated by WaveWatch III over 36 years in the U.S. to characterize and assess wave energy behavior using the peak-over-threshold methodology. This methodology used extreme statistics, segmented the wave energy with different thresholds, and assessed wave energy production on a temporal and spatial framework. Three areas were studied in this paper, including the Gulf of Mexico, the East and West U.S. Coasts. The results indicated that wave energy behaved as a two-state energy system with each state having independent characteristics. The main difference among the three studied areas was the constant baseline of wave power density, with the West Coast having the highest constant baseline and the Gulf of Mexico having the lowest baseline.
Francisco Haces-Fernandez; Hua Li; David Ramirez. Wave energy characterization and assessment in the U.S. Gulf of Mexico, East and West Coasts with Energy Event concept. Renewable Energy 2018, 123, 312 -322.
AMA StyleFrancisco Haces-Fernandez, Hua Li, David Ramirez. Wave energy characterization and assessment in the U.S. Gulf of Mexico, East and West Coasts with Energy Event concept. Renewable Energy. 2018; 123 ():312-322.
Chicago/Turabian StyleFrancisco Haces-Fernandez; Hua Li; David Ramirez. 2018. "Wave energy characterization and assessment in the U.S. Gulf of Mexico, East and West Coasts with Energy Event concept." Renewable Energy 123, no. : 312-322.
Layout optimization has become one of the critical approaches to increase power output and decrease total cost of a wind farm. Previous researches have applied intelligent algorithms to optimizing the wind farm layout. However, those wind conditions used in most of previous research are simplified and not accurate enough to match the real world wind conditions. In this paper, the authors propose an innovative optimization method based on multi-objective genetic algorithm, and test it with real wind condition and commercial wind turbine parameters. Four case studies are conducted to investigate the number of wind turbines needed in the given wind farm. Different cost models are also considered in the case studies. The results clearly demonstrate that the new method is able to optimize the layout of a given wind farm with real commercial data and wind conditions in both regular and irregular shapes, and achieve a better result by selecting different type and hub height wind turbines.
Ying Chen; Hua Li; Bang He; Pengcheng Wang; Kai Jin. Multi-objective genetic algorithm based innovative wind farm layout optimization method. Energy Conversion and Management 2015, 105, 1318 -1327.
AMA StyleYing Chen, Hua Li, Bang He, Pengcheng Wang, Kai Jin. Multi-objective genetic algorithm based innovative wind farm layout optimization method. Energy Conversion and Management. 2015; 105 ():1318-1327.
Chicago/Turabian StyleYing Chen; Hua Li; Bang He; Pengcheng Wang; Kai Jin. 2015. "Multi-objective genetic algorithm based innovative wind farm layout optimization method." Energy Conversion and Management 105, no. : 1318-1327.
Many researchers have focused on the layout design of a wind farm using the computational methods. Most of previous researches focused on relevant large cell size and using same hub height wind turbines. In this paper, the authors investigate the possibility of using different hub height wind turbines in a wind farm. A limited area (2 km × 2 km) with constant wind speed and direction is considered as the potential wind farm area, and a nested genetic algorithm is used as optimisation algorithm. Two different hub height wind turbines are introduced with two different cell sizes. Power output, cost, payback period, and total profit are selected as evaluation criteria when comparing the layouts with same hub height wind turbines with the layouts with different hub height wind turbines. The results demonstrate that it is feasible and possible to use different hub height wind turbines in a wind farm.
Ying Chen; Hua Li; Kai Jin; Yousri Elkassabgi. Investigating the possibility of using different hub height wind turbines in a wind farm. International Journal of Sustainable Energy 2014, 36, 1 -9.
AMA StyleYing Chen, Hua Li, Kai Jin, Yousri Elkassabgi. Investigating the possibility of using different hub height wind turbines in a wind farm. International Journal of Sustainable Energy. 2014; 36 (2):1-9.
Chicago/Turabian StyleYing Chen; Hua Li; Kai Jin; Yousri Elkassabgi. 2014. "Investigating the possibility of using different hub height wind turbines in a wind farm." International Journal of Sustainable Energy 36, no. 2: 1-9.
In a region traditionally known for agriculture, the Western Gulf Basin of South Central Texas has recently become a major player in the oil and gas industry. The shale gas and oil development in the area, now known as the Eagle Ford Shale region, has generated a significant boost to South Texas. However, the issue of whether the development has benefited all residents in the region (most of whom are Hispanic and low income) and how the development has affected the social life of the local communities in general, remains an unanswered question. To investigate the general economic and social impacts of the development to the local residents in the region, a research team at Texas A&M University-Kingsville has conducted a large-scale social survey in the region. Adopting a multi-stage probability sampling frame, the survey has randomly selected 1590 respondents in the region for interview. In the paper, we describe in detail the research design and survey instrument, and provide results of preliminary analysis of the data thus collected.
Hua Li; Jieming Chen; Jennifer E. Pearce-Morris; Brenda Hannon; Kai Jin; Lian Yang; Emilio Alaniz; Jaime Herrera; Ruth Zabelin. Investigation and Analysis of Social Impacts of Eagle Ford Shale on Local Communities. Shale Energy Engineering 2014 2014, 543 -551.
AMA StyleHua Li, Jieming Chen, Jennifer E. Pearce-Morris, Brenda Hannon, Kai Jin, Lian Yang, Emilio Alaniz, Jaime Herrera, Ruth Zabelin. Investigation and Analysis of Social Impacts of Eagle Ford Shale on Local Communities. Shale Energy Engineering 2014. 2014; ():543-551.
Chicago/Turabian StyleHua Li; Jieming Chen; Jennifer E. Pearce-Morris; Brenda Hannon; Kai Jin; Lian Yang; Emilio Alaniz; Jaime Herrera; Ruth Zabelin. 2014. "Investigation and Analysis of Social Impacts of Eagle Ford Shale on Local Communities." Shale Energy Engineering 2014 , no. : 543-551.
Layout optimization is one of the methods to increase wind farm’s utilization rate and power output. Previous researches have revealed that different hub height wind turbines may increase wind farm’s power output. However, few researches focus on optimizing a wind farm’s layout in a two-dimensional area using different hub height wind turbines. In this paper, the authors first investigate the effect of using different hub height wind turbines in a small wind farm on power output. Three different wind conditions are analyzed using nested genetic algorithm, where the results show that power output of the wind farm using different hub height wind turbines will be increased even when the total numbers of wind turbines are same. Different cost models are also taken into account in the analysis, and results show that different hub height wind turbines can also improve cost per unit power of a wind farm. At last, a large wind farm with commercial wind turbines is analyzed to further examine the benefits of using different hub height wind turbines in more realistic conditions.
Ying Chen; Hua Li; Kai Jin; Qing Song. Wind farm layout optimization using genetic algorithm with different hub height wind turbines. Energy Conversion and Management 2013, 70, 56 -65.
AMA StyleYing Chen, Hua Li, Kai Jin, Qing Song. Wind farm layout optimization using genetic algorithm with different hub height wind turbines. Energy Conversion and Management. 2013; 70 ():56-65.
Chicago/Turabian StyleYing Chen; Hua Li; Kai Jin; Qing Song. 2013. "Wind farm layout optimization using genetic algorithm with different hub height wind turbines." Energy Conversion and Management 70, no. : 56-65.