Projects

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12. Strathclyde Centre for Doctoral Training (SCDT) in “Artificial Intelligence (AI)-based Ocean Forecast for Marine Operation” (mArIneCAST CDT)                                                        

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• Principal Investigators: Bahareh Kamranzad, Katy Tant (M&S) and Laibing Jia (NAOME)
• Budget: £264K
• Funded by: University of Strathclyde, United Kingdom

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11. Project title: Climate change impact on the sustainability of wave energy resources in NE Asia and Japan                                      

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• JSPS Grant-in-Aid for Scientific Research (C) No. 20K04705

• Period: 2020/4/1 - 2023/3/31

• Budget: ¥4,290,000 

• Role: Principal investigator

• Funded by: Japan Society for the Promotion of Science

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Short Introduction

Among the renewable energies and ocean resources, wave energy has been less investigated due to high Levelized Cost of Energy (LCOE) associated with uncertainties in energy production estimations. However, development in the extraction technology is fast and the efficiency and suitability of wave energy exploitation depend on the areas where the technology is deployed, and it affects the estimated LCOE. Recent achievements in wave energy studies show that considering factors such as short-term variations and long-term changes are important in locating suitable sites with higher efficiency. The main purposes of this research are:
1. To identify the suitable sites in the study area for the most efficient energy production from waves
2. To assess the impact of climate change on locating suitable sites for energy extraction and energy production

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Project achievements (until now)

Journal papers: 

1. Kamranzad B*, Takara K. (2020). A climate-dependent sustainability index for wave energy resources in Northeast Asia. Energy. 209, 118466. LINK

 

Conference papers:

1. Kamranzad B, Takara K. (2020) Change of wave energy resources in Japan in 5 decades. RENEW 2020 4th International Conference on Renewable Energies Offshore. Lisbon, Portugal.  Our paper as book chapter   LINK to program

2. Kamranzad B. (2020) Sustainability of wave energy potential in Japan. JpGU-AGU 2020. Chiba, Japan. Accepted. LINK

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10. Project title: Climate Change Impact Assessment on Ocean Wave Energy and Coastal Hazards and Reducing the Uncertainties in Pursuit of Sustainable Development

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• Period: Oct. 2018- Sep. 2023

• Role: Principal investigator

• The Hakubi Center for Advanced Research

• Funded by: The Hakubi Center for Advanced Research, Kyoto University, Japan

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Short Introduction
Renewable energy resources are proper alternatives to mitigate the negative effects of fossil fuels on global warming and climate change. Marine renewable energies are massive resources to provide parts of the energy demand in areas adjacent to open water bodies. Among them, waves have the highest density and lowest visual and environmental impacts, however, the available resources are strongly affected by climate change, which alters the wind magnitude and pattern and consequently, the wave climate. In addition, development from full-scale testing to the commercialization of wave energy farms has been relatively slow, partly due to the financial risks connected to uncertainties in quantifying the wave energy resources. Moreover, installment of wave energy converters (WECs) will impact the sea state and coastal morphology in the areas where the wave energy exploitation is planned. Therefore, my research is focused on assessing the climate change impacts on wave energy resources and extreme events to ensure a reliable supply of energy and efficient use of it, as well as reducing the uncertainties in coastal hazards and investigating the combined impact of climate change and installment of WECs on sea state and coastal morphology to reduce the uncertainties in planning for a future sustainable development.

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Project achievements (until now)

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Journal papers: 

1. Kamranzad B*, Hadadpour. S (2020). A multi-criteria approach for selection of wave energy converter/location. Energy. 204, 117924 LINK

2. Kamranzad B*, Lavidas, G. (2020). Change of nearshore extreme wind and wave climate in Southeast Africa. IJEGE. (SCACR19-SI), 1, 59-63. LINK

3. Kamranzad B*, Lavidas G, Takara K. (2020). Spatio-temporal assessment of climate change impact on wave energy resources using various time dependent criteria. Energies. 13(3), 768. LINK

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Conference papers: 

1. Kamranzad B, Tatebe H, Takara K. (2020) Multi-Decadal Variability in Global Wind and Wave Climate: An Analysis Based on MIROC6 dataset. 22nd IAHR-APD Congress. Sapporo, Japan.  PDF   LINK to program

2. Kamranzad B, Tatebe H, Takara K. (2020) Spatio-temporal assessment of long-term historical wave simulation using MIROC6 wind dataset; A global scale study. Ocean Sciences Meeting 2020, San Diego, California. LINK

3. Kamranzad B, Lavidas G. (2019) Change of nearshore extreme wind and wave climate in southeast Africa. SCACR2019 – International Short Course/Conference on Applied Coastal Research Engineering, Geology, Ecology & Management, Bari, Italy. LINK

4. Lavidas G, Kamranzad B. (2019) Classifying the global wave resource through its persistence and rate of change. SCACR2019 – International Short Course/Conference on Applied Coastal Research Engineering, Geology, Ecology & Management, Bari, Italy. LINK

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9. Project title: Sustainability of ocean renewable energy resources in Chinese nearshore areas of the South China Sea

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• Period: Jan. 2019- Dec. 2020

• Role: Principal investigator

• Funded by: State Key Laboratory of Hydraulics and Mountain River Engineering (SKHL), Sichuan University, China

• Budget Amount: 80,000 RMB 

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Short Introduction

In this project, long-term wave climate will be evaluated in Chinese nearshore areas of the South China Sea in order to assess the sustainability of the available wave energy resources in long-term (5-decades) and select the most appropriate location/technology not only based on the amount of energy but also on novel criteria taking into account the sustainable development goals.

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Project achievements 

Journal papers:

1. Kamranzad B*, Lin P. (2020). Sustainability of wave energy resources in the South China Sea based on five decades of changing climate. Energy. 210, 118604. LINK

Conference papers: 

1. Kamranzad B, Lin P, Wen Y. (2020) Inter and intra-annual variation of wave energy in Southeast Asia. 22nd IAHR-APD Congress. Sapporo, Japan. PDF   LINK to program

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8. Project title: Wave energy resource characterization for Sri Lanka in a changing ocean climate

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• Period: Feb 2019- June 2019

• Role: Collaborating research expert

• PI: Swansea University

• Funded by: Global Challenges Research Fund (GCRF)- UK Research and Innovation, UK

 

Short Introduction

Wave Energy resources in Sri Lanka can be a vast source of energy considering the exposure of the country to Indian Ocean. However, climate change impacts on wave energy should also be considered for future sustainable development. Hence, in this study, wave energy potential and its future change have been discussed around Sri Lanka.​

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Project achievements (until now)

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Journal papers: 

1. Karunarathna H, Maduwantha P, Kamranzad B, Rathnasooriya H, de Silva K. (2020) Evaluation of spatio-temporal variability of ocean power resource around Sri Lanka. Energy. 200, 117503. LINK

2. Karunarathna H, Maduwantha P, Kamranzad B, Rathnasooriya H, de Silva K. (2020) Impacts of Global Climate Change on the Future Ocean Wave Power Potential: A Case Study from the Indian Ocean. Energies. 13(11), 3028. LINK

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Conference papers: 

1. Maduwantha P, Karunarathna H, Kamranzad B, Rathnasooriya H, De Silva K. (2020) Global Climate Change Impacts on Wave Energy Potential Along the South Coast of Sri Lanka. 6th International Moratuwa Engineering Research Conference. Moratuwa, SRI LANKA.   LINK    LINK to program  DOI: 10.1109/MERCon50084.2020.9185291

2. Kamranzad B, Maduwantha P, Rathnasooriya H, De Silva K, Karunarathna H. (2020) The effect of future climate-related variabilities of tropical monsoons in the Indian Ocean on wave energy resource around Sri Lanka. JpGU-AGU 2020. Chiba, Japan. Accepted. LINK

3. Maduwantha P, Karunarathna P, Kamranzad B, Ratnasooriya H, de Silva K. (2019) Investigations on ocean wave energy assessment for Sri Lanka. National Energy Symposium 2019, Sri Lanka. LINK

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7. Project title: Projection of wave climate and wave energy due to global warming

• Period: Nov. 2016- Sep. 2018

• Role: Principal investigator

• Disaster Prevention Research Institute, Kyoto University

• Funded by: Japan Society for the Promotion of Science (JSPS)

• Budget Amount: ¥1,400,000

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Short Introduction

The aim of this research was to investigate the sustainability of wave energy resources in an appropriate location with high potential of wave energy harvesting considering the climate change impacts. The Indian Ocean was selected as the target area due to the lack of any comprehensive study in that area on climate change impact on wave characteristics and wave energy. The wind data to force the wave model was obtained from a super-high-resolution product of the Japan Meteorological Agency (JMA) (MRI-AGCM3.2S) with horizontal spatial and temporal output resolutions of 20 km and 1 hr., respectively. The wave modeling was performed for both historical (1979-2003) and future (2075-2099) projections. Based on the fifth phase of the Coupled Model Inter-comparison Project (CMIP5), the scenario of future climate was considered by Representative Concentration Pathway (RCP) 8.5 as defined by -representing trajectories of increasing global radiative forcing reaching +8.5 W m-2, by the year 2100 compared to pre-industrial conditions. SWAN numerical model was used to simulate the wave characteristics in the study area. Satellite multi-mission wave measurements available from 2010 to 2018 covering the whole domain with spatial and temporal resolutions of 1° and daily, respectively, were used for validation of the wave model. After the model validation, it was used to generate the wave characteristics in the domain for historical and future projections and the produced time series were used for climate analysis. The discussion was carried out in different time scales to consider oceanic phenomena such as monsoons and tropical cyclones. In addition, the short-term variations in annual, seasonal and monthly scales and long-term changes due to climate change and their combination were investigated focusing on the nearshore areas around the Indian Ocean basin to represent a novel concept for the stability of the wind and wave parameters. 

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Project achievements

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Journal papers: 

1. Spatio-temporal assessment of climate change impact on wave energy resources using various time-dependent criteria   LINK

2. Future wind and wave climate projections in the Indian Ocean based on a super-high-resolution MRI-AGCM3.2S model projection   LINK

3. Regional Wave Climate Projection Based on Super-High-Resolution MRI-AGCM3.2S, Indian Ocean   LINK

4. Performances of Long-Term Wave Hindcasts in the Northern Indian Ocean   LINK

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Conference papers:

1. Kamranzad B, Mori N. (2019) Future change of wave energy projections in Western Indian Ocean; A regional assessment in southeast Africa. 13th European Wave and Tidal Energy Conference. Napoli, Italy. LINK​

2. Kamranzad B, Mori N. (2019) Future change of tropical cyclone-induced waves in the Indian Ocean; An analysis based on super-high-resolution MRI-AGCM3.2 climate model. Japan Geoscience Union Meeting. LINK​

3. Kamranzad B, Mori N. (2018) Future projection of wave energy in Indian Ocean based on high resolution MRI-AGCM3.2S projection. Grand Renewable Energy. Yokohama, Japan. LINK

4. Bouchard RH, Jensen RE, Montalvo S, Kamranzad B. (2018) Finding NOMAD: An Examination of the Impacts of Changing Wave Systems on Long-term Wave Measurements. AGU Ocean Sciences.Oregon, USA. LINK​

5. Kamranzad B, Mori N, Shimura T. (2017) Spatio-temporal wave climate using nested numerical wave modeling in the northern Indian Ocean. 1st International Workshop on Waves, Storm Surge and Coastal Hazards. Liverpool, UK. P30. LINK

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6. Project title: Global wave hindcast and future projection

• Role: Project Collaborator

• The Coordinated Ocean Wave Climate Project (COWCLIP)” research group

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Project achievements

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Journal paper: 

1. Morim J, Hemer M, Wang XL, Cartwright N, Trenham C, Semedo A, Bricheno L, Camus P. Casas-Prat M, Erikson L, Mentaschi L, Mori N, Shimura T, Timmerman B, Aarnes O, Breivik Ø, Behrens A, Dobrynin M, Menendez M, Staneva J, Wehner M, Wolf J, Kamranzad B, Stopa J, Webb A, Young I, and Andutta F. (2019) Robustness and uncertainties in global multivariate wind-wave climate projections. Nature Climate Change. LINK  LINK

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5. Project title: A hybrid method for wave simulation in selected nearshore areas  

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• Role: Principal Investigator
• Period: Feb. 2015-Jun. 2016
• Iranian National Institute for Oceanography and Atmospheric Science

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Abstract​

Since ocean waves are mainly wind induced, carrying out coastal engineering projects and investigating environmental issues call for determination of wind-generated wave characteristics, especially in nearshore areas. In this study, a nested grid SWAN model and a hybrid approach combining Artificial Neural Network (ANN) and coarse grid SWAN modeling results are used to hindcast the significant wave height in two nearshore locations in the Persian Gulf. However, the results are only valid in the regions where they are trained and tested. The models were calibrated in order to minimize the scatter index and the performances were compared, and the results show that the scatter index for significant wave height for both nearshore locations is less using the hybrid model rather than the nested one and there is no significant difference for the other error indices using both approaches. Regarding that the nesting approach is costly and consumes much more time in comparison to the hybrid one, and also taking into account that the nested model is unable to correctly calibrate wave height and other wave parameters, simultaneously and additional calibration may be required, the alternative hybrid approach is suggested to be used in wave simulation in nearshore areas. It is because the proposed hybrid model takes advantage of both SWAN and ANN merits while trying to avoid their limitations. 

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Project achievements

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Journal paper: 

1. Salah P, Reisi-Dehkordi A, Kamranzad B*. (2016) A hybrid approach to estimate the nearshore wave characteristics in the Persian Gulf. Applied Ocean Research. 57, 1-7. LINK

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4. Project title: Assessment of wind and wave temporal and spatial distributions using long-term data 

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• Role: Principal Investigator
• Period: Sep. 2014- Feb. 2016
• Iranian National Institute for Oceanography and Atmospheric Science   Mentioned in the media

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Abstract

Long-term wind and wave data are valuable resources for research and applied purposes in marine engineering. In this study, temporal-spatial variations of the wind and wave characteristics (wind speed and direction, significant wave height, peak period and wave direction) was investigated using 31 yearly data in the Persian Gulf. Inter-annual variations of the mean wind speed and significant wave height shows a slight increasing in some years, especially in north-western and middle parts of the Persian Gulf. Seasonal variations of the wind and wave characteristics indicates that the highest mean wind speed and significant wave height exist in winter and they decrease in spring and summer and reach the lowest values in autumn. In addition, a reduction of approximately 1% in mean wind speed from winter to autumn has led to a reduction of 25% in corresponding significant wave height. Monthly variations of the mean wind speed and significant wave height illustrate that the variations are affected by dominant Shamal wind in the Persian Gulf. Quantitative assessment of wind and wave characteristics in twenty selected points represents that the winter and summer time Shamal winds influence mostly the middle and north-western parts of the Persian Gulf, respectively. Furthermore, a new zone defining was suggested for the Persian Gulf based on the similarity between the monthly variations of the mean wind speed, significant wave height and peak period. Seasonal and monthly variability indices depict that the variability of significant wave height is higher than the wind speed, while the peak period shows the lowest variability. In addition, the seasonal and monthly sustainability of wind speed and monthly sustainability of significant wave height are higher in eastern part of the Persian Gulf; adjacent to the Strait of Hormuz. Frequency distribution indicates that the highest percentage of occurrence for wind speeds more than 12 m/s exists in a boundary between the northwestern and middle parts, while the highest percentage of occurrence for significant wave heights more than 2 m exists in the middle part of the Persian Gulf. In addition, seasonal wind and wave roses display that the wave direction is more stable than the wind direction in various seasons. Besides, the prevailing wave direction is mostly similar to wind direction, except for some points in which, the wave direction shows a difference of a fourth quarter comparing to the wind direction. 

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Project achievements

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Journal paper:​

1. Kamranzad B*. (2018) Persian Gulf zone classification based on the wind and wave climate variability. Ocean Engineering. 169, 604-435. LINK

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3. Project title Prediction of extreme values of the wave characteristics in: Persian Gulf considering 100-yearly effects of climate change-Part 1

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• Role: Principal Investigator

• Period: Feb. 2014- Feb. 2015
• Iranian National Institute for Oceanography and Atmospheric Science

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Abstract

Prediction of extreme values of the wave characteristics for various return periods is required for design and locating the marine structures. The accuracy of this prediction increases if the long-term data are available. In addition, the selected method for extreme value analyzing influences on the results. Regarding the fact that a small change in wave characteristics results in a considerable change in extreme values, the assessment of climate change impact on wave extreme values is of great importance. This project was defined in two phases in order to estimate the extreme waves and climate change impact on them. In the first phase of this project, the effect of data availability duration, distribution and fitting methods on extreme value analysis are investigated. The extreme value analysis was carried out using data obtained from ISWM II and after the validation of
the utilized methods, the extreme values of the wave characteristics were obtained for 2, 5, 10, 20, 25, 50, 100 years return periods using Weibull, Gumbel and Log-Normal distributions and using Maximum Likelihood, Method of Moments and Method of L-Moments fitness methods. Spatial distribution of the extreme waves showed that the maximum extreme wave occurs in Strait-of-Hormuz and the central parts of the Persian Gulf and the lowest extreme values exist in north-west and south of the domain. Comparison of standard deviation and Probability Plot Correlation Coefficient for various distributions indicated that Gumbel distribution using the maximum likelihood fitness method has the lowest standard deviation and the highest Probability Plot Correlation Coefficient which mean the higher accuracy. In addition, the bias, which was calculated by comparing the results with those of previous studies, was found to be the least value in Gumbel distribution using maximum likelihood fitness method. It must be noted that the bias is positive in eastern and central parts while it is negative in north-western and southern parts of the Persian Gulf. In order to compare the results with the previous studies, ten points were selected in the Persian Gulf based on the bias distribution. The results illustrated that the difference increases by increasing the return period. Moreover, the obtained results are underestimated in points located in north-west and overestimated in other points. Extreme peak periods were also calculated using a linear regression between significant wave height and peak period. Furthermore, for assessing the climate change impact on extreme wave conditions, wind data obtained from a global climate model (CGCM3.1) verified in comparison to ECMWF local winds. The statistical analysis showed that the standard deviation is lower in ECMWF data and ECMWF wind speed values are higher in most of the points. Comparison of wind roses also shows some differences between these two wind sources. Climate change impact on extreme waves will be carried out in the second phase of this study.

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2. Project title: Iranian Seas Wave Modeling-version II (ISWM II)

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• Role: Project collaborator

• Period: Nov. 2011- Nov. 2012
• Iranian National Institute for Oceanography and Atmospheric Science

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Abstract 

Waves are the most important index of sea state. Therefore, knowledge of wave regime for using in design of marine and coastal structures is of great importance. Since Iran is located adjacent to three important seas, i.e. Caspian Sea, Persian Gulf and Gulf of Oman, determination of wave condition for marine activity is very important. Wave measurements are usually gathered in short period and are in limited locations. Satellite data represent also wave data in special paths and with low temporal resolution. Therefore, numerical wave modeling is carried out for generation long time wave data in grids covering the whole domain. Wave modeling in Iranian seas was done before in project "Iranian Seas Wave Modeling (ISWM) in Iranian National Institute for Oceanography (INIO) that contains the wave modeling in 12 years period. This is a short period for achieving the accurate extreme value analysis. Therefore, the current project was carried out in INIO to obtain the more accurate extreme value analysis and wave simulation for 32 years. In addition, in this research, SWAN numerical model was used instead of Mike 21-SW (which was used before in ISWM) for modeling of the wave characteristics. After purchasing the ECMWF wind field and modifying it, wave modeling was done in Iranian seas and the results were calibrated and verified using measured values. Finally, wave atlas was prepared for 32-yearly modeled wave characteristics.

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Project achievements

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Journal papers:​

1. Mazaheri S, Kamranzad B*, Hajivalie F. (2013) Modification of 32 years ECMWF wind field using QuikSCAT data for wave hindcasting in Iranian Seas. Journal of Coastal Research. SI 65, 344-349. LINK

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Conference papers:

1. Mazaheri S, Kamranzad B. (2017) Wave Hindcasting in Persian Gulf and Gulf of Oman Based on the Modified 32-Year ECMWF Data. 36th International Conference on Ocean, Offshore and Arctic Engineering. Trondheim, Norway, 62237. LINK

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1. Project title: Evaluation of wave energy potential in the Caspian Sea, Persian Gulf and Gulf of Oman

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• Role: Project collaborator

• Iranian National Institute for Oceanography and Atmospheric Science
• Period: Sep. 2010-Nov. 2011

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Project achievements

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Journal papers:

1. Kamranzad B, Etemad-Shahidi A, Chegini V. (2013) Assessment of wave energy variation in the Persian Gulf. Ocean Engineering. 70, 72-80. LINK 

2. Kamranzad B*, Etemad-Shahidi A, Chegini V. (2016) Sustainability of wave energy resources in southern Caspian Sea. Energy. 97, 549-559. LINK

3. Kamranzad B*, Chegini V, Etemad-Shahidi A. (2016) Temporal-spatial variation of wave energy and nearshore hotspots in the Gulf of Oman based on locally generated wind waves. Renewable Energy. 94, 341-352. LINK

4. Kamranzad B*, Etemad-Shahidi A, Chegini V. (2017) Developing an Optimum Hotspot Identifier for wave energy extracting in the northern Persian Gulf. Renewable Energy. 114PA, 59-71. LINK

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Conference papers:​

1. Kamranzad B, Chegini V. (2014) Study of Wave Energy Resources in Persian Gulf: Seasonal and Monthly Distributions. 11th International Conference on Coasts, Ports andMarine Structures (ICOPMAS). Tehran, Iran. 658-661. PDF

2. Kamranzad B, Etemad-Shahidi A, Chegini V. (2014) Wave energy and nearshore hotspots in Gulf of Oman. 9th International Scientific Symposium. Nha Trang, Vietnam.

3. Kamranzad B, Etemad-Shahidi A, Chegini V. (2012) Wave energy assessment in the Caspian Sea. 18th congress of the IAHR-APD. Jeju, South Korea. 424-425. PDF

4. Etemad-Shahidi A, Kamranzad B, Chegini V. (2011) Wave energy estimation in the Persian Gulf. International Conference on Environmental Pollution and Remediation. Ottawa, Ontario, Canada. Paper 223. PDF

5. Kamranzad B, Etemad-Shahidi A, Chegini V. (2011) Wind wave hindcasting in Assalouyeh using SWAN. 4th Offshore Industries Conference. Tehran, Iran. (In Persian). PDF

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Book chapter:  LINK

 

Awards:

1. 2014    IOC-WESTPAC young scientists travel grant, Nha Trang, Vietnam

2. 2012     PhD Scholarship for doctoral studies, Ministry of Science, Research and Technology

3. 2012    Excellent Research award for the project "Evaluation of wave energy potential in Iranian Seas" awarded by the ministry of science, research and technology, 13th best researchers' festival, Tehran, Iran

4. 2012     Student competition award at the 18th Congress of IAHR-APD, Jeju Island, South Korea

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