Rajput Krishna Pal, D. N. Srikanth, Kannappan Lakshmanan
{"title":"潮汐资源建模:奥尔德尼竞赛","authors":"Rajput Krishna Pal, D. N. Srikanth, Kannappan Lakshmanan","doi":"10.1109/ACEPT.2018.8610856","DOIUrl":null,"url":null,"abstract":"When we consider sea as a source of energy, tidal energy is one of the most assuring and doable options for extracting energy from the sea. The thrusting force behind the coastal hydrodynamics comes majorly from tides and their interaction with diverse coastal boundaries and it also depends on the seabed profile. The seabed profile and composition give rise to a surface roughness profile which creates a drag force on the flow and modifies the velocity field [1]. These complex characteristics are simplified to a certain level by dividing the tides effect into certain harmonic tidal constants which occurs as a combination of amplitude and phase. Alderney Race (between the islands of Alderney and the cape of La Hague, France) is one of such vital locations where tidal energy can be extracted at a large scale. In our study, the ocean boundaries are mainly forced by 8 tidal constants (Kl, K2, M2, N2, Ol, P1, Ql, S2) that provide motion to ocean water. These tidal constants are predicted from the LeProvost Tidal Database which is a set of legi files and was defined for the entire globe. Also, a quadratically varying friction coefficient function was employed to compensate for the seabed surface roughness. A finite element based 2-dimensional modeling (Advance circulation-ADCIRC) was conducted to estimate the tidal energy density in the region of Alderney Race. This model was validated with the field data collected at certain locations in Singapore and this formed a base for the validity of this model. The estimation of the average power density (APD) is derived from the velocity field, knowing APD to be proportional to the cube of the velocity value. The velocity field and tidal elevation calculated by the model are within the suitable limits as compared with the field data. This paper introduces a unique way of forecasting tidal energy power density using the open source software models and data sources with a maximum level of resolution. The data helps to site the higher tidal energy sites in a remote ocean location and thereby helps to minimize the deployment costs.","PeriodicalId":296432,"journal":{"name":"2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Tidal Resource Modeling: Alderney Race\",\"authors\":\"Rajput Krishna Pal, D. N. Srikanth, Kannappan Lakshmanan\",\"doi\":\"10.1109/ACEPT.2018.8610856\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When we consider sea as a source of energy, tidal energy is one of the most assuring and doable options for extracting energy from the sea. The thrusting force behind the coastal hydrodynamics comes majorly from tides and their interaction with diverse coastal boundaries and it also depends on the seabed profile. The seabed profile and composition give rise to a surface roughness profile which creates a drag force on the flow and modifies the velocity field [1]. These complex characteristics are simplified to a certain level by dividing the tides effect into certain harmonic tidal constants which occurs as a combination of amplitude and phase. Alderney Race (between the islands of Alderney and the cape of La Hague, France) is one of such vital locations where tidal energy can be extracted at a large scale. In our study, the ocean boundaries are mainly forced by 8 tidal constants (Kl, K2, M2, N2, Ol, P1, Ql, S2) that provide motion to ocean water. These tidal constants are predicted from the LeProvost Tidal Database which is a set of legi files and was defined for the entire globe. Also, a quadratically varying friction coefficient function was employed to compensate for the seabed surface roughness. A finite element based 2-dimensional modeling (Advance circulation-ADCIRC) was conducted to estimate the tidal energy density in the region of Alderney Race. This model was validated with the field data collected at certain locations in Singapore and this formed a base for the validity of this model. The estimation of the average power density (APD) is derived from the velocity field, knowing APD to be proportional to the cube of the velocity value. The velocity field and tidal elevation calculated by the model are within the suitable limits as compared with the field data. This paper introduces a unique way of forecasting tidal energy power density using the open source software models and data sources with a maximum level of resolution. The data helps to site the higher tidal energy sites in a remote ocean location and thereby helps to minimize the deployment costs.\",\"PeriodicalId\":296432,\"journal\":{\"name\":\"2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACEPT.2018.8610856\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACEPT.2018.8610856","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
When we consider sea as a source of energy, tidal energy is one of the most assuring and doable options for extracting energy from the sea. The thrusting force behind the coastal hydrodynamics comes majorly from tides and their interaction with diverse coastal boundaries and it also depends on the seabed profile. The seabed profile and composition give rise to a surface roughness profile which creates a drag force on the flow and modifies the velocity field [1]. These complex characteristics are simplified to a certain level by dividing the tides effect into certain harmonic tidal constants which occurs as a combination of amplitude and phase. Alderney Race (between the islands of Alderney and the cape of La Hague, France) is one of such vital locations where tidal energy can be extracted at a large scale. In our study, the ocean boundaries are mainly forced by 8 tidal constants (Kl, K2, M2, N2, Ol, P1, Ql, S2) that provide motion to ocean water. These tidal constants are predicted from the LeProvost Tidal Database which is a set of legi files and was defined for the entire globe. Also, a quadratically varying friction coefficient function was employed to compensate for the seabed surface roughness. A finite element based 2-dimensional modeling (Advance circulation-ADCIRC) was conducted to estimate the tidal energy density in the region of Alderney Race. This model was validated with the field data collected at certain locations in Singapore and this formed a base for the validity of this model. The estimation of the average power density (APD) is derived from the velocity field, knowing APD to be proportional to the cube of the velocity value. The velocity field and tidal elevation calculated by the model are within the suitable limits as compared with the field data. This paper introduces a unique way of forecasting tidal energy power density using the open source software models and data sources with a maximum level of resolution. The data helps to site the higher tidal energy sites in a remote ocean location and thereby helps to minimize the deployment costs.