Daniel R. David, Jeff Hansen, Ryan Lowe, Adi Kurniawan, Hugh Wolgamot, Dirk Rijnsdorp
{"title":"波浪场的多目标优化及海岸影响评估","authors":"Daniel R. David, Jeff Hansen, Ryan Lowe, Adi Kurniawan, Hugh Wolgamot, Dirk Rijnsdorp","doi":"10.9753/icce.v37.structures.93","DOIUrl":null,"url":null,"abstract":"To add to the global renewable energy mix, ocean waves are a consilient and energy-dense untapped resource. However, to generate power on a commercial scale, wave energy converters (WECs) will need to be deployed in arrays or “wave farms”. When deployed as a farm, WECs interact with each other hydrodynamically through the radiated and/or scattered waves. These interactions can either enhance or diminish the overall performance of the system commonly referred to as the “interaction factor (q)” or “park effect”. Thus it is crucial to understand these array interactions to minimize destructive effects. Furthermore, wave farms deployed nearshore have the potential to modify the downstream hydrodynamics and may alter the nearshore circulation patterns due to the attenuation of the wave field. Such changes to the nearshore hydrodynamics may in turn alter sediment transport pathways and could lead to erosion and/or accretion of beaches. This implies that for a commercialscale deployment, understanding how the array interacts with the incident wave field is critical for both understanding power production (and the levelized cost of energy) and potential downstream impacts. The overarching aim of this work is to advance the wave energy industry towards commercial-scale deployment by leading to more efficient/optimal designs (with reduced levelized cost).","PeriodicalId":497926,"journal":{"name":"Proceedings of ... Conference on Coastal Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MULTI-OBJECTIVE OPTIMISATION AND COASTAL IMPACT ASSESSMENTS OF WAVE FARMS\",\"authors\":\"Daniel R. David, Jeff Hansen, Ryan Lowe, Adi Kurniawan, Hugh Wolgamot, Dirk Rijnsdorp\",\"doi\":\"10.9753/icce.v37.structures.93\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To add to the global renewable energy mix, ocean waves are a consilient and energy-dense untapped resource. However, to generate power on a commercial scale, wave energy converters (WECs) will need to be deployed in arrays or “wave farms”. When deployed as a farm, WECs interact with each other hydrodynamically through the radiated and/or scattered waves. These interactions can either enhance or diminish the overall performance of the system commonly referred to as the “interaction factor (q)” or “park effect”. Thus it is crucial to understand these array interactions to minimize destructive effects. Furthermore, wave farms deployed nearshore have the potential to modify the downstream hydrodynamics and may alter the nearshore circulation patterns due to the attenuation of the wave field. Such changes to the nearshore hydrodynamics may in turn alter sediment transport pathways and could lead to erosion and/or accretion of beaches. This implies that for a commercialscale deployment, understanding how the array interacts with the incident wave field is critical for both understanding power production (and the levelized cost of energy) and potential downstream impacts. The overarching aim of this work is to advance the wave energy industry towards commercial-scale deployment by leading to more efficient/optimal designs (with reduced levelized cost).\",\"PeriodicalId\":497926,\"journal\":{\"name\":\"Proceedings of ... Conference on Coastal Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of ... Conference on Coastal Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9753/icce.v37.structures.93\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of ... Conference on Coastal Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9753/icce.v37.structures.93","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MULTI-OBJECTIVE OPTIMISATION AND COASTAL IMPACT ASSESSMENTS OF WAVE FARMS
To add to the global renewable energy mix, ocean waves are a consilient and energy-dense untapped resource. However, to generate power on a commercial scale, wave energy converters (WECs) will need to be deployed in arrays or “wave farms”. When deployed as a farm, WECs interact with each other hydrodynamically through the radiated and/or scattered waves. These interactions can either enhance or diminish the overall performance of the system commonly referred to as the “interaction factor (q)” or “park effect”. Thus it is crucial to understand these array interactions to minimize destructive effects. Furthermore, wave farms deployed nearshore have the potential to modify the downstream hydrodynamics and may alter the nearshore circulation patterns due to the attenuation of the wave field. Such changes to the nearshore hydrodynamics may in turn alter sediment transport pathways and could lead to erosion and/or accretion of beaches. This implies that for a commercialscale deployment, understanding how the array interacts with the incident wave field is critical for both understanding power production (and the levelized cost of energy) and potential downstream impacts. The overarching aim of this work is to advance the wave energy industry towards commercial-scale deployment by leading to more efficient/optimal designs (with reduced levelized cost).