STTR Phase I: Performance Optimization Toolbox for Wave Energy Conversion Devices

这个小型企业技术转让第一期项目的题目是？性能优化工具箱波浪能量转换装置？先进的波浪预测和同时在线调整现有波浪能转换（WEC）设备的运行参数（如液压系统压力和发电机负载）有可能将其功率提取效率提高至少200%。然而，这些先进的控制理论的应用至今尚未在工业中得到实施。这主要是由于两个主要问题：(1)提前20-40秒预测WEC系统遇到的波浪的困难，这需要有效地实施在线调谐策略；(2)考虑到各种非线性系统行为和约束，与优化控制系统相关的挑战。该项目的研究目标是解决这一多学科问题中的关键问题，并开发一个工具箱，使WEC设备开发人员能够优化其设备性能，从而实现WEC设备性能和经济可行性的变革性改进。在第一阶段，将开发和测试一个软件套件，利用先进的模拟、评估和控制工具，这将使现有WEC设备的性能得到显著改善。该项目的更广泛影响/商业潜力将是为波浪能提供有效的成本降低途径。根据美国能源部最近发布的一项研究，仅在美国，波浪能每年可提供高达630TWh的电力，相当于2011年美国电力需求的15%。按照目前8美分/千瓦时的市场价格，这意味着每年有500亿美元的市场机会，并将为美国经济增加超过15万个就业岗位。不幸的是，目前的WEC方法需要大幅降低成本和/或提高性能，才能与其他发电方法竞争。先进的控制和快速调谐将使降低成本的途径，使波浪能与其他发电方法具有竞争力。准确预测波场的能力（在某些情况下，使用先进的控制理论来采取纠正措施，以最小化负载，提高性能和/或操作安全性）在其他领域有许多应用，包括海啸预测、海上作业和海上油气。虽然这些应用在目前的努力中不会进行探索，但本研究奠定的基础很容易扩展到这些相关领域。

This Small Business Technology Transfer Phase I project is titled ?Performance Optimization Toolbox for Wave Energy Conversion Devices?. Advanced wave prediction and concurrent online adjustment of the operating parameters (such as hydraulic system pressure and generator load) of existing wave energy conversion (WEC) devices have the potential to increase their power extraction efficiency by at least 200% over presently used approaches. However, application of such advanced control-theories have not been implemented by industry Todate. This is largely due to two major issues: (1) the difficulty of predicting the waves encountered by a WEC system 20-40 seconds in advance, which is required to effectively implement online tuning strategies, and (2) the challenges associated with optimizing the control system, given various nonlinear system behaviors and constraints. The research objectives of this project are to resolve the key issues in this multi-disciplinary problem and develop a toolbox that allows WEC device developers to optimize their device performance and therefore enable transformative improvements in WEC device performance and their economic viability. During phase I, a software suite will be developed and tested, leveraging advanced simulation, estimation, and control tools, which will enable remarkable performance improvements for existing WEC devices. The broader impact/commercial potential of this project will be to enable an effective cost-reduction pathway for wave energy. According to a recent study released by the US Department of Energy, wave power could provide up to 630TWh/year in the US alone, which corresponds to 15% of the US electrical demand in 2011. At the current market rate of 8 cents/kWh, this represents a market opportunity of $50 billion per year and would add more than 150,000 jobs to the US economy. Unfortunately, current WEC methods need to attain a significant level of cost reduction and/or performance improvement to compete with other power generation methods. Advanced controls and rapid tuning will enable a cost-reduction pathway that will allow wave energy to become competitive with other power generation methods. The ability to accurately predict wave fields (and, in certain cases, to use advanced control theory to take corrective actions to minimize loads and improve performance and/or operational safety) has numerous applications in other areas, including tsunami prediction, maritime operations, and offshore oil & gas. Though these applications will not be explored in the present effort, the foundation laid with the present research could easily be extended to these related fields.