PFI-RP: Development of Novel Inverter Technologies and Prototypes for Enhanced Power Generation from Renewable Energy Resources

这个创新研究伙伴关系（PFI-RP）项目的更广泛的影响/商业潜力是增加可再生能源的可靠发电，并提高国家电网的可靠性和稳定性。可再生能源的连接和控制技术问题导致了许多大规模的故障和可再生能源的能源生产中断，危及国家电力系统的安全可靠运行。拟议中的技术旨在克服现有系统的局限性，提高将基于逆变器的资源连接到电网的可靠性，并允许更多的可再生能源为美国家庭和企业提供电力。实现这些目标将增加客户对电动或插电式混合动力汽车的采用。这项技术可能会提高美国公司在全球逆变器、人工智能（AI）和可再生能源市场的竞争力。该项目的商业影响将通过教育推广计划得到增强，该计划将吸引学生研究人员参与工程设计问题，这些问题将集成并解决与业务相关的约束和客户需求。该项目旨在将人工智能逆变器控制创新转化为商业产品、流程和/或服务。在拟议的项目中，有两个主要的差距需要克服。一个是知识差距，将以前的神经网络控制技术扩展到实际的电网跟踪和电网形成应用，以支持在并网、孤岛和独立条件下基于逆变器的资源的运行。另一个差距是将拟议的创新从实验室转移到现实世界系统的技术障碍。在知识缺口方面，研究将为神经网络控制创新提供支持逆变器运行的模块，以满足各种电网需求。在技术壁垒方面，本项目将进行研究，使开发的神经网络逆变器达到行业标准。预计结果包括可应用于实际电力公用系统的原型，以及可满足电力行业严格可靠性要求的人工智能驱动逆变器技术。商业化计划包括一组指导技术评估，以及与行业合作伙伴就商业潜力和业务计划迭代进行阶段性里程碑。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Partnerships for Innovation - Research Partnerships (PFI-RP) project is to increase dependable power generation from renewable energy resources and to improve the reliability and stability of the nation’s electric power grid. Technical problems in connecting and controlling renewable energy resources have resulted in many large-scale failures and the interruption of energy production from these resources, jeopardizing the safe and reliable operation of the nation’s electric power system. The proposed technology seeks to overcome the limitations of existing systems, increase reliability for connecting the inverter-based resources to the electric power grid, and allow more renewable energy to supply American homes and businesses. Attaining these goals will increase customer adoption of electric or plug-in hybrid electric vehicles. The technology may increase the competitiveness of US companies in the global inverter, artificial intelligence (AI), and renewable energy markets. The commercial impacts of the project are augmented by an educational outreach plan that will engage student researchers in engineering design problems that integrate and address business-relevant constraints and customer needs.The proposed project aims to translate AI inverter control innovation into a commercial product, process, and/or service. There are two main gaps to overcome in the proposed project. One is a knowledge gap to extend the previous neural-network control technology to practical grid-following and grid-forming applications supporting the operation of inverter-based resources in grid-tied, islanded, and standalone conditions. The other gap is a technical barrier to move the proposed innovation out of the laboratory into real-world systems. Regarding the knowledge gap, research will equip the neural-network control innovation with modules that can support the inverter operation to meet various grid needs. Regarding the technical barrier, research will be performed in this project to enable the developed neural network inverter to satisfy the industry standards. The expected results include prototypes that can be applied to practical electric utility systems and AI-driven inverter technology that can meet strict reliability requirements of the electric power industry. The commercialization plan consists of a set of guided technology assessments and staged milestones with industry partners on commercial potential and business plan iteration.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.