Collaborative Research: Advanced and Highly Integrated Power Conversion Systems for Grid Stability and Resiliency

为了加速住宅和商业光伏渗透，以满足未来的公用事业和电网需求，需要将储能和创新的电力电子技术集成到光伏系统中。将储能集成到光伏系统中可以实现电网支持，负荷转移，调峰，能源备份，减少输配电网络中的电力损耗以及优化电力利用。将电网转换为更加分布式的配置将需要远远超出今天简单的并网光伏逆变器的系统能力。该项目的目标是为光伏系统、储能和电网创建可扩展、模块化、高效和灵活的架构和控制。这种高度集成的智能系统将使太阳能更高地渗透到电网中，并通过提供集成，高效和可靠的太阳能解决方案来破坏传统的能源系统。更高的渗透率将导致更高的光伏部署和光伏行业的增长，增加就业机会，促进经济发展。一个完全集成的产品不仅可以降低安装成本和复杂性，还可以确保简化从模块供应商到最终用户的供应链管理。这种硬件和先进控制系统的技术集成及其模块化和可扩展性将为更高的光伏渗透铺平道路。教育推广活动将通过将拟议的研究整合到本科或研究生课程中，使本科和K-12学生可以访问硬件逆变器测试平台，在IEEE电力电子和电力与能源协会会议上组织小组和教程，以及举办开放式网络研讨会来进行。项目团队将建议开发和部署一种新型设计的高效、调制器、分布式控制和可扩展的电力系统，该系统具有集成和协调光伏、本地储能和双向智能微型逆变器的能力。硬件由一个三端口单级功率转换电路集成光伏，电池，电网与一种新的拓扑结构称为飞跨电容多电平逆变器与氮化镓器件。所提出的分散模型预测控制将解决包括能量存储的荷电状态控制、光伏平滑、最大功率点跟踪和能量套利在内的挑战。这将支持电网功能，提供能量转移/调峰，并应用电力管理策略，以在并网和孤岛模式下实现稳定和可预测的电力。此外，一个新的优化问题，协调多个三端口逆变器考虑电压调节和无功功率共享和电压和无功功率的技术约束之间的最佳权衡制定。一个原始-对偶梯度的分布式求解算法是要解决的独特挑战，包括不可分离的目标函数，不可用的全球平均电压，全球耦合无功功率约束。所提出的算法不仅将有效地和高效地解决制定微电网控制问题，但也将有利于分布式优化和控制社区提供一个有用的方法，分布式解决一般形式的优化problem.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

To accelerate residential and commercial photovoltaic penetration to meet future utility and grid needs, energy storage and innovative power electronics need to be integrated into photovoltaic systems. The integration of energy storage into the photovoltaic system can enable grid support, load shifting, peak shaving, energy backup, reduced power loss in transmission and distribution networks, as well as optimization of power utilization. Transforming the grid into a more distributed configuration will require system capabilities well beyond today's simple grid-tied photovoltaic inverters. The goal of this project is to create scalable, modular, highly efficient, and flexible architecture and control for photovoltaic systems, energy storage, and the grid. This smart, highly integrated system will enable higher penetration of solar energy into the grid and disrupt the conventional energy system by delivering an integrated, efficient, and reliable solar energy solution. The higher penetration will lead to higher photovoltaic deployment and growth in photovoltaic industry, increase job creation, and boost economy. One fully integrated product will not only reduce installation cost and complexity but will also ensure simplified supply chain management from module supplier to end user. Such technological integration of hardware and advanced control systems with its modularity and expandability will pave way for even higher photovoltaic penetration. Educational outreach activities will be performed by integrating the proposed research to undergraduate or graduate level courses, making the hardware inverter testbed accessible to undergraduate and K-12 students, organizing panels and tutorials at IEEE power electronics and power and energy society conferences, and hosting open-access webinars. Engaging minority and under-represented groups will be implemented throughout such outreach activities.The project team will propose the development and deployment of a novel design of a highly efficient, modulator, distributedly controlled, and scalable power system with the capability for integration and coordination of photovoltaic, local energy storage, and a bidirectional smart micro-inverter. The hardware consists of a three-port single-stage power conversion circuit integrated with photovoltaic, battery, and grid with a novel topology known as the flying capacitor multilevel inverter with Gallium Nitride devices. The proposed decentralized model predictive control will address challenges including state-of-charge control of energy storage, photovoltaic smoothing, maximum power point tracking, and energy arbitrage. This will support grid functionalities, provide energy shifting/peak shaving, and apply power management strategy for stable and predictable power in both grid-connected and islanded modes. Moreover, a novel optimization problem for coordinating multiple three-port inverters considering optimal trade-off between voltage regulation and reactive power sharing and technical constraints on voltage and reactive power is to be formulated. A primal-dual gradient based distributed solving algorithm is to be developed to address the unique challenges including non-separable objective function, unavailable global average voltage, and globally coupled reactive power constraints. The proposed algorithm will not only effectively and efficiently solve the formulated microgrid control problem but will also benefit the distributed optimization and control community by providing a useful method for distributedly solving a general form optimization problem.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.