Optimal Energy Scheduling in Microgrids with Photovoltaic (PV) Generation and Energy Storage Systems

具有光伏 (PV) 发电和储能系统的微电网中的最优能源调度

• 批准号: 1610396
• 负责人: Jonghyun Park
• 金额: $ 31.53万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1610396&HistoricalAwards=false
• 关键词: Optimal; Energy; Scheduling; Microgrids; Photovoltaic

This award supports fundamental research to address two major threats to public health and welfare, namely global warming and air pollution, by enabling the optimal use of solar photovoltaic energy. This project seeks to create optimal scheduling of energy storage systems incorporated in microgrids, which is a key part of a solar energy solution, and to overcome two critical limits of solar energy, intermittency and uncertainty, by addressing the degradation process of energy storage systems and the uncertainty in solar output and power demand at loads. The research results can help to fully utilize energy storage systems and to minimize their lifetime cost, enabling solar energy to become a vital source of renewable energy. Additionally, the project will engage, motivate, and train US students preparing them for the workforce in the interdisciplinary area of energy, power, and control through the development of interdisciplinary curricula and various science activities for diverse youth. This project addresses a fundamental trade-off in energy storage systems for power grid applications, which involves the integration of PV generation requiring more frequent charge/discharge cycles and the corresponding degradation process. The research will find answers to the following unsolved questions that are essential for optimal energy scheduling of a microgrid: (1) how multiple degradation mechanisms of energy storage systems are coupled, and how battery capacity fade is eventually affected by loading and environmental conditions; (2) what is the impact of uncertainty of solar radiation, market prices, and load on battery loading profiles, and how can uncertainty be addressed in optimal scheduling of microgrids. Specifically, the project has the following four objectives: (1) gain a fundamental understanding of battery degradation mechanisms and how they couple, and integrate that knowledge into a high-fidelity battery model; (2) create a low-order battery model that can generate the predicted results quickly without losing accuracy; (3) understand uncertainty phenomena in microgrids, and create a model to incorporate all of the phenomena; and (4) develop algorithms for optimal scheduling by considering battery degradation and microgrid uncertainty. The proposed research will discover how the uncertain nature of a microgrid can affect individual components, including energy storage degradation; the results are expected to constitute critical knowledge for the power engineering community. In addition, this project will develop a stochastic optimization technique for near-real-time optimal scheduling. It is expected that the general framework developed here will be adaptable for applications beyond power engineering.

该奖项支持基本研究，以解决对公共卫生和福利的两个主要威胁，即全球变暖和空气污染，通过实现太阳能光伏能源的最佳利用。该项目旨在创建在微电网中纳入的能源存储系统的最佳调度，这是太阳能解决方案的关键部分，并通过解决储能系统的退化过程以及负载下的太阳能输出和电力需求的降级过程来克服太阳能，间歇性和不确定性的两个关键限制。研究结果可以有助于充分利用储能系统并最大程度地减少其寿命成本，从而使太阳能成为可再生能源的重要来源。此外，该项目将通过开发跨学科课程和各种科学活动，为多样化的年轻人提供跨学科领域的跨学科领域的劳动力，参与，激励和培训我们为他们准备工作的学生。该项目解决了用于电网应用的能源存储系统中的基本权衡，这涉及在需要更频繁的充电/放电周期和相应的退化过程的PV生成的整合。该研究将找到以下未解决的问题的答案，这些问题对于微电网的最佳能量调度至关重要：（1）如何耦合能量存储系统的多重降解机制，以及如何最终受负载和环境条件影响电池容量； （2）太阳辐射，市场价格和负载对电池加载概况的不确定性有什么影响，以及如何在微电网的最佳计划中解决不确定性。具体而言，该项目具有以下四个目标：（1）对电池降解机制及其搭配的基本了解，并将这些知识整合到高保真电池模型中； （2）创建一个低阶电池模型，该模型可以快速生成预测的结果而不会失去准确性； （3）了解微电网中的不确定性现象，并创建一个模型以结合所有现象； （4）通过考虑电池降解和微电网不确定性来开发用于最佳调度的算法。拟议的研究将发现微电网的不确定性质如何影响各个组件，包括储能降解；预计该结果将构成动力工程社区的关键知识。此外，该项目将开发一种随机优化技术，用于近实时最佳计划。预计此处开发的一般框架将适用于动力工程以外的应用程序。