EAGER: Renewables: Supply Rate Control and Grid Stability with Renewable Power Generation and Co-located Storage

可再生能源发电机面临着功率输出的变化性问题，这使得它们很难与传统发电机竞争。投资于储能设备和系统可以在很大程度上缓解与可变发电率相关的问题。共址存储(位于可再生发电现场的存储)还有助于它们填充传输管道，从而最大限度地提高现有传输系统的效用。例如，在大风的情况下，无法在副输电系统上传输的电力可以用来为电池充电，电池可以在高峰时间供电，而高峰时间通常是风力较小的时候。因此，有很强的理由使用共址存储和可再生能源发电。该项目旨在研究一些关键的理论建模、分析、优化和控制挑战，这些挑战与有效利用这种配备储存的可再生能源发电有关。将从单个可再生能源发电机的角度，以及从试图以分散方式整合若干可再生能源的整个电网的角度，探讨技术挑战。该项目的教育和外联方面包括将研究见解纳入RPI的电力工程和控制系统研究生课程。与电力公司的沟通将被用来最大限度地扩大该项目的产业覆盖面，使该项目具有良好的基础和实际影响。该项目试图从理论建模和分析的角度研究智能电网在以经济高效的方式将可变费率可再生能源供应整合到电网中，同时确保电网稳定所面临的一些基本问题。这些问题从根本上也与使用存储资源的价值有关--无论是从可再生发电机本身的角度，还是从整个电网的角度。其中第一个涉及优化可再生发电机组的提前计划和实时运行(配备共置存储)：在给定前一天(实时)电价和发电率预测的情况下，存储有限的可再生发电机组应该如何提前优化(动态控制，分别)。它的电力供应合同(费率，分别)在输电约束下，最大化其盈利能力。我们在本项目中研究的两个问题中的第二个涉及分散动态控制机制的研究，该机制可用于利用大量配备存储设备的可再生发电机组进行频率调节。这涉及到对随机频率调节方案的稳定性问题的新探索，并对其进行调整以确保收敛以及良好的暂态行为。从理论上讲，解决这些问题需要在随机优化、排队论、分散控制和随机稳定性及其在电力网络中的应用方面探索新的具有挑战性的问题。

Renewable power generators face the problem of variability of their power output, which makes it difficult for them to compete with conventional generators. Investing in energy storage devices and systems can alleviate the problems associated with variable generation rates to a good extent. Co-located storage (storage located at the site of renewable generation) also helps them to fill the transmission pipeline, and thereby maximize the utility of the existing transmission systems. Under high wind conditions, for example, the power that cannot be transmitted on the sub-transmission system can be used to charge batteries, which can be used to supply energy during peak hours, when the wind is typically low. Therefore, there is a strong case for the use of co-located storage with renewable power generation. The project aims at investigating some key theoretical modeling, analysis, optimization and control challenges that relate to making efficient use of such storage-equipped renewable power generation. The technical challenges will be explored both from the perspective of an individual renewable power generator, and from that of the overall grid in attempting to integrate a number of renewable energy sources in a decentralized manner. Education and outreach aspects of the project include integration of research insights into graduate courses in power engineering and control systems at RPI. Communication with power companies will be used to maximize the industrial outreach of the project, to make the project well grounded and practically impactful.The project seeks to investigate - from a theoretical modeling and analysis perspective - some fundamental questions that the smart grid faces in integrating the variable-rate renewable energy supplies into the grid in an economically efficient manner, while ensuring the stability of the grid. The questions are also fundamentally related to the value of using storage resources - both from the viewpoint of the renewable power generators themselves, as well as the grid as a whole. The first of these involves optimizing the day-ahead planning as well as real-time operations of the renewable power generators (equipped with co-located storage): given the day-ahead (real-time) electricity prices and power generation rate forecasts, how should a renewable power generator with limited storage optimize in advance (dynamically control, resp.) its power supply contracts (rates, resp.) under transmission constraints to maximize its profitability. The second of the two issues we investigate in this project involves the study of decentralized dynamic control mechanisms that can be used for frequency regulation using large numbers of storage-equipped renewable power generators. This involves novel exploration of stability issues of randomized frequency regulation schemes, and tuning them to ensure convergence as well as good transient behavior. From a theoretical perspective, addressing these issues requires exploring novel challenging questions in stochastic optimization, queuing theory, decentralized control and stochastic stability, and their applications to power networks.