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的问题是其功率输出的可变性，这使得它们难以与传统发电机竞争。投资于储能设备和系统可以在很大程度上缓解与发电率变化相关的问题。共同定位存储（位于可再生能源发电现场的存储）也有助于他们填充传输管道，从而最大限度地利用现有的传输系统。例如，在大风条件下，不能在子传输系统上传输的功率可以用于对电池充电，电池可以用于在风通常较低的高峰时段期间供应能量。因此，有一个强大的情况下，使用共址存储与可再生能源发电。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存储的可再生能源发电有关。技术挑战将从单个可再生能源发电机的角度和整个电网的角度进行探讨，以分散的方式整合一些可再生能源。该项目的教育和推广方面包括将研究见解融入RPI的电力工程和控制系统研究生课程。通过与电力公司的沟通，最大限度地扩大该项目的产业影响力，使该项目具有良好的基础和实际影响力。该项目旨在从理论建模和分析的角度，探讨智能电网在确保电网稳定性的同时，以经济有效的方式将可变费率的可再生能源供应纳入电网所面临的一些基本问题。这些问题也从根本上与使用存储资源的价值有关-无论是从可再生能源发电机本身还是从整个电网的角度来看。其中第一个涉及优化可再生发电机（配备有协同存储）的日前规划以及实时操作：给定日前（实时）电价和发电率预测，具有有限存储的可再生发电机应该如何提前优化（分别为动态控制）。其电力供应合同（费率，分别）在传输约束下，以最大限度地提高其盈利能力。我们在这个项目中调查的两个问题中的第二个涉及分散的动态控制机制的研究，该机制可用于使用大量配备存储的可再生发电机进行频率调节。这涉及随机频率调节方案的稳定性问题的新探索，并调整它们以确保收敛以及良好的瞬态行为。从理论的角度来看，解决这些问题需要探索新的挑战性问题，随机优化，排队论，分散控制和随机稳定性，以及它们的应用到电力网络。

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.