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输出功率不稳定的问题，这使得它们很难与传统发电机竞争。投资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。同址存储（位于可再生能源发电地点的存储）也有助于它们填充传输管道，从而最大化现有传输系统的效用。例如，在大风条件下，不能在子传输系统上传输的电力可以用来给电池充电，这些电池可以用来在风力通常较低的高峰时段供电。因此，在可再生能源发电中使用同一地点的存储是很有必要的。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能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从整个电网的角度来探讨，试图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整合到RPI电力工程和控制系统的研究生课程中。通过与电力公司的沟通，最大限度地扩大项目的产业外联，使项目落地生根，产生实际影响。该项目旨在从理论建模和分析的角度研究智能电网在以经济有效的方式将可变速率可再生能源供应整合到电网中所面临的一些基本问题，同时确保电网的稳定性。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的角度，还是从整个电网的角度。第一个问题涉及到可再生能源发电机组的日前规划优化和实时运行优化（配置了共址存储）：给定日前（实时）电价和发电速率预测，在输电约束下，有限存储的可再生能源发电机组如何提前（动态控制，等）优化其供电合同（费率，等），使其盈利能力最大化。我们在本项目中研究的两个问题中的第二个问题涉及分散动态控制机制的研究，该机制可用于使用大量配备储能的可再生能源发电机进行频率调节。这涉及到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随机优化、排队论、分散控制和随机稳定性等新的具有挑战性的问题，以及它们在电网中的应用。

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.