超越价格接受者:风能和电池集成能源系统的多尺度优化

Xinhe Chen;Xian Gao;Darice Guittet;Radhakrishna Tumbalam Gooty;Bernard Knueven;John D. Siirola;David C. Miller;Alexander W. Dowling
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摘要

由于风能和其他不可调度资源的间歇性和可变性,将可再生能源整合到电网中具有挑战性。综合能源系统将多种能源技术(如化石能源、核能、可再生能源、储能)结合在一起,以降低成本,提高灵活性和可靠性。然而,标准的技术经济分析(TEA)方法往往高估了环境经济的好处,因为它们没有考虑到能源市场的调整。本文系统地研究了现行价格接受者假设的局限性以及混合能源系统的优化问题。作为一个说导性的案例研究,我们用电池储能改造了RTS-GMLC测试系统(大致模仿美国西南部)中的一个现有风电场,形成了一个IES。我们表明,与我们更严格的多尺度优化相比,标准价格接受者模型对IES的电力收入和净现值(NPV)的高估分别高达178%和30.4%。这些差异的产生是因为引入储能系统创造了一种更灵活的资源,可以影响更大的批发电力市场。此外,这项工作强调了IES通过各种战略竞标对市场的影响,并强调了超越价格接受者的重要性,以实现最佳存储规模和IES的TEA。最后,我们讨论了将所提出的框架推广到其他经济体系的机会,并强调了有关经济体系与市场之间复杂相互作用的新兴研究问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond Price-Taker: Multiscale Optimization of Wind and Battery Integrated Energy Systems
Integrating renewable energy into the electric grid is challenging due to the intermittency and variability of wind and other non-dispatchable resources. Integrated energy systems (IESs) combine multiple energy technologies (e.g., fossil, nuclear, renewables, storage) to reduce costs and improve flexibility and reliability. However, standard techno-economic analysis (TEA) methods often overestimate the benefits of IESs because they fail to account for energy market adjustments. This paper systematically studies the limitations of the prevailing price-taker assumption for TEA and optimization of hybrid energy systems. As an illustrative case study, we retrofit an existing wind farm in the RTS-GMLC test system (which loosely mimics the Southwest U.S.) with battery energy storage to form an IES. We show that the standard price-taker model overestimates the electricity revenue and the net present value (NPV) of the IES up to 178% and 30.4%, respectively, compared to our more rigorous multiscale optimization. These differences arise because introducing storage creates a more flexible resource that impacts the larger wholesale electricity market. Moreover, this work highlights the impact of the IES has on the market via various strategic bidding, and underscores the importance of moving beyond price-taker for optimal storage sizing and TEA of IESs. We conclude by discussing opportunities to generalize the proposed framework to other IESs, and highlight emerging research questions regarding the complex interactions between IESs and markets.
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