A demand bidding model for multi-product industrial plants

IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Xin Tang , Michael Baldea , Elaine T. Hale , Ross Baldick , Richard P. O’Neill
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引用次数: 0

Abstract

The growing contribution of renewable energy sources has increased volatility and uncertainty in electricity markets, challenging traditional grid operation paradigms. Demand bidding (DB), a market participation model where (large) electricity users communicate their willingness to pay for electricity to the grid operator, was shown in previous work to enhance grid stability and lower generation cost. We present a DB model for multi-product industrial plants, based on an extended optimal power flow problem where the plant dynamics are represented using autoregressive with extra inputs (ARX) models. We compare DB to price-based demand-side management, showing that, under certain assumptions, the two approaches are equivalent, while DB provides more transparency and predictability to the grid operator. A case study based on an industrial air separation unit is discussed.
多产品工业厂房需求投标模型
可再生能源日益增长的贡献增加了电力市场的波动性和不确定性,挑战了传统的电网运营模式。需求投标(DB)是一种市场参与模式,(大)电力用户向电网运营商传达他们支付电力的意愿,在之前的工作中显示可以提高电网稳定性并降低发电成本。我们提出了一个多产品工业工厂的DB模型,该模型基于扩展的最优潮流问题,其中工厂动态使用带有额外输入的自回归(ARX)模型表示。我们将数据管理与基于价格的需求侧管理进行了比较,结果表明,在某些假设下,这两种方法是等效的,而数据管理为电网运营商提供了更多的透明度和可预测性。以某工业空分装置为例进行了分析。
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来源期刊
Computers & Chemical Engineering
Computers & Chemical Engineering 工程技术-工程:化工
CiteScore
8.70
自引率
14.00%
发文量
374
审稿时长
70 days
期刊介绍: Computers & Chemical Engineering is primarily a journal of record for new developments in the application of computing and systems technology to chemical engineering problems.
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