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Stochastic control and real options valuation of thermal storage-enabled demand response from flexible district energy systems

机译:灵活的区域能源系统对基于热存储的需求响应的随机控制和实物期权评估

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摘要

In district energy systems powered by Combined Heat and Power (CHP) plants, thermal storage can significantly increase CHP flexibility to respond to real time market signals and therefore improve the business case of such demand response schemes in a Smart Grid environment. However, main challenges remain as to what is the optimal way to control inter-temporal storage operation in the presence of uncertain market prices, and then how to value the investment into storage as flexibility enabler. In this outlook, the aim of this paper is to propose a model for optimal and dynamic control and long term valuation of CHP-thermal storage in the presence of uncertain market prices. The proposed model is formulated as a stochastic control problem and numerically solved through Least Squares Monte Carlo regression analysis, with integrated investment and operational timescale analysis equivalent to real options valuation models encountered in finance. Outputs are represented by clear and interpretable feedback control strategy maps for each hour of the day, thus suitable for real time demand response under uncertainty. Numerical applications to a realistic UK case study with projected market gas and electricity prices exemplify the proposed approach and quantify the robustness of the selected storage solutions. (C) 2014 Elsevier Ltd. All rights reserved.
机译:在由热电联产(CHP)电厂提供动力的区域能源系统中,蓄热可以显着提高CHP的灵活性,以响应实时市场信号,从而改善智能电网环境中此类需求响应方案的商业案例。然而,主要的挑战仍然是在不确定的市场价格情况下控制跨时间存储操作的最佳方法是什么,以及如何以灵活性来评估对存储的投资。在这种前景下,本文的目的是提出一种在市场价格不确定的情况下对热电联产蓄热器进行最优和动态控制以及长期估值的模型。所提出的模型被公式化为一个随机控制问题,并通过最小二乘蒙特卡洛回归分析进行数值求解,其综合投资和运营时间尺度分析与财务中遇到的实物期权估值模型相当。在一天中的每个小时,输出均由清晰易懂的反馈控制策略图表示,因此适用于不确定情况下的实时需求响应。在实际的英国案例研究中,通过对预期的市场天然气和电价的数值应用,证明了所建议的方法并量化了所选存储解决方案的可靠性。 (C)2014 Elsevier Ltd.保留所有权利。

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