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Integrated supply- and demand-side energy management for expeditionary environmental control

机译:集成供需侧能源管理,实现远距离环境控制

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摘要

This paper examines efficiencies achieved by optimal scheduling of power generation equipment and electrical loads in a hybrid smart micro-grid under conditions where load activity may be delayed or advanced with negligible impact to system performance. We model military expeditionary energy systems to analyze the performance of existing unmanaged components and estimate potential savings obtained by coordinated management of battlefield heating and cooling systems. We employ rolling horizon optimization models to examine performance under varying degrees of uncertainty about future load demand and renewable production.We propose a novel mechanism to reduce power production costs through optimal prescriptive scheduling of loads, reducing peak demand and generator peak-to-average power ratios and facilitating a persistent shift to higher fuel efficiencies. In contrast to existing methods that employ either supply-side or demand-side management, we propose intelligently coordinating both sides to achieve greater efficiency. Using sensitivity analysis, this paper quantitatively demonstrates how grid composition, temperature band tolerance, and energy storage capabilities contribute to fuel efficiency under this approach.
机译:本文研究了在负载活动可能被延迟或推进而对系统性能的影响可以忽略不计的情况下,通过优化混合智能微电网中发电设备和电力负载的调度所实现的效率。我们对军事远征能源系统进行建模,以分析现有未管理组件的性能,并估计通过战场供暖和制冷系统的协调管理而获得的潜在节省。我们采用滚动式水平优化模型来检查未来负载需求和可再生能源生产在不同程度不确定性下的性能。我们提出了一种新颖的机制,可通过优化规范的负载调度,降低峰值需求和发电机峰均功率来降低发电成本比率并促进持续向更高的燃油效率转变。与采用供应方或需求方管理的现有方法相比,我们建议智能地协调双方以实现更高的效率。通过敏感性分析,本文定量地证明了采用这种方法时电网组成,温度带公差和储能能力如何有助于提高燃油效率。

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