在中期单位承诺中,严格和紧凑的最低成本规划制订了高分辨率的启动费用

IF 5.6 2区 工程技术 Q2 ENERGY & FUELS
Luis Montero , Germán Morales-España , Antonio Bello , Javier Reneses
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引用次数: 0

摘要

目前,大多数现代电力系统都在向储能和互联设施的大规模扩容发展。然而,这些重大发展的速度还不足以适应可变可再生能源的高度渗透。这种情况增加了需求的可变性,要求火力发电机组具有更大的灵活性,特别是由于其更频繁的启动和关闭过程。因此,在保持计算效率的同时,单元承诺需要更精确和详细的建模。本文根据燃气发电组合的实际燃料消耗曲线,分析了管理长时间启动成本的几种最佳模型。此外,我们提出了一个紧凑的MILP分段公式,提高了启动表示的分辨率,与文献基准相比取得了突出的结果。这种方法的成功表现已在几个着眼于中期的大型案例研究中得到证明。此外,还运行了常规的日前问题,以证明该公式的整体竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tight and compact MILP formulation for a high-resolution of start-up costs in the medium-term unit commitment
Nowadays, most modern power systems are evolving towards a considerable capacity expansion in their energy storage and interconnection facilities. However, these great developments are not being accomplished fast enough to accommodate the high penetration of variable renewable energy sources. This situation raises demand variability, requiring more flexibility from thermal generators, especially due to their more frequent start-up and shut-down processes. Consequently, the unit commitment requires more accurate and detailed modeling while maintaining computational efficiency. This paper analyzes some of the best models to manage long-duration start-up costs according to the real fuel-consumption curves of a gas-fired generation portfolio. Moreover, we propose a tight and compact MILP piecewise formulation that enhances the resolution of start-up representations and achieves outstanding results compared to the literature benchmarks. The successful performance of this methodology is proven in several large-size case studies focusing on the medium term. Furthermore, conventional day-ahead problems are also run to demonstrate the overall competitiveness of the formulation.
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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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