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An integrated GIS and robust optimization framework for solar PV plant planning scenarios at utility scale

机译:适用于公用事业规模的太阳能光伏电站规划方案的集成GIS和强大的优化框架

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摘要

Today, the overall goal of energy transition planning is to seek an optimal strategy for increasing the share of renewable sources in existing power networks, such that the growing power demand is satisfied at manageable short/long term investment. In this paper we address the problem of PV penetration in electricity networks, by considering both (1) the spatial issue of site selection and size, and (2) the temporal aspect of hourly load and demand satisfaction, in addition with the investment and maintenance costs to guarantee a viable and reliable solution. We propose to address this spatio-temporal optimization problem through an integrated GIS and robust optimization model, that allows handling of the ubiquitous dependencies between resource and demand time variability and the selection of optimal sites of renewable power generation. Our approach contributes to the integration of the multi-dimensional and combinatorial aspects of this problem, gathering geographical layers (regional or national scale) and temporal packing (hourly time stamp) constraints, and cost functions. This model computes the optimal geographical location and size of PV facilities allowing energy planning targets to be met at minimal cost in a reliable manner. In this paper, we illustrate our approach by studying the penetration of large-scale solar PV in the French Guiana's power system. Among the results, we show for instance that: (1) our approach performs geographical aggregation with real contextual data, i.e. balances the intermittency of RE sources by spreading out the corresponding installations (location + size) across the territory; (2) the total installed PV capacity can be doubled by removing the 35% penetration limit on intermittent power without exceeding hourly demand; (3) the safest investment scenario is below 30 MW of new PV facilities (approximate to 45M(sic) and 2 plants), though it is theoretically possible to install up to 45MW (> 120M(sic) and 11 plants).
机译:如今,能源过渡计划的总体目标是寻求一种最佳策略,以增加可再生资源在现有电网中的份额,从而以可管理的短期/长期投资来满足不断增长的电力需求。在本文中,我们通过考虑(1)选址和规模的空间问题,以及(2)每小时负荷和需求满足的时间方面以及投资和维护,来解决光伏网络在光伏网络中的渗透问题。成本以确保可行且可靠的解决方案。我们建议通过集成的GIS和健壮的优化模型解决时空优化问题,该模型可以处理资源与需求时间可变性之间普遍存在的依存关系,并选择可再生能源发电的最佳地点。我们的方法有助于整合此问题的多维和组合方面,收集地理层(区域或国家范围)和时间打包(每小时时间戳)约束,以及成本函数。该模型计算出光伏设施的最佳地理位置和规模,从而以可靠的方式以最小的成本满足能源规划目标。在本文中,我们通过研究大型太阳能光伏在法属圭亚那电力系统中的渗透来说明我们的方法。在结果中,我们举例说明:(1)我们的方法使用真实的上下文数据执行地理汇总,即通过在整个区域内分布相应的安装(位置+大小)来平衡可再生能源的间歇性; (2)在不超过每小时需求的情况下,通过取消对间歇性电力的35%渗透极限,可以将总装机光伏容量增加一倍; (3)最安全的投资方案是新建光伏设施低于30兆瓦(大约45M(sic)和2座电厂),尽管理论上可以安装45MW(> 120M(sic)和11座电厂)。

著录项

  • 来源
    《Applied Energy》 |2020年第15期|114257.1-114257.18|共18页
  • 作者

  • 作者单位

    Univ Reunion Univ Montpellier ESPACE DEV IRD 275 Route Montabo BP 165 Cayenne 97323 French Guiana;

    Univ Reunion Univ Guyane IRD ESPACE DEV Univ Montpellier 500 Rue Jean Francois Breton F-34090 Montpellier France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    GIS; Robust optimization; Spatiotemporal dimensions; Solar PV; Energy planning; Site selection;

    机译:地理信息系统强大的优化;时空维度;太阳能光伏;能源规划;选址;

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