Screening Curve for Valuing Power Generation and Storage Technologies in the 21st Century Grid

Y. Pratama, Niall Mac Dowell
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Abstract

The 21st century grids are characterised by increasing complexity of the system: high intermittent renewable energy sources (iRES) penetration requires additional flexibility and ancillary services from the other technologies (for example inertia, frequency responses, etc.). Accordingly, evaluating power technologies, i.e., power generation and storage, with LCOE, that exclusively emphasises the value of energy, alone can be misleading. On the other hand, performing detailed modeling analysis requires an enormous amount of effort and data which may not be accessible. To fill this gap, this study proposes a new metric to evaluate the performance of power technologies in the system. In addition to energy, a range of ancillary services is also considered. To balance completeness and ease of use, only the most valuable services are included in the new concept. To quantify the value of those services, we employed the Electricity System Optimisation framework with ancillary services (ESO-ANCIL) using UK electricity system as the case. Our analysis shows that although all services are valuable, capacity and energy services are the most significant. Whilst the technology screening curve is a practical approach to value those services and to derive optimal technology mix based on the system’s load duration curve, such method cannot evaluate iRES and electricity storage in the system. Therefore, we introduced a new set of rules and formulations to allow the application of the analysis for those technologies. As such, the proposed concept is particularly valuable to estimate the optimal deployment level and role or power technologies in providing energy and capacity services to the grid. Our proposed concept proves to be an easy-to-use concept that is capable in valuing a more complete set of services offered by power generation and storage technologies and can be used as an alternative to the LCOE.
21世纪电网中发电和储能技术评价的筛选曲线
21世纪电网的特点是系统日益复杂:高间歇性可再生能源(iRES)渗透需要额外的灵活性和其他技术的辅助服务(例如惯性、频率响应等)。因此,仅用LCOE来评估电力技术,即发电和储存,只强调能源的价值,可能会产生误导。另一方面,执行详细的建模分析需要大量的工作和可能无法访问的数据。为了填补这一空白,本研究提出了一种新的指标来评估系统中电源技术的性能。除能源外,还考虑了一系列辅助服务。为了平衡完整性和易用性,新概念中只包含最有价值的服务。为了量化这些服务的价值,我们以英国电力系统为例,采用了电力系统优化框架和辅助服务(ESO-ANCIL)。我们的分析表明,虽然所有的服务都是有价值的,但容量和能源服务是最重要的。虽然技术筛选曲线是一种实用的方法来评估这些服务,并根据系统的负载持续时间曲线得出最佳的技术组合,但这种方法无法评估系统中的iRES和电力存储。因此,我们引入了一套新的规则和公式,以允许对这些技术进行分析。因此,所提出的概念对于估计电力技术在向电网提供能源和容量服务方面的最佳部署水平和作用特别有价值。我们提出的概念被证明是一个易于使用的概念,能够评估发电和存储技术提供的一套更完整的服务,并且可以用作LCOE的替代方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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