Principles based modeling of costs of integrating intermittent renewable generation

本研究的目的是了解和模拟间歇性可再生能源的整合。该研究旨在系统地了解由于辅助服务需求和传输增加而导致的成本以及大规模集成的收益。这种方法既要考虑短期经营，也要考虑长期资本扩张。短期建模涉及考虑满足北美可靠性公司（NERC）频率控制标准所需的辅助服务数量。分析将通过将风力发电建模为随机过程，并使用与自动发电控制的可再生能源控制性能水平相关的敏感性分析来完成。长期建模增强了传统的筛选曲线分析，以表示对大量辅助服务和增加传输需求的资本和运营成本影响。该研究的知识价值在于，它将比现有的可再生能源集成研究更现实地反映问题，并且还将寻求避免基于全生产成本模拟的数据密集型和计算密集型方法。这项工作将开发筛选工具，这些工具将有助于估算成本和进行政策分析，并对重要问题提供定性见解。更广泛的影响这里提出的工作将产生更广泛的影响，考虑到可再生能源发电资产整合的全部影响，对减少温室气体排放的最经济方式进行基于原则的分析。这一认识将有助于在发电资源组合中进行具有成本效益的投资，以减少总体温室气体排放。

The objective of this research is to understand and model integration of intermittent renewables. The research is aimed at systematically understanding the costs, due to increased Ancillary Services requirements and transmission, and benefits of large-scale integration. The approach is to consider both short-term operations and long-term capital expansion. The short-term modeling involves the consideration of the amount of Ancillary Services necessary to satisfy North American Reliability Corporation (NERC) standards for frequency control. The analysis will be accomplished through modeling wind power production as a stochastic process and using a sensitivity analysis with respect to the level of renewables of the control performance of automatic generation control. The long-term modeling augments classical screening curve analysis to represent the capital and operating costs implications of the need for large amounts of Ancillary Services and increased transmission.Intellectual MeritThe intellectual merit of the research is that it will more realistically represent issues than in existing renewable integration studies, and will also seek to avoid data intensive and computationally intensive approaches based on full production cost simulation. The work will develop screening tools that will be useful to estimate costs and for policy analysis, and provide qualitative insights into important issues.Broader ImpactThe work proposed here will have the broader impact of enabling principles-based analysis of the most economic ways to reduce greenhouse emissions, considering the full implications of integration of renewable generation assets. This understanding will inform cost-effective investment in a portfolio of generation resources to reduce overall greenhouse emissions.