Non-Gaussian Multivariate Processes for Renewable Energy and Finance

随着分布式光伏（PV）面板在邻近屋顶上的不断推广，电网正面临挑战。 这种光伏装置由于微尺度天气模式和日变化而产生可变的、不确定的和间歇性的电力供应。了解这种不确定的可再生能源的影响需要高分辨率的时空辐照度数据;然而，精细尺度辐照度数据是罕见的，因此，影响评估必须依赖于模拟情景。与此同时，加密货币越来越成为企业和个人投资者的常见投资领域。然而，技术和价格记录的新生状态留下了历史数据的缺乏。因此，金融建模和投资研究需要同时考虑多个加密货币联合行为的模拟场景。 该项目将开发新的方法，以产生可用于风险和影响研究的现实的综合数据集。 此外，本项目将支持学生的教育和培训，他们将获得统计学、可再生能源科学和金融学交叉领域的跨学科研究经验。本研究将为表现出间歇性跳跃行为的多变量非高斯过程开发新的建模框架。 这些方法将更好地了解太阳辐照度的变化性和不稳定性以及主要加密货币投资组合的联合行为。 基于辐射强度计的时空原位测量和一套流行的现代加密货币历史价格将用于说明新方法。 开发的方法将直接受益于能源科学、气象学、金融和经济学领域，并适用于许多其他学科，包括地理学、生态学、环境科学和物理学等。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The electrical grid is experiencing challenges with the expanding introduction of distributed photovoltaic (PV) panels over neighborhood rooftops. Such PV installations generate variable, uncertain and intermittent electricity supply due to microscale weather patterns and diurnal variation. Understanding the impacts of such an uncertain renewable energy resource requires high resolution space-time irradiance data; however, fine scale irradiance data are rare, and impacts assessments must therefore rely on simulated scenarios. In a parallel vein, cryptocurrencies are increasingly common investment areas for businesses and individual investors. However, the nascent state of the technology and price record leave a dearth of historical data. Thus, financial modeling and investment studies require simulated scenarios that consider the joint behavior of multiple cryptocurrencies simultaneously. This project will develop new methodology to produce realistic, synthetic data sets that can be used in risk and impacts studies. Moreover, this project will support education and training of students who will gain interdisciplinary research experience at the intersection of statistics, renewable energy science and finance.This research will develop new modeling frameworks for multivariate non-Gaussian processes that exhibit intermittent jump-like behavior. Such approaches will afford better understanding of the variability and intermittency of solar irradiances and the joint behavior in major cryptocurrency portfolios. Space-time in situ pyranometer-based measurements of irradiances and a suite of popular modern cryptocurrency historical prices will be used to illustrate the new approaches. The methods developed will directly benefit the fields of energy science, meteorology, finance and economics with applicability in many further disciplines including geography, ecology, environmental science and physics, among others.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.