CAREER: Adaptive Investments for Resilience of Electricity Infrastructure Systems

该教师早期职业发展（CAREER）计划项目将：（i）产生新的决策理论和模型，以帮助政府决策者制定激励措施，以推动公私企业资本形成和投资电力基础设施系统;（ii）调查并提供自组织的恢复计划。灵感来自生物系统中的自我修复特性，如形态发生（适应环境变化的基因）和伤口愈合（由于再生而引起的细胞功能变化），这个CAREER项目将扩展复杂适应系统的范例，方法是将现实主义和经验数据结合到具有实际意义的模型中，例如，为了增强系统，在特定的电力技术组合中投资多少resilience.除了在激励电力市场参与者方面创造新的决策理论外，成果之一将是一个决策支持平台，以促进公私企业参与社区抗灾工作。为了将研究内容纳入教育活动，该项目将：㈠将社会创新和创业精神纳入各级学生的学习; ㈡创建一个分层的创客空间学院，向高中和科学、技术、工程和数学学生提供知识，通过将项目任务纳入正式和非正式学习过程，建立决策的经验和分析模型;以及（iii）将经济学、运筹学和生物学的方法与工程知识相结合。多学科的方法将有助于扩大在研究和积极影响工程education.This研究是在预测分析用于预测电力中断和强大的随机优化模型，用于确定在政策和技术性能的顺序和多个不确定性的能源技术组合的投资预测的关系。该项目将把这些方法整合到一个生物启发的复杂适应系统框架中，以评估以绩效为导向的动态投资，并使用情景分析来提取提高效率的电力技术组合的阈值。PI将把系统修复过程解释为基础设施衰退、运行状态/环境、适应性、冗余以及资产分散化的潜力的动态函数，以限制损害传播和停机时间延长的灾害倾向。该框架将采用多个泰勒级数函数与广域测量系统数据，用于在修改后的IEEE总线测试系统内进行系统稳定性预测。该项目将借助综合评估模型，如全球变化评估模型（GCAM）和可计算一般均衡（CGE）模型，在系统相互依存的更大方案中评估弹性基础设施系统的价值，这些模型注入了物理系统退化的数学表示。如果成功的话，这个CAREER项目将为多学科方法的有效性提供第一个科学测试。这个奖项反映了NSF的法定使命，并被认为是值得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的支持。

This Faculty Early Career Development (CAREER) Program project will: (i) generate new decision theories and models to help government policymakers in crafting the incentives to advance public-private enterprise capital formation and investments into electricity infrastructure systems; and (ii) investigate and provide self-organized restoration plans in the advent of a disruption. Inspired by the self-healing properties in biological systems such as morphogenesis (genes adapting to environmental changes) and wound healing (functional changes in cells due to regeneration), this CAREER project will expand the paradigms of complex adaptive systems by incorporating realism and empirical data into models that have practical implications such as how much to invest in a particular electricity technology portfolio in order to enhance system resilience. In addition to creating new decision theories in incentivizing players in the electricity market, one outcome will be a decision support platform for policymaking to enhance public-private enterprise participation in community resilience efforts. To integrate the research components into educational activities, this project will: (i) incorporate social innovation and entrepreneurship to reach students at all levels; (ii) create a hierarchical makerspace academy to provide high school and STEM students the knowledge to build empirical and analytical models of decision making by including project tasks in formal and informal learning processes; and (iii) integrate methods from economics, operations research, and biology with engineering knowledge. The multi-disciplinary approach will help broaden participation of underrepresented minorities in research and positively impact engineering education.This research is at the nexus of predictive analytics used to forecast electric power disruptions and robust stochastic optimization models used to determine investments into energy technology portfolios under sequential and multiple uncertainties in policy and technological performance. This project will integrate these approaches in a bio-inspired complex adaptive system framework to evaluate performance-oriented dynamic investments, and use scenario analysis to distill the thresholds of resilience-enhancing electricity technology portfolios. The PI will interpret the system healing process to be a dynamic function of infrastructural decay, operating status/environment, adaptation, redundancy, and the potential for assets decentralization to limit disaster propensity for damage propagation and downtime protraction. This framework will employ the multiple Taylor Series function with wide area measurement system data for system stability prediction within a modified IEEE bus test system. This project will evaluate the value of a resilient infrastructure system in the larger scheme of systems interdependence with the aid of Integrated Assessment Models such as Global Change Assessment Model (GCAM) and Computable General Equilibrium (CGE) models infused with mathematical representations of physical system degradation. If successful, this CAREER project will provide the first scientific test of the efficacy of the multi-disciplinary approach.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.