CAREER: Redesign of Ancillary Services via Aggregation and Disaggregation of Information, Flexibility, and Capability

About This Grant

This NSF CAREER project aims to provide the theoretical foundation of aggregating and disaggregating nodal generation capacity, flexibility, and information, which will allow exploiting the full potential of distributed energy resources and electrified transportation in future decarbonized power grids. The project will transform the conventional energy and ancillary service co-optimization-based power grid operation scheme into a novel capacity-flexibility dispatch and redispatch control framework. This will be achieved by converting existing resource planning problems with system-wide requirements into granular control problems with multi-scale, multi-domain nodal requirements. The intellectual merits of the project include developing nodal demand, capacity, flexibility composite models and computationally efficient aggregation algorithms with guaranteed characteristics under uncertainty. The broader impacts of the project include promoting the integration of research and education for students with varied backgrounds. Pre-college and undergraduate students will benefit from resulted summer research programs, workshops, capstone projects, and open-access curriculum materials. If successful, this project will also provide power system operators with technology advancements to integrating large-scale renewable energy and enhancing grid resilience. Uncertainties by fast-growing penetration of distributed energy resources, proliferation of electrified transportation, and climate change intertwine and amplify challenges posed on power system reliability. Consequently, widespread and prolonged power outages have been occurring increasingly more frequently and severely in recent years, which illustrates the inadequacy of existing ancillary services provided by reserving unloaded capacity on generation resources. The proposed project will redesign conventional resource planning-based ancillary services into a novel capacity-flexibility dispatch/redispatch control problem through three major technical innovations: (1) Mathematical models and effective aggregation of nodal flexibility provided by both distributed energy resources and electrified transportation through novel cost-aware, multi-period optimization techniques. (2) Computationally effective, granular control policies for the proposed nodal level co-dispatch are established as theoretical co-optimization problems converted through transformations and information aggregation, which will be solved both precisely with guaranteed performance and approximately as a data-driven problem. (3) Aggregating nodal information to determine nodal ancillary service requirements by extended Minkowski sum of polytopes, which will be further integrated into a unified theoretical framework by Difference of Convex programming. 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.