Coordinated Resource Management of Cyber-Physical-Social Power Systems

Abstract:

Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid. The project integrates ideas from economics and behavioral science into frameworks grounded in control theory and power systems. Our central construct is that of a resource cluster, a collection of distributed resources (ex: solar PV, storage, deferrable loads) that can be coordinated to efficiently and reliably offer services (ex: power delivery) in the face of uncertainty (ex: PV output, consumer behavior). Broadly, we aim to develop novel incentive mechanisms and real-time control algorithms to simultaneously manage millions of flexible end-use devices in the periphery of the electric power system. The ultimate goal is to transform the role of consumers from passive recipients of energy to active participants that willingly serve the systemic needs of the electric grid - turning the current operating paradigm on its head. We have recently put theory to practice in an experimental demand response pilot with Consolidated Edison Inc. involving the direct control of several thousand residential air- conditioning (AC) units in New York City. The idea is simple. There are roughly six million wall-mounted AC units in New York City. In total, their power consumption amounts to roughly eight gigawatts at peak -- the equivalent capacity of four large nuclear power plants. These AC loads constitute a tremendous source of demand-side flexibility that until today remains largely untapped. Our ultimate goal is to fully harness this flexibility through automatic control mechanisms. In order to do so, however, one must also design incentives to effectively recruit and retain small residential loads for such programs. Traditional marginal-cost based incentives have historically failed. In short, the money available to each individual is too small to motivate a response. Inspired by recent efforts at Stanford to decongest transportation systems, we have tackled this challenge using tools from behavioral science. Instead of paying customers small deterministic rewards for participation (as is common), we offer each customer the chance (however small) to win a large sum of money. Essentially, these raffles exploit an individual's tendency towards risk-seeking behavior in games of chance. Our initial experimental results have shown these raffle-based incentives to significantly outperform the standard incentives used in practice. An experimental result of this type has the potential to profoundly change the nature and scope of DR programs in the coming years.