Smart Power Systems of the Future: Foundations for Understanding Volatility and Improving Operational Reliability

Abstract:

This project addresses architectural considerations in the design and operation of future power grids. This includes the consideration of sophisticated sensing, communication, and actuation capabilities on the system's reliability, price volatility, and economic and environmental efficiency. This project addresses the following components:  (a) the development of tractable cross-layer models; physical, cyber, and economic, that capture the fundamental tradeoffs between reliability, price volatility, and efficiency,  (b) the development of computational tools for quantifying the value of information on decision making at various levels, (c) the development of tools for performing distributed robust control design at the distribution level in the presence of information constraints, (d) the development of dynamic economic models that can address the real-time impact of consumer's feedback on future electricity markets, and finally (e) the development of  cross-layer design principles and metrics that address critical architectural issues of the future grid.

1. New Architectures for Dynamic Demand Response and Integration of Renewables:

  • Efficiency and Risk Tradeoffs: In order to study the impact of dynamic demand response in future smart grid, we examine in an abstract framework, how a tradeoff between efficiency and risk arises under different market architectures. We first examine the system performance under the non-cooperative and cooperative market architectures, both under marginal production cost pricing. The statistics of the stationary aggregate demand processes show that, although the non-cooperative load scheduling scheme leads to an efficiency loss, the stationary distribution of the corresponding aggregate demand process has a smaller tail, corresponding to less aggregate demand spikes. We also investigate, in a non-cooperative setup, how real-time electricity pricing can be used as a tool by the system operator to optimally strike the tradeoff between efficiency and risk. We further provide a convex characterization of the Pareto front of system performance measures, which serves as a benchmark of the tradeoffs for the system operator to evaluate the pricing rules. We observe that under marginal cost pricing, neither cooperative nor non-cooperative is Pareto optimal. This suggests that marginal cost pricing rule should be revisited in order to improve the overall efficiency and robustness of power systems.
  • Decentralized Congestion Control:  In an energy market with dynamic pricing, consumers can optimize their individual utilities adopting several mechanisms among which load-shifting is one of most effective ones. However, the response of a large number of uncoordinated price-responsive consumers might lead to local or global congestion of the power distribution system. This work studies architectures that provide guarantees that a large number of price-responsive consumers would not compromise the reliability of the network while maximizing their own utilities. This architecture is based on the computation of the largest set of admissible decisions that are going to preserve the integrity of the system, while giving maximum freedom to the users. It is shown that this set admits a precise mathematical characterization defined by a relation of partial ordering. This set of admissible decisions can be effectively used along with a constrained multi-object auction mechanism to establish a verified decision protocol providing both the efficiency of a distributed dynamic pricing system and the reliability of a centralized approach.
  • CPS Domains
  • Energy Sector
  • Smart Grid
  • Control
  • Energy
  • Critical Infrastructure
  • Foundations
  • National CPS PI Meeting 2013
  • Poster
  • Academia
  • CPS PI Poster Session
Submitted by Munther Dahleh on Fri, 10/25/2013 - 10:27