CAREER: Self-Organizing Demand Side Management for Smart Grid: A Dynamic Game-Theoretic Framework

Texas Tech University, Lubbock TX

Investigators

Abstract

The objective of this research is to apply dynamic game theory to develop a new self-organizing demand side management paradigm that can adapt and coordinate consumers load in response to changes in electricity prices and renewable power availability and when the system reliability is at risk, with minimal overhead on utilities. The approach is to first design new plug-and-play hardware/software energy consumption scheduling agents that control the consumers load, such as charging electric cars. Then to build a game-theoretic foundation and new mathematical tools to investigate and optimally shape the operation of energy consumption scheduling agents to encourage consumer cooperation, support renewable power integration, minimize generation cost, and maintain power quality. Intellectual Merit: The challenges in modeling the energy consumption management agents and their interactions will be investigated with respect to the inter-temporal and locational dependencies in demand, renewable generation, and conventional generation in both micro-grid and macro-grid scenarios. Novel competitive and cooperative dynamic game-theoretic demand side management solutions will be derived. A self-organizing demand side management test-bed will be developed. Broader Impacts: This project has a transformative potential to replace existing centralized demand response programs with decentralized self-organizing systems that can encourage large-scale consumer participation to reach the twenty percent peak load shaving goal identified by the Federal Energy Regulatory Commission. The education plan includes organizing LEGO Energy Competitions and Energy Camps for K-12 students to increase awareness about demand side management, recruiting a minority graduate student, developing a new course on smart-grid, and training students for energy careers.