Real time evaluation and operation of the smart grid using game theory

Utilities are implementing smart grid technology on their electric grids in an effort to receive more information and have more control of their electric grid. As a result, the utilities are able to take advantage of this new technology in the form of load reduction, reliability, and automations of the utility's grid. With the advent of Automated Meter Infrastructure (AMI), Supervisory Control and Data Acquisition (SCADA), Digital Relays, Engineering and Analysis software (EA), Power Quality meters (PQ) and Geographic Information Systems (GIS), utilities can receive more information about the power system than has been available in the past. However, with most utilities the integration of all the information available has not become a reality. This may be due to time or the cost of each piece of infrastructure and the implementation of integrating them into a single network of information. The purpose of this paper is to present a method for evaluating a fully automated electric grid in real time and finding potential problem areas or weak points within the electric grid by using the game theory principles of decision trees and "The Prisoner's Dilemma" to evaluate the best possible actions to implement within the electric grid to avoid potential problems before they happen. The process uses the output of an EA that is using real time information from the grid and calculating information such as voltage drops, current, load flow, transformers, substations, sectionalizing and switching. The algorithm allows for each utility to define their acceptable grid operating limits and this information is used by the algorithm to analyze the output of the EA. Output from the segments in the EA that are found to be outside the utility's defined grid operating limits are then sent to the part of the algorithm that uses the game theory principles to evaluate the information and look at the possible solutions and tradeoffs affecting the electric grid if those solutions are implemented. This part of the algorithm then picks the best possible solution to implement within the electric grid to avoid a potential outage, system failure or reliability issue.