A Genetic Algorithm Approach for Clearing Aggregator Offers in a Demand Response Exchange

In this paper, a pool-based market structure is implemented to trade demand response (DR) in a fully deregulated day-ahead electricity market. In this structure, the demand response aggregator provides load shifting/curtailment as DR offers to the demand response exchange (DRX) market competitively. The independent system operator (ISO) utilizes the DR service only during economic inefficiency. The DRX needs to clear the DR offers such that the overall system economic efficiency improves. Two search techniques have been implemented to clear the DRX market efficiently. One of the search methods is a local search where one DR offer is selected at a time; the other is the genetic algorithm (GA). We implement a rank-based GA in which the bus sensitivities were used for seeding the initial population to speed up convergence. These search techniques are implemented on IEEE RTS-96 system, and the DRX was cleared efficiently to improve the economic performance of the system.