Hybrid GA/SA based generation maintenance scheduling with line flow constraints in power market

This paper presents a Hybrid GA/SA (Genetic Algorithm(GA) combined with Simulated Annealing (SA)) methodology for finding the optimum preventive maintenance schedule of generating units of GENCO with line flow constraints in restructured power system. In this environment, management of GENCOs and grid is separated, each maximizing its own benefit. Therefore , the principle to draw up the unit maintenance scheduling will be changed significantly. The profit of a GENCO is defined as the total profit, which is the sum of the individual units profits from the auctions over the horizon. So every GENCO hopes to put its maintenance on the weeks when the Market Clearing Price(MCP) is lowest , so that Maintenance Investment Loss (MIL) descends. Therefore objective function for the GENCO is to sell electricity as much as possible, according to the market clearing price forecast. The objective function of Independent System Operator (ISO) is to maximize the reserve capacity of the system at every time interval. ISO solves its maintenance scheduling according to its objective function. Each GENCO specifies optimum maintenance scheduling according to its objective function. Depending upon the fitness, profit and reliability index, select GENCO's maintenance scheduling (or) ISO's maintenance scheduling. Various technical constraints such as generation capacity, duration of maintenances, maintenance continuity and line flow are being taken in to account.