A new mathematical model has been proposed for a hydrothermal Generating Company (GENCO) considering profit maximization as objective function is presented initially. Followed by this, bi-objective problem of profit maximization with simultaneous emission minimization has been formulated. Further, the different bidding strategies adopted for maximizing the social profit has been discussed. Methods/Statistical Analysis: IEEE 30-bus system has been chosen as the test case here. All the above mentioned problem formulations are simulated using a hybrid algorithm of LR-PSO (Lagrangian Relaxation - Particle Swarm Optimization). Findings: In Short-Term HydroThermal Scheduling (STHTS), the problem of fuel cost minimization has been attempted for several decades. In the competitive electricity market there is a need for maximization of profit rather than thermal plants fuel cost minimization subjected to hydro-thermal constraints. This necessitates a suitable mathematical model. In this paper the required model has been arrived at for the IEEE test case. The findings obtained prove effectiveness of the LR-PSO algorithm in arriving at the optimal scheduling much suitable for the GENCO in the deregulated environment. Applications: The various strategies followed will definitely enable the GENCO in the optimal allocation of selling the power that is generated as well as the reserve power generated in the deregulated market. This will also provide an opportunity for the ISO to maximize the social profit.
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