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These include unit commitment, economic dispatch and regulation services.
Mixed integer linear programming is one of the main approaches used to solve unit commitment problems.
In this, the unit commitment schedule is coded as a string of symbols.
This paper presents an improved particle swarm optimization algorithm (IPSO) for power system unit commitment.
A more efficient unit commitment algorithm based on operational cycles is developed.
This paper proposes a floating-point genetic algorithm (FPGA) to solve the unit commitment problem (UCP).
Unit commitment (UC) is an important function in generation resource management.
For this purpose, equipment malfunction or failure should be considered in unit commitment.
One of these includes the option of running the model with unit commitment.
This makes predicting unit commitment and dispatch ahead of time difficult.
In this paper, a robust unit commitment model to minimize the generalized social cost is proposed for the optimal unit commitment decision taking into account uncertainty of the price elasticity of demand.
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