Background: The increasing concern of global climate change, the promotion of renewable
energy sources, primarily wind generation, reduces the power generation from conventional plants that
lead to the reduction in pollutant emission. The exploitation of wind power generation is rising
throughout the world. The objective of Unit Commitment (UC) is to identify the optimal generation
scheme of the committed units such that the overall generation cost is reduced, when subjected to a
variety of constraints at each time interval. The optimum generation planning in electrical power system
is difficult, since UC Problem has many variables and system and unit constraints of thermal generating
units. Nowadays, it is essential to include reliability analysis of the power system in operation strategy
of the generating units. Here, the generator failure and malfunction are considered in UC problem
Methods: This paper presents a meta-heuristic algorithm based approach to determine the thermal
generation schedule with consideration of wind energy system. A novel evolutionary algorithm known
as Grey Wolf Optimization (GWO) algorithm is applied to solve the UC problem.
Results: The potential of the GWO algorithm is validated by the standard test systems. Besides, the
ramp rate limits are also incorporated in the mathematical problem formulation. In order to validate the
applicability of the GWO, the standard test system is used for demonstration.
Conclusion: The GWO algorithm is applied for the first time to solve wind integrated thermal UC
problem considering generator forced outage rates. The simulation results reveal that the GWO
algorithm has the capability of obtaining economical resolutions with good solution quality. The
implementation of algorithm for solving the chosen problem is simple and robust which indicates that
the GWO is a promising alternative for solving wind integrated thermal UC problems.