The Unit Commitment Problem: A Mixed Integer Coded Genetic Algorithm-based Approach

Unit commitment(UC) is one of the essential activities in power systems planning and operation that comprises two decisions: scheduling of on/off states of electricity generating units and their dispatching over the planning horizon. The objective is the minimization of total operating costs -fuel and startup costs-, while meeting the forecasted load requirements, and satisfying several operational and technical constraints. Some of these constraints are initial status restriction of each unit, minimum up and down times, capacity and generation limits, limited ramp rate, power balance and spinning reserve constraints. UCP is a mixed integer, non-linear and combinatorial problem, making it difficult to develop any rigorous optimization method for a real-size system. Hence, we intend to develop a Genetic Algorithm to obtain an optimal/near-optimal for the UC problem. While doing so, scheduling of on/off status of generating units in each period is handled by the genetic operators. Nevertheless, dispatching decisions related to power generation levels of committed units in each period are made by the Lambda Iteration Method. The main difficulty in the genetic algorithm for the UCP is it has several constraints -both continuous and binary types. Thus, we have developed a mixed-integer coding scheme that can handle these constraints. Our approach can provide satisfactorily good schedules and power generation levels for large scale power systems in a reasonable computation time.


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Citation Formats
T. Karabaş and F. S. Meral, “The Unit Commitment Problem: A Mixed Integer Coded Genetic Algorithm-based Approach,” 2019, Accessed: 00, 2021. [Online]. Available: