A Solution Methodology for the Unit Commitment Problem in Traditional-and-wind Integrated Hybrid Power Systems Under Supply/Demand Uncertainty and Emission Limitations
Tolga Karabaş METU, Department of Industrial Engineering
Unit commitment problem (UCP) is one of the essential problems in operations planning of power generation systems. The objective is to minimize total operating cost while meeting the forecasted load requirements and satisfying several operational and technical constraints. Nevertheless, the UCP is a mixed integer, non-linear, combinatorial and NP-hard problem, making it difficult to develop any rigorous optimization method for a real-size system. In this study, we address two variants of the UCP: (1) the deterministic UCP in conventional power systems, (2) the stochastic UCP in wind integrated hybrid power systems. For the first one, an effective and efficient Genetic Algorithm-based approach is developed. For the second one, Mixed-Integer Quadratic Programming-based approaches are developed. In these approaches for the stochastic UCP, novel expected energy not served (EENS) approximation methods are proposed to model both load demand uncertainties and supply uncertainties due to intermittent nature of wind power generation and outages in conventional generation. Furthermore, the proposed approaches are extended to consider: (i) the Valve Point Loading Effect in efficiencies of conventional generating units by proposing efficient multi-area piecewise linear approximation, (ii) the impacts of Emission Control Technologies and Emission Trading and Taxing Mechanisms in mitigating greenhouse gas and air pollutant emissions caused by conventional generating units. According to numerical experiments and sensitivity analysis results, both Genetic Algorithm-based and Quadratic Programming-based approaches are proven to be valid and effective, and they can provide satisfactorily good power generation schedules for large scale power systems in a reasonable computational time.
Tolga Karabaş received his B.Sc. degree from Middle East Technical University Industrial Engineering Department in 2017. In the following year, he earned his Minor degree from Middle East Technical University Business Administration Department. He received his M.Sc. degree from Middle East Technical University Industrial Engineering Department in 2020. He currently holds a Research Assistant position in the Department of Industrial Engineering METU, where he continues his Ph.D. studies. Prior to his current position, he had worked as a Central System Operations Specialist in Enerjisa Başkent Elektrik Dağıtım A.Ş. for more than two years. His main responsibilities were grid asset management and project management to improve grid operations and maintenance activities in the power grids of Ayedaş, Başkent EDAŞ, and Toroslar EDAŞ. His research interests include mathematical modelling and optimization, stochastic programming, and data analytics applications with an emphasis on sustainable energy planning and management problems.
Friday, April 9, 2021, 4.00 pm - Zoom Meeting