Cost and emission optimization in short term power generation scheduling

Abstract

Worldwide a considerable increase in energy use is being experienced day by day. Likewise, ever increasing electrical energy demand leads to an increasing need in installed capacity, clean energy resources and low cost generation technologies. In this respect, efficient electrical energy generation plays a crucial role in worldwide energy policies globally. This study aims to construct an optimization model of Short Term Generation Scheduling (STGS) problem to generate a short term dynamic power generation profile for a given set of power plants (PPT) for any specified scheduling period, such as a daily or weekly time horizon. The constructed STGS model aiming the minimization of the total electricity generating cost is determined as a single main model including the combination of two subproblems called the Unit Commitment and the Economic Dispatch problems. Having originated from this point of view, both selection of the individual PPTs when to be in operation and for how long, and optimal allocation of the power demand among the committed and operating units are determined in one main model, in a clear and applicable way. The STGS model, which is formulated as a mixed integer non-linear programming model, is solved under a variety of scenarios. Accordingly, this study is expected to provide a platform to better analyze the effects of various key factors such as customer load demand, system maximum emission limit, total cost per production, and minimum up and down time limitations on the STGS. Moreover, in the study, comparative analyses of the scenario results are discussed and presented in detail.