Generation Schedule Optimisation for Gas Turbine Power Systems

Abstract

In the last decades, the approach to dispatch and manage electricity in power generation plants has been one of the most difficult problems in the electricity market. Despite of all the benefits of distributed poly-generation and combined heat and power systems, their penetration in the power market worldwide is quite modest and one of the barriers against their increasing participation is the high fees for back-up supplies, which is one of the problems addressed in this investigation. This paper introduces a hybrid dynamic programming adapted priority list technique to solve the multi unit generation schedule optimization problem of a pool of independent gas turbines based power generation units. The combination of the traditional Dynamic Programming algorithm and the proposed heuristic Adapted Priority List technique allowed a significant reduction on the complexity of the original problem without rejecting the optimal solution. Despite of the power generation optimization studies available in the technical literature, none of them have been modeled for such pool of independent power generators trading electricity in the competitive market. This approach shows that the proposed concept can result in a significant saving to generators/end-users trading electricity in a competitive market.

Techno-economic evaluation and optimization of CCGT power Plant: A multi-criteria decision support system

“…However, maintenance costs are deeply affected by the GT hot section life consumption, where engine health state degradation is more prominent and non-recoverable and this has not been considered in the maintenance cost models [10,13,15,19,21,31,32]. In previously published studies [26,[33][34][35], the plant's total power setting was deemed to be constant for each condition, and thermodynamic/thermo-economic optimization was applied to determine the power distribution between different engine sets.…”

“…The detailed process is explained as follows. Firstly, the weight factor, 𝑤, [26,[33][34][35] is defined for different criteria, as shown in Eq. (10).…”