The interest in microturbines and new distributed generation technologies is growing in the entire world because of the many potentially beneficial characteristics they can offer and the developments achieved so far. This paper investigates the performance and degradation effects of microturbines for electric power generation. Diagnostics investigation is also carried out to obtain optimal instrumentation sets for degradation faults. Here the capacity of the gas turbines analyzed is 29kW simple and regenerative cycles. The engine performance is also analyzed operating at constant and variable speed. To simulate the gas turbine performance and carry out the diagnostic analysis the software Pythia and Turbomatch, developed by Cranfield University, were used. In this paper the engines above are simulated at degraded conditions. The effects of the degradation in the compressor, turbine and recuperator on the performance of the engines were investigated. Despite of the improvement on performance achieved with regenerative cycle and variable speed operation the results show that the performance of variable speed microturbines is more sensitive to components degradation than constant speed engines. Also recuperator degradation has greater effect on variable speed than constant speed engines. Due the effects of degradation on each engine different diagnostic approaches are observed.
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.
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