Optimum Planning of Electricity Production

Author:

Cerri Giovanni1,Gazzino Marco1,Iacobone Francesca Alessandra1,Giovannelli Ambra1

Affiliation:

1. Dipartimento di Ingegneria Meccanica e Industriale, Università Roma Tre, Roma 00146, Italy

Abstract

The problem of planning the production of a pool of power plants has been deeply investigated. Maintenance management and load allocation problems have been assumed as crucial aspects for achieving maximum plant profitability. A production-planning approach has been developed, and genetic algorithm techniques have been adopted to implement the developed approach. Life consumption of gas turbines’ hot-section components has been considered as a key element required in simulating plants’ behaviors. As a result, a deterioration model has been developed and included into the planning algorithm. The developed approach takes market scenarios, as well as actual statuses and performances of plant components into account. The plants’ physical models are developed on a modular approach basis and provide the operating parameters required by the planning algorithm. Neural network techniques have been applied to speed up the simulation. Economic implications related to maintenance strategies, including postponement or anticipation of maintenance interventions, are investigated and the results obtained by the numerical simulation are presented and widely discussed.

Publisher

ASME International

Subject

Mechanical Engineering,Energy Engineering and Power Technology,Aerospace Engineering,Fuel Technology,Nuclear Energy and Engineering

Reference44 articles.

1. High Efficiency Electric Power Generation: The Environmental Role;Beèr;Prog. Energy Combust. Sci.

2. Cerri, G., Borghetti, S., and Salvini, C., 2006, “Models for Simulation and Diagnosis of Energy Plant Components,” ASME Paper No. PWR2006-88146.

3. Hot Section Life Assessment by a Creep Model to Plan Gas Turbine Based Power Plant Electricity Production;Cerri

4. An Application of Neural Network in Combustion Processes Evaluations;Boccaletti

5. Neural Network Approach in Gas Expansion Evaluations;Boccaletti

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