Optimize Operation Of Combined Cycle Power Plant: Model, Arithmetic And Application

As a large number of gas-steam combined cycle power plants established in China, researching on optimal operation at plant-level had great significance in theory and practice. This paper investigated the optimize operational model, algorithm and application aim at S109FA-burning natural gas, heavy-duty gas turbine combined-cycle single unit, and the contents of optimal operation include load distribution, compressor washing and shutdown optimization, these aspects correspond to the urgent request of combined cycle power plant to run securely, steadily and economically.The load optimal distribution between units can be divided into two parts, real-time load distribution and load distribution plan. With the changing of load, unit performance will change significantly. Under the condition of security running, considering the operating costs, including fuel consumption, open consumption and shutdown consumption, through immune-taboo algorithm, the best units load distribution mode can be calculated, and give decision advice at unit operation.The compressor optimal washing is to deal with the compressor fouling mainly due to deposits formed on the compressor blades by particles carried in by the air that are not large enough to be blocked by the inlet filter. As a direct result of the compressor fouling, the capacity of flow and compress will decline, and depressed unit's thermal efficiency. Through the analysis of compressor washing standard, the washing suggestion proposed on the basis of real-time performance calculation both in actual and theory.The shutdown optimization under the restriction of the gas quantity was by the study the performances of target unit to formulate shutdown plans for units respectively, in ensuring security under the premise of downtime, to achieve the purpose of generating more electricity and produce more economic benefits.In the program, the .NET framework and programming language C# were used, and made full use of PI real-time/historical database and SQL Server in their respective strengths on data management. In order to improve the user experience, the major data were showed on graphics in the WEB interface.