Energy efficiency assessment and improvement in energy intensive systems through thermoeconomic diagnosis of the operation

Advanced monitoring techniques can play a key role in improving energy efficiency of operating energy intensive systems. In particular, thermoeconomic diagnosis aims at the determination of fuel consumption variation, the identification of causes of its increment from design conditions and the quantification of the effect of each one of these causes. A thermoeconomic diagnosis system installed in a coal-fired power plant has been used to analyse its operation during a time span of more than 6 years, quantifying the effects of variations in components (degradation, repairing and substitution), fuel quality, ambient conditions and operation strategy. The diagnosis method proposed (quantitative causality analysis) provides a precision of ±3% in addressing the source of inefficiency for about 70% of the cases.

[1]  Yong-Jin Joo,et al.  Implementation of on-line performance monitoring system at Seoincheon and Sinincheon combined cycle power plant , 2005 .

[2]  Antonio Valero,et al.  On-Line Thermoeconomic Diagnosis of Thermal Power Plants , 1999 .

[3]  Andrea Toffolo,et al.  Four approaches compared on the TADEUS (thermoeconomic approach to the diagnosis of energy utility systems) test case , 2006 .

[4]  Andrea Toffolo,et al.  On the Thermoeconomic Approach to the Diagnosis of Energy System Malfunctions - Indicators to Diagnose Malfunctions: Application of a New Indicator for the Location of Causes , 2004 .

[5]  Luis Correas On the Thermoeconomic Approach to the Diagnosis of Energy System Malfunctions - Suitability to Real-Time Monitoring , 2004 .

[6]  A. Valero,et al.  On-line monitoring of power-plant performance, using exergetic cost techniques , 1996 .

[7]  Rodolfo Taccani,et al.  On the Thermoeconomic Approach to the Diagnosis of Energy System Malfunctions The Role of the Fuel Impact Formula , 2004 .

[8]  A. Bejan,et al.  Thermodynamic Optimization of Complex Energy Systems , 1999 .

[9]  Hao Li,et al.  TOWARDS A LOW CARBON FUTURE , 2010 .

[10]  Andrea Lazzaretto,et al.  On the Thermoeconomic Approach to the Diagnosis of Energy System Malfuntions. Part-2 Malfunction Definitions and Assessment. , 2004 .

[11]  Soon Heung Chang,et al.  Algebraic approach for the diagnosis of turbine cycles in nuclear power plants , 2005 .

[12]  Antonio Valero,et al.  A Reconciliation Method Based on a Module Simulator - An Approach to the Diagnosis of Energy System Malfunctions , 2004 .

[13]  Onder Ozgener,et al.  Monitoring of energy exergy efficiencies and exergoeconomic parameters of geothermal district heating systems (GDHSs) , 2009 .

[14]  Antonio Valero,et al.  Quantitative Causality Analysis for the Diagnosis of Energy Systems , 2007 .

[15]  Miguel A. Sanz-Bobi,et al.  DADICC: Intelligent system for anomaly detection in a combined cycle gas turbine plant , 2008, Expert Syst. Appl..

[16]  Luis Correas Usón Diagnóstico termoeconómico de la operación de un ciclo combinado , 2001 .

[17]  Andrea Toffolo,et al.  On the thermoeconomic approach to the diagnosis of energy system malfunctions – Part 3 Approaches to the diagnosis problem. , 2003 .

[18]  Andrea Lazzaretto,et al.  On the Thermoeconomic Approach to the Diagnosis of Energy System Malfuntions. Part-1 The TADEUS Problem , 2002 .

[19]  Vittorio Verda,et al.  Thermoeconomic Analysis and Diagnosis of Energy Utility Systems - From Diagnosis to Prognosis , 2004 .

[20]  Soon Heung Chang,et al.  Advisory system for the diagnosis of lost electric output in nuclear power plants , 2005, Expert Syst. Appl..