Operation Optimization Approaches of Thermal Power Units with Big Data-Driven Hybrid Modeling

2014 ◽  
Vol 631-632 ◽  
pp. 362-366
Author(s):  
Ning Ling Wang ◽  
Yong Zhang ◽  
Long Fei Zhu ◽  
Zhi Ping Yang
Keyword(s):  
Energy Consumption ◽  
Thermal Power ◽  
Hybrid Modeling ◽  
Data Driven ◽  
Fuzzy Rough Set ◽  
Operation Optimization ◽  
Operation Conditions ◽  
Energy Consumption Model ◽  
Practical Guidelines ◽  
Data Driven Modeling

An accurate and reliable energy-consumption model is the key to operation optimization and energy-saving diagnosis of thermal power units especially under different operation conditions and boundaries. Conventional mathematical and data-driven modeling methods were overviewed and compared in this paper. A hybrid modeling based on thermodynamic theory and fuzzy rough set (FRS) method was proposed to process the great volume of operation data and describe the energy-consumption behavior of thermal power units. On this basis, the operation optimization was performed with intelligent computation methods to derive the realizable benchmark state with the whole set of operation parameters. The resultant optimum operation state reflects the exterior factors and system behavior, taking practical guidelines for the modeling and optimization of large thermal power units.

Intelligent Energy-Saving Decision Making and Delicacy Management for Power Enterprises

2014 ◽  
Vol 631-632 ◽  
pp. 1282-1286
Author(s):  
Yong Zhang ◽  
Ning Ling Wang
Keyword(s):  
Decision Making ◽  
Energy Saving ◽  
Management System ◽  
Thermal Power ◽  
Big Data Analytics ◽  
Fuzzy Rough Set ◽  
Operation Optimization ◽  
Operation Conditions ◽  
Performance Indexes ◽  
Decision Making Model

Energy-saving management is playing increasingly important parts in the energy conservation of thermal power generation. The economic performance indexes were decomposed and clarified to set a delicacy energy-saving management system. With the great volume of operation data, an fuzzy rough set (FRS) –based big data analytics were introduced to build the intelligent energy-saving decision-making model. Based on such energy-saving management system, the operation optimization practice was performed on a 600MW thermal power unit to determine the optimum working state under specific operation conditions. The result shows that the proposed energy-saving management can makes great guidelines for the operation optimization and energy-saving diagnosis of thermal power units.

Mechanism of Energy-Consumption Benchmark State for Coal-Fired Power Units with Varying Boundary

2013 ◽  
Vol 860-863 ◽  
pp. 690-695
Author(s):  
Yong Zhang ◽  
Peng Fu ◽  
Ning Ling Wang
Keyword(s):  
Boundary Condition ◽  
Energy Consumption ◽  
Working Conditions ◽  
Economic Performance ◽  
Thermal Power ◽  
Operation Optimization ◽  
Operation Conditions ◽  
Optimal Values ◽  
New Challenges ◽  
Equipment Performance

The in-depth energy conservation of thermal power units is confronting new challenges under the varying operation conditions and ambient constraints. Compared with traditional optimal values, the description of energy-consumption benchmark state was proposed to describe the economic performance of thermal power units with the varying operation boundary, operation conditions and equipment performance. The energy consumption interactions of units were divided into 4 parts: parameters, equipment, subsystems and units. The models for energy-consumption benchmark states were established with the fuel specific consumption (FSC) setting as the optimization objective. Such a method was performed on a 600MW supercritical power unit and the results show that the energy-consumption benchmark state, which is related with the varying boundary, can reflect the boundary condition, operation lever and equipment performance. It makes significant reference for the energy-saving diagnosis and operation optimization of thermal power units under overall working conditions.

Method for Determining Energy-Consumption Benchmark State in the Thermal System of Coal-Fired Units Based on Hybrid Model

2014 ◽  
Vol 654 ◽  
pp. 93-96
Author(s):  
Long Fei Zhu ◽  
Ning Ling Wang ◽  
Peng Fu ◽  
Zhi Ping Yang
Keyword(s):  
Energy Consumption ◽  
Hybrid Model ◽  
Working Conditions ◽  
Thermal Power ◽  
Thermal System ◽  
Mechanism Analysis ◽  
Heat Transfer Characteristics ◽  
Operation Optimization ◽  
Operation Conditions ◽  
New Challenges

Considering the varying operation conditions and ambient constraints, the in-depth energy conservation of thermal power units is confronting new challenges. Based on the already made ‘energy-consumption benchmark state’ concept, the description of energy-consumption benchmark state was obtained in this paper to describe the economic performance of coal-fired power thermal system with the varying operation boundary, operation conditions and equipment performance. Breaking the limitations of traditional modelling which always make statistic analysis and mechanism analysis isolate, hybrid modeling method synthesizing the merit of the mechanism analysis and statistical method was proposed. Considering the heat transfer characteristics of thermal system, this model make the energy-consumption of unit correspondence with parameter sets of thermal system. Optimized parameter sets were gained with the fuel specific consumption setting as the optimization objective, thus obtain the energy-consumption benchmark state in thermal system of coal-fired units. The results show that the method for determining energy-consumption benchmark state in the thermal system of coal-fired units based on hybrid model makes significant reference for the energy-saving diagnosis and operation optimization of thermal power units under overall working conditions.

scholarly journals The Application of Cyber Physical System for Thermal Power Plants: Data-Driven Modeling

Energies ◽  
2018 ◽  
Vol 11 (4) ◽  
pp. 690 ◽  
Author(s):  
Yongping Yang ◽  
Xiaoen Li ◽  
Zhiping Yang ◽  
Qing Wei ◽  
Ningling Wang ◽  
...  
Keyword(s):  
Physical System ◽  
Power Plants ◽  
Thermal Power ◽  
Data Driven ◽  
Cyber Physical System ◽  
Thermal Power Plants ◽  
Data Driven Modeling

Big Data Analytics-Based Energy-Consumption Feature Selection of Large Thermal Power Units

2013 ◽  
Vol 860-863 ◽  
pp. 1862-1866 ◽  
Author(s):  
Ning Ling Wang ◽  
De Gang Chen ◽  
Yong Ping Yang
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Data Analytics ◽  
Thermal Power ◽  
Big Data Analytics ◽  
Boundary Constraints ◽  
Operation Conditions ◽  
Complex Nonlinear System ◽  
Key Features ◽  
Selection Of

Large coal-fired power unit is a complex nonlinear system with more uncertainty to address, evaluate and optimize. It is essential and difficult to determine the key features contributing to the energy consumption of power units, especially considering the varying boundary constraints, operation conditions and system characteristics. In this paper idea of big data analytics is employed to clean the historian operation data efficiently and select the key energy-consumption features with less information losses. The result shows that the resultant key features reflect the exterior factors and system behavior. It makes great reference for the modeling and optimization of large thermal power units.

Data-Driven Modeling for Energy Consumption Estimation

2018 ◽  
pp. 1057-1068
Author(s):  
Chunsheng Yang ◽  
Qiangqiang Cheng ◽  
Pinhua Lai ◽  
Jie Liu ◽  
Hongyu Guo
Keyword(s):  
Energy Consumption ◽  
Data Driven ◽  
Data Driven Modeling
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