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

Abstract

Optimal operation of energy systems plays an important role to enhance their lifetime security and efficiency. The determination of optimal operating strategies requires intelligent utilization of massive data accumulated during operation or prediction. The investigation of these data solely without combining physical models may run the risk that the established relationships between inputs and outputs, the models which reproduce the behavior of the considered system/component in a wide range of boundary conditions, are invalid for certain boundary conditions, which never occur in the database employed. Therefore, combining big data with physical models via cyber physical systems (CPS) is of great importance to derive highly-reliable and -accurate models and becomes more and more popular in practical applications. In this paper, we focus on the description of a systematic method to apply CPS to the performance analysis and decision making of thermal power plants. We proposed a general procedure of CPS with both offline and online phases for its application to thermal power plants and discussed the corresponding methods employed to support each sub-procedure. As an example, a data-driven model of turbine island of an existing air-cooling based thermal power plant is established with the proposed procedure and demonstrates its practicality, validity and flexibility. To establish such model, the historical operating data are employed in the cyber layer for modeling and linking each physical component. The decision-making procedure of optimal frequency of air-cooling condenser is also illustrated to show its applicability of online use. It is concluded that the cyber physical system with the data mining technique is effective and promising to facilitate the real-time analysis and control of thermal power plants.

A Green Quality Management Decision Model with Carbon Tax and Capacity Expansion under Activity-Based Costing (ABC)—A Case Study in the Tire Manufacturing Industry

“…In Equation (37), (G 1 , G 2 , G 3 , G 4 ) is an SOS1 set of 0-1 variables, within which exactly one variable must be one, which is a set of 0-1 indicator variables. If G 1 = 1, then G 2 = G 3 = G 4 = 0 from Equation (37), 0 ≤ A t ≤ G 1 Q 1 from Equations (30) and (31), and B t = C t = D t = 0 from Equations (32)- (36). Thus, TCQ falls within the first range of Figure 4, in which the carbon tax is zero.…”

“…As Industry 4.0 and the era of the Internet of Things approach [30], with the help of wider usage of information extraction technology through the Internet and cloud computing, integration of both upstream and downstream information can be easily realized in combination with an automatized factory system. Intelligent manufacturing will be a niche market that can cater to customers' demands in the future [31]. In addition, sensors/actuators, high-performance computing systems, and the production control of intelligent factories will manage to detect various available production capacities in a short time and arrange configurations correspondingly and effectively, which avoids inadequate production.…”

Performance Assessment of a Boiler Combustion Process Control System Based on a Data-Driven Approach

“…The general combustion control system should include a complete set of equipment to make coal chemical energy into heat energy, such as fuel system (including ignition system, pulverizing system, etc. ), combustion equipment (ignition equipment, pulverized coal burner), flue gas system and the thermal control system ensuring combustion process safe, economical and stable [35,36].…”

Sensor attack detection and isolation based on sliding mode observer for cyber‐physical systems

“…A system with a tight coupling of cyber and physical objects is called cyber‐physical system (CPS), and based on reference, a CPS consists of (1) physical, biological, or engineered systems that are usually large‐scale and complex and (2) a cyber core, comprised of communication networks and computational availability that monitors, coordinates, and controls the physical part. Such systems interact intensively between physical entities and cyber infrastructure and commonly exist in the industrial processes and our daily lives . CPSs are hot topics recently and literature for investigation on CPSs is available .…”

“…Such systems interact intensively between physical entities and cyber infrastructure and commonly exist in the industrial processes and our daily lives. 2,3 CPSs are hot topics recently and literature for investigation on CPSs is available. [4][5][6][7][8][9][10][11] Due to the complexity of the CPSs, dealing with the security issues of a CPS becomes extraordinarily significant.…”