OVERALL INTELLIGENT HYBRID CONTROL SYSTEM FOR A FOSSIL-FUEL POWER UNIT

open_access
Open Access
Author:
Garduno-Ramirez, Raul
Graduate Program:
Electrical Engineering
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
June 09, 2000
Committee Members:
Mario Sznaier, Committee Member
Constantino Manuel Lagoa, Committee Member
Robert M Edwards, Committee Member
Jeffrey Scott Mayer, Committee Member
Kwang Yun Lee, Committee Chair/Co-Chair
Keywords:
INTELLIGENT HYBRID SYSTEMS
OVERALL CONTROL
POWE PLANTS
Abstract:
The current global problem scenario faced by power plants is characterized by a changing multiplicity of everyday-tighter operation requirements (e.g., life extension, pollution regulation, cyclic operation, heat rate improvement, etc.). In this situation, an overall approach for optimal operation and control of power units becomes of paramount relevance for the survival of utilities competing under liberalized generation markets. In response to these circumstances, this dissertation contributes a methodology to design a generalized overall unit control system for a fossil fuel power unit (FFPU), and develops a minimum prototype to demonstrate its feasibility. Toward the above goal, the associated research project was undertaken as a technology innovation process with its two ends identified as follows. First, it is recognized that the coordinated control strategies constitute the uppermost control level in current FFPUs, and so, are responsible for driving the boiler-turbine-generator set as a single entity. Second, a FFPU is envisioned as a complex process, subject to multiple changing operating conditions, that should perform as an intelligent system, for which an advanced integral control concept is needed. Therefore, as an outcome of the innovation process, a generalized unit control concept that extends the capabilities of current coordinated control schemes is proposed. This concept is presented as the Intelligent Coordinated Control System (ICCS) paradigm, which establishes an open reference framework for the development of overall unit control schemes. The ICCS realizes a multi-agent system for which a multidisciplinary approach, that amalgamates control, process, and software engineering concepts, is established for its design. The ICCS's system goals are identified using power plant process engineering concepts, and intelligent control systems engineering concepts are used to identify main tasks and to achieve system functional decomposition. A software engineering agency concept is used to identify and group agents according to their knowledge and purpose interactions. The resultant ICCS structure is an open set of functionally grouped agent clusters in a two-level hierarchical system. The upper level, mainly characterized for knowledge-driven processes, performs the supervisory functions needed to provide self-governing operation characteristics, while the lower level, mainly characterized for data-driven processes, performs the fast reactive behavior functions necessary for hybrid real-time control and protection. The Minimum Prototype of the Intelligent Coordinated Control System (ICCS-MP) comprehends a minimum set of functions needed by the power unit to participate in the total automation of power systems. Basically, the ICCS-MP provides the means to achieve optimized wide-range cyclic operation, by being able to follow any given unit load demand profile issued by upper level economic dispatch and unit commitment agents, and to optimally accommodate an arbitrary number of generally conflicting operating objectives. Developed through several stages, the ICCS-MP finally implements a two-level hierarchical intelligent hybrid multi-agent coordinated control system. The supervisory functions include optimization and command generation, learning and control tuning, and performance and state monitoring. The direct level consist of a multivariable feedforward and feedback control scheme. The implementation core of the system is formed by three modules: reference governor, feedforward control processor, and feedback control processor. The performance and state monitoring, and learning and control tuning functions can be executed either under demand in an off-line basis or are implicitly included in the main modules. The reference governor generates set-point trajectories for the lower level control loops by solving a multiobjective optimization problem, for which the objective functions and their priorities can be set arbitrarily, in number and form. This approach allows for process optimization, and provides a way to specify the operating policy to accommodate a great diversity of operating scenarios. The proposed feedforward-feedback control scheme is an extension of the general linear single-input-single-output feedback control scheme, with both reference feedforward and disturbance feedforward actions, to the nonlinear multivariable case. The feedforward control processor is implemented using a set of multi-input-single-output fuzzy inference systems designed from plant input-output data using a neural network paradigm. This approach provides the control system with off-line learning capabilities to attain process optimization under changing operating conditions. The feedback control path is implemented as a PID-based decentralized (multiloop) control scheme with a loop interaction compensator. The compensator is equivalent to a disturbance feedforward compensator and is designed using the relative gain array technique. Both the control algorithms and the compensator are first order Sugeno-type fuzzy inference systems, scheduled in two dimensions (power and pressure) to achieve satisfactory disturbance rejection and uncertainty compensation during wide-range operation. The process operating window is partitioned to take into account the process nonlinear characteristics, and tuning is carried out by a genetic algorithm at the points of interest in the partitions. The performance of the ICCS-MP is demonstrated through simulation experiments. Results show the feasibility of the proposed ICCS paradigm. An open purposeful self-governing overall unit control system for a FFPU can be systematically designed, built and upgraded to effectively satisfy arbitrary operation conditions. Remarkably, the ICCS paradigm provides a convenient conceptual framework such that the integration of applications can be carried out making use of the best characteristics that either algorithmic or heuristic techniques have to offer, while keeping large system complexity manageable.