SEVERAL PHILOSOPHICAL THOUGHTLETS ON THE AUTOMATION SYSTEMS INTEGRATION

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DEVELOPMENT OF THE AUTOMATION SYSTEMS FOR HYDROPOWER PLANTS

Therefore, the hydropower has being given high priority in the global energy development strategies. In developed countries, over 80% of reserve waterpower has been harnessed whereas much less waterpower has been utilized in the developing countries. There are 6.76×105MW waterpower reserves in the rivers in China, from which 3.78×105MW power capacity of hydroelectric generating units can be installed, and annual electric energy can reach 1.92×1012kWh. Therefore, China is the world NO.1 in water energy reservation, but the development rate was only 16.5% by the end of 1998 [Zhou Dabing 1999].
As the economy grows rapidly, the demand for electric energy increases at a very high speed, and the scale of hydropower projects under construction has remained large in the past decades in China. Now one third of world hydroelectric projects under construction is in China. The Three Gorges Hydropower Plant, with 18,200 MW of installed capacity, is the biggest power plant mankind ever built. Therefore, Hydroelectrical Engineering research has great application background in China.
The automation system is the “neural” system for the whole HP, because the system connects all the electrical and mechanical equipments of the plant into a system that controls, operates, diagnoses, manages these equipments, and makes them work in order and harmony. These equipments include hydropower generating units, auxiliary facilities and equipments (like governing systems, excitation systems, water supply systems, oil systems, pressure air systems, etc.), fire fighting equipments, sluice gate driving systems, safety measurement and supervision systems for hydraulic structures etc. For the huge HP like The Three Gorges Hydropower Plant, its automation system is of great importance because of the particularities and the unique role of the power plant in the nationwide electric power systems.
The automation systems in HP have been developed dramatically in the past 40 years. Table 1 shows the development history of automation systems for HP [Yu 2000a]:
In Table 1, to show the development levels, “+” indicates for developed, “⊕” indicates for the beginning, and “-” indicates for not developed. Like the automation systems in any manufacturing or process industry enterprises, the automation system in HP can be divided into three functional domains: Control, Technical Management (TM), and Maintenance, from the functional point of view.

CURRENT SITUATIONS AND PROBLEMS TO BE RESOLVED IN THE AUTOMATION SYSTEMS FOR HPS

The influence of IT (Information Technology) on all aspects of our society is enormous. From above analysis, it can be seen that IT plays a key role in the automation systems for hydropower plants. As the rapid development of the computer and network technologies, the industrial automation technologies change with each passing day. In past decade, there has been much big advancement in the area of HP automation. The following are some main points of it:
Distributed and hierarchical control systems are widely used in automation systems for HP [Fang 2000][Zhang 1999] [Danial et al. 2000].
As the number and the types of automation devices increase, the quantity of field data increases sharply, and the complexity of the automation systems mounts up.
As the automation technologies changes fast, the pace of extension and upgrade for the automation devices and systems speed up. The contents of ‘Automation system for HP’ has enriched from supervision, control, protection, etc. into three big functional domains, i.e. Control, Maintenance, and Technical management [Ye et al. 2000] [Yu et al. 1999] [Yu et al. 2001]
However, some new problems emerge:
A. Different types of automation devices and systems are relatively closed and isolated from each other. The main subsystems of HP automaton include Local Control Unit, Governing system, Excitation control system, protection systems for the main equipment, and automation system for the common auxiliary systems, are relatively closed to each other. Even in the same subsystem, their monitoring devices are isolated. For example, for the hydro turbine, the devices for monitoring vibration, efficiency and cavitation are relatively isolated. Nevertheless, the HGU (Hydroelectric Generating Unit) is a dynamic system, which involves several physical processes: hydraulic, mechanical and electrical, etc. There are many correlations among the system components. If these correlations are omitted, some general characteristics of the systems can’t be indicated. This also causes overlapping investment, communication barriers, data inconsistency, information collision among the systems, and makes them very difficult to work together in harmony.
B. The economic indexes (efficiency of the unit, electric power price, energy consumption inside the plant, man and material cost, etc.) are either unavailable or dis-organized. Technical management system for real-time production planning, scheduling and decision making is under development.
C. MMI (Man Machine Interface) is still under development. The operator concerns about some general state information like the overall operation conditions of the unit, the degradation of the unit, possibility potential failures, necessity of maintenance, etc. However, these pieces of information are not available yet.
D. The quantity of field data has been increasing sharply. In the next four years, it is predicted that the field data will increase 10 to 30 times [Xu et al. 2000]. Therefore, it becomes an increasingly urgent task to face the problems of ‘data explosion’, well organize the field data, and extract the useful information from it.
E. Automation products and their standards upgrade faster and faster, and this makes the lifecycle of the automation products shorter, wastes a lot of money and resources. There are many such lessons in the automation systems for HP in China and abroad [Iung 1992] [Ye et al. 2000].
F. There are many international standardization projects on automation system integration, and some progresses have been achieved, such as ISA-dS95 [ISA-dS95 1999]. However, most of the standards are still in the draft stages, and the applications of standards have not reached a satisfactory level [Chen et al. 2001]. This makes the integration, maintenance, and reengineering of the automation systems for HP very difficult and costly.

CURRENT SITUATIONS IN ENTERPRISE INTEGRATION

Above listed problems are correlated with each other, and it is not a good approach that the problems are solved one by one independently. Thus, the comprehensive and formal approaches are necessary for solving these problems. Enterprise Integration is a new discipline that can be applied for this purpose.
Therefore, it’s necessary to study the achievements in enterprise integration, and apply these achievements to define and seek the possible solutions for the problems in automation systems of HP.

BRIEF INTRODUCTION TO ENTERPRISE INTEGRATION

Enterprise Integration (EI) consists in breaking down organizational barriers to improve synergy within the enterprise so that business goals are achieved in a more productive and efficient way [Vernadat 2000].
Enterprise Modeling (EM) is the art of externalizing enterprise knowledge which adds value to the enterprise or needs to be shared. It consists of making models of the structure, behavior and organization of the enterprise. EM is the precondition for EI [Vernadat 2000].
Enterprise is a system, which has the characters of Wholeness, Correlation, and Evolution. When the environment (including market, technologies etc.) changes, enterprises must adapt themselves to the environment for surviving. In a system the ‘order’ or ‘organization’ of their components is crucial to the overall performance of the system, i.e., ‘1’ + ‘1’ usually not equal to ‘2’, especially when the system is complex. Modern enterprises have been evolved into very complex systems. The complexities are represented in:
Fast changing environment drives the enterprises changing fast;
Varieties and numbers of the components increased;
Fast growing influences of modern science and technologies, especially the IT.
In the development history of this discipline, many paradigms were proposed: CIM (Computer Integrated Manufacturing) [Harrington 1974], JIT (Just-In-Time), Lean Manufacturing, Concurrent Engineering, Networked Engineering, and Enterprise Integration (EI), etc. [Vernadat 2000]. The Chinese scholars proposed a new paradigm: CIMS: Computer Integrated Manufacturing System [Li 1994], and later was evolved into Contemporary Integrated Manufacturing System [Wu et al. 1999], which emphasizes the modelling optimization and coordination. At the same time, many modelling methodologies were proposed, most internationally recognized of them are:
IDEF (ICAM Definition Method) [Mayer 1991];
GRAI-GIM (GRAI Integrated Methodology) [Doumeingts 1995];
CIMOSA (CIM Open System Architecture) [AMICE 1993] [Vernadat 1996] [Vernadat 1998];
All those paradigms and methodologies have enriched the knowledge about enterprise modelling and integration. Nevertheless, they are diversified and some of them are overlapping or evolving in contents. In order to achieve the final goals of enterprise integration, “Integration of all knowledge”, i.e., standardization is the only way out. Many international organizations have been working on this matter for many years. Although most of them are still in draft phases, some standards can be applied to direct the enterprise modelling and integration process. David Chen and François Vernadat surveyed the standardization on enterprise modelling and integration in [Chen et al. 2001].

ENTERPRISE INTEGRATION LEVELS

To simplify problems of enterprise modelling and integration, an enterprise is divided into several hierarchical levels. According to PERA, enterprise can be divided into 6 levels, which is shown in Fig. 1 [From PERA web site].
In CIMOSA, enterprise integration problems are classified into three levels: physical system integration, application integration and business integration, which are shown in Fig. 2 [Vernadat 2000].

CURRENT SITUATIONS IN AUTOMATION INTEGRATION: CMMS/IAMS AND MES

In manufacturing enterprises, there is a gap between the real time world of the manufacturing process and the transactional world of the business administrations [Kroczek 1999]. In order to execute the business strategies in the manufacturing process, and represent the state of the production process in the forms that can be easily ‘understood’ by the operators and the entities in the business level, there should be interfaces between the Business level and Process level. MES (Manufacturing Execution System) is just for this purpose. Therefore, MES is to master the synchronic evolution of the process (material/energy) flows with the diachronic ‘state-oriented’ supervision and management by operators through information flows (discrete views) representing the continuous flows [D. Galara 1998]. ISA-dS95 defines the interfaces between enterprise activities and control activities [ISA-dS95 1999].
New automation integration trends for HP
To realize MES functions, there should be intelligence in both process and business levels. In the process level of the manufacturing enterprises, this goal can be implemented by CMMS (integrated Control, Maintenance and technical Management System) and IAMS (Intelligent Actuation and Measurement System), which are the new paradigms for plant automation system integration and implementation [Morel et al. 1994] [IUNG 1992]. They are the results from several European projects: ESPRIT II-DIAS (Distributed Intelligent Actuation and Sensors), ESPRIT III PRIAM (Prenormative Requirements for Intelligent Actuation and Measurement), ESPRIT III EIAMUG (European Intelligent Actuation and Measurement User Group), ESPRIT IV IAM-PILOT (Intelligent Actuation and Measurement Pilot) [Petin 1995] [Neunreuther 1998] [Leger 1999] [Morel et al. 1997] and EIAM-IPE [Ye et al. 1999].
CMMS and IAM are two aspects of the same system. CMMS means to integrate the three isolated automation islands at the plant level using system thought. IAMS emphasizes the intelligence distribution among fields components to ensure the interoperability and openness. CMMS ensures the synergy among the automation function modules, while the IAMS provides the implementation architecture and technology for CMMS. Therefore, CMMS and IAM contradict in appearance, but agree in nature.
Through the EU-China join project EIAM-IPE, CMMS and IAM were synthesized and developed into ICMMS (Intelligent Control-Maintenance-Management System)[Wang 1999][Zhang 1999][Ye et al. 2000].$

NEW AUTOMATION INTEGRATION TRENDS FOR HP

THE INTEGRATION LEVELS IN A PLANT OF PROCESS INDUSTRY

According to the way of processing material, the production industry processes are usually classified into continuous processes and discrete processes. Most of the enterprise integration efforts, especially the CIM or CIMS, are mainly dedicated to discrete manufacturing process. However, most of the results in CIM or CIMS can be applied in process industries. A new concept CIPS is proposed, which apply the CIMS paradigms in process industry [Rao et al. 1994] [Chai et al. 1999] [Xiong et al. 2000][Mo et al. 1999]. The hierarchical levels of CIPS are different in above-mentioned references, but they can be unified by a common reference framework, like the hierarchical PERA structure for process industries [Williams 1988].

Table of contents :

CHAPTER 1: INTRODUCTION
1.1 DEVELOPMENT OF THE AUTOMATION SYSTEMS FOR HYDROPOWER PLANTS
1.2 CURRENT SITUATIONS AND PROBLEMS TO BE RESOLVED IN THE AUTOMATION SYSTEMS FOR HPS
1.3 CURRENT SITUATIONS IN ENTERPRISE INTEGRATION
1.3.1 BRIEF INTRODUCTION TO ENTERPRISE INTEGRATION
1.3.2 ENTERPRISE INTEGRATION LEVELS
1.4 CURRENT SITUATIONS IN AUTOMATION INTEGRATION: CMMS/IAMS AND MES
1.5 NEW AUTOMATION INTEGRATION TRENDS FOR HP
1.5.1 THE INTEGRATION LEVELS IN A PLANT OF PROCESS INDUSTRY
1.5.2 AUTOMATION SYSTEM INTEGRATION FOR HP
1.6 OBJECTIVES AND STRUCTURES OF THE THESIS
1.6.1 OBJECTIVES OF THE THESIS
1.6.2 STRUCTURE OF THE THESIS
CHAPTER 2: AN ICMMS REFERENCE MODEL FOR HYDROPOWER PLANTS
2.1 INTRODUCTION
2.1.1 PROBLEM STATEMENT
2.1.2 REFERENCE MODELS
2.1.3 ARRANGEMENT OF THIS CHAPTER
2.2 GERAM
2.3 ENTERPRISE/CONTROL SYSTEM INTEGRATION STANDARDS
2.4 THE CHARACTERS OF HYDROPOWER PLANTS
2.4.1 THE COMMON FEATURES OF HYDROPOWER PLANTS
2.4.2 THE MOST CHANGEABLE PARTS OF A HP: AUTOMATION SYSTEMS.28
2.5 THE FUNCTIONAL ANALYSIS OF ICMMS FOR HPS
2.6 A ICMMS REFERENCE MODEL FOR HYDROPOWER PLANTS
2.7 SUMMARY
CHAPTER 3: THE IMPLEMENTATION ARCHITECTURES OF ICMMS FOR HYDROPOWER PLANTS
3.1 INTRODUCTION
3.2 STATE OF THE ART ON THE AUTOMATION SYSTEMS FOR HP
3.3 CURRENT PROBLEMS
3.4 INTELLIGENT CONTROL-MAINTENANCE-TECHNICAL MANAGEMENT SYSTEMS􀋄ICMMS􀋅FOR HPS
3.5 THE HYBRID SMART AUTOMATION SYSTEMS FOR HYDROELECTRIC GENERATING UNITS
3.5.1 FIELDBUS-BASED CONTROL SYSTEMS􀋄FCS􀋅 FOR HYDRO GENERATING UNITS
3.5.2. HSAS􀋄HYBRID SMART AUTOMATION SYSTEM􀋅FOR HYDROELECTRIC GENERATING UNITS
3.6 SUMMARY
CHAPTER 4: PERFORMANCE EVALUATION METHODOLOGIES FOR HYDROELECTRIC GENERATING UNITS
4.1 INTRODUCTION
4.2 THE CRITERIA AND METHODS TO EVALUATE THE OVERALL PERFORMANCE OF HGUS
4.2.1 THE COMPREHENSIVE PERFORMANCE EVALUATION INDEXES IN THE LIFECYCLE OF HGU
4.2.2 THE PERFORMANCE INDEX MATRIX AND OVERALL PERFORMANCE INDEXES OF HGUS
4.3 THE ECONOMIC PERFORMANCE CRITERIA AND EVALUATING METHOD FOR HGUS
4.3.1 THE IMPORTANCE RELATED TECHNOLOGIES OF ECONOMIC PERFORMANCE FOR HGUS
4.3.2. THE ESTABLISHMENT OF THE ECONOMIC PERFORMANCE INDEX SYSTEM AND EVALUATION CRITERIA
4.3.3 THE ENERGY FLOW ANALYSIS FOR HGU
4.3.4 THE OVERALL EFFICIENCY OF AN HGU ηs
4.3.5 IDEAL EFFICIENCY OF HGU: ηsi
4.3.6 REACHABLE EFFICIENCY OF HGUηsr
4.3.7 OPERATIONAL EFFICIENCY OF HGUηso
4.3.8 THE ECONOMIC EVALUATION CRITERIA FOR THE MAINTENANCE AND OPERATION MANAGEMENT OF HGU
4.4 IMPLEMENTATION OF THE ECONOMIC PERFORMANCE EVALUATION FOR HGUS
4.4.1 THE IMPLEMENTATION SCHEME UNDER ICMMS REFERENCE MODELS
4.4.2 AN ECONOMIC PERFORMANCE EVALUATION SYSTEM AND TESTING
4.5 A NEW MAINTENANCE STRATEGY: EBM (ECONOMIC PERFORMANCE BASED MAINTENANCE)
4.5.1 INTRODUCTION
4.5.2 EBM IN ICMMS
4.5.3 THE EFFECTIVENESS OF EBM FOR HYDROPOWER PLANTS
4.6 SUMMARY
CHAPTER 5: CONDITION MONITORING SYSTEMS FOR HYDROPOWER PLANTS
5.1 INTRODUCTION
5.1.1 IMPORTANCE OF CONDITION MONITORING SYSTEMS FOR HYDROPOWER PLANTS
5.1.2 OBJECTIVES OF THIS CHAPTER
5.2 THE CONCEPT AND FUNCTIONS OF CONDITION MONITORING
5.2.1 CONCEPT OF CONDITION MONITORING
5.2.2 THE FUNCTIONS OF A CONDITION MONITORING SYSTEM
5.3 CURRENT SITUATION AND PROBLEMS FOR THE CM OF HGUS
5.3.1 CONDITION MONITORING TECHNOLOGIES IN HYDROPOWER PLANTS 86
5.3.2 THE DIAGNOSIS AND PROGNOSIS TECHNOLOGIES
5.3.3 CURRENT PROBLEMS IN THE CM SYSTEMS FOR HGUS
5.4 THE REFERENCE MODELS OF CONDITION MONITORING SYSTEM FOR HYDRO ELECTRICAL GENERATING UNITS
5.4.1 TWO POSSIBLE SOLUTIONS TO THE INTEGRATION OF THE CM SYSTEMS FOR HYDROPOWER PLANTS
5.4.2 THE REFERENCE MODELS FOR THE CONDITION MONITORING SYSTEMS OF HYDROPOWER PLANTS
5.5 SUMMARY²
CHAPTER 6: CONTRIBUTIONS TO THE CONTROL DOMAIN OF ICMMS: DAA
6.1 INTRODUCTION
6.2. MODEL OF HYDRAULIC TURBINE GOVERNING SYSTEM
6.3 DAA-BASED DESIGN METHOD FOR THE HYDRAULIC TURBINE GOVERNORS
6.3.1. MODEL DEVELOPMENT FOR A HYDRAULIC TURBINE GOVERNING SYSTEM
6.3.2. DAA-BASED CONTROL ALGORITHM FOR HYDRAULIC TURBINE GOVERNORS
6.4. SIMULATION AND RESULTS
6.5 SUMMARY
CHAPTER 7: SEVERAL PHILOSOPHICAL THOUGHTLETS ON THE AUTOMATION SYSTEMS INTEGRATION
7.1 THE DEVELOPMENT TRACES OF SYSTEM SCIENCE
7.2 THE DEVELOPMENT PROCESS OF THE AUTOMATION SYSTEMS
7.3 PHILOSOPHY OF SYSTEM INTEGRATION FOR HYDROPOWER PLANTS
7.4 SUMMARY
CHAPTER 8: CONCLUSIONS AND PERSPECTIVES
8.1 CONCLUSIONS
8.2 PERSPECTIVES
REFERENCES

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