Ing Ind - Inf (Mag.)(ord. 270) - BV (477) ENERGY ENGINEERING - INGEGNERIA ENERGETICA

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A

ZZZZ

097471 - ADVANCED PROCESS CONTROL

Ing Ind - Inf (Mag.)(ord. 270) - MI (473) AUTOMATION AND CONTROL ENGINEERING - INGEGNERIA DELL'AUTOMAZIONE

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A

ZZZZ

090916 - AUTOMATION OF ENERGY SYSTEMS

055511 - MODELLING AND CONTROL OF ENERGY SYSTEMS (C.I.)

097471 - ADVANCED PROCESS CONTROL

Ing Ind - Inf (Mag.)(ord. 270) - MI (475) ELECTRICAL ENGINEERING - INGEGNERIA ELETTRICA

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A

ZZZZ

090916 - AUTOMATION OF ENERGY SYSTEMS

Ing Ind - Inf (Mag.)(ord. 270) - MI (481) COMPUTER SCIENCE AND ENGINEERING - INGEGNERIA INFORMATICA

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A

ZZZZ

090916 - AUTOMATION OF ENERGY SYSTEMS

099452 - AUTOMATION OF ENERGY SYSTEMS FOR ENG4SD

Obiettivi dell'insegnamento

Foreword. Systems for the production, distribution and use of energy are becoming more and more complex and articulated. As a result, their level of automation is increasing. This involves virtually any component of such systems, from production plants to transmission, distribution and district networks, down to single units. Also, modern energy systems need to integrate with one another to improve efficiency. Aspects such as comfort, economy and environmental impact, are steadily gaining importance. Most importantly, the goal of full decarbonisation of the energy sector by the year 2050 will require to design an operate strongly innovative generation systems, entailing completely new control strategies. To effectively address this scenario, an engineer needs both detailed knowledge of energy production and transformation processes and a system-level view of their compound. The two modules of this integrated course cooperate toward that direction.

Advanced process Control. This module provides the methodological foundations for the control-oriented dynamic modelling of energy systems, focusing on the control-relevant phenomena and on how to use such models to design effective control strategies. Particular emphasis is put on the concept that the achievable control performance is determined by the dynamic physical behaviour of the process and on establishing explicit links between physical process behaviour and control-relevant aspects.

The concepts are applied to a number of examples in the field of process control and thermal power generation, focusing on individual units, such as single hydro power or thermal power generation unit. The course mostly deals with cases that can be analyzed with simple, closed-form analytic models, but also briefly discusses the role of numerical modelling and simulation for more complex cases.

This view is complementary to the perspective of the Automation of Energy Systems module, which leverages on extremely simplified models of individual units and focuses on system-level controls.

Automation of Energy Systems. This module aims at providing the student with a system-level view - typical of the automation engineer - on the overall scenario, the control problems encountered, the solutions adopted to date, and their possible future developments, with particular reference to electric and heat networks. It also deals with control structures that can be exploited to master the complexity of such systems. The module does not delve into details on the various types of generators, utilisers and so forth, as these are dealt with in the Advanced Process Control module.

Risultati di apprendimento attesi

At the end of the course, the student

knows the basic conservation equations governing thermo-mechanical-hydraulic processes, both lumped-parameter (0D) and distributed-parameters (1D)

knows the constitutive equations of the models of specific phenomena (such as pressure losses or heat transfer) as well as of specific machinery (such as valves, turbines, compressors, etc.)

understands the time scale of different dynamic phenomena in these processes

is aware of how classical control problems are solved in the field of fluid processing and thermal power generation

understands how the mechanical design parameters and the operating point of such systems influence their controllability and how it may be possible to improve the control performance also by changing these parameter (process-control co-design)

understands the role of simplified analytical control-oriented models and of more detailed numerical simulation models for the design of control systems

masters the main control structures, including optimisation-related ones where applicable, devoted to the control of energy systems at both unit and network scale

understands the basic principles behind the operation, the control and the management of complex energy systems, with particular reference - as paradigmatic examples - to electric and heat networks.

The student is able to

explain what are the main control problems in a number of applications in the field of fluid processing and thermal power generation and which model-based control strategies can be used to solve them

estimate the time scale of different dynamic phenomena in thermo-hydraulic-mechanical processes, so as to select the ones which are relevant for control while neglecting those which are not

derive control-oriented dynamic models of thermo-hydraulic-mechanical processes

analyze these models and simplify them as much as possible to gain insight on the relationship between the mechanical design and operating parameters, the control design, and the achievable control performance

use appropriate numerical methods to extract control-relevant information from detailed numerical simulation models of the process

address control-oriented system modelling, control synthesis and assessment cases, at a complexity level compatible with the course extent.

interact with specialists in the area of thermo-hydraulic-mechanical process design in multi-disciplinary teams with the ultimate goal of designing better-controlled innovative systems

Argomenti trattati

ADVANCED PROCESS CONTROL

Introduction and fundamental equations

Role of modelling for the design of control systems

Detailed models for numerical simulation vs. simplified analytical models for control design

Mass, energy and momentum balance equations for 0D systems

Mass, energy and momentum balance equations for 1D systems

Estimation of time scales of different phenomena in 1D systems

Equations of state and thermodynamic properties of working fluids

Modelling of components of thermo-hydraulic and power production processes

Control valves and piping equipment

Turbomachinery: pumps, compressors, turbines

Simplified models of combustion phenomena

Single-phase heat exchangers

Two-phase heat exchangers and boilers

Electrical power generation and transmission equipment

Analysis and design of control systems

Control of simple hydraulic circuits

Power/frequency control in hydro power plants

Temperature control in single-phase heat exchangers

Control pressure, level and load in simple steam generators

Control problems in coal-fired and combined-cycle power plants

Numerical methods to extract control-relevant information from numerical models

Applications in the control of innovative power generation systems

AUTOMATION OF ENERGY SYSTEMS

Introduction. This part quickly provides a high-level view of the matter. It also introduces the basic concepts related to energy systems, generalities, and the corresponding terminology.

Control structures for energy systems. The main control structures used in energy systems are discussed. These include feedforward compensation, cascade control, decoupling, Smith predictor, Internal Model Control, override, and ratio control. The typical uses of such structures in energy systems is discussed. Care is taken to orient their choice and composition based on the characteristics of the encountered dynamic systems rather than (only) on the physical nature of the controlled variables. Most relevant, the logic associated with the addressed structures (interlocks, auto/manual management and the like) is explained.

Actuation schemes for energy systems. The main such schemes (daisy chain, split range, time division output) are treated, with the same approach just outlined for control structures.

Control-oriented modelling principles. The mathematical and modelling principles used in the course are introduced. As the focus is on system-level automation, this part aims at synthetically capturing the relevant dynamics with minimal complexity. To allow for physically interpretable parameters, first-principle modelling is privileged.

Electric systems. After presenting the above general ideas, these are monographically applied to the electric case, by discussing the management of an AC grid. The treatise includes primary and secondary power/frequency control, optimum generation allocation, and the basics of load flow. Care is taken to present the subjects above within an integrated view, and to evidence connections with neighbouring technologies. This means on the one hand relating the presented matter to detailed generator-level control, and on the other hand outlining the variety of forms taken by network-level optimisation when this involves multiple actors, conflicting objectives, bidding, and so forth.

Thermal systems. A second monographic part, with objectives similar to the one above and therefore structured in an anaologous manner, is devoted to thermal systems, with specific reference to heat networks.

The concepts and methods learnt are put to work during practice hours with simple exercises, also in a view to preparing for the written test. Case studies of (slightly) higher complexity are addressed using open source control synthesis, analysis and simulation tools, made available to the students and introduced in the laboratory activity.

Prerequisiti

A solid understanding of the design of linear SISO controllers (PID-type) using Bode's criterion, basic MIMO linear control design, cascaded control, and disturbance compensation techniques. A good understanding of the performance limitations of linear controllers, particularly in the case of non-minimum-phase processes is also recommended.

Basic knowledge of technical thermodynamics: fluid properties, enthalpy and entropy, basic heat transfer (convection, radiation, conduction) and storage phenomena, basic understanding of the working principles of turbomachinery (pumps, compressors, turbines) and of power generation cycles (Brayton, Rankine). Basic knowledge of electrical system modelling.

Modalità di valutazione

The students will be required to carry out a project by using the learnt methods and tools. They will have to deliver a brief written report following a template, that will provided and explained in the class together with the project themes.

The students will have to choose one theme, either from the set provided in Advanced Process Control or from that provided in Automation of Energy Systems.

Themes from Advanced Process Control concern the design of control systems for power generation units, including the assessment of the control system performance by simulation. The process model is provided with the assignment.

Themes from Automation of Energy Systems concern control-oriented modelling and control synthesis for simple electric and heat networks, including the simulation assessment of the synthesised controls.

The project will contribute approximately 40% of the total score. The rest will come from a written test on the entire content of both modules, composed of both numerical exercises and questions. To pass the exam, the written test must score 18/30 or more.

Bibliografia

The course slides and some relevant web resources will be made available to the students.G. Quazza, Controllo dei Processi, Editore: CLUP, Anno edizione: 1976
R. Dolezal, L. Varcop, Process Dynamics - Automatic Control of Steam Generation Plants, Editore: Elsevier, Anno edizione: 1970
C. Maffezzoni, Dinamica dei generatori di vapore, Editore: Masson, Anno edizione: 1989
C. Maffezzoni, Controllo dei generatori di vapore, Editore: Masson, Anno edizione: 1990
F. Saccomanno, Electric Power Systems: Analysis and Control, Editore: Wiley Interscience, Anno edizione: 2003
S.G. Dukelow, The control of boilers, Editore: ISA, Anno edizione: 1991

Software utilizzato

Nessun software richiesto

Forme didattiche

Tipo Forma Didattica

Ore di attività svolte in aula

(hh:mm)

Ore di studio autonome

(hh:mm)

Lezione

65:00

85:00

Esercitazione

30:00

45:00

Laboratorio Informatico

4:00

5:00

Laboratorio Sperimentale

0:00

0:00

Laboratorio Di Progetto

1:00

15:00

Totale

100:00

150:00

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