The South African economy, which is largely based on heavy industry such as minerals extraction and processing, is by nature very energy intensive. Based on the abundance of coal resources, electricity in South Africa remains amongst the cheapest in the world. Whilst the low electricity price has contributed towards a competitive position, it has also meant that our existing electricity supply is often taken for granted. The economic and environmental benefits of energy efficiency have been well documented. Worldwide, nations are beginning to face up to the challenge of sustainable energy - in other words to alter the way that energy is utilised so that social, environmental and economic aims of sustainable development are supported. South Africa as a developing nation recognises the need for energy efficiency, as it is the most cost effective way of meeting the demands of sustainable development. South Africa, with its unique economic, environmental and social challenges, stands to benefit the most from implementing energy efficiency practices. The Energy Efficiency Strategy for South Africa takes its mandate from the South African White Paper on Energy Policy. It is the first consolidated governmental effort geared towards energy efficiency practices throughout South Africa. The strategy allows for the immediate implementation of low-cost and no-cost interventions, as well as those higher-cost measures with short payback periods. An initial target has been set for an across sector energy efficiency improvement of 12% by 2014. Thermal and energy system simulation is globally recognised as one of the most effective and powerful tools to improve overall energy efficiency. However, because of the usual extreme mathematical nature of most simulation algorithms, coupled with the historically academic environment in which most simulation software is developed, valid perceptions exist that system simulation is too time consuming and cumbersome. It is also commonly known that system simulation is only effective in the hands of highly skilled operators, which are specialists in their prospective fields. Through previous work done in the field, and the design of a dynamic thermal and energy system simulation scheme for cross industry applications, it was shown that system simulation has evolved to such an extent that these perceptions are not valid any more. The South African mining and commercial building industries are two of the major consumers of electricity within South Africa. By improving energy efficiency practices within the building and mining industry, large savings can be realised. An extensive investigation of the literature showed that no general suitable computer simulation software for cross industry mining and building thermal and energy system simulation could be found. Because the heating, ventilation and air conditioning (HVAC) of buildings, closely relate to the ventilation and cooling systems of mines, valuable knowledge from this field was used to identify the requirements and specifications for the design of a new single cross industry dynamic integrated thermal and energy system simulation tool. VISUALQEC was designed and implemented to comply with the needs and requirements identified. A new explicit system component model and explicit system simulation engine, combined with a new improved simulation of mass flow through a system procedure, suggested a marked improvement on overall simulation stability, efficiency and speed. The commercial usability of the new simulation tool was verified for building applications by doing an extensive building energy savings audit. The new simulation tool was further verified by simulating the ventilation and cooling (VC) and underground pumping system of a typical South African gold mine. Initial results proved satisfactory but, more case studies to further verify the accuracy of the implemented cross industry thermal and energy system simulation tool are needed. Because of the stable nature of the new VISUALQEC simulation engine, the power of the simulation process can be further extended to the mathematical optimisation of various system variables. In conclusion, this study highlighted the need for new simulation procedures and system designs for the successful implementation and creation of a single dynamic thermal and energy system simulation tool for cross industry applications. South Africa should take full advantage of the power of thermal and energy system simulation towards creating a more energy efficient society. / Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2005.

The South African economy, which is largely based on heavy industry such as minerals extraction and processing, is by nature very energy intensive. Based on the abundance of coal resources, electricity in South Africa remains amongst the cheapest in the world. Whilst the low electricity price has contributed towards a competitive position, it has also meant that our existing electricity supply is often taken for granted. The economic and environmental benefits of energy efficiency have been well documented. Worldwide, nations are beginning to face up to the challenge of sustainable energy - in other words to alter the way that energy is utilised so that social, environmental and economic aims of sustainable development are supported. South Africa as a developing nation recognises the need for energy efficiency, as it is the most cost effective way of meeting the demands of sustainable development. South Africa, with its unique economic, environmental and social challenges, stands to benefit the most from implementing energy efficiency practices. The Energy Efficiency Strategy for South Africa takes its mandate from the South African White Paper on Energy Policy. It is the first consolidated governmental effort geared towards energy efficiency practices throughout South Africa. The strategy allows for the immediate implementation of low-cost and no-cost interventions, as well as those higher-cost measures with short payback periods. An initial target has been set for an across sector energy efficiency improvement of 12% by 2014. Thermal and energy system simulation is globally recognised as one of the most effective and powerful tools to improve overall energy efficiency. However, because of the usual extreme mathematical nature of most simulation algorithms, coupled with the historically academic environment in which most simulation software is developed, valid perceptions exist that system simulation is too time consuming and cumbersome. It is also commonly known that system simulation is only effective in the hands of highly skilled operators, which are specialists in their prospective fields. Through previous work done in the field, and the design of a dynamic thermal and energy system simulation scheme for cross industry applications, it was shown that system simulation has evolved to such an extent that these perceptions are not valid any more. The South African mining and commercial building industries are two of the major consumers of electricity within South Africa. By improving energy efficiency practices within the building and mining industry, large savings can be realised. An extensive investigation of the literature showed that no general suitable computer simulation software for cross industry mining and building thermal and energy system simulation could be found. Because the heating, ventilation and air conditioning (HVAC) of buildings, closely relate to the ventilation and cooling systems of mines, valuable knowledge from this field was used to identify the requirements and specifications for the design of a new single cross industry dynamic integrated thermal and energy system simulation tool. VISUALQEC was designed and implemented to comply with the needs and requirements identified. A new explicit system component model and explicit system simulation engine, combined with a new improved simulation of mass flow through a system procedure, suggested a marked improvement on overall simulation stability, efficiency and speed. The commercial usability of the new simulation tool was verified for building applications by doing an extensive building energy savings audit. The new simulation tool was further verified by simulating the ventilation and cooling (VC) and underground pumping system of a typical South African gold mine. Initial results proved satisfactory but, more case studies to further verify the accuracy of the implemented cross industry thermal and energy system simulation tool are needed. Because of the stable nature of the new VISUALQEC simulation engine, the power of the simulation process can be further extended to the mathematical optimisation of various system variables. In conclusion, this study highlighted the need for new simulation procedures and system designs for the successful implementation and creation of a single dynamic thermal and energy system simulation tool for cross industry applications. South Africa should take full advantage of the power of thermal and energy system simulation towards creating a more energy efficient society. / Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2005.

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Die vorliegende Arbeit befasst sich mit datengetriebenen Modellierungsansätzen in der Gebäudetechnik zum Zweck des Entwurfs modellprädiktiver Regler. Dabei widmet sich der erste Teil (Kapitel 2 und 3) im Wesentlichen den theoretischen Grundlagen der Systemidentifikation wohingegen im zweiten Teil (Kapitel 4 bis 6) praktische Anwendungen der Identifikation sowie die Implementierung modellprädiktiver Regler im Gebäudebereich im Vordergrund stehen. Die Grundlage der Arbeit stellt die Systemidentifikation mittels der Prädiktionsfehlerminimierung (Prediction Error Minimization – PEM) dar, deren Basis stochastische Modelle dynamischer Systeme bilden. Daher wird ausgehend von den unterschiedlichen Darstellungsformen stochastischer linearer zeitinvarianter Systeme (LTI-Systeme) die Problematik der optimalen Prädiktion thematisiert, wobei ein allgemeiner Ausdruck zur Berechnung der Mehrschrittprädiktion von LTI-Systemen hergeleitet wird. Anschließend werden Implementierungsaspekte von Mehr- bzw. Multischritt-PEM-Verfahren diskutiert und der Schätzer im Frequenzbereich analysiert, wobei sich verglichen mit der 1-Schritt-PEM eine erwartungsgemäß andere Wichtung des geschätzten Modells im Frequenzbereich ergibt. Die aus diesen Untersuchungen gewonnen Identifizierbarkeitsbedingungen entsprechen im offenen Regelkreis den bekannten Bedingungen der 1-Schritt-PEM, wohingegen sich im geschlossenen Regelkreis eine restriktivere Bedingung ergibt. Die weiterhin durchgeführte Genauigkeitsanalyse führt letztlich zu einem Ausdruck für die Abschätzung der Schätzfehlerkovarianzmatrix der Modellparameter, welche wiederum für die Varianz- bzw. Konfidenzschätzung anderer Systemmerkmale genutzt werden kann. In der Gebäudetechnik spielen nichtlineare Modellansätze eine wichtige Rolle. Für diese ist die explizite Berechnung der optimalen Prädiktion, und damit eine Identifikation mittels PEM, in der Regel problematisch bzw. nicht möglich. In der Arbeit werden daher zwei nichtlineare Modellstrukturen vorgeschlagen, für welche entsprechende Ausdrücke angegeben werden können, sodass eine direkte Anwendung der PEM ermöglicht wird. Dabei hat sich im Anwendungsteil der Arbeit herausgestellt, dass einer dieser Ansätze sinnvoll in der Gebäudetechnik genutzt werden kann. Aufgrund der Ähnlichkeit zum linearen Fall können zudem die Ideen, die typischerweise für die Parametrierung stochastischer LTI Systeme genutzt werden, auf den nichtlinearen Fall übertragen werden. Im Anwendungsteil der Arbeit wird dann die Nutzung der PEM im Gebäudebereich anhand praktisch aufgenommener Messdaten einiger Demonstratoren veranschaulicht. Es werden Modell- und Identifikationsansätze für die Schätzung von thermischen Raummodellen sowie einer Gastherme und einer Wärmepumpe vorgeschlagen, wobei plausible Identifikationsergebnisse erzielt werden konnten. Weiterhin wird im Rahmen der Identifikation von thermischen Raummodellen auch auf die wichtige Problematik nicht messbarer Störungen (z. B. Raumbelegung sowie Wärmeströme aus Nachbarräumen) eingegangen und mögliche Lösungsansätze aufgezeigt. Aufgrund der umfangreichen Sensorausstattung einiger Demonstratoren konnte zudem ein direkter Vergleich eines LTI-Modells mit dem obig genannten nichtlinearen Modellansatz durchgeführt werden, wobei eine vergleichbare Prädiktionsgüte beider Modellierungsansätze festgestellt wurde. Im letzten Teil wird dann der Entwurf modellprädiktiver Regler anhand zweier typischer Beispiele aus der Gebäudetechnik veranschaulicht. Für die Demonstration des Vorgehens werden Regelstreckenmodelle mittels der Modelica Buildings Bibliothek entworfen und dann für die Generierung synthetischer Daten verwendet, welche zur Identifikation von Modellen für den MPC Entwurf verwendet werden. Die identifizierten Modelle sind in beiden Fällen in der Lage das dynamische Verhalten des Modelica Prozessmodells hinreichend gut vorherzusagen, was die Sinnhaftigkeit des gewählten Modellierungs- bzw. Identifikationsansatzes untermauert. Aufbauend wird dann für beide Beispiele auf die Formulierung einer prädiktiven Regelungsstrategie eingegangen, wobei spezielle Modelleigenschaften ausgenutzt werden. Für beide Beispiele konnten simulativ Vorteile gegenüber einer konventionellen Regelungsstrategie nachgewiesen werden.