Optimal Energy Management and Component Sizing of a Stand-Alone Building Energy System

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1 Diss. ETH No Optimal Energy Management and Component Sizing of a Stand-Alone Building Energy System A dissertation submitted to ETH ZURICH for the degree of Doctor of Sciences presented by Samuel Felix Fux MSc ETH in Mechanical Engineering born October 9, 1983 citizen of St. Niklaus, VS, Switzerland accepted on the recommendation of Prof. Dr. Lino Guzzella, examiner Prof. Dr. Jean-Louis Scartezzini, co-examiner Dr. Jürg Tödtli, co-examiner 2013

2 Abstract The energy consumption of buildings represents a large part of the world s total energy consumption. Due to sustainability concerns, fossil energy sources in the energy supply of buildings are increasingly being substituted by renewable energy sources. The integration of renewable energy sources and storage systems results in complex building energy systems. To exploit the full ecological and economic potential of such complex systems, a methodology is investigated in this thesis for determining the optimal sizes of the system components taking into consideration the optimal energy management. The methodology derived is tested on the specific case of a standalone energy system of an alpine lodge. Its energy system integrates photovoltaics and a thermal solar collector, which supply the lodge with electricityandheat. Acombinedheatandpowerplantservesasabackup power system. First, an optimal energy management system (EMS) is developed for the energy system studied. The approach chosen is based on model predictive control. The optimal control problem associated with the energy management is formulated as a mixed-integer linear program using a simplified model of the system. Logic statements resulting from system and operating constraints are transformed into mixed-integer linear inequalities to integrate them in the optimization problem. To provide the predictive EMS with the required forecasts of the electric and thermal loads, a forecasting algorithm based on the least squares support vector machine method is introduced. The optimal component sizing of the energy system studied is investigated using the predictive EMS developed to control it. The net present costs and the non-renewable cumulative energy demand of the energy system are analyzed for various sizes of the system components. A detailed simulation tool is applied to evaluate the operating performance vii

3 Abstract of the energy system for the various combinations of the component sizes. In the case at hand, the combination of fossil and renewable energy sources is found to be the best option from an economic and an ecological point of view. Finally, the predictive EMS developed is compared with a conventional rule-based EMS. The comparison shows that the predictive EMS enhances the operating performance of the energy system studied, provided that accurate weather and load forecasts are available. It also shows that the EMS applied affects the optimal component sizing of the energy systems studied. This fact emphasizes the need for a careful choice of an appropriate energy management strategy already during the design stage of complex energy systems. viii

4 Zusammenfassung Der Energieverbrauch von Gebäuden macht einen grossen Teil des gesamten weltweiten Energieverbrauchs aus. Aufgrund von Nachhaltigkeitsanliegen werden darum fossile Energiequellen in der Energieversorgung von Gebäuden vermehrt durch erneuerbare Energiequellen ersetzt. Werden jedoch erneuerbare Energiequellen und Energiespeicher in Gebäuden platziert, ergeben sich komplexe Gebäudeenergiesysteme. Damit das vorhandene ökologische und ökonomische Potential von solchen komplexen Systemen vollständig ausgenutzt werden kann, behandelt die vorliegende Arbeit eine Methodik zur optimalen Dimensionierung der Systemkomponenten unter Berücksichtigung des optimalen Energiemanagements. Die aufgezeigte Methodik wird am spezifischen Fall des autonomen Energiesystems einer Berghütte getestet. Ihr Energiesystem verfügt über eine Photovoltaikanlage und thermische Solarkollektoren, welche die Hütte mit Elektrizität und Wärme versorgen. Ein Blockheizkraftwerk dient als Hilfsversorgungssystem. Zuerst wird ein optimales Energiemanagementsystem (EMS) für das betrachtete Energiesystem entwickelt. Der gewählte Ansatz basiert auf der modellprädiktiven Regelung. Das optimale Regelungsproblem für das Energiemanagement wird unter Verwendung eines vereinfachten Systemmodells als gemischt-ganzzahliges, lineares Optimierungsproblem formuliert. Logische Aussagen, welche von System- und Betriebsbedingungen stammen, werden ins Optimierungsproblem einbezogen indem sie in lineare, gemischt-ganzzahlige Ungleichungen umgeformt werden. Die vom prädiktiven EMS benötigten Vorhersagen des elektrischen und thermischen Verbrauchs werden von einem Vorhersagealgorithmus bereitgestellt, welcher auf der Methode der Least Squares Support Vector Machine basiert. ix

5 Zusammenfassung Anschliessend wird die optimale Dimensionierung der Komponenten des betrachteten Energiesystems untersucht, wobei das entwickelte prädiktive EMS zu seiner Regelung verwendet wird. Die Nettogegenwartskosten und der nicht erneuerbare kumulative Energieverbrauch des Energiesystems werden für verschiedene Grössen der Systemkomponenten analysiert. Das Betriebsverhalten des Energiesystems für die verschiedenen Kombinationen der Komponentengrössen wird mit einer detaillierten Simulationsumgebung ausgewertet. In der vorliegenden Anwendung zeigt sich die Kombination von fossilen und erneuerbaren Energiequellen vom ökonomischen sowie vom ökologischen Standpunkt aus betrachtet als die beste Option. Das neu entwickelte prädiktive EMS wird schliesslich mit einem herkömmlichen, auf Regeln beruhenden EMS verglichen. Dieser Vergleich deckt auf, dass das prädiktive EMS das Betriebsverhalten des betrachteten Energiesystems verbessert, vorausgesetzt dass präzise Wetter- und Verbrauchsvorhersagen verfügbar sind. Er zeigt ebenfalls, dass sich das verwendete EMS auf die optimale Komponentendimensionierung des betrachteten Energiesystems auswirkt. Dieser Umstand verdeutlicht die Notwendigkeit einer sorgfältigen Wahl der Energiemanagementstrategie schon während der Planungsphase von komplexen Energiesystemen. x

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