MODEL PREDICTIVE CONTROL OF ENERGY SYSTEMS FOR HEAT AND POWER APPLICATIONS

Building and transportation sectors together account for two-thirds of the total energy consumption in the US. There is a need to make these energy systems (i.e., buildings and vehicles) more energy efficient. One way to make grid-connected buildings more energy efficient is to integrate the heating, ventilation and air conditioning (HVAC) system of the building with a micro-scale concentrated solar power (MicroCSP) sys- tem. Additionally, one way to make vehicles driven by internal combustion engine (ICE) more energy efficient is by integrating the ICE with a waste heat recovery (WHR) system. But, both the resulting energy systems need a smart supervisory controller, such as a model predictive controller (MPC), to optimally satisfy the en- ergy demand. Consequently, this dissertation centers on development of models and design of MPCs to optimally control the combined (i) building HVAC system and the MicroCSP system, and (ii) ICE system and the WHR system. In this PhD dissertation, MPCs are designed based on the (i) First Law of Thermo- dynamics (FLT), and (ii) Second Law of Thermodynamics (SLT) for each of the two energy systems. Maximizing the FLT efficiency of an energy system will minimise energy consumption of the system. MPC designed based on FLT efficiency are de- noted as energy based MPC (EMPC). Furthermore, maximizing the SLT efficiency of the energy system will maximise the available energy for a given energy input and a given surroundings. MPC designed based on SLT efficiency are denoted as exergy based MPC (XMPC). Optimal EMPC and XMPC are designed and applied to the combined building HVAC and MicroCSP system. In order to evaluate the designed EMPC and XMPC, a com- mon rule based controller (RBC) was designed and applied to the combined building HVAC and MicroCSP system. The results show that the building energy consump- tion reduces by 38% when EMPC is applied to the combined MicroCSP and building HVAC system instead of using the RBC. XMPC applied to the combined MicroCSP and building HVAC system reduces the building energy consumption by 45%, com- pared to when RBC is applied. Optimal EMPC and XMPC are designed and applied to the combined ICE and WHR system. The results show that the fuel consumption of the ICE reduces by 4% when WHR system is added to the ICE and when RBC is applied to both ICE and WHR systems. EMPC applied to the combined ICE and WHR system reduces the fuel consumption of the ICE by 6.2%, compared to when RBC is applied to ICE without WHR system. XMPC applied to the combined ICE and WHR system reduces the fuel consumption of the ICE by 7.2%, compared to when RBC is applied to ICE without WHR system

Integration and optimal control of microcsp with building hvac systems: Review and future directions

Heating, ventilation, and air-conditioning (HVAC) systems are omnipresent in modern buildings and are responsible for a considerable share of consumed energy and the electricity bill in buildings. On the other hand, solar energy is abundant and could be used to support the building HVAC system through cogeneration of electricity and heat. Micro-scale concentrated solar power (MicroCSP) is a propitious solution for such applications that can be integrated into the building HVAC system to optimally provide both electricity and heat, on-demand via application of optimal control techniques. The use of thermal energy storage (TES) in MicroCSP adds dispatching capabilities to the MicroCSP energy production that will assist in optimal energy management in buildings. This work presents a review of the existing contributions on the combination of MicroCSP and HVAC systems in buildings and how it compares to other thermal-assisted HVAC applications. Different topologies and architectures for the integration of MicroCSP and building HVAC systems are proposed, and the components of standard MicroCSP systems with their control-oriented models are explained. Furthermore, this paper details the different control strategies to optimally manage the energy flow, both electrical and thermal, from the solar field to the building HVAC system to minimize energy consumption and/or operational cost

Characterization of the role of genome organizer protein Satb2 in memory formation

Das DNA-bindende Protein Satb2, das hauptsächlich im Cortex und in den CA1 Regionen des Gehirns exprimiert wird, reguliert die Transkription, indem es die Chromatin Architektur beeinflusst. Es ist zwar bekannt, dass es für die kortikale Entwicklung notwendig ist, aber die Funktion im erwachsenen Gehirn blieb unentdeckt. Bei Menschen verursachen SATB2 Mutationen schwerwiegende Lerndefizite, verbunden mit einem Risiko für Schizophrenie, was auf eine entscheidende Rolle in der Plastizität hindeutet. Wir nutzten Prosencephalon-spezifische Satb2 konditionale Knockout (cKO) Mäuse, um die Rolle von Satb2 in der Gedächtnisbildung zu untersuchen. Erwachsene cKo Mäuse wiesen keine Defekte in Wachstum, Fortpflanzung, Cortex und CA1 Architektur oder groben motorischen Funktionen auf. Eine Funktionsanalyse zeigte, dass Knockout Tiere eine beeinträchtigte LangzeitPotenzierung in der Spätphase in CA1, sowie verminderte konditionierte Angst hatten. Außerdem konnten sie Objekte nach 24 Stunden schlechter lokalisieren und aus der Erinnerung heraus erkennen, nicht jedoch nach 1 Stunde, was auf eine eingeschränkte Entwicklung des Langzeitgedächtnisses hindeutet. RNA-seq mit CA1 zeigte eine Deregulierung mehrerer Protein-kodierender Gene und eines signifikanten Anteils an miRNAs, von denen viele als wichtig für die Gedächtnisbildung beschrieben werden. CA1 Microarrays, die nach der Erkundung einer neuen Umgebung durchgeführt wurden, identifizierten mehrere Gene, die von der Umgebung beeinflusst worden waren, aber keines der Gene war entscheidend für den Interaktionseffekt zwischen der Umgebung und dem Genotyp, was impliziert, dass Satb2 für die Umgebungs-induzierte mRNA Synthese nicht notwendig ist. cKos hatten auch niedrigere Arc Level in CA1 und das Wiedereinsetzen von Satb2 in den dorsalen Hippocampus von cKO Mäusen durch AAV (adeno-assoziierte Viren) Satb2 Genübertragung konnte sowohl das Defizit des Langzeitgedächtnisses, als auch die Arc Genexpression retten. Weiter untersuchten wir durch die Anwendung von Dunkelheit-Anpassungs Paradigmen und IEGs als Aktivitätsmarker, wie Satb2 Level die neuronale Aktivität im visuellen Cortex beeinflussen. Variabilität der neuronalen Satb2 Level und Veränderungen der Satb2 Level, bei erneuter Lichteinstrahlung nach Aufzucht im Dunkeln, implizierten, dass die neuronale Aktivität die Satb2 Expression beeinflussen kann. Neuronale Satb2 level korrelierten positiv mit IEGs, stärker mit Egr1 und nur mäßig mit Arc. Die Deletion von Satb2 hingegen beeinflusste nur die Arc Reaktion. Dass eine Satb2 Deletion Egr1 nicht beeinflusst, impliziert, dass Satb2 nicht die neuronale Erregbarkeit beeinflusst. Da Satb2 die Arc Reaktion beeinflusst ohne mit den Arc Leveln in den Neuronen zukorrelieren, steigert die Möglichkeit einer für homöostatischen Beziehung zwischen Satb2 und Arc, die eine Rolle bei der neuronalen Selektion spielt.DNA-binding protein Satb2, expressed mainly in cortex and CA1 regions of the brain, regulates transcription by influencing chromatin architecture. While known to be necessary for cortical development, its function remained unexplored in the adult brain. Mutations of SATB2 in humans cause severe learning deficits along with risk of schizophrenia, pointing to a crucial role in plasticity. We used forebrain-specific Satb2 conditional knockout (cKO) mice to study role of Satb2 in memory formation. Adult cKO mice did not reveal any defects in growth, reproduction, cortex and CA1 architecture, or gross motor functions. Functional analysis revealed that knockout animals had impaired late-phase LTP in CA1 and impaired contextual fear, object location and recognition memories after 24h, but not 1h, indicating impaired long-term memory formation. RNA-seq using CA1 revealed dysregulation of several protein coding genes and a significant proportion of miRNAs, many of them described to be important for memory formation. CA1 microarrays performed following novel environmental exploration identified about several genes to be environmentally affected but none were significant for interaction effect between environment and the genotype, implying Satb2 is not necessary for environment induced mRNA response. cKOs also had lower Arc levels in CA1 and reinstatement of Satb2 into dorsal hippocampus of cKO mice by AAV-mediated satb2 gene delivery could rescue both long-term memory deficit and Arc expression. We further investigated how Satb2 levels affect neuronal activity in visual cortex using dark adaptation paradigms and IEGs as markers of activity. Variability of neuronal Satb2 levels and change in Satb2 levels upon re-exposure to light after dark rearing implied neuronal activity can affect Satb2 expression. Neuronal Satb2 levels correlated positively with IEGs, stronger with Egr1 and only modestly with Arc, but Satb2 deletion only affected Arc response. Satb2 deletion not affecting Egr1 implied Satb2 does not influence neuronal excitability. While Satb2 affecting Arc response without correlating with Arc levels in neurons raises the possibility of a homeostatic interrelationship between Satb2 and Arc playing a role in neuronal selection.by Chethan ReddyMedical University of Innsbruck, Dissertation, 2017OeBB(VLID)230780

Optimal exergy-wise predictive control for a combined MicroCSP and HVAC system in a building

This paper presents a new control method to minimize the energy consumption of a micro-scale concentrated solar power (MicroCSP) system and building heating, ventilation, and air conditioning (HVAC) system. A new realtime optimal control method is proposed using the concept of “exergy” and model predictive control (MPC) techniques. To achieve this, first law of thermodynamics (FLT) and second law of thermodynamics (SLT) based mathematical models of MicroCSP are developed and integrated into a model of an office building located at Michigan Technological University. Then, an exergy-wise MPC framework is designed to optimize MicroCSP operation in accordance with the building HVAC needs. The new controller reduces exergy destruction by 28%, compared to a common rule-based controller (RBC). This leads to 23% energy saving, compared to the applied RBC

Integration and Optimal Control of MicroCSP with Building HVAC Systems: Review and Future Directions

Heating, ventilation, and air-conditioning (HVAC) systems are omnipresent in modern buildings and are responsible for a considerable share of consumed energy and the electricity bill in buildings. On the other hand, solar energy is abundant and could be used to support the building HVAC system through cogeneration of electricity and heat. Micro-scale concentrated solar power (MicroCSP) is a propitious solution for such applications that can be integrated into the building HVAC system to optimally provide both electricity and heat, on-demand via application of optimal control techniques. The use of thermal energy storage (TES) in MicroCSP adds dispatching capabilities to the MicroCSP energy production that will assist in optimal energy management in buildings. This work presents a review of the existing contributions on the combination of MicroCSP and HVAC systems in buildings and how it compares to other thermal-assisted HVAC applications. Different topologies and architectures for the integration of MicroCSP and building HVAC systems are proposed, and the components of standard MicroCSP systems with their control-oriented models are explained. Furthermore, this paper details the different control strategies to optimally manage the energy flow, both electrical and thermal, from the solar field to the building HVAC system to minimize energy consumption and/or operational cost

Integration and Optimal Control of MicroCSP with Building HVAC Systems: Review and Future Directions

Heating, ventilation, and air-conditioning (HVAC) systems are omnipresent in modern buildings and are responsible for a considerable share of consumed energy and the electricity bill in buildings. On the other hand, solar energy is abundant and could be used to support the building HVAC system through cogeneration of electricity and heat. Micro-scale concentrated solar power (MicroCSP) is a propitious solution for such applications that can be integrated into the building HVAC system to optimally provide both electricity and heat, on-demand via application of optimal control techniques. The use of thermal energy storage (TES) in MicroCSP adds dispatching capabilities to the MicroCSP energy production that will assist in optimal energy management in buildings. This work presents a review of the existing contributions on the combination of MicroCSP and HVAC systems in buildings and how it compares to other thermal-assisted HVAC applications. Different topologies and architectures for the integration of MicroCSP and building HVAC systems are proposed, and the components of standard MicroCSP systems with their control-oriented models are explained. Furthermore, this paper details the different control strategies to optimally manage the energy flow, both electrical and thermal, from the solar field to the building HVAC system to minimize energy consumption and/or operational cost

Zooplankton dynamics in the coastal waters of adubidri, Karnataka

134-141Water samples were collected from five locations selected along 5, 10 and 15 m depth contour, from February 2008 to January 2009 in the coastal waters of Padubidri near the proposed dupi Power Corporation Ltd, (UPCL). Total rainfall during the period of study was approximately 2600 mm, of that more than 82% occurred during the southwest monsoon season. Air temperature varied from 287°C to 32.6°C. Water temperature, pH, salinity, dissolved oxygen and B were in the ranges of 28°C-31.4°C; 7.8-8,4; 3 L28 ppt - 35A 1%o; 4,0 mg/1-6.5 mg/1; 0040 mg/1-4A8 mg/II respectively. 24 groups of zooplankton were recorded of which, copepods formed the dominant groups. The distribution of zooplankton showed higher abundance at 5 m depth, followed by 10 m and 15 m

Community structure of net phytoplankton along surf zone of Mangalore during southwest monsoon season

445-448Data collected from surf waters of Mangalore revealed the time scale variation of hydrographical parameters and phytoplankton community. Salinity and plant nutrients specially nitrate and silicate exhibited a conspicuous fluctuation in relation to intensity of precipitation. Surf water was characterized with much higher levels of limiting nutrients than the Redfield ratio. Diatoms dominated numerically among phytoplankton in the surf waters followed by dinoflagellates and blue green algae. Lower salinity associated with high load of nutrients favored the growth of bloom forming centric types of diatoms. While diverse forms of diatoms, dinoflagellates and blue green algae occurred with increasing salinity in surf waters. Shannon’s species diversity varied from 0.049 to 2.125 and Shannon’s evenness index varied from 0.020 to 0.735. Diversity indices indicated gradual increase in diversity and evenness values in relation to variation of salinity and nutrient

Model predictive control of a dual fuel engine integrated with waste heat recovery used for electric power in buildings

Waste heat recovery (WHR) system uses the thermal energy from the exhaust gases of an internal combustion engine (ICE) to assist in the electricity generated by the ICE generator in buildings. This paper presents a model predictive control (MPC) framework to minimize the fuel consumption of an ICE by integrating it with a WHR system. To this end, a control oriented model of a WHR system is developed and then integrated to a control oriented model of a turbocharged dual fuel diesel-natural gas ICE. The ICE model is derived based on experimental data collected from a 6.7 L Cummins ISB engine modified for dual fuel operation. The designed MPC framework optimizes the ICE combustion, turbocharger, and organic Rankine cycle (ORC) system in the WHR to minimize fuel consumption of the ICE. The designed control framework also allows to meet time-varying exhaust gas temperature requirements of the ICE to meet exhaust emission constraints. The results show that the optimal operation of the WHR and the ICE reduces the fuel consumption of the ICE by 6.7%