Micro-Cooling, Heating and Power (CHP) is the decentralized generation of electricity in which normally wasted heat is recovered for use in heating and cooling of the space. A micro-CHP demonstration facility is needed to showcase the system and allow for experiments to be performed. This thesis illustrates the steps taken for the installation and instrumentation of a Micro-CHP (Cooling, Heating, and Power) demonstration facility. Equipment sizing was performed by creating an accurate building model and performing a transient building analysis. Temperature, pressure, flow rate, and relative humidity are measured in order to determine accurate energy balances through each piece of equipment in the micro-CHP system. The data is collected using a number of LabView subroutines while a Visual Basic program was developed to display the information.

An emerging category of energy systems, consisting of power generation equipment coupled with thermally-activated components, has evolved as Cooling, Heating, and Power (CHP). The application of CHP systems to buildings has developed into a new paradigm ? Cooling, Heating, and Power for Buildings (CHP-B). This instructional module has been developed to introduce undergraduate engineering students to CHP-B. In the typical ME curriculum, a number of courses could contain topics related to CHP. Thermodynamics, heat transfer, thermal systems design, heat and power, alternate energy systems, and HVAC courses are appropriate for CHP topics. However, the types of material needed for this mix of courses vary. In thermodynamics, basic problems involving a CHP flavor are needed, but in an alternate energy systems course much more CHP detail and content would be required. This series of lectures on CHP-B contains both a stand-alone CHP treatment and a compilation of problems/exercises.

Cooling, Heating, and Power (CHP) is an emerging category of energy systems consisting of power generation equipment coupled with thermally activated components. The application of CHP systems to residential and small commercial buildings is known as micro-CHP (m-CHP). This instructional module has been developed to introduce engineering students to m-CHP. In the typical engineering curriculum, a number of courses could contain topics related to m-CHP. Thermodynamics, heat transfer, HVAC, heat and power, thermal systems design, and alternate energy systems courses are appropriate m-CHP topics. The types of material and level of analysis for this range of courses vary. In thermodynamics or heat transfer, basic problems involving a m-CHP flavor are needed, but in an alternate energy systems course much more detail and content would be required. This instructional module contains both lecture material and a compilation of problems/exercises for both m-CHP systems and components.

In this study, the feasibility of using an organic Rankine cycle (ORC) in trigeneration plants is examined through thermodynamic modeling and thermoeconomic optimization. Three novel trigeneration systems are considered. Each one of these systems consists of an ORC, a heating-process heat exchanger, and a single-effect absorption chiller. The three systems are distinguished by the source of the heat input to the ORC. The systems considered are SOFC-trigeneration, biomass- trigeneration, and solar-trigeneration systems. For each system four cases are considered: electrical-power, cooling-cogeneration, heating-cogeneration, and trigeneration cases. Comprehensive thermodynamic analysis on each system is carried out. Furthermore, thermoeconomic optimization is conducted. The objective of the thermoeconomic optimization is to minimize the cost per exergy unit of the trigeneration product. The results of the thermoeconomic optimization are used to compare the three systems through thermodynamic and thermoeconomic analyses. This study illustrates key output parameters to assess the trigeneration systems considered. These parameters are energy efficiency, exergy efficiency, net electrical power, electrical to cooling ratio, and electrical to heating ratio. Moreover, exergy destruction modeling is conducted to identify and quantify the major sources of exergy destruction in the systems considered. In addition, an environmental impact assessment is conducted to quantify the amount of CO2 emissions in the systems considered. Furthermore, this study examines both the cost rate and cost per exergy unit of the electrical power and other trigeneration products. This study reveals that there is a considerable efficiency improvement when trigeneration is used, as compared to only electrical power production. In addition, the emissions of CO2 per MWh of trigeneration are significantly lower than that of electrical power. It was shown that the exergy destruction rates of the ORC evaporators for the three systems are quite high. Therefore, it is important to consider using more efficient ORC evaporators in trigeneration plants. In addition, this study reveals that the SOFC-trigeneration system has the highest electrical energy efficiency while the biomass-trigeneration system and the solar mode of the solar trigeneration system have the highest trigeneration energy efficiencies. In contrast, the SOFC-trigeneration system has the highest exergy efficiency for both electrical and trigeneration cases. Furthermore, the thermoeconomic optimization shows that the solar-trigeneration system has the lowest cost per exergy unit. Meanwhile the solar-trigeneration system has zero CO2 emissions and depends on a free renewable energy source. Therefore, it can be concluded that the solar-trigeneration system has the best thermoeconomic performance among the three systems considered.

In this study, the feasibility of using an organic Rankine cycle (ORC) in trigeneration plants is examined through thermodynamic modeling and thermoeconomic optimization. Three novel trigeneration systems are considered. Each one of these systems consists of an ORC, a heating-process heat exchanger, and a single-effect absorption chiller. The three systems are distinguished by the source of the heat input to the ORC. The systems considered are SOFC-trigeneration, biomass- trigeneration, and solar-trigeneration systems. For each system four cases are considered: electrical-power, cooling-cogeneration, heating-cogeneration, and trigeneration cases. Comprehensive thermodynamic analysis on each system is carried out. Furthermore, thermoeconomic optimization is conducted. The objective of the thermoeconomic optimization is to minimize the cost per exergy unit of the trigeneration product. The results of the thermoeconomic optimization are used to compare the three systems through thermodynamic and thermoeconomic analyses. This study illustrates key output parameters to assess the trigeneration systems considered. These parameters are energy efficiency, exergy efficiency, net electrical power, electrical to cooling ratio, and electrical to heating ratio. Moreover, exergy destruction modeling is conducted to identify and quantify the major sources of exergy destruction in the systems considered. In addition, an environmental impact assessment is conducted to quantify the amount of CO2 emissions in the systems considered. Furthermore, this study examines both the cost rate and cost per exergy unit of the electrical power and other trigeneration products. This study reveals that there is a considerable efficiency improvement when trigeneration is used, as compared to only electrical power production. In addition, the emissions of CO2 per MWh of trigeneration are significantly lower than that of electrical power. It was shown that the exergy destruction rates of the ORC evaporators for the three systems are quite high. Therefore, it is important to consider using more efficient ORC evaporators in trigeneration plants. In addition, this study reveals that the SOFC-trigeneration system has the highest electrical energy efficiency while the biomass-trigeneration system and the solar mode of the solar trigeneration system have the highest trigeneration energy efficiencies. In contrast, the SOFC-trigeneration system has the highest exergy efficiency for both electrical and trigeneration cases. Furthermore, the thermoeconomic optimization shows that the solar-trigeneration system has the lowest cost per exergy unit. Meanwhile the solar-trigeneration system has zero CO2 emissions and depends on a free renewable energy source. Therefore, it can be concluded that the solar-trigeneration system has the best thermoeconomic performance among the three systems considered.

Combined cooling, heating and power (CCHP) systems are known as trigeneration systems, designed to provide electricity, cooling and heating simultaneously. The CCHP system has become a hot topic for its high system efficiency, high economic efficiency and less greenhouse gas (GHG) emissions in recent years. The efficiency of the CCHP system depends on the appropriate system configuration, operation strategy and facility size. Due to the inherent and inevitable energy waste of the traditional operation strategies, i.e., following the electric load (FEL) and following the thermal load (FTL), more efficient operation strategy should be designed. To achieve the highest system efficiency, facilities in the system should be sized to match with the corresponding operation strategy. In order to reduce the energy waste in traditional operation strategies and improve the system efficiency, two operation strategy design methods and sizing problems are studied (In Chapter 2 and Chapter 3). Most of the improved operation strategies in the literature are based on the ''balance'' plane, which implies the match of the electric demands and thermal demands. However, in more than 95% energy demand patterns, the demands cannot match with each other at this exact ''balance'' plane. To continuously use the ''balance'' concept, in Chapter 2, the system configuration is modified from the one with single absorption chiller to be the one with hybrid chillers and expand the ''balance'' plane to be a ''balance'' space by tuning the electric cooling to cool load ratio. With this new ''balance'' space, an operation strategy is designed and the power generation unit (PGU) capacity is optimized according to the proposed operation strategy to reduce the energy waste and improve the system efficiency. A case study is conducted to verify the feasibility and effectiveness of the proposed operation strategy. In Chapter 3, a more mathematical approach to schedule the energy input and power flow is proposed. By using the concept of energy hub, the CCHP system is modelled in a matrix form. As a result, the whole CCHP system is an input-output model. Setting the objective function to be a weighted summation of primary energy savings (PESs), hourly total cost savings (HTCs) and carbon dioxide emissions reduction (CDER), the optimization problem, constrained by equality and inequality constraints, is solved by the sequential quadratic programming (SQP). The PGU capacity is also sized under the proposed optimal operation strategy. In the case study, compared to FEL and FTL, the proposed optimal operation strategy saves more primary energy and annual total cost, and can be more environmental friendly. Finally, the conclusions of this thesis is summarized and some future work is discussed. / Graduate

L’objectif de cette thèse est l’optimisation énergétique d’un système de micro-cogénération et micro-tri-génération à pile à combustible. Dans un premier temps, une modélisation mathématique de tous les composants du système de cogénération à pile à combustible a été menée. L'influence de plusieurs paramètres tels que la pression et la densité de courant sur les performances de système micro-cogénération est examinée. La pertinence énergétique et environnementale du système proposé pour le contexte français est étudiée. Ensuite, une étude numérique d’un système de tri-génération composé d’une pile à combustible et d’une machine à absorption simple effet H2O/ Li-Br a été menée. L’unité de micro-tri génération est couplée à une maison unifamiliale et la performance énergétique du système est évaluée. Enfin, afin d’évaluer le potentiel de coupler le système de micro-tri-génération avec les énergies renouvelables, un système de production d’hydrogène avec les panneaux photovoltaïques «PV-H2» a été étudié. Une modélisation des différents composants du système «PV-H2» a été réalisée. Les résultats de simulation du couplage du système PV-H2 avec une maison individuelle de l’éco-quartier de la Glacerie sont présentés. / The objective of this thesis is the energy optimization of the micro-cogeneration and micro-tri-generation fuel cell system. First, a mathematical modeling of all the components of the fuel cell cogeneration system was conducted. The influence of several parameters such as pressure and current density on micro-CHP system performance is examined. The energy and environmental relevance of the system for the French context is studied. Then, a numerical study of a tri-generation system consisting of a fuel cell and a single-acting H2O / Li-Br absorption machine was conducted. The micro-tri-generation unit is coupled to a single-family house and the energy performance of the system is evaluated. Finally, in order to evaluate the potential of coupling the tri-generation system with renewable energies, a hydrogen production system with photovoltaic panels «PV-H2» has been studied. A modeling of the various components of the "PV-H2" system has been carried out. The simulation results of the coupling of the «PV-H2» system with an individual house in the eco-district of La Glacerie are presented.

This research focuses on developing strategies for the optimal control of large-scale Combined Cooling, Heating and Power (CCHP) systems to meet electricity, heating, and cooling demands, and evaluating the cost savings potential associated with it. Optimal control of CCHP systems involves the determination of the mode of operation and set points to satisfy the specific energy requirements for each time period. It is very complex to effectively design optimal control strategies because of the stochastic behavior of energy loads and fuel prices, varying component designs and operational limitations, startup and shutdown events and many more. Also, for large-scale systems, the problem involves a large number of decision variables, both discrete and continuous, and numerous constraints along with the nonlinear performance characteristic curves of equipment. In general, the CCHP energy dispatch problem is intrinsically difficult to solve because of the non-convex, non-differentiable, multimodal and discontinuous nature of the optimization problem along with strong coupling to multiple energy components. <div><br></div><div>This work presents a solution methodology for optimizing the operation of a campus CCHP system using a detailed network energy flow model solved by a hybrid approach combining mixed-integer linear programming (MILP) and nonlinear programming (NLP) optimization techniques. In the first step, MILP optimization is applied to a plant model that includes linear models for all components and a penalty for turning on or off the boilers and steam chillers. The MILP step determines which components need to be turned on and their respective load needed to meet the campus energy demand for the chosen time period (short, medium or long term) with one-hour resolution. Based on the solution from MILP solver as a starting point, the NLP optimization determines the actual hourly state of operation of selected components based on their nonlinear performance characteristics. The optimal energy dispatch algorithm provides operational signals associated with resource allocation ensuring that the systems meet campus electricity, heating, and cooling demands. The chief benefits of this formulation are its ability to determine the optimal mix of equipment with on/off capabilities and penalties for startup and shutdown, consideration of cost from all auxiliary equipment and its applicability to large-scale energy systems with multiple heating, cooling and power generation units resulting in improved performance. </div><div><br></div><div>The case-study considered in this research work is the Wade Power Plant and the Northwest Chiller Plant (NWCP) located at the main campus of Purdue University in West Lafayette, Indiana, USA. The electricity, steam, and chilled water are produced through a CCHP system to meet the campus electricity, heating and cooling demands. The hybrid approach is validated with the plant measurements and then used with the assumption of perfect load forecasts to evaluate the economic benefits of optimal control subjected to different operational conditions and fuel prices. Example cost optimizations were performed for a 24-hour period with known cooling, heating, and electricity demand of Purdue’s main campus, and based on actual real-time prices (RTP) for purchasing electricity from utility. Three optimization cases were considered for analysis: MILP [no on/off switch penalty (SP)]; MILP [including on/off switch penalty (SP)] and NLP optimization. Around 3.5% cost savings is achievable with both MILP optimization cases while almost 10.7% cost savings is achieved using the hybrid MILP-NLP approach compared to the current plant operation. For the selected components from MILP optimization, NLP balances the equipment performance to operate at the state point where its efficiency is maximum while still meeting the demand. Using this hybrid approach, a high-quality global solution is determined when the linear model is feasible while still taking into account the nonlinear nature of the problem. </div><div><br></div><div>Simulations were extended for different seasons to examine the sensitivity of the optimization results to differences in electric, heating and cooling demand. All the optimization results suggest there are opportunities for potential cost savings across all seasons compared to the current operation of the power plant. For a large CCHP plant, this could mean significant savings for a year. The impact of choosing different time range is studied for MILP optimization because any changes in MILP outputs impact the solutions of NLP optimization. Sensitivity analysis of the optimized results to the cost of purchased electricity and natural gas were performed to illustrate the operational switch between steam and electric driven components, generation and purchasing of electricity, and usage of coal and natural gas boilers that occurs for optimal operation. Finally, a modular, generalizable, easy-to-configure optimization framework for the cost-optimal control of large-scale combined cooling, heating and power systems is developed and evaluated.</div>