A automação de uma central de água gelada é muito utilizada para reduzir o consumo energético de edificações comerciais ao controlar a operação dos seus componentes e consequentemente das vazões de ar e água em função da carga térmica. Considerando as estratégias de controle atualmente em uso, existe a possibilidade de melhorá-las por meio do controle das variáveis de temperatura do sistema (temperaturas de insuflação do ar, da água gelada e da água de condensação), que na maioria dos casos são mantidas fixas para as condições de dimensionamento do sistema ou alteradas apenas em função das condições externas. Estudos demonstram que o controle adequado de cada uma dessas temperaturas nas condições de operação momentâneas (condições climáticas e carga térmica), seja de forma individualizada ou integradas, pode proporcionar reduções significativas no consumo de energia do sistema de climatização. Dessa forma, o presente estudo avaliou os ganhos de uma automação isolada e integrada dessas três temperaturas em base anual para as condições climáticas brasileiras, implementando a automação em diferentes cidades representativas do zoneamento bioclimático brasileiro via simulação computacional utilizando o software EnergyPlus(TM) para uma edificação comercial típica. Os resultados obtidos para a automação integrada indicam reduções globais de consumo que variam com a condição climática entre 5,03% e 19,68% quando comparado com o controle de temperatura fixa, e quando comparado com um controle que varia apenas em função das condições externas as reduções variam entre 3,22% e 8,21%. Esses resultados demonstram que o controle sugerido é melhor que os modelos adotados como referência de mercado. / Automation of a central chilled-water plant is widely used to reduce the energy consumption of commercial buildings by controlling the operation of its components and consequently the air and water flow rates according to the thermal load. Considering the control strategies currently in use, there is a possibility to improve them by controlling the system temperature variables (air insufflation, cold and condensation water temperatures), which in most cases are fixed in system design conditions or variable only according to the external weather. Studies demonstrate that an adequate control of each of these temperatures under momentary operating conditions (climatic conditions and thermal load), whether in an individualized or integrated way, can provide significant reductions in the energy consumption of the HVAC system. Thus, the present study intends to evaluate the energy consumption gains of an individualized and integrated automation of the three variable temperatures on an annual basis for Brazilian climatic conditions, implementing automation for different cities representing the Brazilian bioclimatic zoning. Such evaluation was made by computer simulation using EnergyPlus(TM) software for a typical commercial building. The results obtained with the integrated automation show savings in global consumption that change with the weather between 5,03% and 19,68% when compared with a fixed control, and when compared with a control that varies according to weather conditions the savings are between 3,22% and 8,21%. These results show that the proposed control is better than both models adopted as market benchmarks.

A automação de uma central de água gelada é muito utilizada para reduzir o consumo energético de edificações comerciais ao controlar a operação dos seus componentes e consequentemente das vazões de ar e água em função da carga térmica. Considerando as estratégias de controle atualmente em uso, existe a possibilidade de melhorá-las por meio do controle das variáveis de temperatura do sistema (temperaturas de insuflação do ar, da água gelada e da água de condensação), que na maioria dos casos são mantidas fixas para as condições de dimensionamento do sistema ou alteradas apenas em função das condições externas. Estudos demonstram que o controle adequado de cada uma dessas temperaturas nas condições de operação momentâneas (condições climáticas e carga térmica), seja de forma individualizada ou integradas, pode proporcionar reduções significativas no consumo de energia do sistema de climatização. Dessa forma, o presente estudo avaliou os ganhos de uma automação isolada e integrada dessas três temperaturas em base anual para as condições climáticas brasileiras, implementando a automação em diferentes cidades representativas do zoneamento bioclimático brasileiro via simulação computacional utilizando o software EnergyPlus(TM) para uma edificação comercial típica. Os resultados obtidos para a automação integrada indicam reduções globais de consumo que variam com a condição climática entre 5,03% e 19,68% quando comparado com o controle de temperatura fixa, e quando comparado com um controle que varia apenas em função das condições externas as reduções variam entre 3,22% e 8,21%. Esses resultados demonstram que o controle sugerido é melhor que os modelos adotados como referência de mercado. / Automation of a central chilled-water plant is widely used to reduce the energy consumption of commercial buildings by controlling the operation of its components and consequently the air and water flow rates according to the thermal load. Considering the control strategies currently in use, there is a possibility to improve them by controlling the system temperature variables (air insufflation, cold and condensation water temperatures), which in most cases are fixed in system design conditions or variable only according to the external weather. Studies demonstrate that an adequate control of each of these temperatures under momentary operating conditions (climatic conditions and thermal load), whether in an individualized or integrated way, can provide significant reductions in the energy consumption of the HVAC system. Thus, the present study intends to evaluate the energy consumption gains of an individualized and integrated automation of the three variable temperatures on an annual basis for Brazilian climatic conditions, implementing automation for different cities representing the Brazilian bioclimatic zoning. Such evaluation was made by computer simulation using EnergyPlus(TM) software for a typical commercial building. The results obtained with the integrated automation show savings in global consumption that change with the weather between 5,03% and 19,68% when compared with a fixed control, and when compared with a control that varies according to weather conditions the savings are between 3,22% and 8,21%. These results show that the proposed control is better than both models adopted as market benchmarks.

This thesis develops a calibrated model of the Cal Poly Central Chilled Water Plant with Thermal Energy Storage for use in determining an optimal operating control strategy. The model was developed using a transient systems simulation program (TRNSYS) that includes plant performance and manufacturer data for the primary system components, which are comprised of pumps, chillers, cooling towers, and a thermal energy storage tank. The model is calibrated to the actual measured performance of the plant using the current control strategy as a baseline. By observing and quantifying areas for potential improvement in plant performance under conditions of high campus cooling load demands, alternative control strategies for the plant are proposed. Operation of the plant under each of these control strategies is simulated in the model and evaluated for overall energy and demand-usage cost savings. These results are used to recommend improvements in the plant’s current control strategy, as well as to propose an optimal control strategy that may be applied to reduce plant operating costs. The results of the model identify that the plant can perform more economically by employing more chiller power to charge the Thermal Energy Storage tank to higher capacities during overnight periods when the utility rates are lower. Staging the operation of the different chillers to more precisely follow the tank charges during these off-peak periods can ensure faster tank charging when its capacity may not be sufficient to meet the peak and part-peak cooling load demands. A proposed control strategy to accomplish this breaks the overnight Off-Peak rate period into three periods with separate control setpoints, which are designed to maintain the tank charge capacity at the minimum levels to be able to accommodate the daily campus cooling demands during peak and part-peak hours.

Cooling towers form an important part of chilled water systems and perform the function of rejecting the heat to the atmosphere. These systems are often not operated optimally, and cooling towers being an integral part of the system present a significant area to study and determine possible energy saving measures. Operation of cooling towers in economizer mode in winter and variable frequency drives (VFDs) on cooling tower fans are measures that can provide considerable energy savings. The chilled water system analysis tool (CWSAT) software is developed as a primary screening tool for energy evaluation for chilled water systems and quantifies the energy usage of the various components and typical measures that can be applied to these systems to conserve energy, all while requiring minimum number of inputs to analyze component-wise energy consumption and incurred overall cost. A careful investigation of the current model in CWSAT indicates that the prediction capability of the model at lower wet bulb temperatures and at low fan power is not very accurate. A new model for accurate tower performance prediction is imperative, since economizer operation occurs at low temperatures and most cooling towers come equipped with VFDs. In this thesis, a new model to predict cooling tower performance is created to give a more accurate prediction of energy savings for a tower. Further the economic feasibility of having additional cooling tower capacity to allow for economizer cooling, in light of reduced tower capacity at lower temperatures is investigated.

The increasing price of oil and the destabilisation of the world’s climate are urging governments, businesses and individuals to constantly investigate energy-efficient technologies and methodologies and pursue the adoption of energy efficiency programmes in a global effort to reduce energy consumption, greenhouse gas emissions and ultimately energy costs. In New Zealand, one of the biggest industrial energy efficiency projects was started in 2002 by a multinational dairy company, the Fonterra Co-operative Group, in partnership with the energy service company Demand Response Ltd; the project currently aims at reducing by 15% the energy costs at all Fonterra’s major production sites throughout the country. This thesis, undertaken as part of the above project, examines the development and implementation of a structured and integrated energy monitoring and targeting methodology (M&T) for the most efficient operation of all Fonterra’s chilled water systems, with an initial focus on the ones installed at Clandeboye, one of the Fonterra’s sites involved in the energy saving project. A data collection system (Insite) was already in place at Clandeboye to enable storage and analysis of some of the site’s utility metering data. After identification of key chilled water system components and definition of data requirements for M&T purposes, an analysis of past energy consumption trends (based on multiple regression calculations) was carried out to develop an historical benchmark of the energy used, compare it with current energy performance and thus identify opportunities for future improvements. The creation of an M&T reporting system for presenting findings to operators and management was the last essential part of the thesis development. The study has highlighted that the robustness of the proposed regression model was badly affected by the unreliability of the existing data collection system and the uncertainty associated with poorly documented changes to operating conditions/plant configuration that had occurred over time. The conclusion is that, while the developed M&T methodology is theoretically valid and readily applicable, further developments are necessary (and recommended) to make it suitable for other similar systems.

Fossil fuels are the major sources of electrical power generation in the world. Among all fossil fuels, oil is considered as the most sought-after fuel. The burden on countries that provide subsidized electricity produced from oil-fired power plants is noteworthy. Kuwait is a notable example of these countries. Electricity in Kuwait is heavily consumed by residential air conditioning, which comprises 60% of the total electricity generated at peak times on a hot summer day. From this perspective, residential air conditioning in Kuwait was selected to undergo further investigation regarding low energy air conditioning choices. Three solutions to control the rapid growth of demand for electricity by residential air conditioning are examined. The first solution investigated assesses the orientation and grouping of houses in Kuwait in order to examine their effect on cooling load and electrical energy consumption for future houses. Four residential cases were developed; each case comprises six typical houses. The cases identified are: (1) single block facing east-west, (2) single block facing north-south, (3) double block facing east-west and (4) double block facing north-south. Cooling loads are calculated using the DesignBuilder building thermal simulation software. Case (2) is found to have the smallest cooling load, and case (1) the largest. The estimated savings from applying case (2) compared to the average of the four cases for the future houses planned to be built by the government by the year 2016 (i.e. approximately 20,000 houses) are found to be approximately .US 33 million of power system capital costs, 15 GWh per year of electrical energy consumption and 11 kilotons per year of CO2 emissions. In the second solution, a lifecycle cost analysis is performed to evaluate the economic feasibilities of electricity driven chilled water system compared to predominant air conditioning system in Kuwaiti houses which is Packaged- Direct Expansion. The study considers the total cash paid by the consumer and the total cash paid by the government, since electricity is subsidized in Kuwait. The study finds that the chilled water system is not cost-effective for consumers due to high installation cost. However, a chilled water system would be cost-effective for the government because it consumes 40%less electrical energy than Packaged-DX. So, the study suggests subsidising the installation of chilled water systems so that the installation cost to the consumer is the same as for Packaged-DX systems. In the third solution, the study examines the viability of a single-effect LiBr absorption chiller driven by steam extracted from the steam turbine in the configuration of a combined cycle power plant (CCPP). The analysis shows that CCPP with absorption chiller yields less net electrical power available to utility grid compared to similar CCPP giving electricity to the grid and to Direct-Expansion air conditioning systems for the same cooling requirements. The reasons for that are the reduction in steam turbine power output resulted from steam extraction, and the amount of electrical energy required to operate the configuration of CCPP with absorption chiller.

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

Provisioning for power failure is an important element of data center design. It is important to assess both tangible and intangible costs of unplanned data center downtime. These costs must be compared with the capital cost of providing various levels of backup power infrastructure to compute and cooling equipment. Various levels of backup power infrastructure each lead to a most probable transient scenario after utility power failure. Because of differences between facilities, the level of risk that unacceptable compute equipment inlet temperature associated with each level of backup power infrastructure is not standardized; in particular, facilities with differing compute equipment power densities may require different levels of backup power infrastructure to maintain safe operation. Choosing one level of backup power infrastructure above another is not necessarily obvious for every facility, as there may be large gaps in costs and unknown levels of risk for lower levels of provisioning. A first order model is also used to compare inclusion of various thermal capacitance values with experimental results. Room level experiments also illustrate the relative level of risk associated with various levels of provisioning for the same control volume and compute equipment. Although provisioning to back up as much equipment as possible remains the "safest" solution, cost will continue to play a factor in facility design decisions. This work offers a step toward appropriate modeling of data center power failure events and suggests further steps to continue the process.