Energy efficiency and renewable energy become more attractive in smart grid. In order to efficiently reduce global energy usage in building energy systems and to improve local environmental sustainability, it is essential to optimize the operation and the performance of combined heat and power (CHP) systems. In addition, intermittent renewable energy and imprecisely predicted customer loads have introduced great challenges in energy-efficient buildings' optimal operation. In the deterministic optimal operation, we study the modeling of components in energy-efficient building systems, including the power grid interface, CHP and boiler units, energy storage devices, and building appliances. The mixed energy resources are applied to collaboratively supply both electric and thermal loads. The results show that CHP can effectively improve overall energy efficiency by coordinating electric and thermal power supplies. Through the coordinated operation of all power sources, the daily operation cost of building energy system for generating energy can be significantly reduced. In order to address the risk from energy consumption forecast errors and renewable energy production volatility, we utilize the approach of stochastic programming and robust optimizations to operate energy-efficient building systems under uncertainty. The multi-stage stochastic programming model is introduced so that the reliable operation of building energy systems would be probabilistically guaranteed with stochastic decisions. The simulation results show that the stochastic operation of building energy systems is a promising strategy to account for the impact of the uncertainty on power dispatch decisions of energy-efficient building systems. In order to provide absolute guarantee for the reliable operation of building energy systems, a robust energy supply to electric and thermal loads is studied by exploring the effectiveness of energy storage on energy supply against the uncertainty. The robustness can be adjusted to control the conservativeness of the proposed robust operation model. For the purpose of achieving adaptability in the robust optimal operation and attaining robustness in the stochastic optimal operation of building energy systems, we also develop an innovative robust stochastic optimization (RSO) model. The proposed RSO model not only overcomes the conservativeness in the robust operation model, but also circumvents the curse of dimensionality in the stochastic operation model.

Due to the growing number of diverse power systems disruptions, including extreme weather events, technical factors, and human factors, assessing and quantifying the resilience of electric power subsystems has become an indispensable step to develop an efficient strategic plan to enhance the resilience and reliability of these systems and to endure the diverse interruptions. In this study, factors and sub-factors that may have either direct or indirect impact on the resilience of biomass-based combined heat and power systems are identified, and the interdependencies among them are determined as well. A Bayesian network model is implemented to quantify the resilience of a bCHP system, and the results are analyzed by applying three different techniques, which are sensitivity analysis, forward propagation analysis, and backward propagation analysis.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第17560号 / 工博第3719号 / 新制||工||1566(附属図書館) / 30326 / 京都大学大学院工学研究科航空宇宙工学専攻 / (主査)教授 吉田 英生, 教授 中部 主敬, 准教授 松本 充弘 / 学位規則第4条第1項該当

A CO2 emission analysis and system investigation of a direct fuel cell waste energy recovery and power generation system (DFC-ERG) for pressure letdown stations was undertaken. The hybrid system developed by FuelCell Energy Inc. is an integrated turboexpander and a direct internal reforming molten carbonate fuel cell system in a combined circle. At pressure letdown stations, popularly called city gates, the pressure of natural gas transported on long pipelines is reduced by traditional pressure regulating systems. Energy is lost as a result of pressure reduction. Pressure reduction also results in severe cooling of the gas due to the Joule Thompson effect, thus, requiring preheating of the natural gas using traditional gas fired-burners. The thermal energy generated results in the emission of green house gases. The DFC-ERG system is a novel waste energy recovery and green house gas mitigation system that can replace traditional pressure regulating systems on city gates. A DFC-ERG system has been simulated using UniSim Design process simulation software. A case study using data from Utilities Kingston’s city gate at Glenburnie was analysed. The waste energy recovery system was modelled using the design specifications of the FuelCell Energy Inc’s DFC 300 system and turboexpander design characteristics of Cryostar TG120. The Fuel Cell system sizing was based on the required thermal output, electrical power output, available configuration and cost. The predicted performance of the fuel cell system was simulated at a current density of 140mA/cm2, steam to carbon ratio of 3, fuel utilization of 75% and oxygen utilization of 30%. The power output of the turboexpander was found to strongly depend on the high pressure natural gas flowrate, temperature and pressure. The simulated DFC-ERG system was found to reduce CO2 emissions when the electrical power generated by the DFC-ERG system replaced electrical power generated by a coal fired plant. / Thesis (Master, Chemical Engineering) -- Queen's University, 2010-08-31 02:02:11.392