A Two-Stage Model for Optimal Operation of Multi-energy Hub System for Resilience Enhancement Against Natural Disasters

The climate change leads to more natural disasters which can lead to two results, one is that some generation and transmission infrastructures of energy will endure serious damages, and another is that cities and districts will probably be exposed to potentially large-scale blackouts. The pressures of energy and environment problems have prompted people to reflect on existing energy consumption patterns and begin to study the comprehensive utilization of various types of energy such as electricity, gas and heat. The concept of energy hub (EH) has emerged. It is a key hub within multi-energy network. A Two-stage model for the operation of multi-energy hub system for resilience enhancement in natural disasters was established in this thesis. The system includes three different energy hub systems, each EH consists of electric transformer, Combined Cooling, Heating and Power (CCHP), Energy Storage System (ESS) and chiller which are responsible for energy conversion and transfer. Each EH is connected to the main electric network and natural gas network. There are also transmission lines and pipelines connected between them for energy communication. The purpose of this model is to reduce the load shedding as much as possible while ensuring the maximum economic benefits including operation costs and load curtailment punishing fees of both two stages, so that each EH system can make a reasonable energy supply externally and maintain stable operation internally. When disaster happens, the system will go through two stages, first stage is the one before disaster and second stage is the one when disaster occurs. The choices made by the system will be different at these two stages, including selling and purchasing value from the main network, storing and releasing energy value of ESS, conversion ratio for different energies within EH and the load shedding value of demand side because each stage has different transmission rate and load demand. Three case studies have been done. YALMIP toolbox of MATLAB has been used to solve these problems. In case study one, the result shows that the total cost of two-stage model reduced by about 25% compared to the separate stage model, and load curtailment, especially electricity, was reduced sharply. In case study two, after load priority setting, load curtailment fee has been reduced obviously by 8.2%, shedding value of significant load has been reduced up to 26.9%. In case study three, the total cost of coordinated 3-EH model has been reduced by 57.59% compared to the model without coordination, and each EH has saved cost by 32.92%, 69.38% and 53.21% respectively. The result shows great advantages of this model, by using the two stage the total cost and load curtailment value reduced significantly for both whole system and each EH

Marginal Structural Cox Model for Survival Data with Treatment-Confounder Feedback

In an observational longitudinal study, there can be time-varying exposure/treatment and time-varying confounders. When the confounders affect the exposure and prior exposure also has an impact on levels of confounders, there is treatment confounder feedback. To admit estimation of unbiased causal effects, these conditions need to be hold, exchangeability, positivity, consistency. The traditional method of conditioning on potential confounders does not meet these 3 conditions. Therefore, parameter estimates from traditional Cox model are biased casual effect estimates when the treatment confounder feedback exists. The marginal structural Cox model can be used to address this issue. By calculating and including inverse probability (IP) weights, the impact of confounding can be removed. Estimates from models with IP weights are interpreted as the causal effect that comparing always in treatment group vs. never in treatment group. In this study, first, I introduced basic concepts of causal inference, treatment confounder feedback and the marginal structural model; detailed steps of calculating IP weights and model fitting. In simulation study, I compared the time-dependent Cox models and the marginal structural Cox model; Also, for the marginal model, results using three types of IP weights were compared: un-stabilized weight, stabilized weight, and stabilized weight considering censoring. Performance metrics of each method were evaluated based on their bias, percentage bias, empirical standard deviation, standard error and coverage probability of 95% confidence intervals. Aerobics Center Longitudinal Study (ACLS) data were used to explore the causal effect of cardiorespiratory fitness on hypertension incidence. Overweight or obese is a risk factor of hypertension. We hypothesized that cardiorespiratory fitness may help lower BMI via physical exercise, while reduced BMI or improved overweight status may promote cardiorespiratory fitness. Thus, there exists cardiorespiratory (treatment) overweight (confounder) feedback, and the marginal structural Cox model may deepen our understanding of association between hypertension and CRF through ACLS data

Development of integrated assessment platform for biofuels production via fast pyrolysis and upgrading pathway

Growing concern over Greenhouse Gas (GHG) emissions from petroleum-based fuel consumption have prompted interest in the production of alternative transportation fuels from biorenewable sources. As required by the Energy Independence and Security Act of 2005, the U.S. Environmental Protection Agency (EPA) finalized the Renewable Fuel Standard (RFS) and mandated petroleum refineries and oil importers to increase the volume of renewable fuel that is blended into petroleum-based transportation fuels. Although biomass is a promising renewable energy for fuels and chemicals production, the technology, economics and environmental issues for bioenergy systems should be extensively evaluated. Other researchers have analyzed bioenergy systems from a number of different perspectives but these perspectives have not been combined into an integrated analysis methodology because of the large number of disparate disciplinary fields that would have to be considered including bioenergy sciences and engineering, environmental sciences, economics, optimization, and numerical modeling. Nor is it a simple matter to integrate the different analytical methods used in economic assessment, environmental impact evaluation, supply chain management, and logistic planning. This dissertation explores the development of integrated assessment platform for biofuels production, using separate modules to evaluate process engineering, economic feasibility, logistics of supply, and environmental impact within a general framework. Four modules are included: process simulation (module A), economics analysis (module B), life cycle assessment (module C), and supply chain & logistics optimization (module D). In this dissertation, the specific instance of production of drop- in biofuels using fast pyrolysis and upgrading is employed as the case study to examine this methodology. Two different bio-oil upgrading pathways are examined using this integrated assessment platform: 1. commodity chemicals production via forest residue fast pyrolysis and hydrotreating/fluidized catalytic cracking (FCC) pathway 2. Co-production of hydrogen and transportation fuels via corn stover fast pyrolysis and hydrotreating/hydrocracking pathway. The preliminary results prove that this developed integrated assessment methodology is a powerful tool to evaluate the biofuels production via fast pyrolysis pathway. This integrated assessment platform could also extended for other energy resource examination

A Two-Stage Model for Optimal Operation of Multi-Energy Hub System for Resilience Enhancement Against Natural Disasters

The climate change leads to more natural disasters which can lead to two results, one is that some generation and transmission infrastructures of energy will endure serious damages, and another is that cities and districts will probably be exposed to potentially large-scale blackouts. The pressures of energy and environment problems have prompted people to reflect on existing energy consumption patterns and begin to study the comprehensive utilization of various types of energy such as electricity, gas and heat. The concept of energy hub (EH) has emerged. It is a key hub within multi-energy network. A Two-stage model for the operation of multi-energy hub system for resilience enhancement in natural disasters was established in this thesis. The system includes three different energy hub systems, each EH consists of electric transformer, Combined Cooling, Heating and Power (CCHP), Energy Storage System (ESS) and chiller which are responsible for energy conversion and transfer. Each EH is connected to the main electric network and natural gas network. There are also transmission lines and pipelines connected between them for energy communication. The purpose of this model is to reduce the load shedding as much as possible while ensuring the maximum economic benefits including operation costs and load curtailment punishing fees of both two stages, so that each EH system can make a reasonable energy supply externally and maintain stable operation internally. When disaster happens, the system will go through two stages, first stage is the one before disaster and second stage is the one when disaster occurs. The choices made by the system will be different at these two stages, including selling and purchasing value from the main network, storing and releasing energy value of ESS, conversion ratio for different energies within EH and the load shedding value of demand side because each stage has different transmission rate and load demand. Three case studies have been done. YALMIP toolbox of MATLAB has been used to solve these problems. In case study one, the result shows that the total cost of two-stage model reduced by about 25% compared to the separate stage model, and load curtailment, especially electricity, was reduced sharply. In case study two, after load priority setting, load curtailment fee has been reduced obviously by 8.2%, shedding value of significant load has been reduced up to 26.9%. In case study three, the total cost of coordinated 3-EH model has been reduced by 57.59% compared to the model without coordination, and each EH has saved cost by 32.92%, 69.38% and 53.21% respectively. The result shows great advantages of this model, by using the two stage the total cost and load curtailment value reduced significantly for both whole system and each EH