Optimal Assessment Of Weigh-In-Motion Data For Structural Reliability Based Rating Of Bridge Superstructures

The first objectives of this research are to propose a simplified procedure to reduce the vehicle dataset need to be considered for load rating of bridge superstructures. The second objective is to explore the effectiveness of Reliability Based Design Optimization (RBDO) to develop a State-specific rating load model for a set of bridge superstructures. Finally, an alternative novel approach to develop rating models as effective as an ideal RBDO solution is proposed. The proposed solutions can substantially reduce the computational effort while not compromising the level of accuracy

Smart PV Inverter Control for Distribution Systems

PV solar systems employ inverters to transform dc power from solar panels into ac power for injecting into the power grids. Inverters that perform multiple functions in addition to real power production are known as “smart inverters”. This thesis presents a novel control of PV inverter as a dynamic reactive power compensator – STATCOM. This “smart PV inverter” control enables a PV solar inverter to operate in three modes – i) Full PV, ii) Partial STATCOM, and iii) Full STATCOM, depending upon system needs. The novel control is developed and demonstrated for the objectives of a) symmetrical voltage regulation, b) temporary overvoltage reduction, c) power factor correction, and d) reactive power control. In Full PV mode, the inverter performs only real power production based on solar radiation. In Partial STATCOM mode, the controller uses the remaining capacity of the inverter for voltage control, power factor correction and reactive power control. The Full STATCOM mode is invoked in emergency scenarios, such as faults, or severe voltage fluctuations. In this mode, the real power production is shut down temporarily and the entire inverter capacity is utilized for voltage regulation or TOV curtailment for providing critical support to the power system. This thesis presents a comprehensive design of the proposed smart inverter controller with all its associated system components. The performance of the smart inverter is simulated using the electromagnetic transients software PSCAD/EMTDC. It is further validated through Real Time Digital Simulation and Control Hardware in the Loop (CHIL) simulation. Finally the successful performance of the smart inverter controller is demonstrated on a 10 kW inverter in the laboratory on a simulated feeder of Bluewater Power, Sarnia, where this smart inverter is proposed to be installed. The smart PV inverter control is further shown to enhance the connectivity of PV solar farms in a realistic 44 kV Hydro One distribution feeder. It is demonstrated that if such a novel control is implemented on a 10 MW solar farm, the need for the actually installed STATCOM for voltage regulation and TOV control can be either minimized or altogether eliminated, bringing a significant savings for the utility PV solar systems employ inverters to transform dc power from solar panels into ac power for injecting into the power grids. Inverters that perform multiple functions in addition to real power production are known as “smart inverters”. This thesis presents a novel control of PV inverter as a dynamic reactive power compensator – STATCOM. This “smart PV inverter” control enables a PV solar inverter to operate in three modes – i) Full PV, ii) Partial STATCOM, and iii) Full STATCOM, depending upon system needs. The novel control is developed and demonstrated for the objectives of a) symmetrical voltage regulation, b) temporary overvoltage reduction, c) power factor correction, and d) reactive power control. In Full PV mode, the inverter performs only real power production based on solar radiation. In Partial STATCOM mode, the controller uses the remaining capacity of the inverter for voltage control, power factor correction and reactive power control. The Full STATCOM mode is invoked in emergency scenarios, such as faults, or severe voltage fluctuations. In this mode, the real power production is shut down temporarily and the entire inverter capacity is utilized for voltage regulation or TOV curtailment for providing critical support to the power system. This thesis presents a comprehensive design of the proposed smart inverter controller with all its associated system components. The performance of the smart inverter is simulated using the electromagnetic transients software PSCAD/EMTDC. It is further validated through Real Time Digital Simulation and Control Hardware in the Loop (CHIL) simulation. Finally the successful performance of the smart inverter controller is demonstrated on a 10 kW inverter in the laboratory on a simulated feeder of Bluewater Power, Sarnia, where this smart inverter is proposed to be installed. The smart PV inverter control is further shown to enhance the connectivity of PV solar farms in a realistic 44 kV Hydro One distribution feeder. It is demonstrated that if such a novel control is implemented on a 10 MW solar farm, the need for the actually installed STATCOM for voltage regulation and TOV control can be either minimized or altogether eliminated, bringing a significant savings for the utilit

Load Truncation Approach for Development of Live Load Factors for Bridge Rating

Various local governments have developed state-specific vehicular live load factors for bridge rating. However, a significant computational demand is often associated with such an effort. This is due to the large size of the weigh-in-motion (WIM) databases frequently used in the procedure. In this study, a method is proposed that can significantly reduce the computational cost of the analysis, while still maintaining reasonable accuracy. The proposed approach develops approximate live load random variable statistics by truncating the WIM database based on gross vehicle weight, then a complete reliability analysis is conducted to develop new live load factors that meet AASHTO-specified rating standards. Two WIM databases, one based on typically legal vehicles and another based on unusually heavy vehicles, are considered for evaluation. Results of the proposed approach are compared to an exact assessment as well as to a simplified method suggested by AASHTO. It was found that the proposed approach may provide very large reductions in computational cost with minimal loss of accuracy, whereas significant inaccuracies were found with the existing simplified approach

Development of Traffic Live Load Models for Bridge Superstructure Rating with RBDO and Best Selection Approach

Reliability-based design optimization (RBDO) is frequently used to determine optimal structural geometry and material characteristics that can best meet performance goals while considering uncertainties. In this study, the effectiveness of RBDO to develop a rating load model for a set of bridge structures is explored, as well as the use of an alternate Best Selection procedure that requires substantially less computational effort. The specific problem investigated is the development of a vehicular load model for use in bridge rating, where the objective of the optimization is to minimize the variation in reliability index across different girder types and bridge geometries. Moment and shear limit states are considered, where girder resistance and load random variables are included in the reliability analysis. It was found that the proposed Best Selection approach could be used to develop rating model as nearly as effective as an ideal RBDO solution but with significantly less computational effort. Both approaches significantly reduced the range and coefficient of variation of reliability index among the bridge cases considered

Dynamic Distributor Routing in Supply Chain Networks with Stochastic Travel Time

Minimizing the distribution time in supply chain networks is critical. By minimizing the total time of distribution in the network we can reduce the cost as well as decrease the product wastage for goods with fast approaching expiration date such as dairy products. In real-world the traveling time in supply chain network is not deterministic most of the time and uncertainties in the form of randomness are not avoidable. For this reason, for finding the optimal path of distributor vehicles in the distribution network that has the lowest travel time, a probabilistic dynamic optimization model has been used in this study and the results of a numerical example are discussed

Study of Student Financial Aid at Oklahoma State University

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