Simulation of hydrodynamics and sediment transport patterns in Delaware Bay

This research seeks to increase understanding of hydrodynamic processes influencing the salinity intrusion and sediment transport patterns by simulating the complex flows in Delaware Estuary. For this purpose, a three-dimensional numerical model is developed for the tidal portion of the Delaware Estuary using the UnTRIM hydrodynamic kernel. The model extends from Trenton, NJ south past the inlet at Cape May, NJ and incorporates a large portion of the continental shelf.The simulation efforts are focused on summer 2003. A variable, harmonically decomposed, water level boundary condition of three diurnal (K1, Q1, O1) and four semidiurnal (K2, S2, N2, M2) components are used to regenerate the observed tidal signals in the bay. The effect of forcing by the Chesapeake Bay through the Chesapeake-Delaware canal is also modeled. The major forcings such as inflow and wind is used to better reproduce the observed characteristics.Various turbulence closure models are compared for use in Delaware Estuary to best represent the salinity intrusion patterns. In particular, seven different turbulence closures, five of which are two-equation closure models, are used for comparison. Four of these models are implemented in the UnTRIM hydrodynamic code using Generic Length Scale (GLS) approach that mimics the models through its parameter combinations. The original Yamada Mellor level 2.5 code is used as the fifth one.The water levels are compared with data available from National Oceanic and Atmospheric Administration observation stations. Harmonic analysis to observations and simulations are performed. All turbulence models perform similar in performance representing the tidal conditions.Salinity time series data is available at Ship John Shoal Light Station for the 62 day simulation period. In addition to the time series data, a survey performed by University of Delaware along the main shipping channel in June 2003 is available. Simulation with different turbulence closures yielded substantially different results. Among the seven closures compared, the k −ε parameterization of GLS is found to best represent the observed salinity characteristics.The k −ε model is used in the sediment transport modeling. The model results are compared to the available sediment data from a survey performed in spring 2003. The location of turbidity maximum is accurately identified by k −ε model.Ph.D., Civil, Architectural & Environmental Engineering -- Drexel University, 200

Speed control of hydraulic turbines for grid synchronization using simple adaptive add-ons

Background: Parameters of the hydroelectric power plant controllers are typically tuned at the nominal operating conditions such as nominal head and single unit operation. Water level variations in reservoir and/or tailwater, and the presence of other active units sharing the penstock are common disturbances to the nominal assumption. Methods: This article proposes two adaptive add-ons, namely gain scheduling and model reference adaptive control, to the existing speed controllers to improve grid synchronization performance when the site conditions are not nominal. The add-ons were designed and tested on a validated dynamic model of a power plant unit by using a software-in-the-loop simulation setup. An off-season scenario is simulated, in which the original controller of the unit cannot bring the turbine to synchronize with the grid due to low gross head. Then, the add-ons were implemented on-site and experiments were performed under similar conditions. The parameter sets used in gain scheduling for different operation bands are determined off-line with the help of operational experience. The model reference adaptive control add-on requires a reference model and a learning rate. A description of the turbine speed-up profile at nominal operating conditions is sufficient to be used as the reference model. The proposed piecewise linear reference model favors stability over speed in settling to the nominal speed. Results: It is experimentally shown that the proposed add-ons compensate the negative effect of head loss in grid synchronization, and perform similar to the ideal performance at the nominal head. Conclusion: Both add-ons can be implemented on the available off-the-shelf speed governor controllers. They are suitable for use in all hydroelectric power plants, especially in unmanned ones, for automatic synchronization with less waste water. © The Author(s) 2018

Frequency Containment Control of Hydropower Plants Using Different Adaptive Methods

With the growth in the share of variable renewable energy sources, fluctuations in the power generation caused by these types of power plants can diminish the stability and flexibility of the grid. These two can be enhanced by applying frequency containment using hydropower plants as an operational reserve. The frequency containment in hydropower plants is automatically controlled by speed governors within seconds. Disturbances such as fluctuations in the net head and aging may diminish the performance of the controllers of the speed governors. In this study, model reference adaptive control approaches based on the Massachusetts Institute of Technology (MIT) rule and Lyapunov method were exploited in order to improve the performance of the speed governor for frequency containment control. The active power control with frequency control was enhanced by the aforementioned adaptive control methods. A mathematical model of a hydropower plant with a surge tank and medium penstock was constructed and validated through site measurements of a plant. It was shown that, as they are applicable in real life, both methods perform significantly better compared to conventional proportional-integrator control. Even in first five deviations, the performance of the conventional controller improved by 58.8% using the MIT rule and by 65.9% using the Lyapunov method. When the two adaptive control approaches were compared with each other, the MIT rule outputted better results than the Lyapunov method when the disturbance frequency was higher; however, the latter was more functional for rare disturbances