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Smith, Brennan T

Publications and source records attributed to Smith, Brennan T.

A Hydropower facility as an Energy Water Signal Processor

In recent times, various efforts have been made to address the challenge of adequately representing hydropower systems in modeling frameworks, accounting for the lack of data to represent the multiple constraints in hydropower operation. This research is a pilot data-driven methodology for characterizing, classifying, and comparing the water-to-energy and energy-to-water signal transformations that hydropower facilities as signal processors accomplish. In this study, a Box Jenkins transfer function/noise model is used to identify the relationship between reservoir inflows and outflows. For examining the feasibility of this methodology, 5-minute fleet data for five storage and five run-of-river facilities was provided by the Tennessee Valley Authority (TVA) and transfer function models are developed. The influence of past inflow and outflow values on the current outflow decisions was investigated and summarized by examining the results of Box Jenkins methodology. Finally, dominance analysis was introduced to add value to the Box Jenkins model results and provide different stakeholders with a set of concepts to convey the functionality of hydropower.

13 HYDRO ENERGY↗

Enhancing the resiliency of small hydropower projects: environmental function, modularity, and stakeholder elicitation as design priorities

Small hydropower plants supply reliable renewable energy to the grid, though few new plants have been developed in the Unites States over the past few decades due to complex environmental challenges and poor project economics. This paper describes the current landscape of small hydropower development, and introduces a new approach to facility design that co-optimizes the extraction of hydroelectric power from a stream with other important environmental functions such as fish, sediment, and recreational passage. The approach considers hydropower facilities as an integrated system of standardized interlocking modules, designed to sustain stream functions, generate power, and interface with the streambed. It is hypothesized that this modular eco-design approach, when guided by input from the broader small hydropower stakeholder community, can lead to cost savings across the facility, reduced licensing and approval timelines, and ultimately, to enhanced resiliency through improved environmental performance over the lifetime of the project.

Witt, Adam M↗

Development and application of a standardized flow measurement uncertainty analysis framework to various low-head short-converging intake types across the United States federal hydropower fleet

Turbine discharges at low-head short converging intakes are difficult to measure accurately. The proximity of the measurement section to the intake entrance admits large uncertainties related to asymmetry of the velocity profile, swirl, and turbulence. Existing turbine performance codes [10, 24] do not address this special case and published literature is largely silent on rigorous evaluation of uncertainties associated with this measurement context. The American Society of Mechanical Engineers (ASME) Committee investigated the use of Acoustic transit time (ATT), Acoustic scintillation (AS), and Current meter (CM) in a short converging intake at the Kootenay Canal Generating Station in 2009. Based on their findings, a standardized uncertainty analysis (UA) framework for velocity-area method (specifically for CM measurements) is presented in this paper given the fact that CM is still the most fundamental and common type of measurement system. Typical sources of systematic and random errors associated with CM measurements are investigated, and the major sources of uncertainties associated with turbulence and velocity fluctuations, numerical velocity integration technique (bi-cubic spline), and the number and placement of current meters are being considered for an evaluation. Since the velocity measurements in a short converging intake are associated with complex nonlinear and time varying uncertainties (e.g., Reynolds stress in fluid dynamics), simply applying the law of propagation of uncertainty is known to overestimate the measurement variance while the Monte Carlo method does not. Therefore, a pseudo-Monte Carlo simulation method (random flow generation technique [8]) which was initially developed for the purpose of establishing upstream or initial conditions in the Large-Eddy Simulation (LES) and the Direct Numerical Simulation (DNS) is used to statistically determine uncertainties associated with turbulence and velocity fluctuations. This technique is then combined with a bi-cubic spline interpolation method which converts point velocities into a continuous velocity distribution over the measurement domain. Subsequently the number and placement of current meters are simulated to investigate the accuracy of the estimated flow rates using the numerical velocity-area integration method outlined in ISO 3354 [12]. The authors herein consider that statistics on generated flow rates processed with bi-cubic interpolation and sensor simulations are the combined uncertainties which already accounted for the effects of all those three uncertainty sources. A preliminary analysis based on the current meter data obtained through an upgrade acceptance test of a single unit located in a mainstem plant has been presented.

Smith, Brennan T↗

Impact of the Number of Applied Current Meter Sensors on the Accuracy of Flow Rate Measurements across a Range of Hydroelectric Facilities Indicative of the Domestic Hydroelectric Fleet

The following paper represents the results of an investigation into the impact of the number and placement of Current Meter (CM) flow sensors on the accuracy to which they are capable of predicting the overall flow rate. Flow measurement accuracy is of particular importance in multiunit plants because it plays a pivotal role in determining the operational efficiency characteristics of each unit, allowing the operator to select the unit (or combination of units) which most efficiently meet demand. Several case studies have demonstrated that optimization of unit dispatch has the potential to increase plant efficiencies from between 1 to 4.4 percent [2] [3]. Unfortunately current industry standards do not have an established methodology to measure the flow rate through hydropower units with short converging intakes (SCI); the only direction provided is that CM sensors should be used. The most common application of CM is horizontally, along a trolley which is incrementally lowered across a measurement cross section. As such, the measurement resolution is defined horizontally and vertically by the number of CM and the number of measurement increments respectively. There has not been any published research on the role of resolution in either direction on the accuracy of flow measurement. The work below investigates the effectiveness of flow measurement in a SCI by performing a case study in which point velocity measurements were extracted from a physical plant and then used to calculate a series of reference flow distributions. These distributions were then used to perform sensitivity studies on the relation between the number of CM and the accuracy to which the flow rate was predicted. The following research uncovered that a minimum of 795 plants contain SCI, a quantity which represents roughly 12% of total domestic hydropower capacity. In regards to measurement accuracy, it was determined that accuracy ceases to increase considerably due to strict increases in vertical resolution beyond the application of 49 transects. Moreover the research uncovered that the application of 5 CM (when applied at 49 vertical transects) resulted in an average accuracy of 95.6% and the application of additional sensors resulted in a linear increase in accuracy up to 17 CM which had an average accuracy of 98.5%. Beyond 17 CM incremental increases in accuracy due to the addition of CM was found decrease exponentially. Future work that will be performed in this area will investigate the use of computational fluid dynamics to acquire a broader range of flow fields within SCI.

Flow Measurement↗

Stream-reach Identification for New Run-of-River Hydropower Development through a Merit Matrix Based Geospatial Algorithm

Even after a century of development, the total hydropower potential from undeveloped rivers is still considered to be abundant in the United States. However, unlike evaluating hydropower potential at existing hydropower plants or non-powered dams, locating a feasible new hydropower plant involves many unknowns, and hence the total undeveloped potential is harder to quantify. In light of the rapid development of multiple national geospatial datasets for topography, hydrology, and environmental characteristics, a merit matrix based geospatial algorithm is proposed to help identify possible hydropower stream-reaches for future development. These hydropower stream-reaches sections of natural streams with suitable head, flow, and slope for possible future development are identified and compared using three different scenarios. A case study was conducted in the Alabama-Coosa-Tallapoosa (ACT) and Apalachicola-Chattahoochee-Flint (ACF) hydrologic subregions. It was found that a merit matrix based algorithm, which is based on the product of hydraulic head, annual mean flow, and average channel slope, can help effectively identify stream-reaches with high power density and small surface inundation. The identified stream-reaches can then be efficiently evaluated for their potential environmental impact, land development cost, and other competing water usage in detailed feasibility studies . Given that the selected datasets are available nationally (at least within the conterminous US), the proposed methodology will have wide applicability across the country.

Pasha, M. Fayzul K.↗