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Forecasting Tools for Run-of-River Hydroelectric Systems
Lead Companies
University of Washington
Lead Researcher (s)
- Nam Song
With an increasing interest in constructing new run-of-the-river (ROR) hydroelectric generation over the more traditional reservoir-based hydroelectric systems, there is an increasing operational challenge due to the volatility of streamflow. The Snohomish County Public Utilities District (SnoPUD) has recently invested in the construction and operation of 3 new run-of-the-river projects in Northwestern Washington along Calligan Creek, Hancock Creek, and Youngs Creek. In order to effectively plan generation dispatch, SnoPUD has expressed interest in the development of an accurate forecasting tool to predict the generation capacity for these ROR systems. The following research project aims to use statistical learning models, namely Hidden Markov Models (HMMs), to predict day-ahead generation capacities for the aforementioned ROR systems. These models are constructed using 12 years of historical streamflow data collected at the intake sites and precipitation data recorded at the National Oceanic and Atmospheric Administration (NOAA) Alpine Meadows station. Four methods of constructing the models are studied for their forecast accuracies, and are compared with the persistence model. Despite using only one set of observable variables, the HMMs are shown to have slight improvements in accuracy over the persistence model approach, which shows great optimism for future work.
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
complete
Completion Date
2018
- Conventional Hydro
Hydropower as a Signal Processor [HydroWIRES]
Lead Companies
Oak Ridge National Laboratory (ORNL)
Lead Researcher (s)
- Srijib Mukherjee (mukherjeesk@ornl.gov)
The Hydropower Signal Processor project will develop a data-driven methodology for classifying and comparing the water-to-energy and energy-to-water transfer functions that succinctly characterize the essential regulating and converting behavior of hydropower facilities. If one considers the time series of flow (and the specific energy conveyed by that flow) in a river as the signal, insight may be gained by examining how this inflow signal, with its myriad and periodic fluctuations, is lagged, filtered, and otherwise converted into an outflow signal by a hydropower facility, with a corresponding electric power output signal. By taking advantage of analytics from the signal processing and information flow domains, this effort will develop an efficient method for encapsulating the complex and facility-specific behavior of many hydropower facilities. The hypothesis of the project is that the transfer functions of facilities, derived from time series data, in the same archetype (run-of-river, ponding storage, and long-term storage for example) will exhibit similarities and features that can be used to classify facilities and model facilities more coherently and consistently in river and power system models, and understand which hydropower project archetypes warrant more detailed study and effort to improve their representation in models. These hydropower facility transfer functions and their facility-specific parameters derived from historical time series data will ultimately be intuitively and quantitatively linkable to hydropower parameters production cost modeling (e.g., modes of operation for hydropower facilities) and water balance modeling, routing, and scheduling. This research and proposed methodology is not intended to create yet another model for how hydropower participates in power systems; it will provide an analysis tool, lexicon, and set of concepts that enable river system and power system decision-makers and modelers to mutually convey the functionality and value of hydropower to electric power systems.
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
ongoing
Completion Date
TBD
- Conventional Hydro
Hydropower Storage Capacity Dataset [HydroWIRES]
Lead Companies
Oak Ridge National Laboratory (ORNL)
Lead Researcher (s)
- Carly Hansen, hansench@ornl.gov
Accurate descriptions of existing storage capabilities and constraints of conventional hydropower projects are essential for understanding how existing conventional hydropower reservoirs can support grid reliability and transitioning energy sources (i.e., intermittent sources that require substantial storage). This information helps inform flexible plant operation and potential management strategies. Coarse estimates of energy storage can be derived from reservoir-specific volume and elevation characteristics and simple power plant capacities; more realistic and finer-scale estimates must also account for hydrologic variability and hydraulic and operational constraints. This project catalogs and define types of storage (with increasing levels of detail and complexity) and translate these types of storage into MWh and duration of energy generation. Methodologies to estimate fundamental characteristics of reservoirs and their storage capacity and duration will be developed and applied for across the fleet of conventional US hydropower reservoirs, which will enable more comprehensive evaluations of storage and flexibility for a broader suite of hydropower resources.
Technology Application
Conventional Hydro
Research Category
Technology
Research Sub-Category
Hydraulic Forecasting
Status
ongoing
Completion Date
TBD
- Conventional Hydro
Hydropower Training Project
Lead Companies
CEATI International
Lead Researcher (s)
- #0431
4 modules developed so far: Module 1 – General Features and Role of Hydropower Projects and Systems; Module 2 – Load-Resource Analysis; Module 3 – Operating Objectives and Principles for Water Management; Module 4 – Hydrologic Data
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
complete
Completion Date
2020
- Conventional Hydro
Identification of spatial and topographical metrics for micro hydropower applications in irrigation infrastructure
Lead Companies
Colorado State University
Lead Researcher (s)
- Brian Campbell
A recent agreement between the Federal Energy Regulatory Commission and the State of Colorado seeks to streamline regulatory review of small, low-head hydropower (micro hydropower) projects located in constrained waterways, (Governor’s Energy Office, 2010). This regulatory change will likely encourage the development of micro hydropower projects, primarily as upgrades to existing infrastructure. Previous studies of low-head hydropower projects have estimated the combined capacity of micro hydro projects in Colorado between 664 MW to 5,003 MW (Connor, A.M., et al. 1998; Hall, D.G., et al. 2004, 2006). However, these studies did not include existing hydraulic structures in irrigation canals as possible hydropower sites. A Colorado Department of Agriculture study (Applegate Group, 2011) identified existing infrastructure categories for low head hydropower development in irrigation systems, which included diversion structures, line chutes, vertical drops, pipelines, check structures and reservoir outlets. However, an accurate assessment of hydropower capacity from existing infrastructures could not be determined due to low survey responses from irrigation water districts. The current study represents the first step in a comprehensive field study to quantify the type and quantity of irrigation infrastructure for potential upgrade to support micro hydropower production. Field surveys were conducted at approximately 230 sites in 6 of Colorado’s 7 hydrographic divisions at existing hydraulic control structures. The United States Bureau of Reclamation contributed approximately 330 additional sample sites from the 17 western states. The work presented here describes a novel method of identifying geospatial metrics to support an estimation of total site count and resource availability of potential micro hydropower. The proposed technique is general in nature and could be utilized to assess micro hydropower resources in any region.
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
complete
Completion Date
2012
- Conventional Hydro
Identifying Sources of Uncertainy in Flood Frequency Analysis
Lead Companies
Bureau of Reclamation
Lead Researcher (s)
- Amanda Stone
We postulate that true FFA uncertainty may be larger than currently appreciated and that different components of the modeling chain such as model choice, parameter values or initial conditions impact FFAs by different amounts. We propose to explore key components of the modeling chain: 1) expanding from one model to a multi-model ensemble, 2) varying model parameters, and 3) varying initial conditions for each model structure. Furthermore, uncertainty and sensitivity characteristics likely vary across hydroclimatic regime. To address this hypothesis, we will use continuous ensemble simulations across model structures with parameter perturbations to drive a stochastic event simulation framework to reveal true FFA uncertainty and understand sensitivities across several case-study basins spanning the hydroloclimatology of the 17 western states.
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
ongoing
Completion Date
2020
- Conventional Hydro
Improving distributed hydrologic models using multiscale thermal infrared, near infrared, and visible imagery from sUAS and satellite-based sensors
Lead Companies
Bureau of Reclamation
Lead Researcher (s)
- Lindsay Bearup
Can the use of sUAS combined with satellite data effectively improve calibration of distributed hydrologic models? Previous work has focused on developing techniques to control variables such as evapotranspiration using satellite remote sensing. The critical component is the equilibrium surface temperature which is normally calibrated using thermal remote sensing data from MODIS (MODerate resolution Imaging Spectroradiometer) or AATSR (Advanced Along-Track Scanning Radiometer) which have a 1 km ground sample distance. This study seeks to improve thermal calibration techniques using much finer-resolution thermal measurements derived from a sUAS. The use of a sUAS will allow for the collection of high resolution imagery (< 1 cm – 1 m or more depending upon research goals) of landscape components, repeatedly and during desired time frames. Thermal data from a sUAS will provide much greater spatial and temporal resolution than satellite-based measurements, and will be obtained at a relatively low cost. This study seeks to determine the added benefit of improved spatial and temporal resolution of observations, evaluated through the existing model calibration framework of a sub-daily, sub-kilometer hydrologic model with complex terrain and vegetation, typical of many mountain headwaters systems experiencing change in the West.
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
ongoing
Completion Date
2020
- Conventional Hydro
Improving the robustness of southwestern US water supply forecasting
Lead Companies
Bureau of Reclamation
Lead Researcher (s)
- Dagmar Llewellyn
This research will address the overarching question of whether observed past climate trends have induced sufficient non-stationarity in climate and hydrologic systems in the western US to alter their predictability, which has consequences for water management. Key question include the following: When and where in the western US are hydroclimate trends and/or decadal variability leading to systematic biases in statistical and model-based waters supply forecasts? What practical adjustments can be made to current forecasting approaches to make seasonal water supply forecasts robust in the face of such phenomena? In particular, can hydrologic sensitivities to temperature be accounted for by leveraging operational temperature forecasts as streamflow predictors or weighting factors in conventional seasonal forecasting procedures? What are the marginal benefits of improvements in seasonal streamflow predictions for water management in the Upper Rio Grande River basin?
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
ongoing
Completion Date
2021
- Conventional Hydro
Improving volume forecasting tools for snow dominated basins
Lead Companies
Bureau of Reclamation
Lead Researcher (s)
- Joel Fenolio
In 2018, the GP Region developed the PyCast Software application to address some of the aforementioned issues. The software provides an interactive tool that allows users to search-for and download relevant hydrologic datasets and develop well performing statistical runoff forecast equations using a variety of regression techniques. The software uses a set of novel search algorithms to find skillful and predictive forecast equations using from the complete set of hydrologic data, and allows users to analyze groups of forecast equations for similarities and outliers. This project seeks to: (a) evaluate the capabilities of the PyCast software, (b) develop additional functionality for the program, and (c) determine how remote sensing products developed in other S&T projects can improve forecast skill. The software will be evaluated by generating hindcasts in GP and PN basins, as well as conducting real-time forecasting during the 2019, 2020, and 2021 seasons. Developers from the PN and GP regions will continue to develop the software, train users, gather user input and suggestions, and add additional features and compatibility. New snow water equivalent (SWE) and snow covered area datasets proposed under two concurrent GP and MP S&T projects will be incorporated into the software and the resulting forecasts will be compared to traditional snow products from the NRCS.
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
ongoing
Completion Date
2021
- Conventional Hydro
Inflow Forecast Competition
Lead Companies
CEATI International
Lead Researcher (s)
- #0434
In order to better understand recent developmnets with AI related to forecasting water, this project will perform a yearlong competition between five forecast methods, with a live website for members to view the verification results on a daily basis.
Technology Application
Conventional Hydro
Research Category
Interconnect Integration and Markets
Research Sub-Category
Hydraulic Forecasting
Status
ongoing
Completion Date
Expected 2022
Don’t see your waterpower research?
Have questions about WaRP?
Contact Marla Barnes at: marla@hydro.org