Browsing by Subject "Grid"

Now showing 1 - 9 of 9

Application of discontinuous schemes to numerical reservoir simulation
(1987) Brantferger, Kenneth Mark, 1962-; Sepehrnoori, Kamy, 1951-
The numerical modeling of hyperbolic conservation laws is presented using discontinuous schemes based upon exploiting knowledge of the flow entering and leaving a grid block. The solutions are constructed by piecing together local exact solutions taken from Riemann problems. In particular, two schemes are discussed, 1) the uniform sampling method initiated by Glimm and 2) the higher-order Godunov method. The methods are introduced using the convection equation and Buckley-Leverett problem to illustrate their implementation. After the basic concepts have been discussed, the methods are extended to three successively more complex problems involving a spatially dependent flux function describing the flow of acid in a pore throat, a quasilinear hyperbolic equation with a source term implemented in a sandstone matrix acidizing simulator, and a nonstrictly hyperbolic system of conservation laws defining the three phase flow of oil, gas and water in a porous media. For the final problem, the uniform sampling method is applied to a two-dimensional waterflood problem. The example calculations focus on the use of operator splitting, grid orientation effects, and mesh refinement
Consumer-Data Approach to Assess the Effect of Residential Grid-Tied Photovoltaic Systems and Electric Vehicles on Distribution Transformers
(IEEE, 2014-06) Uriarte, F. M.; Toliyat, A.; Kwasinski, A.; Hebner, R. E.
The authors examine the impact of residential photovoltaic arrays and electric vehicles on distribution transformers by using 3-D surface and 2-D filled contour plots. These visualizations, somewhat unorthodox to power distribution analysis, elucidate the impact of hundreds of assets on distribution transformers on a single view. The visualizations are created with a smart grid computer model that accepts residential electrical recordings in one minute intervals. An analysis of simulation results shows that the electrical footprint experienced by a residential community and its distribution transformers stems from photovoltaic arrays rather than from electric vehicles. Additionally, the results indicate the existing distribution assets may be ready to support the proliferation of photovoltaic arrays and electric vehicles, a common concern across utilities in the United States.
A dynamic model-based estimate of the potential value of a vanadium redox flow battery for energy arbitrage and frequency regulation in Texas
(2012-08) Fares, Robert Leo; Webber, Michael E., 1971-; Meyers, Jeremy P.
Large-scale electrochemical energy storage is a technology that is uniquely suited to integrate intermittent renewable energy sources with the electric grid on a large scale. Grid-based energy storage also has the potential to reduce costs associated with periods of peak electric demand. For these reasons, this work describes the potential applications for grid-based energy storage, and then reviews large-scale energy storage technology innovations since the development of the lead-acid battery. The potential value of grid-based battery energy storage is discussed in the context of restructured electricity markets; then, a dynamic model-based economic optimization routine is developed to gauge the potential value of a vanadium redox flow battery (VRFB) operating for wholesale energy arbitrage and frequency regulation in Texas. Based on this analysis, the relative value of a VRFB in various regions of Texas for energy arbitrage and frequency regulation is examined. It is shown that frequency regulation is an appealing application for a grid-based VRFB, with a VRFB utilized for frequency regulation service in Texas potentially worth approximately $1500/kW. Finally, the effect of a VRFB’s characteristics on its value for frequency regulation and energy arbitrage are compared, and the operational insight developed in this work is used to glean how policies to integrate a large-scale energy storage with the electricity market might be crafted.
Impact of high renewable penetration on wholesale electricity prices and grid reliability in the ERCOT energy-only market
(2022-05-09) Sears-Greer, Daniel; King, Carey Wayne, 1974-; Zarnikau, Jay; Butler, John C; Cole, Wesley
The ever-growing interest in climate change prevention continues to promote the growth of renewable sources of electricity in our country. Texas is on the forefront of that growth with the second highest penetration of renewable resources of any state in the U.S. It is therefore imperative to understand how this growth will impact a market that was not originally designed to handle significant renewable penetration. Because ERCOT is an energy-only market, where prices are largely based on the short run marginal cost of a generator, there is a risk that, as renewable penetration increases, and low marginal costs technology are more frequently setting the wholesale electricity price, generators may not earn enough revenue to incentivize investment in new capacity to maintain grid reliability. Using a multi-model analysis, I investigate the impact of increasing renewable penetration, and whether those renewables are dispatchable versus variable, on electricity prices, capacity mix, and grid reliability. I also look at how reserve requirements and price caps further impact these results. I found that, at renewable penetrations greater than 60%, we start to see an increase in the number hours with prices at or near $0/MWh. 6 Additionally, at this penetration level, we start to see peak prices, up to $50,000/MWh in the 100% renewable scenarios. I then implemented a series of price caps at $4,500; $9,000; and $20,000/MWh, and found that, while a price cap does suppress peak prices, it also results in dropped load due to prices not being high enough to compensate new capacity to serve that load. Access to dispatchable technologies helps mitigate these issues by providing a resource with higher short run marginal costs that can be turned up or down when needed. Based on these findings, Texas and the PUCT should consider new mechanisms to compensate assets for providing long term reliability services to help encourage market participants to play a larger role in the security of the Texas grid.
Improving electrical power grid resiliency and optimizing post-storm recovery using LiDAR and machine learning
(2020-02-03) Davis, Michael Andrew, II; Bajaj, Chandrajit
While many external factors influence resiliency, weather remains the single greatest threat to the electric power grid, and the impacts caused by significant storms can be long-lasting and widespread. When damage occurs, it is very costly to identify due to the vast size of electrical transmission and distribution circuits, which can span hundreds of miles. Pinpointing a failure in a circuit requires the expensive process of dispatching human teams to “walk the line” and physically inspect the circuit to identify damage. It is proposed that this problem can be optimized through automation, by leveraging flight vehicles, light detection and ranging (LiDAR) technology, and machine learning. The goals for this project are: 1) Investigate the feasibility of, and problems associated with, developing a system to remotely inspect electrical power transmission and distribution infrastructure with lidar. 2) Investigate the feasibility of developing an automated system to classify and detect damage to terrestrial transmission and distribution assets with lidar and artificial intelligence. 3) Develop a proof of concept of such a system, including a simulation of real-time lidar data collection and damage assessment
Modeling Gas Condensate Reservoirs and Development of a New Hybrid Well Model
(2003-05) Sharma, Ravi; Pope, Gary A.; Sepehrnoori, Kamy
Gas condensate reservoirs have been receiving a lot of attention in the past few years. Main reasons for the growing interest is the increasing demand for natural gas as an energy source and the discovery of many new gas fields every year. Natural gas is also cheaper and has environmental advantages over other sources of energy such as coal and oil. It is the fastest-growing primary energy source in the world. Most of the gas reserves have severe temperature and pressure conditions which increases the cost and risk involved in the development of the fields. Gas condensate reservoirs exhibit even more complex behavior because of the retrograde condensation. During the depletion of gas condensate reservoirs, retrograde condensation occurs when the bottom hole pressure falls below the dew point pressure. The productivity of many gas condensate wells is reduced by the formation of a condensate bank in the near well region. Formation of the condensate bank reduces the relative permeability to gas which leads to the loss of productivity. One important step in the study of gas condensate fields is the phase behavior modeling of the gas condensate mixture. This is essential for accurately predicting the amount of liquid dropout and phase equilibrium during a compositional simulation. To study the gas condensate fields, it is essential to capture the near well effects such as condensate bank formation, changes in gas relative permeability at high trapping number and high velocity phenomena such as non-Darcy flow. Fine grid simulation is necessary to have adequate resolution in these regions of intense activity. However, in the conventional fine grid method, a large number of superfluous cells are generated. This is because the grid lines cannot terminate inside the well grid block and are extended to the model boundaries. Increase in the number of cells in the model also increases the memory requirement and the computational time. This in turn limits the size of the model that can be simulated. One alternative to the conventional fine grid simulation is local grid refinement. In local grid refinement, only the area of interest is refined and rest of the field is modeled with coarse grids. Local grid refinement has been a subject of study for many years and there have been great advances in this field. But local grid refinement has its limitations, as it is much more complex and difficult to implement.
Residential PVs and EVs: Before and After
(0000-00-00) Uriarte, F. M.; Hebner, R. E.
Power distribution systems are experiencing higher load levels, unbalanced distributed generation, a wealth of load diversity, and more uncorrelated events than ever before. To provide quantitative information regarding the changes, this paper contrasts the electrical state of the largest Smart Grid residential community in Austin, Texas before and after the proliferation of its PVs and EVs. This community is the research focus of the authors, local utilities, and many others attempting to hinder detrimental consequences of the uncontrolled, fast proliferation of residential assets on the grid. The authors use surface and filled contour plots to show new electrical footprints, and show its impact on transformer utilization, feeder demand, current unbalance, and distribution losses.
Solar in the Galapagos Islands: A Quantitative Analysis
(2023-04) Parker, Olivia
This paper explores the current state of the grid and the problems facing the implementation of solar energy through the lens of the Galapagos Islands. The first part of this paper will cover the various problems associated with solar installation: including installation and maintenance, storage, public attitude, and cost. In addition, it will lay out the strengths of the region in the transition to green energy, as well as previous precedents that can be used in formulating a plan for energy transition. In Part II, potential solutions are presented, including publicly funded and public program scenarios with tourist fee funding, as well as a comparison of the three scenarios. The paper also addresses installation and maintenance solutions and various storage options, including alternative storage solutions, and presents an overall storage recommendation. Finally, the paper concludes with final thoughts on the feasibility of solar energy implementation in the studied areas.
Technoeconomic modeling of nuclear hybrid energy systems with heat storage
(2020-12-04) Mann, William Neal; Landsberger, Sheldon; Webber, Michael E., 1971-; Forsberg, Charles W; Leibowicz, Benjamin D
This work seeks to quantify the technical and economic feasibility of integrating nuclear power plants with renewable energy generation and heat storage. A variety of technoeconomic models were developed for this purpose, including cash-flow based project financing models; capital cost scaling models for heat storage systems; thermodynamic models of heat storage charging, discharging, and standing losses; an electric grid unit commitment and economic dispatch model for modeling prices; and statistical models of load, wind, and solar PV at various locations for Monte Carlo market analyses. Based on the assumptions of recent market conditions in three major electricity markets in the United States, all systems evaluated would not be economically viable. Average electricity prices varied from around $25/MWh (ERCOT) to $42/MWh (Mid-Columbia) and $54/MWh (PJM). For integrating a new nuclear power plant with wind and hydrogen production, the very high capital costs of the nuclear plant led to multi-decade payback times, and the assumed cost of hydrogen at $2.50/kg was too low to justify the capital investment in the associated chemical plant. For the heat storage systems evaluated, power-related capital costs varied $1,200–2,300/kW, and energy-related capital costs ranged $36–140/kWh. Increasing the size of the power block had significant positive effects on net revenue, while increasing the size of the energy storage reservoir was generally not helpful beyond five hours of storage time. However, when considering the entire cash flow of a system beyond its operating revenue, no heat storage system had enough free cash flow to break even in the markets and scenarios analyzed, with the smallest system having the best overall economic performance. In contrast to other studies where only a single representative year of load and weather data is used, this work showed that the historical variability of those time series can lead to significant spreads in the distributions of results. Selecting a “lucky” year could yield revenue estimates three times greater than the median. However, the results were more sensitive to the capital cost assumptions than to the weather year. Integrating renewable energy generation and/or heat storage with nuclear power plants is unlikely to be economically feasible in the near term without significant changes in energy markets, significant decreases in capital costs of power turbines, or significant increases in development or operating subsidies for these system concepts.