The Bonneville Power Administration is an American federal agency operating in the Pacific Northwest. BPA was created by an act of Congress in 1937 to market electric power from the Bonneville Dam located on the Columbia River and to construct facilities necessary to transmit that power. Congress has since designated Bonneville to be the marketing agent for power from all of the federally owned hydroelectric projects in the Pacific Northwest. Bonneville is one of four regional Federal power marketing agencies within the U.S. Department of Energy . Wikipedia.
News Article | July 24, 2015
News Article | April 28, 2015
News Article | November 2, 2015
Seattle-based startup 1Energy has been a small but spirited contender in the emerging energy storage management software field, with a decided emphasis on an open-standards-based approach to linking batteries and other grid-connected assets at scale. For the past few years, it has deployed its software in the form of an intelligent controller, integrating with individual battery-inverter systems in a showcase set of Pacific Northwest utility pilot projects, while promising a fleet management platform to tie them all together. Last month's launch of 1Energy's Distributed Energy Resource Optimizer, or DERO, platform marks the delivery on that promise, with some extras to boot. First, 1Energy disclosed a set of partners that have been using its software for a broad set of applications, from AES Energy Storage to Duke Energy. Second, it has expanded the range of distributed energy resources (DERs) it can manage beyond batteries. Snohomish Public Utility District is the first customer for 1Energy’s DERO platform, which makes sense, since it’s the first utility to deploy multiple batteries, of different chemistries and serving different needs, using the startup’s software. “We really believe that, while DERO is initially managing a fleet of storage assets for Snohomish, it will manage not just storage, but other distributed resources like solar in the near future,” Rogers Weed, 1Energy’s vice president of product management, said in a Thursday interview. In fact, “the second customer for DERO wants us to use it to manage more than storage,” he said. While he didn’t name the customer, he did say that “they’re interested in DERO optimizing grid-connected solar [and] behind-the-meter solar.” That makes 1Energy’s new platform less of a standard energy storage management system, he said, and more of a distributed energy resource management system, or DERMS, in GTM Research parlance. In fact, “we think it’s a better DERMS product, first of all, because it relies on local intelligence with local assets, and then focuses on the fleet-level stuff.” The local level comes from 1Energy’s intelligent controller software, which runs battery systems being deployed by home-state partners Snohomish PUD and Puget Sound Energy. It’s installed on a server at the site, and keeps the entire thing running, according to a set of operating parameters that can be preset to engage when certain local grid conditions are met, or when ordered to do so by central control. DERO, by contrast, works at the fleet or utility level, with each individual end-node as a partner, so to speak. “It integrates with transmission and operations platforms and energy-trading platforms, and it will execute and optimize fleet-level applications,” he said. “We’re delivering optimization, not just aggregation -- and we started with storage, the super-set asset,” he said. That’s not just another way to say "holy grail," by the way. It’s referring to the full-spectrum value available to storage systems that can switch from charge to discharge, and from active to reactive power, at the drop of a hat. That’s only if the software that’s running them is flexible and reliable enough to take advantage of the money-making reasons to do so, of course. In the case of Snohomish PUD, 1Energy will be putting together a stack of imperatives, ranging from responses to local grid conditions to energy market imbalances driven by changes in wind farm production a thousand miles away. Snohomish PUD’s batteries -- two 1.5-megawatt, 500-kilowatt-hour lithium-ion batteries from LG Chem and Mitsubishi-Yuasa, and a 2-megawatt vanadium redox flow battery system from UniEnergy Technologies -- have as their first priority relieving any local distribution grid constraints that could overload circuits or transformers, as part of their value in delaying the replacement of these assets. That’s managed by local control, which can also override commands that would push the system into unsafe operating zones and the like. With DERO, Snohomish PUD will be adding a list of value propositions to each system’s stack. “Energy arbitrage will be the default plan,” with each system taking a five-day forecast of expected prices to charge when they’re low and discharge when they’re high. But higher-value services await, starting with the Bonneville Power Administration (BPA), the federal agency that runs the region’s hydro-powered transmission network. “BPA will be sending them transmission constraint signals, along with a value for alleviating that for BPA. Snohomish will look at that every six hours ahead” to adjust its batteries’ charge-discharge plans. More pressing still is the utility’s exposure to the spot power market, driven by the variable nature of its share of wind power. “You only have a few hours' notice before you forecast that wind is going to under-deliver,” and the cost of making up for the difference depends on hard-to-predict spot prices that have to be integrated into the calculation. Finally, Snohomish has to pay BPA “energy-imbalance mitigation” costs when its hourly forecast of its energy needs falls out of a certain band of tolerance, in order to put a price on failing to meet one’s grid commitments. “The problem is, you don’t really know how you’re going to do on your hourly forecast until you’re into the hour itself,” he said, since the variable being measured is how reality is failing to perform to the best predictive models. That requires five- to ten-minute projections of whether the utility is going to end the hour in the penalty zone, what that penalty costs versus doing whatever else the battery had stacked up to do that hour, and deciding whether or not to act. All in all, it’s a complicated set of decisions being made at the fleet level. At the same time, these decisions rely on each distributed energy asset actually being on-line when it’s needed, and ready to respond to dispatch. It also relies on knowing each battery’s cost of charging and discharging at different power densities at different rates, and how well it stacks up to every other battery in the fleet. All of this complexity would be better managed through common standards, rather than by the one-off systems-integration methods used in most of today’s energy storage deployments. 1Energy has played a central role in one such standards effort, dubbed the Modular Energy Storage Architecture (MESA), which includes long-time partners such as Alstom Grid, Parker Hannifin and Pacific Northwest National Laboratory, and more recently, big utility Duke Energy. Duke also used 1Energy’s software in its 1.5-megawatt, 300-kilowatt-hour Rankin battery project, according to the project list the startup released last week. The project tested different approaches and algorithms for using batteries to balance the effects of lots of solar PV at the end of a stressed-out distribution grid circuit, indicating how solar might link up with storage for 1Energy’s mysterious DERO customer number two. 1Energy’s list of deployments also includes AES Energy Storage’s 20-megawatt, 5-megawatt-hour Cochrane project in Chile, which helps remote desert mining operations manage their extreme power needs. AES Energy Storage has built its own software to manage the energy-market-facing aspects of its hundreds of megawatts of grid battery systems, but it’s been partnering with project developers and other software vendors to manage other aspects of their operations. These projects, its home-state deployments, and a newly announced 1.5-megawatt, 3-megawatt-hour project for Texas utility Austin Energy using Tesla Energy's batteries, brings the startup’s total list to some 20 megawatts and 28 megawatt-hours of batteries that plan to use its software. It’s a figure that helps put 1Energy into clearer ranking with such energy storage management software heavyweights such as Younicos, Greensmith, or NEC Energy Solutions. Meanwhile, 1Energy isn’t alone in seeking to create software that can standardize how energy storage systems interact with the broader IT infrastructure. Rival startup Geli is working on similar concepts, although Geli tends to focus on building operations as its key user, while 1Energy has focused on utilities as its customers.
News Article | May 18, 2015
RESTON, Va.--(BUSINESS WIRE)--The Utility Variable-Generation Integration Group (UVIG) has released an updated version of a summary table detailing markets and market rules for variable generation (VG) in North America. Capturing the state of markets as of March 2015, the document is the third update of a table first issued in December 2004. This year, solar energy was added to the table in recognition of the significant growth in installed solar power capacity. The table was also reorganized and streamlined to improve readability and to enable comparison and contrast between the entities profiled in the table. UVIG appreciates the financial and technical support of the Lawrence Berkley National Laboratory (LBNL) and the U.S. Department of Energy’s Office of Electric Delivery and Reliability. Some of the major findings are that every Regional Transmission Organization, Independent System Operator (ISO), Transmission System Operator (TSO) and utility in North America that is integrating a large amount of wind power is using wind plant output forecasts to improve the reliable and economic operation of their system; solar power forecasts are not as prevalent, but some of these same entities are experimenting with solar power forecasting; wind generation is increasingly being required to follow dispatch signals at short time intervals; and a small but growing number of requirements for variable generation to provide or be capable of providing different types of grid support services, such as frequency response and inertial response, are being seen. The document was compiled by Kevin Porter and Kevin Starr of Exeter Associates with UVIG participation and LBNL support, based on a survey covering PJM Interconnection, the New York Independent System Operator, ISO New England, the Ontario Independent System Operator, Midwest ISO, Southwest Power Pool, the Electric Reliability Council of Texas, California Independent System Operator, Alberta Electric System Operator, Bonneville Power Administration, Public Service Company of Colorado (a subsidiary of Xcel Energy), Arizona Public Service, PacifiCorp, and Puget Sound Electric. The table presents responses to a number of questions, with the more important ones noted below: The document can be downloaded at http://uvig.org/resources/ Formerly known as the Utility Wind Integration Group, the Utility Variable-Generation Integration Group (UVIG) was established in 1989 to provide a forum for the critical analysis of wind technology for utility applications and to serve as a source of credible information on the status of wind technology and deployment. The group’s current mission is to accelerate the development and application of good engineering and operational practices supporting the appropriate integration of wind and solar power for utility applications through the coordinated efforts and actions of its members, in collaboration with the U.S. Department of Energy, its National Renewable Energy Laboratory and utility research organizations. UVIG is an international organization with over 180 members from the United States, Canada, Europe, and Asia, including investor-owned, public power, and rural electric cooperative utilities; transmission system operators, corporate members; and associate member government and academic organizations.
Organic particulate matter formation at varying relative humidity using surrogate secondary and primary organic compounds with activity corrections in the condensed phase obtained using a method based on the Wilson equation
Chang E.I.,Bonneville Power Administration |
Pankow J.F.,Portland State University
Atmospheric Chemistry and Physics | Year: 2010
Secondary organic aerosol (SOA) formation in the atmosphere is currently often modeled using a multiple lumped "two-product" (N·2p) approach. The N·2p approach neglects: 1) variation of activity coefficient (¶i) values and mean molecular weight MW̄in the particulate matter (PM) phase; 2) water uptake into the PM; and 3) the possibility of phase separation in the PM. This study considers these effects by adopting an (N·2p)¶̄ approach (θ is a phase index). Specific chemical structures are assigned to 25 lumped SOA compounds and to 15 representative primary organic aerosol (POA) compounds to allow calculation of ¶ and MW̄values. The SOA structure assignments are based on chamber-derived 2p gas/particle partition coefficient values coupled with known effects of structure on vapor pressure pL̊i (atm). To facilitate adoption of the (N·2p)¶pMW̄θ approach in large-scale models, this study also develops CP-Wilson.1 (Chang-Pankow-Wilson.1), a group-contribution ¶-prediction method that is more computationally economical than the UNIFAC model of Fredenslund et al. (1975). Group parameter values required by CP-Wilson.1 are obtained by fitting ¶ values to predictions from UNIFAC. The (N·2p)¶pMW̄θ approach is applied (using CP-Wilson.1) to several real Î±-pinene/O3 chamber cases for high reacted hydrocarbon levels (δHC≈400 to 1000 μgm-3) when relative humidity (RH) ≈50%. Good agreement between the chamber and predicted results is obtained using both the (N·2p)¶MW̄θ̧ and N·2p approaches, indicating relatively small water effects under these conditions. However, for a hypothetical α-pinene/O3 case at ΔHC=30 μgm-3 and RH=50%, the (N·2p)¶MW̄θ̧ approach predicts that water uptake will lead to an organic PM level that is more double that predicted by the N·2p approach. Adoption of the (N·2p)¶MW̄θ approach using reasonable lumped structures for SOA and POA compounds is recommended for ambient PM modeling. © 2010 Author(s).