Ascend Analytics is proud to announce that it has achieved “best practices” through an Evergreen Economics Report. In January 2014, the State of Montana Public Service Commission engaged Evergreen Economics, a third party consulting firm, to assist Commission staff in reviewing analysis conducted by NorthWestern Energy (NWE) and Ascend Analytics in support of NWE’s $900 million bid to acquire 11 hydroelectric generation assets from PPL Montana. Through a systematic and thorough evaluation of Ascend’s software models and analysis, Evergreen Economics recognized Ascend’s models’ consistency and completeness with industry “best practices.” It is highly unusual for a third party to give high praise in an evaluation, therefore Ascend is pleased with the outcome of this assessment. Evergreen’s report further solidifies Ascend as a leader in portfolio management and long-term resource planning. Ascend continues to stand apart from the competition by offering industry recognized “best practice” models and analysis, which enable power producers to better evaluate their portfolios, assess their risks, and maximize their revenues.
On July 9, 2014, Gary Dorris, the President of Ascend Analytics, delivered expert testimony on behalf of NorthWestern Energy during a hearing held by the Montana Public Service Commission regarding NorthWestern Energy’s bid to purchase $900 million of hydroelectric assets from PPL Montana. Ascend’s team, and its PowerSimm software, consulted and modeled the acquisition and potential impacts to NorthWestern Energy’s ratepayers. Ascend Analytics concluded that NorthWestern Energy’s proposed purchase of 11 hydroelectric dams will initially increase rates, but these rates will ultimately become more stable and reliable for consumers according to a longer-term forecast. Dr. Dorris handled cross examination with great deftness, furthering the economic merit of the hydro asset acquisition.
Ascend Analytics to present Best Practices in Risk Based Resource Planning
October 20-21, 2014
This course builds on the success of Ascend’s new risk based modeling approach for resource planning that has been utilized in regulatory filings in MT and CA.
Dr. Gary Dorris our President at Ascend Analytics, will be presenting at the upcoming EUCI course to speak on the Best Practices in Risk Based Resource Planning.
Dr. Dorris has been a pioneer of innovative solutions for energy planning and risk. Gary has introduced utilities to new solutions to model and analyze planning portfolios. His analytic innovations and expertise are sought by industry leaders including expert testimony in some of the most prominent resource planning and risk management proceedings in the country. His company’s software solutions are used by 3 of the top 5 utilities in America and more COOPs and municipalities.
For more information about this upcoming conference: Best Practices in Risk Based Resource Planning
That pile of coal in the generation yard is more than the sum of its tons. Two lumps of coal in the same shovel load might present two points on a graph of constantly fluctuating uncertainty.
Coal piles loom as data-dense aggregates of source, grade, contract pricing, spot price, emission qualities, projected dispatch load and storage cost. But while the complexity in that pile of coal could seem overwhelming, it’s not immeasurable. Ascend Analytics PowerSimm will take that pile apart lump by lump and reassemble it in a model that gives utility managers a view of supply, cost, emissions, hedge pricing and projected dispatch. It’s a view they are not going to find anywhere else.
“Nobody else can do this,” says Ascend Energy Analyst Trevor Rehm, explaining that competing software fails to project dispatch price accurately because the programs can’t dissect the coal pile the way PowerSimm does.
“We are able to deliver two different train loads of coal from different places at two different prices, blend the fuels, blend the emissions and price the whole thing optimized to dispatch to maximize profits.” – Trevor Rehm
The competitors’ models also lack Ascend’s sophisticated forward price simulations that include the market’s current liquid forward strip correlated to historical data and calculated volatilities. Two trainloads would be a simple exercise. The PowerSimm coal inventory module can blend price and emissions grade from as many sources as there are lumps in the coal pile. That feature offers an unprecedented advantage for portfolio managers who know that coal has cost beyond the spot and contract prices. It costs money to store coal and move coal. With forward purchase contracts, it even costs money to leave coal in the ground.
At the same time, without an adequate supply in contracts, utility managers are forced to make spot purchases at higher rates. For optimum profits, the coal pile has to be just the right size and that “just-right” size fluctuates constantly. “That pile is going to grow over time with deliveries and it’s going to shrink at the same time with coal burn,” Trehm points out. With PowerSimm, portfolio managers can match the height of the pile to the depth of the demand: a pair of synchronized curves on a color-coded graph with spot market purchases ideally relegated to a sliver in the portfolio. PowerSimm simulations allow users to see that dynamic relationship and run additional simulations for changing market conditions.
Getting the size of their coal piles just right is why utilities like Tucson Electric Power are buying PowerSimm. Where competing software products run on deterministic analysis, Ascend Analytics offer precise projections using state space modeling. The effect is dramatic, especially now, with natural gas prices at portfolio rattling lows. Coal plants that may have been running off peak while gas-fired generators sat idle, are now kept off line with utilities relying on lower-emission natural gas for bigger chunks of the day. As a result, coal piles in the East and Southeast grow ominously high with costs climbing to match. New PowerSimm features in development will warn portfolio managers long before that happens, indicating a cost penalty when forward-purchase contracts rise above an optimum threshold. PowerSimm’s more accurate simulations coupled with the exclusive ability to view a coal pile in all its intricacy provide a competitive advantage to portfolio managers who can use hedge pricing to optimize contract purchases and see the risk exposure on the spot market. Viewed from the loading yard, it may look like a great mass of black and soot, but PowerSimm users see the coal pile more accurately: as a set of numbers. Competing software product might see tons. What they see beyond that can’t match the accuracy of Ascend products. “They don’t model the coal pile,” Rehm says. “Or even how it became a coal pile.” PowerSimm, Rehm says, sees the pile in all its intricacy, from the mine to the fire box, and every step in between.
Electricity customers buy on price and customer services, switching suppliers as a direct function of competiveness of price.
Despite the fact that the Retail Energy Supply Association claims that only 50 percent of residential consumers know they have a choice in where they buy their power, customer loyalty has been a relatively negligible factor.
Knowing that, customer attrition is an almost inevitable blotch in a power retailer’s profit/loss statement but planning for that attrition, with proper hedging and risk assessment, can determine the color of that blotch. Not enough customers, combined with long contracts on power, turns that blotch dark red. Setting the right rate and buying forward contracts for the right load quantity can keep the books in the black: the kind of outcome Ascend Analytics software users have come to expect.
Planning against customer attrition isn’t easy. Guessing on the wrong assumptions with an unsophisticated deterministic model sets utility retailers on a high-risk trajectory. With Ascend’s PowerSimm state-space modeling simulations, retailers gain a confident outlook of not only the expected impact of customer attrition on revenues, but also a clear idea of the uncertainty surrounding this revenue impact. Using this information, a retailer can keep risks to a minimum. “You know how much to contract for,” explains Ascend analyst Scott Nelson. “You know how to hedge your loads properly.”
Ascend Analytics products operate at the state-of-the-art edge of statistical modeling. With PowerSimm, retailers input their own predicted customer attrition curves. These curves are then combined with the load and price simulations rigorously benchmarked to capture the key structural weather-load-price relationships and aligned to the current market outlook. Within each simulation path, the incumbent rate is compared to the market price, and based on that differential, a percentage of the contracted load will likely leave. The value of PowerSimm is in the precise quantification of the uncertainty surrounding this revenue impact. Software that generates simulations using deterministic modeling can’t quantify the uncertainty of this revenue risk, since deterministic models fail to capture the uncertainty in volumetric risk, price risk and the correlations between the two.
Retailers often find themselves in a situation where a competitor can make a strategic decision to lower rates. The shoppers might walk out of the store. “All that revenue is basically at risk due to attrition,” Nelson notes. Retailers cannot predict every competitor’s move but a robust simulation of market price can help anticipate the likelihood of such rate changes, allowing retail managers to plan accordingly. “You might want to look into basically setting up some kind of hedge to mitigate that risk,” Nelson adds. “You can’t actually model very effectively what rate a competitor is going to put together but you can say ‘this is where the market is and this is where it’s going.’” If a retailer has an idea of where wholesale power prices are headed, that manager may be able to set a rate that slows or eliminates customer attrition.
So while customer attrition may be inevitable, the uncertainty around its impact can be calculated. PowerSimm does that accurately, and automatically. The customers might still walk out the door. But when their departure is accounted for in Ascend’s PowerSimm, they won’t take the profits with them.
With estimates of new electric vehicles and plug-in hybrids climbing in every research report, you can already hear politicians boasting about “electric highways” with charging stations sprouting out of the ground outside every Starbucks.
But the truth is most EV owners are going to charge up at home and how long and when they charge will ripple across the power industry, affecting everybody from early adopters accessing “smart house” applications with their iPhones to coal miners shaking the dust out of their boots. Ascend Analytics’s PowerSimm and Curve Developer programs can help portfolio managers keep that ripple from splashing over their profits. Modeling for load, regulations and fuel prices, Ascend products factor risk and uncertainty into decision analysis. Electric vehicles owners promise plenty of both.
A report released in July by the Electric Power Research Institute placed their mid-range prediction at 35 million electric vehicles on the road by 2030 and pegged the annual power consumption for those cars at 80 terawatt hours.
EPRI’s more optimistic estimate brought the number of EVs on the road up to 65 million, more than doubling the electricity demand.
At either number, the impact could be dramatic when residential customers start plugging their cars into high-amp chargers all timed to click on at 9 p.m. spiking the load on a system tuned to off-peak evening hours (a study released in September noted that 89 percent of customers intend to charge their cars at home). Businesses running fleets of EVs and plug-in hybrids could be switching their chargers to “on” at entirely different times.
Utility managers know that off-peak and on-peak load can be served by different mixes of generation assets and they know that mix will shift constantly over time with fuel prices, regulation costs, transmission upgrades and new renewables coming on line. Ascend Analytics products can handle all of that with precision, tallying uncertainty and optimizing financial performance.
With simulations for load, spot market fuel costs, renewables, forward option volatility, weather and regulation modeled in short-term and long-range runs, utility executives can optimize their portfolio to meet the potential growth in off-peak demand. PowerSimm models load by the hour and into the years, with portfolio managers able to look at dispatch scenarios constrained to meet a user-selected set of inputs. PowerSimm also models renewables by site so a manager might know that the night wind picks up at a particular wind farm just in time to charge a factory fleet of plug-in hybrids.
That kind of data granularity will be indispensable to utilities and retailers customizing rate plans for homes equipped with smart meters and vehicle charging stations or business fleets drawing power under demand resource contracts.
Nobody is predicting electric vehicles will replace internal combustion autos tomorrow, but with Ascend Analytics software, portfolio managers can be ready for those changes today.
A continuing battle over EPA emissions has left power industry professionals scrambling to keep their portfolios prepared for regulations that could seemingly lurch in any direction, but developers at Ascend Analytics say their modular, customizable energy analysis software is ready to make sense of the energy outlook no matter whichway it tilts. The last four months have seen tectonic shifts across the regulatory landscape. In July, the EPA introduced Cross State Air Pollution Rule (CSAPR) restrictions on SO2 and NOx with a market launching in 2012 to trade emission allowances. Less than two months later, the Obama administration delayed new ozone standards until 2013, a move widely decried by environmental activists as a surrender to big business. But now the administration is promising to veto a GOP-sponsored bill that would impose lengthy delays on CSAPR and other upcoming emissions mandates. The Transparency in Regulatory Analysis of Impacts on the Nation act (TRAIN) was approved by the U.S. House of Representatives Sept. 23. The act would require detailed financial analyses on the EPA rules’ impact. The act would delay new mercury rules for power plants and postpone the NOx and SO2 restrictions and trading market. Ascend Analytics President Gary Dorris says the seesaw shifts make it difficult for executives to manage capital investments and shape portfolios for natural gas, coal and renewable energy. Dorris says his company’s software allows users make as many plans for as many changes as they can foresee, and run each through an advanced simulation engine.
“If you don’t know what’s going to happen, you have to be ready for anything to happen,” Dorris says. “Our customers can build a plan and a portfolio for each scenario and then take it for a test ride.”
Whatever the environmental or economic merits, rolling out regulations and then rolling them back can have enormous impacts. In the four days after the NOx and SO2 reductions were announced in July, broker trades for NOx emission allowances climbed from $150 per ton to $9500 – that spike occurring a full six months before the emissions market would even open. Such increases would make older coal plants lacking scrubber technology uneconomical. If those rules don’t happen, the plants could remain profitable. Market uncertainty floats as a data point in every energy portfolio but political uncertainty of this magnitude remains difficult to quantify. With Ascend Analytics software, energy portfolio planners test as many permutations of EPA rules as they wish to model. Providing streaming market forward curves with CurveDeveloper, and risk-based decision analysis from PowerSimm, Ascend provides a comprehensive platform to model proposed regulations for integrated utilities, wholesalers, and retail providers. PowerSimm applies detailed modeling and simulation of emissions, power, and fuel markets synched to generation, load, and hedge strategies to determine future costs and risk. The model can then select an future supply portfolio optimized to changing regulatory and market risks and costs. Armed with solid simulations and data, Ascend Analytic’s customers can plan with confidence for new EPA restrictions. Whatever they turn out to be.