PowerSimm Editor 4.1

We are excited to announce the release of PowerSimm Editor 4.1. This new release of PowerSimm is a major upgrade from previous versions, involving significant improvements on the user interface functionality, menu contents and layouts, new validation rules for notifying users of errant inputs or configuration, and remediation of existing bugs. This new UI makes substantive strides to improve the software usability and error trapping of problematic data or configurations. PowerSimm 4.1 also incorporates, for the first time, a user interface for Credit Manager, our enhanced analysis tool for credit exposure.

A lot of valuable feedback from client users and our analysts went into the development of this new release. Our main goal was to provide users a more integrated and intuitive editing/execution environment. Diligent validation and QA testing were performed on this new release by experienced IT and Services analysts to ensure error-free functionality of various components.

Major highlights from the new version of PowerSimm™ are given below. More detailed lists of enhancements, new validation rules, and bug fixes are provided in Appendices 1 through 3 at the end.

Updated Look with a New Menu System – The main editor now features a leaner UI theme inspired by Windows 8 Metro where icons for the most commonly used editors are tiled in meaningful groupings. The menu system of PowerSimm™ has been significantly changed with this release. All previous menu functionality is still present, but has been organized in a more intuitive form.


Tabbed Windows – In a form similar to web browsers but placed at the bottom of the frame, the newly-featured windows tabs allow the user to focus on, organize, and close work windows with more ease.


Backstage Menu – Also new in this version is what is termed a “backstage” menu section, accessible by clicking on the gear icon in the upper left corner of the main editor. The backstage menu hosts the configuration and administrative functions of the main editor.


Completely Rebuilt Generation Editor – The generation editor was rebuilt to improve its usability by grouping the types of configuration data into several screens: Resource Variables, Scheduled Outages, and Historical Input. Additional features include an added end date filter, a more accessible flat view toggle, and additional validation rules, including new checks of heat rate, startup/shut down, and outage data.


Many New Validation Rules – PowerSimm™ Editor version 4.1 adds many new input data validation checks to help prevent configuration errors in new or updated data. New and updated validation rules for the Generation Editor, Instrument Editor, Forward Curve Editor, and many more, improve the reliability of configurations and data. This includes more checks on generator configuration, trade details, load and pricing data, to name a few. Also, the new Report Manager has improved capability of preventing data- and configuration-related run failures. Building on the input data error checking process in version 4.0, the “Check Data” link allows users to check if their changes (additions or updates) have any issues before submitting the changes to the database.


User Interface Integration for Credit Manager – PowerSimm™ now features a user interface for Credit Manager, a credit risk analysis tool for collateral, exposure, and simulated potential future exposure across multiple departments.

Upgrading to PowerSimm™ 4.1 – This new version of PowerSimm™ will be available for installation on ATLAS. For all features to work, a database update is required. Please meet with your Ascend project manager for creating an update plan to review the new editor and develop a deployment testing schedule.

Appendix 1 – Enhancements

  • Credit UI
  • Using ribbon menus with new menu layout
  • Updated icons
  • Tabbed MDI windows
  • Metro-style facelift to main form
  • Added speed-dial
  • Moved book indicator to status bar
  • Permissions for study creation/deletion added
  • Altered the report manager study list logic to exclude studies whose types do not have a showflag=1 condition
  • Removed hiding the variable editor if there is an issue getting the data. The variable editor will open and display an exception instead.
  • Made the following changes to the User Management screen –
    • User List filtered to show only OPS users
    • Ability to edit the user – role mapping
    • Replaced the OPS username by Windows friendly name in the User List in the UI
  • Ability to scroll and drag the tree nodes in Portfolio Editor
  • Replaced Portfoliomanagement trigger with procedure to avoid missing column errors
  • Added filter to Market price model, basis, wind, spot and Load editor to filter moduleprocess
  • Added default variable functionality to startpowersimmstudy
  • Added new sensitivity job tables and their trigger logic
  • Added logic to automatically update the calculation order in case of missing values
  • Jobidtable logging records application modifying the table
  • Log machine running cost in the jobrunnerspectable_log
  • Locations all default to 1 (world) in items
  • Added and updated validation rules for:
    • Generation Editor
    • Instrument Editor
    • Forward Curve Editor
    • Main Model Editor
    • Renewables Editor
    • Load Editor
    • Basis Editor
    • Gas Storage Editor
  • AscendHelp table updated and consolidated to POWERMAN
  • Report manager has new validation rule selection capability
  • Report Manager does not show CD studies in study lists
  • ScheduleStudyToRun updated to include OPS parameters
  • Spot Price Editor updated to be a “filter form” similar to load, wind, etc.
  • Default time step of 4 set in Report Manager
  • Job Error triggers consolidated and updated
  • Portfolio Links now copy with portfolios when copied
  • Study name duplicates prevented
  • Instrument dates adjusted for hour ending. Dates entered in as dates (no times) are given a 1 AM time.
  • Generation Editor rebuilt
  • Report Manager variable search is no longer case sensitive
  • Basis editor date filter logic update
  • Item name added to DSM dropdown in gen editor
  • Archived variables filtered from variable editor
  • Process flow drop-downs in various UIs filtered for context
  • Deleted forward prices indicated in model editor
  • Grids given export to excel function
  • Sensitivity refresh button added to Report Manager
  • Label changes in Generation Editor
  • Calculation Order auto-populated in a better way from the variable editor

Appendix 2 – New Validation Checks

  • Generation Editor
    • Unit Type not null
    • Non-negative times and costs
    • Non-negative Ramp-up/Ramp-down rate
    • Non-negative MMBTUs
    • Non-negative emissions
    • 0 <= Must Run
    • Min <= Max Gen
    • All three historical levels fields filled out (or none)
    • Heat rate Gen’s are monotonically increasing
    • Scheduled Outages: Start/End/% – all or none
    • Set of Fuel Types must equal set of fuel types in HR tab
    • Linked Res.: State must be filled if Unit is filled in
    • Fuel Cost Multiplier must be > 0
  • Instrument Editor
    • Commodity needs to be filled out
    • Instrument Type required
    • Peak Period needs to be filled out
    • one out of the 6 PRICE columns should be filled out for each record
    • Warn on missing Quantity and/or Quantity type
    • Transaction date cannot be null
  • Forward Curve Editor
    • Must have commodity filled out
    • Multiple Commodity/Peak Period (PP) pairs are not allowed within a given item
    • Use CD is checked, market name must be filled out
    • If Use Adjustments is checked, make sure there are adjustments!  (NOT USED!!! HIDE Adjustments tab and checkbox)
    • If one column is filled out, then they all need to be (less Update Date)
    • PP must match the parent
  • Main Model Editor
    • Description, Curve Type, Process Flow, Source & Weight Schema must all be filled out.
    • Description should be unique (database change)
    • Must be filled out: System Load, Gas %, Electric % (6 columns)
  • Renewables Editor
    • Expected Peak > Capacity –> Error
    • TimeIntervalInHours * ExpectedPeakGen < ExpectedEnergy –> Error
    • StartDate>EndDate –> Error
    • Gaps –> Warning
    • Overlaps –> Warning
  • Load Editor
    • Data type should be set (default to Energy)
    • Load needs a value
    • For a load, if forecasts are filled out, but no data, warn regarding setting the proper process flow.
    • Total installed Cap = Sum of other cap
    • Expected Peak Demand*[Hours in (End Date – Start Date)] > Expected Energy
    • Of use column checked then fill out other columns
    • Run orders exclusive
    • Check if more than one record per load => Run order filled out
  • Basis Editor
    • Check for overlapping date ranges in the scaling data
    • Check for date gaps in the scaling data
  • Gas Storage Editor
    • Check for overlap in Capacity date ranges
    • Check for Utilization Min < Max
  • Report Manager
    • Warn on previous study resubmission

Appendix 3 – Bug Fixes

  • Limited number of jobs shown in Study Viewer to 10,000 to prevent memory errors.
  • Load, Hydro, Wind, FC editors, ST price, Weather handle database errors upon save.
  • Fixed: Instrument Editor throws an error when there are zero instrument items
  • Modified Ascendhelp table entries to point to latest value
  • Modified AALOOKUPIDTABLE primary key from composite to single key, added foreign keys
  • Added unique key to counterpartyratings table
  • Fixed language errors in jobidtable triggers, made it schema independent and combined them into a single trigger
  • Modified basis editor to point to newly created view to show archived forwardcurve values correctly
  • Double-click of some item types (hydro, wind, FC, load) in portfolio editor opens form with item in focus
  • User Management error when closing fixed
  • Null active flags in instruments set to 0
  • “copy” concatenation added for long item names
  • Various credit database corrections (missing FKs and PKs)
  • Extra line after paste issue fixed
  • Credit date interval issue in Report Manager fixed

Ascend Helps NorthWestern Monetize Risk In S.D. Resource Plan

Ascend Analytics recently put its PowerSimm Planner software to great success for NorthWestern Energy in its formulation of a 10-year integrated resource plan (IRP) for South Dakota.

PowerSimm Planner helped NorthWestern realize value of adding highly flexible peaking resources to its generation fleet in the SPP and MISO market. Despite these markets having some of the lowest average energy costs in the country, Ascend uncovered a hidden opportunity to realize additional value through internal combustion units (ICU’s).

The ICU’s (Wartsila 50SG) attributes of no start-up costs and small heat rate penalty at minimum load provide substantial economic operating advantages over standard combustion turbines (GE 7FA).  These advantages are realized through capturing the more dynamic price signals of the 5 minute real-time energy market for energy and ancillary services.

“NorthWestern’s decision to enlist Ascend to provide the analytics for its South Dakota integrated resource planning (IRP) further solidifies our position as a leader in electric utility planning sing sophisticated modeling software to help power companies more cost-effectively predict and monetize unique opportunities,” Ascend Analytics President Gary Dorris said.

It marks the company’s second such collaboration with NorthWestern.  Last year, Ascend provided modeling support for NorthWesterns successful bid to acquire $870 million of hydroelectric generation in Montana.

NorthWestern also used PowerSimm to model supply portfolio, regional commodity prices, and energy resource characteristics in South Dakota.  The software introduced “meaningful uncertainty” into future simulations, capturing both the expected costs and risks of its portfolio there.

Traditional resource planning tools lack the sophistication of PowerSimm and fail to capture the extreme volatility and value of more flexible generating resources.  Other software planning models for IRPs fall short recognizing the value of flexible generating assets.

NorthWestern Energy concluded that current peaking options such as GE 7FA are not cost competitive with more flexible internal combustion engines (Wartsila 50 SG).  The additional value of a flexibility added an order of magnitude increase in profits.

Check out Ascend’s contribution to NorthWestern’s South Dakota resource plan via the utility’s website: Chapter 4 — Portfolio Modeling and Analysis

For more information, please contact Ascend Analytics at (303) 415-1400 at info@ascendanalytics.com.

Ascend’s PowerSimm Propels Riverside Utilities New IRP Over Finish Line

Riverside Public Utilities recently won final approval of its 2014-2033 Integrated Resource Plan, thanks in part to Ascend Analytics’s PowerSimm Planner, which provided its analytic backbone.

Utility officials put the software to the test, quantifying costs and risks associated with critical IRP components, including retirement of coal-generation plant InterMountain Power Project, capacity expansion planning, renewable resources and energy storage.

PowerSimm Planner, a complete analytics platform for energy portfolio planning, capacity expansion and financial analysis, is designed to help energy planners and financial managers model revenue requirements, optimize power expansion plans and compare their financial impacts.

“We’re thrilled to have had the opportunity to help RPU get the biggest bang for its customers’ bucks and solidify its bottom line,” said Ascend President Gary Dorris.  “We helped utility officials determine the best path forward for swapping out its InterMountain coal-fired power generation for less-carbon intensive electricity production.  It’s a win-win-win for everyone involved – the consumers, the utility and the environment.”

PowerSimm Planner helped Riverside officials quantify projected costs and risks arising from 12 different resource planning scenarios to make up for the lost generation resulting from IPP’s phase-out.

All of them involved making market-hedged purchases according to varying degrees of load growth rate (weak to strong), prospective IPP phase-out dates (2020 and 2025), and percentage of renewables required (33% and 40%) in the utility’s power generation mix.

PowerSimm’s analysis showed that the rate of load growth proved a significant factor in future costs. Weak load growth produced COSLN forecasts ranging from 10% to 14% higher through 2033.

The IRP plan concludes that combined effects of phasing out InterMountain too early and termination of its free carbon allowances could drive up electricity costs as much as 1¢/kWh.

“From a strictly economic perspective, it does not currently make sense to try and unilaterally terminate our IPP contract any earlier than necessary.  Rather, we should continue to support a market driven dispatch scheme that recognizes the inherent carbon cost embedded in this energy asset, while planning for a replacement option that can come online just a few years before the IPP contract terminates,” the IRP plan states.

In addition, Riverside officials, with PowerSimm’s help, considered five other non-market-forward alternatives to replace IPP’s lost generation.  Those included: 1) building a new 100 MW GE LMS-100 high-efficiency, simple cycle gas plant; 2) using five 9.3MW Warsila 20V34SG simple cycle internal combustion units stacked together in a 46.5 MW generation facility; 3) purchasing 50W of the 1,000 MW IPP Repower Project; 4) replacing 75MW of IPP coal energy with renewable resources through a new long-term contract; 5) acquiring a near-term 150MW commercial tolling contract, effective January, 2016.

Overall, four of five alternatives presented resulted in higher service costs, and all of them produced greater uncertainty than the market-hedge scenarios.

Read the plan

For more information on Ascend’s PowerSimm Software Suite, contact sales at info@ascendanalytics.com or (303) 415-1400.

Accounting for Customer Attrition

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.

Plug-In Hybrids and Plugged-in Headaches

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.