Coal Piles as Inventory to Model

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.