Joe O’Donnell, Manager, Market Intelligence, Kansas City Power and Light
“I’ve used DSMore for five years and I really appreciate the speed with which I can evaluate a measure.
We’re putting together a demand side resource plan for implementation in 2012 and we have a 60 page set of requirements that we need to cover, including cash flow, costs and benefits of avoided energy, and all that. When we packaged the programs and presented them for review an intervener asked why we didn’t include LEDs. To accommodate the request I found a run on CFLs and made some changes to the assumptions and within 15 minutes we had the LED results.
DSMore also allows you to quickly vary the underlying assumptions to see what the impacts might be.
For example air conditioning typically runs May through September. But in May and late September you might only see three percent usage, while July and August will account for 70 percent of total kilowatt hours used. So you can accurately evaluate a measure using a defined load shape.
You can also check assumptions for variable time of use rates.
Soon after we started using DSMore I was working with a consultant from an engineering firm who worked up a methodology to construct a time of use model where summer off-peak prices were only 6 cents down from 11 cents, while the on-peak price was 36 cents for four hours on week days. During this four hour period they’d pay 36 cents, while every other hour they’d get the discount. The consultant modeled this using a spreadsheet that showed that the amount of added revenue from the load at 36 cents more than covered the amount lost during the discounted hours. But when I modeled it in DSMore, it showed me the proposed rate structure was highly sensitive to the percentage of load that needed to shift. The consultant used a fixed percentage in his spreadsheet and if the assumption was off by more than 5 percent then we would end up losing 20 percent revenue. Needless-to-say, we changed the consultant’s rate plan.
What’s more, DSMore gives us credibility and defensibility with agencies like public utility commissions, offices of public council, interveners who scrutinize our results.
Once they see the model and our input assumptions they don’t challenge the results. Plus we can also easily accommodate specific regulatory requirements. For example, the Kansas commission required us to evaluate all measures with an assumed 2 percent reduction in performance every year. This was an easy calculation since degradation of savings is a readily available option in DSMore. It also looks at things like net to gross ratios, free ridership, and tax benefits, so you can look at all sorts of factors to get a better understanding.
I admit there have been times when I’ve needed an ability to input something that wasn’t in the current version.
But I’ve found Integral Analytics to be very responsive to my needs. I recently talked to them about the fact that I could only enter a single weekend price for time of use rates, but I need a summer and winter aspect to the rate. So I discussed it with Jason Crabtree and he agreed to incorporate it into the next version. They do this based on other people’s input as well, such as earlier request to add the ability to input different discount rates for societal, or participant, or utility. Now you can easily value the costs and benefits at different discount rates.
It takes a while to learn how to use it, but I’ve never had any issues.
The service model is more than adequate and is always responsive to any questions or issues. Any time I’ve had an issue I always get an answer within a day. Plus there is an active user community that can help you with ideas as well.
DSMore is a great tool with a lot of flexibility.
I definitely recommend the product and the company.”
—Joe O’Donnell, Manager, Market Intelligence, Kansas City Power and Light