Is this the future? A simple method for performance-based smart grid regulation

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Editor's note: Paul Alvarez, a consultant with deep experience evaluating smart grid performance, recently told us why we should switch to performance-based regulation and then suggested a better way to do smart grid cost recovery. In this final installment of his series, Paul addresses some of the more common smart grid performance metrics regulators are requesting and offers interesting perspectives for Smart Grid News readers.

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By Paul Alvarez

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In previous contributions to Smart Grid News, I’ve made the case for performance-based recovery of IOUs’ smart grid investments. I've suggested they incorporate both rewards (incentives) and risks (penalties) for shareholders. My premise was that capital investment does not make a grid smart; the value comes from the way utilities make use of the resulting new data and capabilities.

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In short, I’ve argued that regulated utilities should be rewarded not for simply making smart grid investments but for maximizing smart grid value (by completing difficult organizational, operational, data utilization and customer-facing changes). I’ve also described some of the more desirable characteristics of performance-based recovery of smart grid costs, including risk/reward symmetry and the appropriate sizing of risks and rewards relative to the size of investments. I also described the approaches that Ohio, Oklahoma, Maryland, and Illinois were using to introduce performance-based cost recovery risks and rewards for IOUs.

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A discussion on performance-based cost recovery leads logically into a conversation about how performance should be measured. Though only a few states are dabbling in performance-based cost recovery so far, several states are requiring IOUs to report on specific deployment and performance metrics. In this final installment in my three-part series I’ll characterize and review some of the more common metrics regulators are requiring of IOUs making large smart grid investments.

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Deployment metrics

Some of the most common types of metrics relate to deployment, including cost and schedule. Perhaps the single most common metric measures deployment costs relative to capital budgets or business plans. In many cases, regulators have set caps on smart grid deployment cost, placing utilities at risk for any cost overruns. However, as such caps do not specify associated minimum capabilities, it may be possible for a utility to simply cut back on planned functionality if cost overruns are encountered during the course of a deployment.

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Other regulators are understandably interested in the status of deployments relative to planned schedules. Schedule metrics provide a reference point by which to evaluate deployment costs incurred to date, but are also being used by a few wise regulators to help them anticipate (and perhaps help accelerate) the point in time when smart grid investments can be expected to begin delivering economic, reliability, and customer service benefits. These regulators recognize that customer payback periods can be affected by delays in the delivery of economic benefits as well as by more common concerns about the size of such benefits. The Maryland PSC requires the utilities it regulates to report on almost 90 deployment metrics.

IOUs are understandably concerned that the proliferation of different metrics and objectives can dilute management focus, hamper identification of best practices, and increase costs.  As smart grid operating experience grows, it is becoming increasingly clear that a limited number of consistently-defined deployment and performance metrics covering only the most significant economic, reliability, and customer service benefits (the 80/20 rule) could increase (and more clearly document) the value created by smart grid investments.  As an example, my experience leading independent deployment evaluations indicates that 80-90% of the smart grid’s economic benefit potential comes from just 3 sources (manual meter reading savings; TOU rates/Demand Response; and Integrated Volt/VAr Control).  By adding some metrics on customer services and a few standardized reliability metrics, a simple performance metric system should accomplish most of what regulators and other stakeholders are seeking.  The next step is to address regulatory structures and rules that inhibit IOUs from maximizing smart grid benefits, but that is a subject for another day.

 

It’s natural for regulators to be interested in using deployment and performance metrics to encourage the utilities they regulate to maximize the benefits of smart grid investments.  But stakeholder opinions and concerns are many, and it’s impractical to design a metrics system that addresses everything.  What do you believe are the most critical metrics?  How do you think they should they be used?  And whom do you believe should take the lead in developing a standardized set of metrics?  We’re still early in the smart grid evolution, so please post comments to share your ideas on this important issue.                 

 

Paul Alvarez is the President of the Wired Group, a distribution business consultancy with a focus on smart grid benefit quantification and performance measurement.  He has led teams that have completed comprehensive, independent evaluations of smart grid deployments for Xcel Energy (SmartGridCity) and the Ohio PUC (Duke Energy’s Ohio deployment). For links to benefit and performance measurement resources, and more visit www.wiredgroup.net.

 

Also in this series…

Part 1: Smart grid regulation: Why we should switch to performance-based regulation

Part 2: A better way to do smart grid cost recovery (PUCs pay attention)

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