At the CPUC’s first workshop on distribution planning, the buzz word that came up in almost every presentation was “optimal location.” But what does “optimal location” mean? From who’s perspective? Over what time horizon? Who decides? The parties gave hints of where they stand and they are probably far apart.
Paul De Martini gave an overview of the technical issues that the rulemaking can address, but I discussed earlier, there’s a set of institutional matters that also must be addressed. Public comment came back repeatedly to these questions of: who should be allowed into the emerging market with what roles, and how will this OIR be integrated with the multitude of other planning proceedings at the CPUC? I’ll leave a discussion of those topics to another blog.
The more salient question is defining “optimal location.” I’m sure that it sounded good to legislators when they passed AB 327, but as with many other undefined terms in the law, the devil is in the details. “Least cost-best fit” for evaluating new generation resources similarly sounds like “mom and apple pie” but has become almost meaningless in application at the CPUC in the LTPP and RPS proceedings. Least cost best fit has just led to frustration for both many developers of innovative or flexible renewables such as solar thermal and geothermal, and for the utilities who want these resources.
SCE and SDG&E were quite clear about how they saw optimal location would be chosen: the utility distribution planners would centrally plan the best locations and tell customers. Exactly HOW they would communicate these choices was vague.
Many asked how project developers and customers might know where to find those optimal locations among the utilities’ data. Jamie Fine of EDF might have had the best analogy. He said he now lives in a house that clearly needs a new paint job, so painters drop flyers on his doorstep and not on his neighbors who’s paint is not peeling. Fine asked, “when will the utilities show us where the paint is peeling in their distribution systems?” His and others’ questions call out for a GIS tool that be publicly viewed, maybe along the view of the ICF tool recently presented.
I can think of a number of issues that will affect choices of optimal locations, many of them outside of what a utility planner might consider. The theme of these choices is that it becomes a decentralized process made up of individual decisions just as we have in the rest of the U.S. market place.
- Differences in distributed energy resource characteristics, e.g., solar vs. bioenergy;
- Regional socio-economic characteristics to assess fairness and equity;
- Amount of stranded investment affected;
- The activities and energy uses both of the host site, neighboring co-users/generators, and surrounding environs;
- Differences in valuation of reliability by different customers;
- Interaction with local government plans such as achieving climate action goals under SB 375.
- Opportunities for new development compared to retrofitting or replacing existing infrastructure.
In such a complex world, the utilities won’t be able to make a set of locational decisions across their service territory simply because they won’t be able to comprehend this entire set of decision factors. It’s the unwieldly nature of complex economies that brings down central planning–it’s great in theory, but unworkable in practice. The utilities can only provide a set of parameters that describe a subset of the optimal location decisions. State and local governments will provide another subset. Businesses and developers yet another set and finally customers will likely be the final arbiters if the new electricity market is to thrive.
As a final note, opening up information about the distribution system (which the utilities have jealously guarded for decades) offers an opportunity to better target other programs as well such as energy efficiency and the California Solar Initiative. Why should we waste money on air conditioning upgrades in San Francisco when they are much more needed in Bakersfield? The CPUC has an opportunity to step away from a moribund model in more than distribution planning if it pursues this to its natural conclusion.
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