Interoperability Case Study: The Smart Grid
July 8, 2012
This case study is part of an ongoing series developed in support of a larger text on interoperability by John Palfrey and Urs Gasser Interop: The Promise and Perils of Highly Interconnected Systems (Basic Books, June 2012).
The book is an extension of their 2007 study and paper, “Breaking Down Digital Barriers: When and How ICT Interoperability Drives Innovation” (Berkman Center Research Publication, 2007). Interop: The Promise and Perils of Highly Interconnected Systems focuses on the relationship between interoperability and innovation in the Information and Communication Technology (ICT) environment and beyond. Palfrey and Gasser seek to sharpen the definition of interoperability and identify its relevance for consumers, companies, governments, and the public by examining its driving forces and inhibitors, while considering how it can best be achieved, and why.
You can download this case study at SSRN.
From Urs Gasser's blog post about this publication:
We would like to introduce the case study on the “smart grid” written by Paul Kominers. Paul submitted the following abstract to introduce the case he researched with us:
Imagine a mountain climber without a map. Rather than going downwards to return to town as might be sensible, he wants to find the highest point in the entire mountain range. But due to a blizzard, he cannot see very far; he can only tell whether a certain direction takes him higher or lower, and he has to stop every fifty yards or so to reevaluate and pick a new direction.
We can imagine many things happening to this mountain climber. He might find a path to the very highest point on the range. But he easily might not. If he finds himself near the top of the second-highest peak, he will probably follow the path to the top of that peak. In fact, if he finds himself approaching any peak, he will probably follow the path up to the top of the peak, unless the blizzard clears and he can see that he is on a lower peak. If he can see where the higher peak is, he might go down far enough to get onto a path that takes him up the higher peak, and then go straight up. Alternately, he might be lazy. He might find himself somewhere that gives him a vantage point to see where the highest peak is, but decide that he does not want to expend the effort to go from his current vantage point to the highest peak. Good enough is good enough for him.
This is an analogy for a fitness landscape. A fitness landscape is a way of picturing an optimization problem. A problem is analogized to a set of coordinates, with each coordinates having a certain fitness value; this builds up an imaginary, n-dimensional landscape. The goal, then, is to find the fittest point on the landscape, but limited sight range and unwillingness to invest to make big changes can get the search for maximum fitness stuck on a suboptimal or local peak.
Our electrical grid is much like the mountain climber stuck on his suboptimal peak. If we had had the sight range to see the next generation of technology back when we built the grid, we would have taken a different path to build that technology in the first place. And big changes require costly investments of time, money, and political capital, all of which are scarce. Further, the path is not perfectly clear. Although we have every reason to believe that a revised electrical grid would pay off substantially, exactly what a revised grid should look like is an incredibly hard problem. This makes moving even harder.
The next generation of the grid is the Smart Grid, a grid built up of intelligent, interoperable components. The Smart Grid comes from making individual grid components more self-aware of what they are doing at every moment. They can then be joined in networks that allow them to make better decisions about how each of them uses and transmits energy.
Currently, a great deal of discussion and debate is taking place. Government regulators, members of industry, and other stakeholders are coming together to discuss what a new, interoperable grid should look like. They are working together to design a more efficient and responsive electrical grid. In essence, they are finding the path to the higher peak.