In mid-October, San Diego Gas and Electric (SDG&E) regulatory filings indicated that the company has changed plans to deploy a foundational private WiMAX network as part of its ongoing smart grid deployment, opting instead for a mix of various public and private network systems.  This move is noteworthy because SDG&E is a leader in adopting a comprehensive, integrated, smart grid communications strategy.  Its abandonment of WiMAX raises questions about the future of private 4G network technology for smart grid.  Pike Research has been bullish on the future of standards-based private wireless for smart grids, so naturally we’re asking ourselves the same questions.

Utilities have a longstanding preference for private wireless over public cellular (though this is often overstated as vocal proponents of private wireless usually also have pervasive public cellular deployments, especially for advanced metering infrastructure (AMI) backhaul).   However, for critical applications (such as distribution and substation automation), private networks are still considered more reliable and resilient in the face of disruptions, and in some areas, the regulatory preference for returns on deployed assets tilts the field toward private networks.  Private 4G technologies such as WiMAX offer a standards-based private solution with strong performance and are expected to displace the plethora of proprietary solutions available.  SDG&E, CenterPoint Energy, and Oklahoma Gas and Electric (OG&E), as well as many smaller utilities in Canada, were and are heading in this direction.

Smart Grid Communications Node Shipments (Excluding Smart Meters), As % of Total, North America: 2012-2020

(Source: Pike Research)

However, as SDG&E discovered, reserving guaranteed spectrum for such private networks is challenging.  SDG&E had earlier been a showcase customer of Arcadian Networks, which built a product offering around dedicated spectrum that covers most of the United States.  However, Arcadian failed to attract enough customers to convince its investors that such networks were the best use of their spectrum, and ultimately failed.  This is less of an issue in Canada, where WiMAX-suitable spectrum has been reserved for utility use, leading to greater usage.

Against some of these challenges, public cellular companies have more aggressively supported some of the bandwidth and service guarantees required by utilities, enabled by new capabilities delivered by their own 4G networks.  Public telecom carriers have been riding a wave of greater acceptance by utilities for AMI applications (both to the meter and for backhaul), but not all of these are considered mission-critical, at least from the perspective of immediate availability during an outage crisis.

Where will this lead? At Pike Research, we still see a strong trend toward adoption of open standards for public and private, wired and wireless network technologies, and the benefits of integrating these in a unified communications architecture rather than in separate application silos is too great to ignore.  The ongoing post-mortems of recent major storms, such as Hurricane Sandy, should help guide in the private versu public network resiliency debate, if utilities are willing to share their experiences.  We still see a strong future for private 4G wireless technologies but also strong growth of public 4G networks (40% CAGR, 2011-2020, for unit shipments into distribution automation and AMI backhaul applications in North America).   We’ve never said that there will be “one network to rule them all,” much to the chagrin of some network equipment vendors.  Diversity will remain the key defining attribute of grid communications networks long into the future.

At the IBM Smarter Cities forum in Rio de Janeiro last week, I had the chance to go behind the scenes and take a first-hand look at Rio’s smart city project. My main impression is that the project represents one of the purest emerging examples of a smart city project that is simultaneously developing smart solutions on multiple fronts – natural disaster management, public safety, health, utilities, to mention a few – and is starting to achieve a true “system of systems” – nirvana in smart city terms. This level of integration and interoperability across city agencies – and the successes Rio has had so far – bodes well for the smart city opportunity not only in emerging markets but worldwide.

The City of Rio de Janeiro has accomplished this by deploying smart technologies ranging from broad, continental-scale weather tracking down to mobile device-enabled notification systems for potholes and burnt-out streetlights. The centerpiece, of course, is the Rio Operations Center, which features Latin America’s largest screen and dozens of stations that provide visualizations of real-time data feeds. Within the center, 35 city agencies work together to synergize their responses to city events. (One interesting detail is that the operators wear uniforms modeled after NASA that create a sense of camaraderie and homogeneity across the historically separate city agencies, which creates something of a spectacle.)

To provide an example of how this works: If heavy rains cause flooding in a specific portion of the city, the operations center coordinates teams that notify citizens ahead of time via text message, close down the streets, mobilize ambulances, and shut down electricity distribution systems in the neighborhood to prevent electrocution. These processes are all pre-determined via standard operating procedures (SOPs). On the city side, bringing all these agencies under one roof helps break the silos that perennially plague the smooth delivery of city services. And, on the citizen side, it certainly helps that Brazil’s mobile device and networks are exploding, providing the platform for vigorous smart city app development and citizen involvement.

But technology is only one part of the winning recipe for a smart city. One persistent barrier echoed many times at the event is that smart city projects often rely heavily on the vision and initiative of specific mayors and administrations, which typically face four-year election cycles. The timetables required for certain types of infrastructure – particularly those involving high-tech and high initial capital expenditures – don’t always fit neatly into mayoral terms. Indeed, Rio’s mayor, Eduardo Paes, who spoke at the event, described the challenges of making progress on the project despite his uncertain future as mayor. Selecting smart city technology measures that optimize in terms of high net-present value, ease of deployment within a tight timeframe, and high PR benefits for the mayoral office seem to be emerging as the most pragmatic smart city solutions that address this challenge.

What differentiates Rio from other smart cities is the added challenge of managing its favelas – shantytowns perched on steep hillsides throughout the city that have historically received little in the way of city services or regulation – and integrating them with Rio’s urban fabric. These areas are among the most vulnerable to disasters such as mudslides as well as important symbolic testing grounds for Rio’s ability to serve even its poorest citizens as scrutiny of the city mounts in the lead-up to the 2014 World Cup and 2016 Olympics. From the perspective of a smart city, the favelas also provide opportunities for infrastructural “leapfrogging,” installing smart systems that could catapult these portions of the city to levels found in the rest of the city using state-of-the-art technology.

All in all, though, the event provided a clear picture of the concrete progress that’s being made on the smart city front and, in particular, the unique opportunities afforded by cities in emerging markets.

After nearly three years of keeping mum to the general public, software startup C3 welcomed analysts into its San Mateo, California global headquarters last week to take a closer look at its offering, learn about its strategy, and meet some of its key clients. Very little has been written on the company, so I wasn’t sure what to expect. In short, I came away impressed by the strides the company has made in such a short time and am confident that the outlook for C3 is going to be very positive.

If you’ve been watching the carbon management software space over the last few years, you’re familiar with the general storyline. Startups such as Hara originally targeted carbon management software as an entry point to the growing carbon economy, bolstered by the Copenhagen Climate Summit and the prospect of a U.S. climate bill. Established software companies and systems integrators such as SAP and Accenture have been developing their own solutions and looking to acquire pureplay carbon management startups. Well, we all know how that U.S. climate bill went, and many of the initial entrants are now retooling to provide broader energy management software.

C3, it turns out, has been going in a different direction all this time. From the outset, C3 targeted cost-effective energy management as its first priority, with carbon as a nice-to-have but not a prerequisite for the platform’s viability. This financially based energy management approach is a core strength of the C3 platform, and one that has already found a number of high-profile customers.

Here’s the skinny on C3:

I had a chance to take a tour of the software and see how it works. The suite consists of five major components:

I was struck by how simple the software is to use. The interface essentially provides users (be they an executive, a facilities manager, or an intern) with a buffet of energy attributes that can be selected to mimic a company’s actual energy profile. The model can be as simple or as complex as the user’s needs require, and the system can be easily scaled to encompass new business units, new energy installations and mitigation projects, as well as other factors across a building’s building and energy portfolio with great ease.

C3 is aiming for a few different channels to sell its service. The first is a direct software-as-a-service approach by which customers, such as Dow Chemical and Pella Windows, can use the software to manage their own energy consumption and assets. The second is an approach that uses C3’s platform as a service that energy service providers, such as utilities, can use to help manage supply-side resources, such as generation facilities, as well as demand-side resources, such as customer energy consumption. PG&E and Constellation Energy are two customers that are already using C3 to help them do what they do better.

The carbon management software and services market is slated to grow from just over $1 billion today to nearly $6 billion worldwide by 2017. C3, with a strong offering and global ambitions, is in a position to do well in this rapidly expanding market, and we’re glad that C3 is finally ready to share its progress with us.

Two sources have provided the bedrock for most attempts to assess the energy and environmental footprint of data centers. One is the EPA’s landmark report to Congress on energy use in U.S. data centers. The other is the work of Jonathan Koomey, and in particular his 2008 report on worldwide data center energy consumption.

Koomey estimated that worldwide data center energy use had doubled between 2000 and 2005 and by 2005 represented 1% of energy consumption. The EPA’s report warned that energy consumption in the United States could double again between 2006 and 2011. The EPA’s report, and the insight provided by Koomey, helped galvanize the industry into addressing the energy efficiency of data centers as demand for IT service continued to increase at a massive rate.

So, Jonathan Koomey’s latest reevaluation of those figures is a significant event, even more so when it shows a reduction in data center energy consumption. In the new report, ”Growth in Data Center Electricity Use 2005 to 2010”, Koomey, who is Consulting Professor at Stanford University, suggests that data center energy consumption worldwide rose by 56% between 2005 and 2010 and in the United States by just 36% over the same period. He estimates that the energy use in global data centers in 2010 is likely to have accounted for between 1.1% and 1.5% of electricity use, and in the United States for between 1.7% and 2.2%.

There are three reasons for this reduction in the growth of energy consumption:

Unfortunately, it would seem that the economic crisis played more of a role than industry attempts to improve energy efficiency, although Koomey himself says it is impossible to be clear how much of the decrease can be attributed to each of these factors.

The numbers are still rather surprising. Even with the economic downturn the demand for data center services has continued to increase as more services and goods become digitalized, even if many companies have held back on significant extension to data center real estate. Virtualization has also been a key development in squeezing more out of existing data centers. Koomey has also made some allowances in his estimates for improved energy efficiency, assuming that there has been a general improvement in Power Usage Effectiveness (PUE) rating for data centers. The uncertainties about the influence of these different factors are compounded by further complexities. Koomey points out that the electricity consumption of individual servers is likely to have increased from his original study (based on IDC server data). This of course is a corollary of the growth in virtualization – while server energy consumption may have increased, virtualization has enabled more efficient use of that capacity. Koomey also points to a number of other areas requiring further investigation, namely the energy consumption of data storage and communications devices. He also highlights the issue of ‘comatose’ servers, which may further obscure the true levels of energy use.

Koomey’s aim is to give as accurate an estimate as possible on total energy consumption in data centers but he does not address the vital question of the productivity of data centers. I would suggest that the uncertainties he identifies and the issues raised by virtualization, cloud computing, and the weakness of PUE, all point to the importance of having better statistics on the workload efficiency of the data centers. Only when we have that information will be able to accurately assess the impact of data center energy consumption for good and bad.

One final insight from Koomey’s report is also worth mentioning. He has managed to elicit an indication from Google that its data center energy consumption is less than 1% of total worldwide consumption. A lesser number than some people imagined but for me it just confirms the idea that focusing on the special sauce of Google data centers is not the way forward for the majority of data centers when it comes to energy efficiency.

So where does this leave Pike Research’s estimates of data center energy use and potential for savings? With additional insight into the changes in energy use after 2006, we had already made some adjustments to our forecasts in our Green Data Center report. Our estimate for worldwide data center energy use was within Koomey’s new upper and lower ranges. For the United States, our forecasts on energy use is close to the original EPA numbers extrapolating energy saving trends from 2005 and above Koomey’s new upper estimate. So overall, I believe our model remains a useful guide to the further potential for saving if efficiency measures are adopted on significant scale.