Navigant Research Blog

China Looks to Cap Energy Consumption

— March 1, 2012

In a webinar earlier this year, my colleague Kerry-Ann Adamson forecast that that governments will move toward a more prescriptive approach to energy policy.  In other words, they will not simply set broad efficiency or emissions targets but will specifically identify the clean energy technologies to reach those targets.  Examples are Australia, with its recommendations for distributed generation and solar power to meet energy efficiency goals, and the EU countries, which Kerry-Ann says will adopt increasingly prescriptive policies to achieve the EU’s mind-boggling goal of cutting carbon emissions by over 80% by 2050.

We can add China to that list, if reports are accurate that the country is considering putting a cap on energy consumption.  You read that right: a national cap on energy consumption.

It’s challenging to pin down details of this reported proposal.  From my reading of China’s 12th Five-Year Plan, which covers 2011 to 2015, the country is still focused on energy-intensity targets, not absolute caps.  The highlights from the English translation that I found are that, from 2010 to 2015, energy consumption per unit of GDP is targeted to drop by 16%, while CO2 emissions per unit of GDP will decrease by 17%.  Another major goal over the next five years is energy diversification.  The plan sets a target for non-fossil fuel resources to rise from 8.3% to 11.4% of primary energy consumption between 2010 to 2015.

Reports of the possible national cap seem to have come from public statements by officials at China’s National Energy Administration (NEA).  According to China Daily, in 2011 a National Energy Administration official said that China was considering a limit on energy consumption for localities, with a goal of “cap[ping] its total energy consumption at four billion tons of coal equivalent by 2015.“  Other reports confirm this.  It has also been reported that renewable energy will be excluded from the cap.

As yet, I have not seen an official policy announcement with details as to how the cap would be implemented.  Certainly the five-year plan goals confirm that China is hoping to shift from a pure growth mode to a sustainable growth model: the five-year plan also calls for a much less heated 7% growth rate in GDP to go along with the focus on decreasing energy intensity.  But setting a cap on the total energy consumption would be an extraordinary step, albeit one that seems to fit within China’s form of “communist capitalism.”  But in trying to build a more sustainable economy, China still faces many of the same pressures that capitalist democracies face.  For example, large swathes of the country have not developed to a modern standard of living and are not likely to be willing to slow their efforts to do so.  Moreover, energy consumption in China is dominated by coal, one of its few domestic energy sources, and it will not be easy to wean the country off this plentiful energy source.  The Guardian recently reported that the energy cap is provoking much debate from provincial governments that want to grow faster than the national government target would allow.  This will be a fascinating story to watch this year, and even more fascinating to see how China might implement a national cap should such a policy come to fruition.


IBM Tackles Transport Snarls in China

— March 1, 2012

IBM has announced its first major customer for the Intelligent Transportation solution it introduced last year. The project is with the Chinese city of Zhenjiang, where IBM is working with the local municipality to deliver an integrated transport management system as part of the “Smarter Zhenjiang, Smarter Tourism” project. Zhenjiang is a city of 3 million people in eastern China and is an important regional hub situated near the Yangtze River and the Grand Canal.

The new system is based on IBM’s Intelligent Operations Center for Smarter Cities (IOC) and will provide a real-time picture of the city’s traffic network with the aim of alleviating congestion, improving traffic management, and providing a better travel experience for citizens and visitors.

A core component of the project is a bus scheduling system that will help increase the efficiency of public transportation. The system will help Zhenjiang manage over 1,000 public transportation vehicles, over 80 city bus routes and 400 upgraded bus stations. A sensor system will collect data from smart devices in buses and bus stations and feed these to the IOC, where the data will be analyzed to help transit personnel adjust bus routes, frequencies, and bus station locations.

IBM China Research Laboratory is working with the city to create what it calls a Transit Route Network Optimization Planning System (TOPS). TOPS will provide a simulation platform for transit fleet and passenger flow on the network. It will draw on a variety of historical and real-time data sources and use predictive analysis to enable proactive management of the transport and transit system.

Amidst the stream of smart city project announcements, this one stands out for a number of reasons.

First, the project is concrete evidence of how China is looking to smart solutions to address the challenges of urban growth. Most analysis of the smart city market, including our own, presumes that China will eventually be at the forefront of smart city development, but to date, actual projects on anything approaching city-scale have been thin on the ground so far. Our report, Smart Cities, identified transport as the segment of the market where Asia, and particularly China, would grow fastest because of the impact of congestion on economic growth and sustainability. According to IBM, China is building more public transit systems than the rest of the world combined, and the country can’t cope with its rising transport demand without more intelligent management.

Second, the project builds on and develops some key innovations in transport management. This will be a state-of-the art system that not only monitors congestion but also uses predictive analytics to proactively manage traffic flows – through the routing of buses to meet demand and avoid bottlenecks, for example. Based on its work with Singapore and other cities, IBM claims its systems can now predict congestion build ups between 5 and 30 minutes ahead of problems arising, allowing traffic managers to take mitigating action.

Third, this is an early vindication for IBM of its IOC model for city management. The base of the system is the IOC platform, customized to meet the needs of the city and enhanced with the new capabilities being developed by its research arm in China.  IBM has the opportunity to build a positive feedback loop as innovations made in Zhenjiang feed back into the solution set and make it even more relevant to the issues facing other cities.


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