The massive electricity outage in India several weeks ago reminded me of a striking graph I saw recently. I have a soft spot in my heart for graphs. A picture is worth a thousand words, or a thousand data points, as the case may be.
The graph* depicts the relationship between energy demand and temperature in Delhi. The horizontal axis plots temperature and the vertical axis plots residual demand, which is basically an educated guess about what actual electricity demand would have been if the grid had been working right and could supply power to everyone who wanted it. The headline grabbing outage two weeks ago made many people aware of the importance of this adjustment, but in truth, there are nearly constant brownouts and blackouts in India, which explains why a number of hotels and hospitals were able to restore power with backup generators. The residual demand, plotted on the vertical axis, is also scaled to make it easier to compare 2000 and 2009.
What is most striking is the change in the relationship between temperature and electricity demand between just 2000 and 2009. In 2000, when temperatures increased from 20 to 40 degrees Celsius, electricity demand went up by about 16 million kilowatt hours. By 2009, for the same change in temperature, electricity demand went up by more than twice that amount: over 40 million kilowatt hours.
A large part of the explanation for this is that air conditioner sales in India have increased dramatically. One estimate suggests that air conditioner sales were growing at a rate of 20 percent per year in 2008.
The pattern depicted in this graph highlights several interesting phenomenon. First, it provides yet more evidence of the extremely rapid adoption of modern conveniences, like air conditioning, in developing countries, and the impact that trend is having on energy demand. I have written academic papers about how households’ energy use goes up dramatically when they enter the middle class and how this is driving extremely rapid growth in energy demand. I’ve also blogged about it here and here, highlighting how current forecasts seem to miss the impact of the rising middle class, and likely underestimate growth in energy demand in the developing world.
It is important to have accurate forecasts of energy demand so that governments and private companies have time to build the infrastructure to satisfy demand. The cause of India’s recent blackout will probably be debated for months if not years, but some have already suggested that it was driven by too much demand on the system.
Second, the graph highlights the importance of integrated assessment modelers, the people who combine models of economic factors, like increased energy demand, with climate models. Integrated assessment models can capture feedback, like what is suggested by the graph above. Simply speaking, as the globe gets warmer, people buy more air conditioners and run the ones they have more intensively. This causes the power plants supplying electricity to the air conditioners to emit more carbon, which makes the globe warmer, which causes people to buy more air conditioners…
There are active debates amongst modelers about how to capture feedback loops like this, but some of the conclusions are truly scary. The world could be very different in the not too distant future.
* My research assistant made the graph as a rough approximation to the figures reported in this paper by Eshita Gupta.
Catherine Wolfram is the Cora Jane Flood Professor of Business Administration at the Haas School of Business, Co-Director of the Energy Institute at Haas, and a Faculty Director of The E2e Project. Her research analyzes the impact of environmental regulation on energy markets and the effects of electricity industry privatization and restructuring around the world. She is currently implementing several randomized control trials to evaluate energy efficiency programs.