Energy System Models for Data Driven Insights

An Energy System Model is a data-driven representation of the interaction of the components of an energy network. Historically, these types of models have played a vital role in strategy and policy formulation. The outcome of these models drives the policy recommendations coming from major global institutions. For example, the current discourse on the #energytransition features copious references to the modeling outcomes that underpin the global conversation.

In an article by Hafeez, Gulshan & Tahira, they compare the number of energy planning models applied in developed and under-developed countries between 1977 and 2019. Over this four-decade period, 642 energy models are captured in the article’s review, of which 75% have been applied within the context of a developed country.

Represented in the top-most chart, is the data from 1977 to 2019 between the developed and under-developed countries. I overlay this trend with that of oil price development over this same period.

Visually, the number of models roughly tracks oil price movement (with some lags observed). For example, between 2001 and 2009, oil price peaked at an average of $97/bbl in 2008 and then declined to $62/bbl in 2009. In this same period, the number of models developed tended to track oil price, but peaked in 2009, a year after the oil price peak.

The next oil peak occurred in 2011/2012 at about $111/bbl. However, it would take 4 years for the number of developed models to peak.

The second chart correlates the number of models (developed and under-developed countries) with oil price and two observations become clear. First, the number of models developed positively correlates with oil price for both country categories. Second, the steeper slope for the trend line of the developed countries shows that they are more responsive to changes in oil price than under-developed countries.

Rose M. Mutiso, Ph.D. has an excellent and brief article in Nature that corroborates the observations above and highlights the implications for underdeveloped parts of the world in the context of #energytransition. Rose M. Mutiso, Ph.D. makes the point that good data, appropriate [energy] models, and local technical expertise are essential in resolving the challenge implied in the graphics presented.