Energy Demand Dynamics in a Global and Interconnected World

By Aiman El-Ramly and Bruce Colquhounfor ZE datawatch

For energy commodities such as power, natural gas, and coal, weather was a principal driver of demand, and hence price. However, in a world that is increasingly interconnected, once predictable pricing patterns are becoming more nuanced.

Rarely have organizations in the energy and commodity markets faced so many fundamental shifts in the economic sectors underlying their business. Not long ago, commercialized markets followed the perceived rule of supply and demand. For energy commodities such as power, natural gas, and coal, weather was a principal driver of demand, and hence price. However, in a world that is increasingly interconnected, once predictable pricing patterns are becoming more nuanced. Globally fungible commodities are extremely elastic and can display regional idiosyncrasies. Every company is competing in a global market, no matter how regional they think their customers are. Under these circumstances, access to a diverse stream of data and the ability to efficiently interpret it is more crucial than ever.

Exploration and production technologies have recently played a major role in driving market price, and this driver of change is accelerating. For example, the cost of solar power is reduced by 30% with each doubling of panel production capacity, and wind by 7.4%. We have seen what happened to the cost of gas with improvements in fracking technology. The laggards are coal and nuclear, with the latter actually seeing its costs rise. Utilities in particular will be challenged by attempting to manage this transition in the energy mix, as power generation continues to be the largest consumer of energy supplies, and substitution between coal, gas, and renewables occurs, particularly during peak demand. Utilities must have extremely advanced abilities to manage this data underlying their purchasing decisions.

Communications technologies have also consolidated the markets. With no limit in bandwidth, process speed, or data storage, analysts and traders using these technologies are now able to analyze, correlate, and forecast infinite intra-commodity relationships to maximize their profits on commodity transactions and take advantage of arbitrage opportunities without the constraints of geography or time zones. And with options such as Software as a Service (SaaS) available, hardware is also not a constraint for analysts and traders who must have access to all the data they require to make informed trade decisions. As 90% of all the data ever created has been created in the last two years, and a fiftyfold increase is expected by 2020 (IDC), it is not surprising that many traders’ worldviews have changed dramatically in the last few years. Markets can expect this global interconnectivity to intensify. As the global data repository grows exponentially, those who are able to quickly extract trends and key observations will experience market success—that is, the proverbial wheat pulled from the chaff (this is a favorite ag quote).

It is clear that accessing and storing market and internal data is a significant and growing challenge; however, this is not the lynchpin to corporate success. It is an analyst’s world, and with instant access to data, there are instant supply and demand effects. The biggest players, whether corporate or political, know this, and are constantly jockeying to best their competitors in data management and analysis. They are investing heavily in the data and analytical tools they need to make proper market assessments and avoid costly mistakes. In the end, they hope to map the inter-dependencies between energy and commodity markets to make more timely and accurate decisions. These organizations understand that success will not be the result of sifting through the exhaust of big data, but will be the result of meticulous data mapping that incorporates fuel substitutions, infrastructure constraints, market distortions, and supply shifts—data mapping upon which models and simulations can be built. Integrated energy curves, not individual fuel and technology cost curves, will prove to be a more accurate determinant of price.

The shale gas technology ripple is an example of the ways in which those who can visualize the connections that exist between all world commodity markets can recognize risks and opportunities more clearly. Recently, gas displaced coal in the U.S., and the U.S. increased coal exports to Europe to displace gas, which was itself feeling the squeeze from renewables, despite nuclear shutdowns. View the impact on pricing in Figure 1: Henry Hub Natural Gas Prices vs. CAPP Coal Prices.


Figure 1: Henry Hub Natural Gas Prices vs. CAPP Coal Prices

In hindsight, this ripple effect seems obvious, but at the time, many were surprised by the impact that a once regional energy asset (U.S. gas) was having globally. To view an example of the impact gas has had on oil prices, see Figure 2: Henry Hub Natural Gas Prices vs. Brent and WTI Oil Prices.


Figure 2: Henry Hub Natural Gas Prices vs. Brent and WTI Oil Prices

New market scenarios like the one described above continuously reshape the energy landscape, and if organizations could make strategic decisions with the benefit of hindsight, market dislocations would not be an issue. This is not the case, though. The reality is that many organizations live and die by their ability to collect, process, and effectively act upon the plethora of internal and market information in a timely fashion, as information arises.

As gas prices fall and rise, fuel switching affects alternate fuels such as coal, LNG, and oil. This in turn drives prices for agricultural products and metals. Recently, dramatic evidence of commodity connectivity was seen in highly elastic crops such as corn and soy, which can be used for food or energy production. This is shown in Figure 3: Corn, Ethanol, Henry Hub Natural Gas, and Brent Oil Prices.


Figure 3: Corn, Ethanol, Henry Hub Natural Gas, and Brent Oil Prices

When energy prices soared in certain regions, gas tanks were filled and mouths went hungry. As witnessed during the Arab Spring and the Ukrainian uprising, hungry people with high energy costs quickly get angry. Their anger, as in the instances mentioned above, can have dramatic global ramifications, both politically and on commodity markets.

Meanwhile, energy-intensive industries that can take advantage of cheap gas are presently doing so, while those tied to the price of oil see no respite in costs. One sector that is seeing a major geographical shift in production is the petrochemical business, which is eyeing an abundance of low cost NGLs in North America set to grow for the foreseeable future. The shale effect has been so strong that even with falling prices for shale products, margins for many products (for example, ethylene) have hit record highs.

This is just the tip of a U.S. manufacturing renaissance that could add $80-120 billion in economic output according to Boston Consulting. However, possibly large structural adjustments will have to be made to the large petrochemical industry in Asia and Europe.

These shifts in global energy markets are not occurring in a vacuum, as the rebalancing of energy demand from West to East and the geopolitical ramifications that will occur as a result add further volatility to markets. By 2015, the Asia Pacific region will account for 38% of the world’s energy consumption, up from 27% in 1995. In addition, China recently surpassed the U.S. as the world’s largest oil importer. China’s imports of other commodities such as iron ore, copper, coal, and soy also hit record highs earlier in the year, even in the face of a slowdown in manufacturing. China’s importance in so many commodity markets will likely add to the cyclical nature of each of them, and any signs of weakening in the Chinese economy will send shudders through these markets.

The China effect will only add to the complexity of risk calculations underlying investments in the energy sector—for example, LNG export terminals, as China, Japan, and South Korea have become disproportionate targets. View Figure 4: Mont Belvieu Ethane (OPIS) Swap Prices vs. Japan C&F Naphtha Prices.


Figure 4: Mont Belvieu Ethane (OPIS) Swap Prices vs. Japan C&F Naphtha Prices

Should China develop its shale formations as rapidly as it hopes and Japan reverse its moratorium on nuclear power, there may be a lot of LNG looking for a new home at prices lower than anticipated. China’s attempt to wean itself off of coal, while toothless at the moment, may gain momentum due to environmental concerns putting added pressure on coal exporting companies in Australia, Indonesia, and the U.S.

Competition among the various economies in Asia for energy will only add to volatility, as was recently witnessed when China set up an oil rig off the coast of Vietnam, an act which sparked protests in that country. If China enforces more assertively their claims in the South China Sea, which extends as far south as Malaysia, then sporadic crises will become more common. The underlying risk in this scenario is an escalation into broad regional conflict. These conflicts might, in turn, push China to bolster its strategic oil reserves, which will have an immediate effect on spot prices.

In light of this multifaceted interplay, tools that can effectively generate and manage complex curves—tools such as ZEMA–will become indispensable to organizations that must dynamically monitor the pricing of both raw inputs and finished products. Organizations–whether a utility in Germany juggling its energy mix, or a petrochemical facility in Asia looking at its fundamental raw material costs–must feed models that accurately reflect dynamic markets with data and curves. With time, new drivers of pricing will again cause structural shifts in the energy markets, and those organizations that have built resiliency and dynamism into their data, trade, and risk systems will more effectively take advantage of the arbitrage opportunities that will emerge.

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