ENERGY WATCH #4 - August 14, 2018
Any self-respecting energy company needs to have state-of-the-art data management and analytics capability. That is hardly a secret. As McKinsey notes in a new article on their website, Building a great data platform, “such a platform acts as a central repository for all data, distills them into a single source of truth, and supports the scaling up of sophisticated digital- and advanced-analytics programs that translate data into business value. Companies without one risk leaving serious value on the table.”
I would say that “leaving serious value on the table” is an understatement. There is no future without big data management for utility companies that compete in the market.
Unfortunately, though, as McKinsey notes, “most energy and materials companies find themselves, in some way, lagging behind early digital adopters, like the retail, travel, and financial-services industries. Although many of these companies have had sophisticated data systems for years for some functions, such as for seismic imaging and processing in oil and gas and for flow visualization in transmission, they often struggle to connect disparate systems and data in an easily scalable way. Many have experienced frustrating complexity, some have suffered painful failures, and a few are still trying to figure out the first steps in building their own data platforms.”
Of course if you have trouble competing in the big data space as an energy company, you can turn to McKinsey to help you out. You can also use their free advice as given in this article.
McKinsey offers five main insights for energy companies looking to build out their data management capacity. I am sometimes a bit sceptical about McKinsey advice, but these insights seem to me not entirely obvious and eminently sensible:
Insight 1: Ensure everything you do starts delivering impact within six months.
Make “rapid return on investment” your watchword when selecting use cases. Leading companies achieve substantial impact fast with their platforms by being clear on which high-impact, quick wins to prioritize.
Insight 2: Us existing data to build in bite-size chunks
Build your platform piece by piece. Start with the data you already have and tackle the use case or end-to-end work flow that has the greatest opportunity for impact.
Insight 3: Deploy analytics only to solve real business problems
Plan and deploy your analytics platform to help you perform better. Apply it to real problems from day one.
Insight 4: Invest twice as much in your talent, culture and processes as in tools
Ensure you focus on people and processes, not tools. No matter how advanced the tool, it will be worthless without the talent and structures for managing and using it.
Insight 5: Democratize data across your business to catalyse innovation from within.
Gear your platform to democratizing data. Make data available to all your employees, teach them how to use the data, and see what unsuspected value they can unlock for your organization.
McKinsey concludes that “once upon a time, companies had to choose between making heavy investments in data infrastructure that didn’t start delivering benefits for a year or two and doing “skunkworks” data projects that drove short-term value but lacked staying power. Now, though, organizations can both have their cake and eat it—namely, drive value in months while simultaneously building a robust enterprise data platform that will serve the company for years. While doing this is no easy matter, the benefits of success considerably outweigh the costs and risks.”
McKinsey also recently looked at “the potential impact of electric vehicles on global energy systems”.
Many studies have concluded that the growth of EVs will not be a major problem for the grid or for our electricity systems. McKinsey confirms this view: EVs, it says, “are unlikely to create a power-demand crisis”. There will be limited need for new electricity generation capacity. However, they are likely to “reshape the load curve”, which will also not come as a big surprise to most readers.
Here is their projection for Germany:
This chart speaks for itself.
With regard to the load curve, “The most pronounced effect will be an increase in evening peak loads, as people plug in their EVs when they return home from work or after completing the day’s errands. However, at a system level, this effect will represent a relatively small percentage at most. Again, taking Germany as an example, we expect an increase in peak load of approximately 1 percent by 2030 and about 5 percent by 2050—increases that the system can likely absorb.”
Again, not a problem. However, McKinsey adds, “the changing load curve will lead to challenges at a local level because the regional spread of EVs will most likely vary—in some cases, significantly. McKinsey’s geospatial-analytics forecast of zip-code-level EV penetration shows suburban areas will likely become early EV-adoption hot spots. Therefore, even at still-low nationwide EV-penetration levels, local pockets with significant EV populations will probably emerge.”
“These residential hot spots and other concentration points of EV charging, such as public EV-fast-charging stations and commercial-vehicle depots, will see significant increases in local peak loads”, notes McKinsey. Nevertheless, “while significant, the peak-load growth in residential areas is not as dramatic as some assume. That is because while a single EV can easily double peak consumption at the individual-household level, the aggregation across many households (those with and without EVs) reduces the relative increase in peak load at a substation, even considering the effects of high-peak outlier days.”
Then there are the “highly volatile and spiky load profiles of public fast-charging stations”. These will also “require additional system balancing … a single fast-charging station can quickly exceed the peak-load capacity of a typical feeder-circuit transformer.”
Energy players have several ways to address this situation, notes McKinsey. “They can influence charging behaviour: for example, time-of-use electricity tariffs can give incentive to EV owners to charge after midnight instead of in the early evening.”
Alternatively, “energy players can deploy more local solutions, such as co-locating an energy-storage unit with the transformer that charges the unit during times of low demand. The storage unit then discharges at times of peak demand, thus reducing the peak load. Another option could be using a small combined heat-and-power plant, which could be an attractive solution if the generated heat has local uses (for example, heating a warehouse as it charges a fleet of delivery vans).”
“As the cost of batteries continues to decline rapidly, using energy storage to smooth load profiles will become increasingly attractive. Other applications include public fast chargers, depot chargers for electric buses and trucks, and residential settings where more EV owners combine rooftop solar panels and home storage.”
Indeed, according to McKinsey, companies should see the changes EVs will cause in the electricity system as opportunities to make money rather than as problems to overcome. “Centrally coordinated, intelligent steering of EV-charging behavior could create value in several ways”, notes the article. “First, it could allow even more effective peak shaving and thus greatly reduce the grid investments discussed. Second, it could allow a reshaping of the load curve beyond peak shaving to optimize generation cost (shifting demand from peak to base-load generation). And, revving charging up at times of excess solar and wind generation or throttling it down at moments of low renewables production could help to integrate a larger share of renewable power production. Finally, by providing demand-response services, smart charging could offer valuable system-balancing (frequency-response) services.”
The next step then could be “vehicle-to-grid plans, which not only shift the power demand from EVs but also make it possible for EVs to feed energy back into the grid under certain conditions. Pilot studies have shown a substantial willingness of EV owners to participate in coordinated smart charging. The total value created can be up to several hundred euros per EV each year, depending on local specifics.”