IEEE Power & Energy Magazine - May/June 2018 - 68
in 2007, the U.s. congress approved the energy independence and security act of 2007, which provided an official
definition of the smart grid. soon after that, billions of dollars from both public and private sectors were poured into
the electric grid, including millions of dollars dedicated to
power systems research. suddenly the field of power engineering became hot again. Many U.s. universities started
to build or rebuild their power engineering programs. student enrollment went up. The ieee power & energy society (pes) membership increased by more than 50% within
the last decade. registrations to major power conferences,
such as the pes general Meeting, were setting record highs.
researchers from other electrical engineering concentrations and even outside electrical engineering departments
were rushing into the field of the smart grid.
in 2014, IEEE Transactions on Power Systems published
another special section on power and energy education to
document the new courses, laboratories, curricula, outreach
activities, and pedagogy developed both in academia and
industry during the past few years. while it seems that our
industry is surviving the workforce crisis through this wave
of grid modernization efforts, we are, in fact, just stepping
into another battle.
in January 2017, the Quadrennial energy review (Qer)
Task force released its second installment, where one chapter was devoted to the changing needs and new opportunities
of the electricity workforce of the 21st century. The task force
confirmed the workforce gap and the challenge due to baby
boomer retirements. it also highlighted the "new business
* Chowdhury, "Power Engineering
Education at the Crossroads," IEEE
* Heydt and Vittal, "Feeding Our
Profession," IEEE Power & Energy
* Sauer et al., "Special Section on
Power Engineering Education,"
IEEE Transactions on Power Systems
* U.S. Department of Energy, "Workforce
Trend in the Electric Utility Industry"
* Energy Independence and
Security Act of 2007
* Pahwa et al., "Special Section on
Power and Energy Education,"
IEEE Transactions on Power Systems
* QER Task Force, "Second
Installment of the QER"
figure 1. A time line of evaluations of the electricity workforce crisis.
ieee power & energy magazine
and employment opportunities" that will "require a wide
array of new skills." along this line, the task force suggested, "The electricity industry will need a cross-disciplinary power grid workforce that can comprehend, design, and
mange cyberphysical systems; the industry will increasingly
require a workforce adept in risk assessment, behavioral science, and familiarity with cyberhygiene."
Role of Analytics in Electricity
The word "analytics" showed up in most major topics of the Qer,
reflecting an emerging need for it across a wide range of business
functions in the power industry, such as grid management, clean
energy, marketing, and customer engagement. on grid management, for example, analytics can help enable more precise, timely,
and predictable consumption responses to system signals so that
the focus can go beyond peak mitigation to grid reliability. overall, the Qer recognized "operational and predictive analytics" as
a "core investment" required to "achieve a clean, affordable, and
reliable electricity sector for the 21st century."
The Utility analytics survey published in June 2017 examined the issues and trends shaping how utilities deploy data and
analytics to achieve business goals; 136 utilities from 24 countries responded to the survey. as shown in figure 2, out of nine
analytics application areas, energy forecasting was recognized
by 52% of the respondents as a high priority, the highest among
all. when asked to pick one most important high-priority area,
20% selected energy forecasting, again, the highest among
all. This was followed by smart-meter analytics, with 50%
considering it a high priority and 17% picking it as the most
The survey also showed that utilities have high expectations
for return on investment from forecasting. with the arrival of
more detailed smart-meter and weather data, along with sophisticated computing architectures, many utility leaders have
turned to energy forecasting for improved bottom-line results,
particularly in today's era of flat or declining energy consumption. numerous studies have shown that a forecast error reduction as small as 1-2% can yield millions of dollars in savings for
a medium or large utility.
To address the analytical challenges in energy forecasting,
pes started a working group on energy forecasting in 2011,
which then organized three major forecasting competitions,
global energy forecasting competitions 2012, 2014, and 2017.
These competitions attracted thousands of participants from
different business sectors across the globe to tackle emerging
forecasting problems in the energy industry. The data sets and
models used in the competitions are now being used as popular
benchmarks in both industry and academia.
when asked which area will have the biggest positive
impact on their business, 22% of the respondents mentioned
customer experience. grid-specific applications such as forecasting/predictive analytics earned second place with 20% of
the responses. The disruption to the traditional customer relationship has created an urgency in reinventing it. retaining