Renewable energy sources will power the future of a viable new energy economy. The urgency to address climate change and sustainable human development and the need for cleaner energy sources become more evident with each passing year. It is the challenge and opportunity of our time.
Environmental data science, the smart grid, and energy storage lay at the heart of this possible social and technical transformation. We’ll need analytics and Big Data to build predictive models for energy demand, supply, and pricing (time-series forecasting), so we can then use these models to suggest optimal policies and behaviors.
Therefore, data scientists will play a critical role in economic and environmental sustainability for decades to come.
Energy Economics, History, and Human Progress
Harnessing energy through technology to do work is a defining trait of humanity. Energy utilization powers nearly all human endeavors. From controlling fire and beasts of burden to the long-dead fossils of plants and animals to the unseen atom, the chronicle of human civilization is marked by energy transformation.
Historically, the two most significant of these shifts were arguably reining fire and the industrial revolution. We now enter the renewable revolution. Our future almost certainly depends on how successfully we adopt and manage non-extractive, renewable energy sources to power civilization.
The good news is that renewable generating capacities, particularly for solar and wind, have climbed exponentially over the past decade. This growth reflects what Energy Central describes as a coming “boom” in renewable energy deployment.
Nonetheless, technical and social evolution on such a grand scale does not come without significant challenges.
The Smart Grid and Energy Storage
The smart grid and energy storage are essential for renewable energy to reach its full potential, says Chris Healey, Data Science Lead for Schneider Electric and an adjunct professor in data science and analytics at Merrimack College.
Healey describes the smart grid as “the combination of hardware and software allowing the ability for utilities, consumers, and solution providers to optimally allocate electricity and shape behavior for cost, efficiency, and sustainability benefits.”
In other words, the smart grid integrates every aspect of electricity generation, transmission, distribution, and consumption as efficiently, fairly, and cost-effectively as possible. It does this every second of every day, learning how to do it better as it goes.
A common criticism of renewable energy is that it doesn’t work when the sun isn’t shining, or the wind isn’t blowing. As renewable technologies become less costly and more efficient, the greatest technical bottleneck becomes grid-scale energy storage. The idea is simple in its concept: capture the energy of the sun or wind for later electrical distribution. But it’s easier said than done, especially at scale.
“For effective decarbonization of our grid, we have to be able to integrate and price renewable energy sources. Energy storage plays a crucial link in matching uncertain supply to uncertain demand,” says Healey.
Data is at the core of this evolving, complex, and networked energy system. “These days, software and cloud platforms are critical to the effective operation of any piece of hardware, providing better value and more resilient operation. Energy storage is no different.” To that end, data science and analytics are “critical for the sustainability, efficiency, and resiliency of our grid.”
Market Opportunity: The “Roaring 20s” of Energy Storage
The “bottleneck” characterization of energy storage should quickly give way in the next ten years as a game-changing technology.
“The best is yet to come,” states the title of an article authored by Darrell Proctor in the energy industry blog Power. “The need for storage is considered paramount to the electrification of transportation and other businesses and continued growth in renewable energy,” says Proctor. The rest of this decade will be the “roaring 20s” for renewable energy storage technology. “The 2020s will be a breakout decade for the energy storage sector,” says Ryan Brown, CEO of Canada-based Salient Energy in the Power article.
In another recent article, CleanTechnica reports on the latest Storage Futures Study from the National Renewable Energy Lab (NREL) entitled Economic Potential of Diurnal Storage in the U.S. Power Sector. That report, according to CleanTechnica, shows that “storage adds the most value to the grid and deployment increases when the power system allows storage to provide multiple grid services simultaneously and when there is greater solar photovoltaic (PV) penetration.”
Installed grid storage capacity is forecast to grow five-fold through 2050, to as much as 680 gigawatts.
An Inflection Point: At The Crossroads for Energy Development
The nexus of technology, economics, and what Ryan Brown calls an “increasingly favorable regulatory environment” make the present moment a crossroads for energy development.
The cost and the intelligence of energy solutions will make it easier for the smart grid to reach its true potential,” says Healey.
Our energy future is at an inflection point. It may have been a long time coming, but, like the Apollo program of the 1960s, there is no better time for talented, creative, and motivated professionals to apply their skills and talent to help change the world.
M.S. in Data Science: Help Shape the Future of Energy
The online Master of Science in Data Science degree program from Merrimack College gives professionals the skills they need to help shape the future energy economy.
The industry-aligned program consists of an eight-course, 32-credit-hour curriculum. Leading industry experts (like Chris Healey) teach each course. Instruction combines self-paced learning with live, online instructor-led sessions.
Courses include:
Foundational Courses
- Foundations of Data Management
- Foundations of Statistical Analysis
- Data Visualization
Intermediate Courses
- Data Exploration
- Data Governance, Laws & Ethics
Advanced Courses
- Predictive Modeling
- Machine Learning
- Data Science Capstone
Make Your Mark in Data Science for the Environment
The M.S. in Data Science program is a collaboration between Merrimack’s School of Science and Engineering and the Girard School of Business. This cross-pollination gives graduates the data science and engineering skills of the trade, plus the business acumen to translate data into stakeholder insights.
Graduates emerge from the curriculum with the theoretical concepts and practical skills the energy sector needs right now in our rapidly changing times.
“Companies are seeing sustainability as a differentiating value in their systems and solutions,” says Healey.
“Businesses are starting sustainability initiatives for many reasons: as a means to attract business, make a difference in climate change, and to engage talented young employees,” he says.
“Energy companies are just starting to develop their data science and analytics competencies, providing a lot of projects and opportunities for new students. At Schneider Electric, we have a college innovation program called ‘Go Green in the City’ offering students an opportunity to pitch sustainable ideas.”
There is no easy path toward a decarbonized, renewable-based energy system. All forms of relatively clean energy production methods must coalesce into an efficient, dependable, fair, and affordable system. If there is a “silver bullet,” we will find it in the data. We need data scientists to help point the way.