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Nukissiorfiit: Strategic planning helps power the Arctic

01

4 min read

Greenland: A land of extremes

Kalaallit Nunaat — a land of extremes, a place of paradox — Greenland. At nearly 2.166 million square kilometers, most located above the Arctic Circle, Greenland is the world’s largest island. Though geologically part of North America, the country has been associated with Denmark, Norway and Iceland for a thousand years. And though only 26 km by sea from the northernmost island of Canada’s Nunavut territory, all routes to Nuuk, Greenland’s capital, run through Copenhagen or Reykjavík.

Color image of Sisimiut hydroelectric power plant
Photo Credit: Nukissiorfiit

Blanketed by the largest ice sheet outside Antarctica — more than 1.7 million square kilometers — and studded with some of the highest peaks in the Arctic, Greenland’s climate is harsh, its terrain forbidding, its beauty sublime. In this most sparsely populated country in the world, most of its 56,000 inhabitants live in isolated towns and settlements, hugging the western and southern fjords of its 27,000-mile coastline. A third of the population lives in the capital, Nuuk.

Providing energy and clean water to any locale, even in temperate zones, presents tough challenges. Engineering, constructing and maintaining utility infrastructure is complex, labor-intensive and costly, from building large power generation facilities — fossil, hydro, nuclear, wind, solar — to linking sprawling transmission networks into grids, maintaining equipment, and supporting persistent service. These and myriad other obstacles confront all utility enterprises, regardless of location.

Providing energy and clean water to any locale, even in temperate zones, presents tough challenges . . . The Arctic environment magnifies these complications dramatically.

The Arctic environment magnifies these complications dramatically. Like many remote circumpolar regions — Alaska, Canada’s Far North, the Russian Arctic — Greenland’s cities and towns are hundreds, sometimes thousands, of kilometers distant from one another. The arrangement of these far-flung, ice-locked communities reflects their ancient hunting-gathering cultures. Long accustomed to isolation and autonomy, they are well-equipped for the hyperlocal. With no land-based transportation infrastructure between towns and settlements — the country has less than 300 miles of roads, and a substantial number of them are gravel — all long-distance travel is by air or sea. These logistical trials have shaped Greenland’s utility ecosystem in ways that have prepared it to embrace the unique opportunity that renewable energy systems offer.

In the early 1970s, responding to escalating costs driven by the global oil crisis, Greenland began planning its transition away from fossil fuels — diesel and heavy fuel oil (HFO) — used to drive its power plants and generators. Over the next two decades, the government recognized that prohibitive transportation costs for importing and distributing fuel, environmental damage from oil spills, and a precipitous rise in greenhouse gases necessitated a new energy policy. In 1991, Greenland’s government assumed control of the country’s water infrastructure organization, Nuna-Tek, and the next year, renamed it Nukissiorfiit, a Kalaallisut word for “where energies are created.” Owned by the autonomous government of Greenland, by 1998 the company supervised all of the country’s water and electricity provision and has since then been the primary provider of electricity, water and heat to residents across 17 cities and 53 settlements.

02

5 min read

Continuous planning for vital infrastructure

Color image of Nukissiorfiit facility with solar array
Photo Credit: Nukissiorfiit

Nukissiorfiit contends with some of the most daunting utility engineering puzzles on the planet. The cost to move high-voltage bulk electricity over vast distances between relatively small communities is prohibitive. Greenland’s largest city and its capital, Nuuk, is home to a town-sized population of 18,000 residents; the country’s 77 other towns and settlements average between 100 and 1,000 residents, from 5,500 in Sisimiut to 11 in Kangerluk. Few of Greenland’s communities are large enough to sustain large-scale infrastructure common to urban areas in Europe or North America. With its communities spread far and wide, most of the island’s electricity must be generated as close to the point of consumption as possible.

In the 1980s, Greenland prepared a hydroelectric development program to end reliance on imported fossil fuel. By the early 1990s, following an Arctic-wide trend toward renewables, Nukissiorfiit launched a comprehensive plan to deliver hydroelectric power to larger communities in the country, opening the Buksefjord hydropower station in 1993. As with most infrastructure projects in Greenland, the facility is distinguished by groundbreaking milestones. Built to serve Nuuk, the plant is sited about 50 km away, across several fjords, embedded 600 meters beneath a mountain, with a 14 km-long tunnel connecting the power station to the reservoir lake. Glacial meltwater collected in nearby Kang Lake travels though this underground penstock to turn the plant’s three turbines. The facility generates 45 megawatts of power transmitted on the 53 km-long Buksefjord-Nuuk 132 kV power line, finally traversing the 5.38 kilometer-wide Ameralik Fjord, noted by Guinness World Records as the world’s longest overhead, high-voltage transmission span.

Few of Greenland’s communities are large enough to sustain large-scale infrastructure common to urban areas in Europe or North America. With its population spread far and wide, most of the island’s electricity must be generated as close to the point of consumption as possible.

Nukissiorfiit operates four other hydropower plants: one on the east coast, a 1.2 megawatt facility at Tasiilaq; in the south, at Qorlortorsuaq, to supply the towns of Qaqortoq and Narsaq with 7.2 megawatts of power; and two locations in the west, at Sisimiut, delivering 15 megawatts of power for heat and electricity generated from glacial melt at Lake Tasersuaq; and Paakitsoq, serving the city of Ilulissat, a completely autonomous facility operated remotely, generating 22.5 megawatts of electricity.

The five hydropower plants produce more than 70% of Greenland’s electricity. The remaining 30%, primarily comprising remote sites where bulk power generation and distribution are impractical, depend on diesel power generation. Most are actively transitioning to renewables, which are well-adapted to off-grid and microgrid installations. And although solar energy is an attractive option in the summer as a potential replacement for diesel and HFO, the island’s position mostly north of the Arctic Circle reduces access to enough sunlight to power through the long winter.

To move Greenland ever closer to its goal of zero carbon energy by 2030, Nukissiorfiit has piloted hybrid energy systems that combine solar, battery storage and wind with diesel electric as a backup. A pilot project at Igaliku combines solar cells and battery backup storage to complement a diesel generator plant to provide electricity for the village; the system can provide most of the energy from renewables throughout the summer. At Sisimiut, Nukissiorfiit hosts a center for small wind turbines to test their mettle in the harsh conditions of the Arctic. The turbines at the site have witnessed some rough storms and very cold weather, losing some blades but generating valuable lessons. Nukissiorfiit plans larger-scale wind farms in Nanortalik, and possibly in Sisimiut to complement the hydropower plant, which is at maximum capacity. Nukissiorfiit has also explored the island’s geothermal potential and experimented with a hydrogen cell facility for energy storage and may revisit hydrogen production or other e-fuel production technology in the future.

Color image of Nukissiorfiit hydroelectric power infrastructure
Photo Credit: Nukissiorfiit

03

8 min read

Annual planning consumed ~20% of the company

Maintaining continuous electrification in the far north demands exceptional strategic planning and execution. The physical discontinuity of Greenland’s utility infrastructure places greater pressure on Nukissiorfiit to fully optimize its operational systems. Because the company receives no financial support from the Danish government, operating its widely dispersed utility system with competence and economy is key to its survival, and keeping energy and water provision stable and affordable for Greenlanders. Achieving these goals includes the ability to create accurate financial projections to support existing operations and investment in new facilities.

“You have a small window in Greenland where you can make outdoor repairs or initiate a new infrastructure project or develop a new power plant,” says Claus Andersen-Aagaard, Chief Financial Officer (CFO) at Nukissiorfiit. “It’s very important that we have 100% visibility and the right insights to make a decision on whether we have the cash flow to do it.”

Color image of Greenland with Aurora Borealis
Photo Credit: Getty Images

Despite its forward-looking approach to energy production, Nukissiorfiit struggled with an antiquated budgeting process worsened by outdated tools. “The system we were working in was very rigid,” says Andersen-Aagaard. “We couldn’t plan with the flexibility we wanted. We needed certainty as to how our financial situation was developing and much more flexible, continuous planning to match the working environment we are in.”

You have a small window in Greenland where you can make outdoor repairs or initiate a new infrastructure project or develop a new power plant. It’s very important that we have 100% visibility and the right insights to make a decision on whether we have the cash flow to do it.

Claus Andersen-Aagaard
CFO, Nukissiorfiit

Locked by inflexible solutions into developing a budget once a year, Nukissiorfiit’s projections were outdated in six to eight months. Disparities in financial planning made initiating new projects difficult. The budgeting process itself demanded the input of 70 of Nukissiorfiit’s 400 employees, diverting precious attention from higher-value activities.

“Each October, 70 people in our organization spent a lot of effort producing a budget. When it came to May, we sometimes needed to revise the budget for the rest of the year because of significant changes in assumptions,” says Andersen-Aagaard. “This involved a substantial number of hours and effort. In reality, our business developed much faster than our budget could absorb when done once or twice a year. We looked at our budgeting process and could see that we used too many resources. At the same time, the output was limited in value.”

The company needed better solutions to manage its financial planning. Nukissiorfiit turned to IBM® Business Partner CogniTech A/S, Denmark’s leading IBM business analytics consultancy, to help it develop a budget planning solution. Ole Moeller Madsen, Chief Sales Officer and Partner at CogniTech, explains why it was vital for Nukissiorfiit to embrace advanced planning. “They had a lot of lag. Not having a precise forecast and budget, they didn’t know where they were headed, and what they had to act on.” Madsen knew that Nukissiorfiit financial analysts could benefit from AI-enabled planning and budgeting solutions.

Color image of Greenland city on a bay
Photo Credit: Getty Images

CogniTech invited Nukissiorfiit to an IBM conference in Stockholm. The conference provided the company an opportunity to preview new versions of IBM Cognos® Analytics, IBM Planning Analytics and other AI solutions to help the company modernize its budgeting processes. CogniTech conducted workshops to show Nukissiorfiit how to transition from existing planning and forecasting solutions to a new solution powered by machine learning and predictive modeling. “We pitched the idea of using AI and machine learning to improve the process,” says Kai Erik Ettrup, Partner at CogniTech, “and Nukissiorfiit bought in.”

“The inspirational sessions we had in Stockholm gave us the confidence to move ahead with the platform and the collaboration with CogniTech,” says Andersen-Aagaard. Among the features Nukissiorfiit required were an intuitive user interface with accurate input and verification processes. “To continuously incorporate the newest information, we needed to move beyond traditional budgeting and start working dynamically with our forecasting, using monthly rolling forecasts with a longer horizon of 18 months,” says Andersen-Aagaard. “And we knew the new process should not create a disproportionate burden on 70 people every month. We could see that with the more than 300 sub-budgets we were handling, we couldn’t expand this process and continue using the traditional way. We needed to think differently, and that’s where AI-driven rolling forecasts come into play.”

Color image of Hydroelectric power plant tailrace
Photo Credit: Getty Images

The inspirational sessions we had in Stockholm gave us the confidence to move ahead with the platform and the collaboration with CogniTech . . . We needed to think differently, and that’s where AI-driven rolling forecasts come into play.

Claus Andersen-Aagaard
CFO, Nukissiorfiit

CogniTech designed a solution and helped Nukissiorfiit adopt the IBM Cognos Analytics platform. The solution uses AI to support the analytics cycle, delivering the governed approach Nukissiorfiit needed to build accurate budget projections and make better business decisions.

Understanding how hundreds of ongoing projects impact each other is crucial to budgeting and planning in the short and long term. The ability of IBM Data and AI tools to deliver what-if scenarios enables Nukissiorfiit to envision how unforeseen circumstances — from weather to unexpected power interruptions — may affect all its operations. This foresight is crucial to budgeting and planning in the short and long term.

“For example,” explains Andersen-Aagaard, “if our people in the south of the country have a delayed project portfolio, are the expenses then coming in later, or is it delayed sufficiently that we can push ahead with other projects in the north? This can be quite a daunting planning task to manage when you have 100 to 200 larger infrastructure projects concurrently running.”

With the new solution designed and delivered by CogniTech, Nukissiorfiit uses automated machine learning and IBM Data and AI solutions to speed and share intelligent forecasts and outcomes across the business. The modernization of the company’s financial planning processes and systems enables it to make better business decisions and continue its push to reach 100% renewable power generation by the end of the decade.

Color image of a solar array
Photo Credit: Getty Images

The solution helps Nukissiorfiit develop a comprehensive, fully scalable, predictive modeling solution that comprises a dizzying array of data types. Types of data include total profit and loss (P&L) and cash flow statements, forecasting models on detailed turnover, site-specific variable expenses, capacity and maintenance costs, and the financial impact of project execution. And the company can factor in long-term weather data — a crucial variable in the Arctic — to forecast the turnover for electricity, heat and water, and its associated variable costs.

“We’ve been using a lot of weather data from the past three years,” explains Ettrup. “Then we use that to analyze what we call a normal weather period, to generate a normal year sale per customer, per area. We gave them a lot of back-end parameters so Nukissiorfiit could control numerous company-specific aspects, such as general vacancy, project completion rate, oil consumption per kilowatt, and much, much more.”

04

4 min read

AI infused forecasts across the organization

Nukissiorfiit now distributes forecasts across the organization, from financial planning experts and engineers to specialists working across Greenland’s remote locales. “We had a lot of considerations regarding how the solution could be architected to provide maximum credibility,” Andersen-Aagaard says. “Our financial books consist of a lot of areas, including turnover, variable costs, capacity costs, such as salary, depreciation, interest costs, and financial costs. All of these areas have unique properties. We were faced with the classic dilemma in budgeting that it’s difficult for people to incorporate all factors. A machine can handle this much better if historical data is extrapolated into the future.” The company has already set up more than 100 different reports that take various aspects of its financial information and provide it to the managers for their action.

Color image of wind turbine nacelle and blades
Photo Credit: Getty Images

“CogniTech helped us eliminate a tremendous amount of administrative work for our technical employees, who hardly took much joy in the task,” says Andersen-Aagaard. “They could confirm results from the AI rather than entering numbers from all locations and classifications manually. They were thrilled to be released from this task and the end result is much better, too. We were able to go from 70 different employees who are involved in the process of developing our budget down to nine people. So that’s quite a reduction,” says Andersen-Aagaard. “Saving time has been a huge factor and benefit for us. The old way, we’d probably be spending 5,000 to 10,000 hours to do this.”

The new solution frees Nukissiorfiit management to undertake more visionary planning decisions and embark on more ambitious infrastructure projects, fueling innovation and bold thinking.

I think it’s worth saying that whenever we do a big project such as the big hydroelectric plant project, you have to have confidence in us as a company. Greenland’s government must make sure that the money let us invest on behalf of the country is taken care of responsibly.

Claus Andersen-Aagaard
CFO, Nukissiorfiit

“One of the best things today is when an input provider is puzzled by the machine input and asks our controllers why the AI would forecast a certain figure contrary to the knowledge of the input provider,” says Andersen-Aagaard. “When they examine it further, they find out, more often than not, that the AI is correct because it takes all the factors and historical data into account. This makes me smile,” he says, “because then I know definitively that what we’ve created provides improved quality to our company and that we’ve saved money and time in the process.”

Looking forward, Nukissiorfiit anticipates incorporating Internet of Things (IoT) technology into the system. Given the huge distances between communities and power generation facilities, having remote sensing options offers a tremendous boon for gathering more accurate data quickly.

“I think it’s worth saying that whenever we do a big project, such as the big hydroelectric plant project, you have to have confidence in us as a company,” says Andersen-Aagaard. “Greenland’s government must make sure that the money they let us invest on behalf of the country is taken care of responsibly.”