Working in a data-driven way is about understanding what has happened and being able to act in time before something happens. As power grids evolve, forecasting is becoming an increasingly important part of utility operations.
In previous parts of this series, we explored how to build a data foundation, visualize the current state of the grid, and work with KPIs. But to take the next step, from reactive to proactive management, you also need the ability to look ahead.
To understand forecasting, we need to start with the data.
There are three fundamental types:
- Historical data – shows what has happened and is used to identify patterns
- Real-time data – describes the current state and is used to correct deviations
- Forecast data – indicates what is likely to happen
No forecast is better than the data it is built on. In practice, successful forecasting requires a combination of all three.
Different forecasts for different decisions
A key insight is that forecasting is not one thing, it consists of several approaches depending on the time horizon.
Short-term forecasting – Managing grid operations
In the short term, forecasting is about understanding what will happen in the grid over the coming hours and days.
Using SCADA/RTU data, smart meter data, load profiles, and weather information, forecasts can be generated up to 48–72 hours ahead.
This enables utilities to:
- Analyze current and future load flows
- Identify risks of overloading cables and transformers
- Detect voltage deviations before they occur
Digpro’s short-term forecasting solution also presents forecasted deviations and alarms in advance, allowing operational teams to prioritize actions based on severity and the time remaining until threshold limits are exceeded.
The result is a shift from reacting to problems to preventing them—and operating closer to the grid’s capacity limits in a safe and controlled manner.
Long-term Planning – Planning the grid
Over longer time horizons, the focus changes.
Here, forecasting is not about operations but about understanding how the grid needs to evolve over time.
By combining project-based demand (such as new customer connections), statistical trends (such as transportation electrification), and scenarios representing high, low, and expected development, grid operators can analyze future power demand.
Digpro’s long-term forecasting solution calculates how demand will evolve over several years and allocates expected load growth across different voltage levels of the network, making it possible to:
- Identify future capacity constraints
- Compare alternative development scenarios
- Prioritize reinforcements and investments
This provides a structured, data-driven foundation for long-term grid development planning and supports both internal decision-making and regulatory requirements.
Connecting short-term and long-term perspectives
The real value emerges when these perspectives are connected.
Short-term forecasts show how close you are to capacity limits today, while long-term forecasts show how quickly you are approaching those limits in the future.
Together, they provide:
- Better prioritization of actions
- A shared view between operations and planning teams
- Stronger decision support for both operational and strategic decisions
This is where forecasting evolves from analysis into actual business management and grid governance.
Where does NIS fit in?
In a Network Information System (NIS) such as dpPower, the network model, structure, and all relevant data are consolidated within the same platform. Because the network model is already established, network structures and assets are already defined, and relevant data is readily available, utilities can work efficiently with both short-term and long-term forecasting.
With Digpro’s new Long-term Planning and Short-term Forecasting modules in dpPower, organizations gain the tools needed to move from reactive operations and planning toward a more proactive and data-driven way of working.
The data-driven power grid
Throughout this blog series, we have explored the key capabilities required to transform power grid operations from a traditional DNO to a modern DSO – from data foundations and visualization to KPIs, capacity planning, and forecasting.
Together, these capabilities create the conditions for better decision-making, more efficient use of resources, and more proactive grid management.
Wherever you are on your digitalization journey, we hope this series has provided inspiration, new perspectives, and practical ideas for taking the next step toward a more data-driven power grid.
Digpro is here to support you along the way with the experience, methodology, and solutions needed to turn data into operational value.
Thank you for joining us on this journey.
- From DNO – DSO – A journey that requires more than technology
- Data warehouse – Building the foundation with a Data Warehouse
- Dashboards – Visualizing information with a clear purpose
- KPIs – Managing by facts, not gut feeling
- Capacity planning – Planning for both operations and development
- Forecasts – Making decisions with the future in mind
Meet the expert
Erling Gustafsson has a solid background in the electricity industry and has supported many companies on their digitalization journeys. He is also the author of the Swedish book “Innovation och utmaningar i ett nytt energisystem: En guide för en proaktiv elnätverksamhet” (Eng.: “Innovation and Challenges in a New Energy System: A Guide for Proactive Grid Operations.”)