IWB: Using machine learning to predict solar power production
Find out how IWB brings transparency to the low-voltage grid with SAP software, enabling it to achieve more active control and helping it take another step in becoming an intelligent sustainable enterprise. הורד את המסמךIWB: Using machine learning to
predict solar power production
Industrielle Werke Basel AG (IWB) is a utilities and energy solutions provider serving the
Basel region in Switzerland for over 150 years. The company offers electricity, heat,
drinking water, telecoms, and mobility solutions through a reliable, connected, and cost-
efficient infrastructure. IWB produces and sells renewable and CO2-neutral energy,
contributing to climate goals and its mission to achieve a fully renewable, climate-
friendly energy supply.
As part of its digitalization strategy, IWB was looking to adapt its grid infrastructure to
manage new photovoltaic power production and consumption, furthering its mission to
create a sustainable future. The goal was to configure prediction calculations that
automatically adapt to the increasing number of installed solar photovoltaic systems. By
bringing transparency to the low-voltage grid, IWB can achieve more active control,
helping it take another step in becoming an intelligent sustainable enterprise.
predict solar power production
Industrielle Werke Basel AG (IWB) is a utilities and energy solutions provider serving the
Basel region in Switzerland for over 150 years. The company offers electricity, heat,
drinking water, telecoms, and mobility solutions through a reliable, connected, and cost-
efficient infrastructure. IWB produces and sells renewable and CO2-neutral energy,
contributing to climate goals and its mission to achieve a fully renewable, climate-
friendly energy supply.
As part of its digitalization strategy, IWB was looking to adapt its grid infrastructure to
manage new photovoltaic power production and consumption, furthering its mission to
create a sustainable future. The goal was to configure prediction calculations that
automatically adapt to the increasing number of installed solar photovoltaic systems. By
bringing transparency to the low-voltage grid, IWB can achieve more active control,
helping it take another step in becoming an intelligent sustainable enterprise.
“The increasing number of decentralized solar PV systems
represents a challenge for planning and operating our
distribution grid. Without knowing how much power is
actually being fed into the grid, a grid-friendly control of this
renewable energy resource is difficult to achieve. The PV
load profile calculated by using machine learning
algorithms provides helpful real-time insight into the low-
voltage grid.”
Daniel Grossenbacher, Head of Asset Management, Industrielle Werke Basel AG
Industrielle Werke
Basel AG
Basel-Stadt, Switzerland
www.iwb.ch
(German)
Industry
Utilities
Employees
950
Revenue
CHF 1.3 billion
US$1.4 billion
Products and services
Electricity provision and
grid management
Featured solutions
SAP Datasphere, SAP Analytics
Cloud, SAP HANA Cloud, and
SAP Energy Data Management
>1,700
Solar plants installed
and adding 300 per
year
>8 hours
Added to forecast
horizon based on
weather forecast
Before: Challenges and opportunities
• Decentralized energy sources, with current and power flows monitored in a low-voltage grid to ensure
equitable power allocation
• An increasing network load requiring intelligent solutions to avoid overinvestment in network expansion
• Increased use of solar panels, electric cars, and heat pumps in the region, forming demand for solar-
powered alternative energy sources
Why SAP
• Advanced functionality to consolidate historical data and local meteorological forecasts offered by
the SAP Datasphere solution
• Digitalized analytics capabilities from the SAP Analytics Cloud solution, enabling clearer data
visualization across the enterprise and granular forecasts thanks to the ML engine in SAP HANA Cloud
• An accessible environment enabling real-time smart meter readings and centralizing load profile
calculations using the SAP Energy Data Management application
After: Value-driven results
• Improved meter readings and enabled smarter decision-making through centralizing data aggregation
and visualization
• Boosted overall sustainability metrics for the company and its community by supporting more
photovoltaic (PV) power units
• Improved power forecasting by aggregating historical data, current data trends, and meteorological
data
Improving sustainable power supply management by integrating
SAP Datasphere and SAP Analytics Cloud with other SAP applications
96000enUS (25/01) © 2025 SAP SE or an SAP affiliate company. sap.com/terms-of-use
represents a challenge for planning and operating our
distribution grid. Without knowing how much power is
actually being fed into the grid, a grid-friendly control of this
renewable energy resource is difficult to achieve. The PV
load profile calculated by using machine learning
algorithms provides helpful real-time insight into the low-
voltage grid.”
Daniel Grossenbacher, Head of Asset Management, Industrielle Werke Basel AG
Industrielle Werke
Basel AG
Basel-Stadt, Switzerland
www.iwb.ch
(German)
Industry
Utilities
Employees
950
Revenue
CHF 1.3 billion
US$1.4 billion
Products and services
Electricity provision and
grid management
Featured solutions
SAP Datasphere, SAP Analytics
Cloud, SAP HANA Cloud, and
SAP Energy Data Management
>1,700
Solar plants installed
and adding 300 per
year
>8 hours
Added to forecast
horizon based on
weather forecast
Before: Challenges and opportunities
• Decentralized energy sources, with current and power flows monitored in a low-voltage grid to ensure
equitable power allocation
• An increasing network load requiring intelligent solutions to avoid overinvestment in network expansion
• Increased use of solar panels, electric cars, and heat pumps in the region, forming demand for solar-
powered alternative energy sources
Why SAP
• Advanced functionality to consolidate historical data and local meteorological forecasts offered by
the SAP Datasphere solution
• Digitalized analytics capabilities from the SAP Analytics Cloud solution, enabling clearer data
visualization across the enterprise and granular forecasts thanks to the ML engine in SAP HANA Cloud
• An accessible environment enabling real-time smart meter readings and centralizing load profile
calculations using the SAP Energy Data Management application
After: Value-driven results
• Improved meter readings and enabled smarter decision-making through centralizing data aggregation
and visualization
• Boosted overall sustainability metrics for the company and its community by supporting more
photovoltaic (PV) power units
• Improved power forecasting by aggregating historical data, current data trends, and meteorological
data
Improving sustainable power supply management by integrating
SAP Datasphere and SAP Analytics Cloud with other SAP applications
96000enUS (25/01) © 2025 SAP SE or an SAP affiliate company. sap.com/terms-of-use
“By integrating SAP solutions, we can better forecast
photovoltaic power production and manage the low-
voltage grid, empowering IWB to adapt to increasing
renewable energy sources.”
Daniel Grossenbacher, Head of Asset Management, Industrielle Werke Basel AG
Power consumption patterns are changing due to the increasing adoption of electric
vehicles and heat pumps. Simultaneously, electricity production is becoming more
decentralized, with more households using solar photovoltaic (PV) systems. PV system
power production directly depends on the amount of sunlight individual units receive. To
accommodate these demand changes, Industrielle Werke Basel AG (IWB) sought to
combine current and historical data, cumulative power load profiles, and meteorological
forecasting data in an environment that would enable near-future production forecasting.
Intent on gaining insights into the diverse power sources in its grid, IWB saw the potential
offered by an interconnected suite of SAP solutions to achieve this aim. This included
SAP Business Technology Platform (SAP BTP), the SAP Datasphere and SAP Analytics
Cloud solutions, the SAP Energy Data Management application, and SAP BTP, Cloud
Foundry environment. By modernizing its approach to predicting power output, the
company aimed to enhance its ability to monitor currents in the low-voltage grid,
ultimately providing a more reliable power supply to its customers.
Using machine learning and integrated data to forecast solar power
energy
24x7
Calculation cycles
based on 163,000
values captured from
2022
photovoltaic power production and manage the low-
voltage grid, empowering IWB to adapt to increasing
renewable energy sources.”
Daniel Grossenbacher, Head of Asset Management, Industrielle Werke Basel AG
Power consumption patterns are changing due to the increasing adoption of electric
vehicles and heat pumps. Simultaneously, electricity production is becoming more
decentralized, with more households using solar photovoltaic (PV) systems. PV system
power production directly depends on the amount of sunlight individual units receive. To
accommodate these demand changes, Industrielle Werke Basel AG (IWB) sought to
combine current and historical data, cumulative power load profiles, and meteorological
forecasting data in an environment that would enable near-future production forecasting.
Intent on gaining insights into the diverse power sources in its grid, IWB saw the potential
offered by an interconnected suite of SAP solutions to achieve this aim. This included
SAP Business Technology Platform (SAP BTP), the SAP Datasphere and SAP Analytics
Cloud solutions, the SAP Energy Data Management application, and SAP BTP, Cloud
Foundry environment. By modernizing its approach to predicting power output, the
company aimed to enhance its ability to monitor currents in the low-voltage grid,
ultimately providing a more reliable power supply to its customers.
Using machine learning and integrated data to forecast solar power
energy
24x7
Calculation cycles
based on 163,000
values captured from
2022