Smart Energy Management with digital twins

Digital twins in energy management

In today’s energy industry, digital transformation is becoming increasingly important. Companies face the challenge of optimizing energy efficiency, reducing costs, and operating more sustainably at the same time. empAI offers an innovative solution that goes beyond conventional data visualization. By leveraging artificial intelligence (AI) and the concept of digital twins, empAI enables precise analysis of energy data and reliable forecasts for optimal energy use. This allows companies to make data-driven decisions to manage energy consumption more efficiently and adapt flexibly to market changes.

The value of digital twins in empAI

The data model behind empAI is based on the concept of digital twins. This technology maps business processes (Behavioural Digital Twin) and energy flows (Energy Twin) using real-time data. By linking multiple data sources, empAI enables precise analysis, simulation, and optimization of these processes. The goal is to provide companies with a data-driven foundation for decision-making to efficiently manage energy consumption, generation, and costs. The technology is built on three core components:

1. Energy Twin – capturing and analysing energy-related data
2. Behavioral Data – considering operational processes and user behaviour
3. Environmental Insights – integrating external factors such as weather or energy prices

By combining these three areas, a complete digital image of a company’s energy landscape is created.

The energy twin – the foundation of energy analysis

The Energy Twin is the core of empAI. It collects and analyses all energy-related data to create a detailed view of a company’s energy flows. Data sources include:

• Consumption and generation data from sensors, smart meters, or directly from the distribution network operator
• IoT data that provides insights into the usage of individual machines and equipment
• Energy consumption analyses to identify optimization potential

Using intelligent algorithms, patterns are identified that enable more efficient energy use. The Energy Twin also offers detailed visualizations, helping companies understand exactly where and when energy is consumed or generated. This is particularly useful for strategic energy planning and integrating renewable energy into business operations.

Behavioural digital twin – how user behaviour impacts energy consumption

In addition to technical data, operational factors play a key role in energy optimization. empAI therefore integrates:

• Shift schedules and working hours to analyse energy use based on operational times
• Production processes and ERP data to link energy consumption with company workflows
• Employee preferences that can affect energy use, such as lighting or workspace temperature

Based on this information, empAI creates a Behavioural Digital Twin. This enables companies to take both technical and organizational measures to boost efficiency. For example, machine runtimes can be adjusted, or energy-intensive processes can be rescheduled to more cost-effective periods. By combining technical and organizational data, companies can develop targeted strategies to reduce energy use in a way that is both cost-effective and sustainable.

Environmental Insights: accounting for external factors

Energy demand is influenced not only by internal processes but also by external factors. empAI therefore takes into account:

• Weather data to forecast energy demand for heating, cooling, and lighting
• Holidays and vacation periods, which impact electricity use in many businesses
• Energy prices to develop cost-efficient procurement strategies

By integrating these external influences, companies can proactively respond to changing conditions. This is especially valuable for those using renewable energy, as it helps identify favourable times for using self-generated electricity or purchasing from the market.

Advantages of digital twins in empAI

The use of digital twins in energy management offers numerous benefits:

• Energy savings through data-driven optimization measures
• Accurate forecasts for better planning of future energy consumption
• Greater flexibility in responding to economic and environmental conditions
• Optimized use of renewable energy by more efficiently integrating self-generated power

By linking all relevant data sources, empAI enables a dynamic and comprehensive view of a company’s energy system.

Smart energy planning through digital twins

With the combination of the Energy Twin, Behavioural Digital Twin, and Environmental Insights, empAI is a powerful software solution that goes beyond traditional energy management tools and enables future-ready energy planning. The intelligent integration of technical, organizational, and external data forms the basis for data-driven forecasts and effective action plans.