CREATE DIGITAL TWIN
Use TIBO EMS platform to design a digital twin of your energy network
Connect your Digital Twin with your data. Monitor your assets and gain insights
Configure your objectives and run possible future scenario’s with future assets
Reduce energy costs & emissions with smart control of your assets
Smart Grid explained
Grid without Battery storage and without controlled assets
Any energy ecosystem without EMS will be subject of the demand for energy by consumers. Without smart management, heat pumps, charging stations, and other energy assets do not respect the energy prices during the day.
With TIBO Energy management the grid will be smart. We forecast energy pricing, imbalance and percentage renewable energy. We also forecast your energy consumption with smart algorithms.
Grid with controlled assets and battery storage, optimized to balance the network for costs efficiency and use of renewable energy
Design. Gain insights. Run Scenarios. Control
Take the lead in energy transition. We help you to achieve your goals!
A smart grid is all about the optimal mix and control of three essential types of energy assets in your energy ecosystem:
Note that some of your assets can be both or even all three. E.g. a a modern building consumes energy heating it, store energy with the heat present, and ‘create’ energy letting sunlight in.
But even when you have only one, you can make advantage of our EMS to gain insights and run scenario’s to make the best decisions and achieve your emission goals!
Complex ecosystems made easy
We will not bother you with complexity of the solution running in the background of our energy management system, but it’s all there!
A smart grid is a modernized and digitized version of the traditional electrical grid. We use advanced technology and automation to improve the efficiency, reliability, and sustainability of the electricity supply. In order to create a smart grid, a number of key components are typically needed.
Smart machine learning
TIBO energy management platform learns the behavior from all connected assets. We optimize the campus with deep knowledge of buildings, human behaviour and understanding of critical assets within the energy network.
Our algoritmes respond quickly and effectively to changing circumstances or new information. In our decision-making
process, decisions are made in a timely manner, based on the most up-to-date information available. This can help to ensure that the decision is appropriate and effective in the current situation.
With the use of machine learning the platform will forecast variables such as the expected solar and wind energy, the heat radiation on a building and the expected amount of EV’s that will charge in the next hour(s). The platform makes hundreds of decisions every minute with the latest forecasting scenario’s.
We aim to provide an optimal viewing experience for our users, offering them digital gridboard using familiar visual cues and patterns to guide you through the actions and decisions you need to make for your optimal smart grid.
A smart grid is a modernized and digitized version of the traditional electrical grid. It uses advanced technology and automation to improve the efficiency, reliability, and sustainability of the electricity supply. In order to create a smart grid, a number of key components are typically needed.
- Advanced sensors and monitoring systems to collect data about the flow of electricity on the grid.
- Smart meters and other technologies to enable real-time monitoring and control of electricity usage
- Advanced communication systems to enable the transmission of data and control signals across the grid
- Automation and control systems to manage the flow of electricity on the grid in real time
- Integration with renewable energy sources, such as wind and solar power, to help balance the supply and demand of electricity on the grid
Energy storage systems, such as batteries, to help balance the supply and demand of electricity on the grid
The smartest of them all!
Our algorithms are an important component of our energy management solution. They are typically used to analyze data about energy usage and identify patterns and trends that can help to optimize the use of energy.
For example, our algorithms are used to identify times when energy demand is high and adjust the use of on-site generation and storage systems to meet that demand. They also identify opportunities for energy conservation, such as by adjusting the operation of equipment or lighting systems to reduce energy usage during periods of low demand.
Additionally, our algorithms are used to predict future energy demand and adjust the operation of the energy management system accordingly.
Overall, TIBO advanced algorithms play a crucial role in the TIBO energy management solution, helping to improve the efficiency and effectiveness of energy usage.