What is Smart Green Energy 2.0?.|
Smart Green Energy 2.0 focuses on the use of IT to optimize all the information flows that regulate the sector’s value chain.
The aim is to contribute to the resolution of the objectives set for the coming years:
Generation vs. demand forecasting
Maintenance of remote farms and plants
Improvement of the information exchanged with the customer
Detection of anomalies in generation and equipment operation.
Unique data management among all the agents involved.
Balancing and control of the distribution network
Optimization of energy purchase and sale processes for defining offers
Early detection of possible energy consumption frauds.
Business intelligence for asset management
Sensorization of machines for remote control and fault detection
Data integration from stations or plants
Prediction of renewable energy production
& Data Analytics
Data-driven strategies for companies in the energy sector:
.| Discover the knowledge hidden in the data, from any source.
.| To do it in a collaborative way among all the participating agents.
.| Enable all levels of the organization to make decisions efficiently.
.| Employ AI capabilities to access hundreds of data visualizations in an intuitive way.
.| Reduce complex reporting and solution development times.
The energy sector generates huge amounts of data at every node of the value chain.
It is essential that data flow and converge among the participating agents to ensure transparency and process optimization.
The incorporation of Internet of Things (IoT) technology has generated needs in terms of infrastructure and data management.
Data mining provides tremendous optimization capabilities at many levels of the chain.
The Internet’s ability to connect with the customer creates a source of data and an opportunity for optimization.
Applied Artificial Intelligence .|
We are experts in computer vision solutions capable of analyzing the content of images and videos, with the deployment of data models in the cloud or on the Edge. Our models detect objects or people and allow text extraction in real-time.
Advanced Analytics & Machine Learning
We analyze data with statistical and advanced methods to obtain metrics and KPIs that provide better conclusions, allowing a complete view of the data and greater clarity for decision-making. In addition, we implement different Machine Learning and Deep Learning models to obtain future predictions and expectations.
What is anomaly detection?.|
IoT and Digital Twins
Sensorization and data processing .|
.| Sensorization of production equipment and plants produces a large amount of data.
.| Sent through the internet, they allow monitoring of the operation of each plant and each generation of equipment.
.| Centralized processing: ingestion, storage, and calculations performed on the information received through the internet.
.| This processing makes it possible to generate predictive models through artificial intelligence, aggregate information for dashboards, etc.
.| This, it is possible to analyze and optimize production and adapt it to current demand.
IoT in the energy sector.|
The IoT allows the storage and processing of relevant information for a park or generation center:
.| Machine operating and maintenance parameters.
.| Environmental information.
.| Presence control.
.| Generation parameters.
.| Distribution parameters.
Digital twins .|
The sensorization of distribution lines allows real-time monitoring of their status.
It allows immediate detection of faults without the need for technical intervention at any point in the network.
Allows modifying the load balance in the network before a complete failure, providing a robust operation.
All the data provided by the sensors can be presented in control panels that provide clear information on the status of the network.
Maintenance data analysis allows you to improve plans for any generation or distribution of equipment.
The system generates the maintenance task and spare parts orders automatically, without human intervention.
Connect the data received from the plants with the actions to be taken to optimize the supply and production chain.
Generate automatic generation balancing instructions to replace equipment scheduled to be shut down for maintenance.
Bravent helps you in the management and exploitation of your data.|
Definition and deployment of anomaly detection solutions.|
Analysis of detectable anomalies in your production system.
Assessment of the degree of criticality.
Definition of the appropriate detection models.
Deployment of AI architecture and models.
Deployment of detection systems, if applicable.
Connection with pre-existing detection systems.
Preparation of reports in PowerBI.
Evaluation of expected return.
Mixed Reality and its tools.|
Microsoft Dynamics 365 Remote Assist
Microsoft Dynamics 365 Remote Assist enables technicians to collaborate and troubleshoot with remote collaborators using Dynamics 365 Remote Assist for mobile devices or Microsoft Teams.
Microsoft Dynamics 365 Guides
Microsoft Dynamics 365 Guides is a mixed reality tool that allows employees to learn through interactive instructions.
Increase employee productivity by up to 25% through the use of available tools.
Improved training and preparation for complex tasks that require several steps for execution.
Quality assurance by providing a better service with a much better-trained workforce
Optimization of direct costs thanks to remote assistance that avoids the displacement of personnel and through employee training
Digitization and automation of processes will allow the standardization of most of the processes.
Digitization and automation of processes will allow the standardization of a large part of the processes.
Maintenance of resources in the electrical network.|
.| Visualization of the electrical network topology.
.| Data collection for each resource in the grid.
.| Definition of rules to generate alerts in case of significant deviations in performance or production parameters.
.| Predictive maintenance to reduce downtime and aggregate maintenance costs.
.| Increased safety control.
.| Reduction in failures of each equipment or plant.
Energy optimization and load balancing.|
.| Balancing energy supply and demand to relieve pressure on the grid, avoiding major outages.
.| Elimination of non-essential infrastructure expansion costs.
.| Incremento de la flexibilidad de la generación, empleando recursos energéticos distribuidos que optimicen el consumo.
Electric mobility .|
.| Deployment, remotely, of electric vehicle charging points, with different charging speeds and for different types of vehicles.
.| Simplification of the use of electric vehicles.
.| Increasing their purchase attractiveness.
.| Visibilization of the efficient use of energy, promoting the sustainability associated with mobility at the level of any user.
Emissions monitoring .|
.| Near real-time monitoring of emissions through sensors located both in cities and on vehicles.
.| Simple and highly visual presentation of data, enabling the sharing of information on carbon and greenhouse gas indices.
.| Support for the promotion of sustainability policies and the adoption of clean energy.
Benefits for the energy sector.|
.| Allows monitoring of the performance of grid assets.
.| Facilitates the optimization of distributed energy resources.
.| Enables reduction of operational costs.
.| Facilitates efficient use of energy across the grid.
.| Ensures the flow of data between all the actors in the sector.
.| Simplifies the balancing of supply and demand.