📇 The Project at a Glance
Distribution Operation Reinforced by Intelligent Switches (DORIS)
An intelligent grid automation system based on smart switches and distributed agents designed to reduce blackouts and improve power distribution management.
🏢 Start-up / Organization
EMAE (Beneficiary), HartBR (Technical Partner), and INESC P&D Brasil (Technical Assistance)
👤 Project Leader(s)
Raúl António da Costa Cravid (EMAE); Valdemira Carvalho (EMAE); Celso Lellis (HartBR); Luiz Eduardo de Antônio (HartBR); Mauro Augusto da Rosa (INESC P&D Brasil); Paulo César Rodrigues (INESC P&D Brasil); Talita Santos Alves Chagas (INESC P&D Brasil)
🌍 Country
Brazil, project developed in São Tomé and Príncipe
⚡ Energy Sector Segment
Grid management, grid automation, monitoring, and maintenance
🧠 Key Technology(ies)
IoT (LoRa, NB-IoT), SCADA integration, distributed intelligent agents (BDI architecture), smart recloser
📊 Status
Pilot and deployment
Hero
Company Overview
EMAE is a public entity with administrative and financial autonomy, under the supervision of the central government body responsible for the water and electricity sector in São Tomé and Príncipe. It is responsible for improving service quality through programs, studies, and the adoption of new technologies. EMAE operates across six districts of São Tomé and the Autonomous Region of Príncipe, serving 54,585 electricity customers.
HartBR is a technology-driven company with strong expertise in electronics, physics, and mechanics. It focuses on developing innovative products for the electrical sector, particularly for automation and protection of overhead distribution lines. Its manufacturing facility is located in Atibaia, São Paulo, Brazil.
INESC P&D Brasil is a non-governmental Scientific and Technological Institution (STI) organized as a private, nonprofit association. It collaborates with Brazilian universities and INESC TEC (Portugal) to deliver R&D&I projects and advanced consulting, focusing on translating research into impactful engineering solutions.
“DORIS represents an innovative solution that will optimize network management, improve the quality of electricity supply, and significantly reduce the economic and social impacts caused by frequent outages.”
Challenge
What problem is being addressed?
São Tomé and Príncipe faces significant challenges in operating and maintaining its electricity distribution network, including frequent blackouts, limited real-time monitoring, and high energy losses. In 2023 alone, the country experienced 38 total blackouts, resulting in estimated economic losses of €2–5 million. Power restoration is currently carried out manually, increasing downtime and operational costs.
Why this issue matters in the local energy ecosystem
Electricity supply instability directly affects economic activity and social development. It also weakens the reliability and efficiency of national infrastructure, limiting the country’s capacity to support growth and essential services.
The Solution
What does the project do?
The DORIS project deploys an automated electricity distribution management system based on intelligent recloser/sectionalizer switches integrated with IoT communication networks (LoRa and NB-IoT). These devices enable remote monitoring, fault detection, and automatic isolation of impacted grid sections. The system can autonomously reconfigure the network and restore power faster, improving stability and service continuity.
What makes it innovative?
The solution relies on distributed automation using intelligent agents structured under a BDI (Beliefs, Desires, Intentions) architecture, allowing devices to make autonomous decisions and restore service with minimal human intervention.
How It Works
In practice
The system operates through the installation of intelligent reclosers at strategic points across the distribution network. Each device interprets network conditions, detects faults, and coordinates with neighboring devices to isolate affected sections and restore service.
Tools / platforms / data used
- ArpeggIO server
- IoT connectivity (LoRa, NB-IoT)
- Self-powered operation
- Integrated geolocation
- Bluetooth 5.0 connectivity
- SCADA compatibility
- Weatherproof protection (IP65)
- LED signaling and mechanical flag
Technologies leveraged
- IoT communication networks
- SCADA integration
- Distributed intelligent agents (BDI architecture)
Who uses it
- EMAE grid operators
- Technical teams responsible for network operation and maintenance
Examples of field applications
- Autonomous network reconfiguration for faster service restoration
- Remote monitoring of equipment and grid conditions
Impact on the Ground
Tangible impact
The system enables faster fault detection and isolation, significantly reducing outage duration and improving the reliability of electricity supply.
Contribution to digitalization and resilience
The intelligent switches continuously monitor the grid and communicate through IoT networks such as LoRa and NB-IoT, enabling real-time remote monitoring. Integrated with SCADA systems, they allow operators to access operational data and manage devices remotely.
Devices can also react locally to faults without relying solely on control center commands, reducing response times and improving operational efficiency and reliability.
Key figures
- 54,585 electricity customers served by EMAE
- 38 total blackouts recorded in 2023
- €2–5 million estimated economic losses due to outages
- 37% aggregate losses in the electrical grid
Results so far
After the first seven months of the project, several milestones have been achieved:
- Detailed technical characterization of the electrical system, including generation, substations, voltage levels, and network topology
- Identification of critical network points and definition of integration requirements for intelligent devices
- Initial development of computational modeling, including database structuring and preliminary power flow analyses
What’s next
The next phase will focus on expanding computational analyses and finalizing criteria for selecting optimal installation points. In parallel, the development and integration of the intelligent agent architecture will begin, followed by simulation testing and preparation for field validation.
