Energy
Energy
Energy consumption in AI systems is a significant consideration due to the computational intensity of many AI algorithms and the hardware required to run them.
- Solar Farms
Data from solar inverters and other components of a PV system is utilized for the purpose of fault detection and diagnostics. By analyzing various parameters such as voltage, current, temperature, and power output analytics, potential issues can be identified, alerts can be generated, and corrective actions can be suggested to operators and other relevant roles.
- Predictive Maintenance
By analyzing patterns and potential failure signatures, data can be utilized to predict maintenance requirements for solar inverters. This approach can effectively minimize unscheduled maintenance, decrease downtime, and optimize the lifespan of the inverters.
- Energy Forecasting
Forecasting solar energy generation for a specific PV system involves considering historical data, weather patterns, and other pertinent factors. This valuable information aids system operators, grid operators, and energy market participants in effectively managing energy supply and demand.
- Performance Optimization
AI has the capability to enhance the performance of solar PV systems by analyzing historical data, weather forecasts, and real-time monitoring data. Through the evaluation of various factors including solar irradiation, shading, temperature, and system configuration, AI algorithms can effectively optimize the operation of solar inverters. This optimization process aims to maximize energy generation and enhance the overall efficiency of the system.
- Grid Integration and Control
AI has the capability to facilitate the intelligent management of solar inverters, thereby aiding in the integration and stability of the grid. Through the analysis of grid conditions, demand patterns, and regulatory mandates, AI algorithms can effectively adapt the functioning of inverters to align with grid specifications, actively engage in grid services, and guarantee a consistent and dependable operation.
Engineering
- Consulting services for digital transformation.
- Data Analytics and Insights
- IOT Consulting
- Software Development and Integration
- System Architecture and Design
- Training and Support
- Application Engineering – Complete cycle Development – Test – Deploy – Integration
- Design Experience: Applications for Audio and Visuals.
- Product Engineering – Co Product Development, System Integration
- Platform Engineering – Migration to cloud /Microservices /benchmarking.