Hourly CO2 emission monitoring
Our Hourly CO2 Emission Monitoring feature enables organizations to track, report, and optimize their carbon footprint with unprecedented accuracy and granularity. Traditional Scope 2 carbon accounting relies on annual averages of grid carbon intensity, which can lead to significant inaccuracies in emission reporting and compliance risks. As the energy landscape evolves with the integration of renewable sources and advanced energy management techniques, such as energy storage and load shifting, a more precise method of carbon accounting is essential.
Key components:
- High-Resolution Data Collection: We connect to all energy sources to collect and predict precise carbon intensity factors on an hourly basis, providing a true representation of the carbon footprint associated with electricity consumption.
- Real-Time Consumption Tracking: The system monitors actual energy usage across different facilities and sources in real-time, capturing the nuances of consumption patterns for multiple buildings with diverse energy profiles.
- Source-Specific Carbon Intensity: For organizations utilizing multiple energy sources (e.g., grid electricity, on-site solar, power purchase agreements), our system accounts for the varying carbon intensities of each source throughout the day.
Benefits:
- More accurate quantification of Scope 2 emissions, potentially avoiding over- or under-estimation by up to 35% compared to annual average methods.
- Precise demonstration of the impact of carbon reduction initiatives.
- Ability to align energy consumption with periods of lower grid carbon intensity to maximize emission reductions.
- Support for the transition to a fully decarbonized electricity system by providing demand-side flexibility that complements variable renewable energy sources.
As we move towards a future where 24/7 Carbon-Free Energy becomes the gold standard, BH Grids' Hourly CO2 Emission Monitoring feature positions your organization at the forefront of sustainable energy management and carbon accounting practices.
Embrace the power of precision in your sustainability journey with BH Grids' Hourly CO2 Emission Monitoring – because every hour counts in the fight against climate change.
Frequently Asked Questions
Hourly CO2 Emission Monitoring by BH Grid Solutions tracks real-time energy consumption and the carbon intensity of different energy sources. This allows for precise emissions monitoring and reporting, enabling organizations to achieve more accurate quantification of their Scope 2 emissions, avoid compliance risks, and better demonstrate the impact of their carbon reduction initiatives.
BH Grid Solutions offers streamlined data integration, connecting with various energy management systems (EMS), building management systems (BMS), IT management systems, and industrial protocols like IEC 61850, DNP3, Modbus TCP/IP, and OPC UA. It also integrates with microgrids, renewable sources, smart meters, and external data sources, providing a unified platform for comprehensive energy management and environmental performance tracking.
Predictive carbon emissions management by BH Grid Solutions leverages AI to provide detailed forecasts of energy consumption and carbon footprints. This enables proactive optimization of workloads and facility operations, helping organizations reduce energy use during peak hours, adjust cooling systems based on forecasts, make informed decisions about renewable energy usage, and continuously improve energy management strategies.
BH Grid Solutions offers regulatory-compliant reporting and benchmarking capabilities. It generates comprehensive reports that ensure compliance with regulations such as the EU's Corporate Sustainability Reporting Directive (CSRD) and Energy Efficiency Directive (EED). The platform calculates standardized metrics, tracks Scope 1, 2, and 3 emissions, analyzes energy consumption, and provides benchmarking against industry standards, aiding enterprises in meeting ESG disclosure requirements and optimizing performance.
BH Grid Solutions uses advanced AI optimization algorithms, including reinforcement learning, model predictive control, and multi-objective optimization. These algorithms dynamically adjust operational parameters, predict future states, detect anomalies, and optimize workload scheduling and demand response participation. This results in significant reductions in energy consumption and carbon emissions while maintaining or improving facility performance and reliability.
Get Precise About Your Decarbonization Goals
Optimize carbon emissions and energy costs with AI-powered monitoring, prediction, and strategic planning for sustainable operations.