One of the fastest growing agency
We design and develop web and mobile applications for our clients worldwide.
Research
Neurobotz AI Blockchain for Renewables and Energy Efficiency
The research aims to aggregate and control building level demand curve to satisfy grid level demand response needs based on Smart tariff (most cost-effective power utilization).
Use a Blockchain technology for smart contract for Demand response event and Increase utility-consumer communication via Blockchain gateway for carbon credit and payment remittance based on ADR (Automated Demand response). The approach uses a Fully automated AI based Smart power optimizer with predictive Demand response AI algorithm that gives flexibility to control and save building level KW utilization up to 20%. The Intelligent algorithm with further Integration of Storage devices and solar PV components would charge at non-peak tariff and deliver Solar priority kva compensation (solar + storage + grid) on peak tariff that could save an extra 15% to consumers.
The Blockchain framework will initiate an automated smart contract that gets further approval from the consumers. The Blockchain infrastructure will capture before and after consumption data to calculate the savings based on solar PV, Energy efficiency interventions and DR events. Then the Blockchain gateway will automate to send out carbon credit, savings remittance and updates the consumer portal.
Blockchain framework for Energy Savings
We'll notify you
You will receive a phone call, email or text, usually the day before utillity company's Energy Savings Day
Reduce Your use
Use less electricity between the time periods indicated by the utility company on an Energy Savings Day
Earn Rewards
Within a few days, you will be notified by phone, email or text to let you know about your savings and cash rewards.
Human-in-loop: The process keeps human in loop where the consumers should be notified ahead of the Demand event or energy savings days.
User Comfort: The consumers can reduce their electric consumption only by not operating high consuming loads like Water heater, pool pump, Dasher/dryer, dishwasher, Oven etc. during demand event. Also, they should plan to program thermostats based on the energy savings event which impacts user comfort.
Health safety: By setting a thermostat to an above average (◦F) during peak tariff and changing it back to normal could lead to health problems
Research Impact
Success of an Automated Demand response programs depends on human-in-loop inclusion approach by constantly educating the consumers to take advantage of effective power utilization based on smart tariff without losing their comfort. Our project aims not just to automate the power optimization scenario and reduce stress on the grid infrastructure but also create a framework for consumers to predict, participate and understand the logic behind power utilization and savings on demand response program. Blockchain framework will help to better communicate via a secured platform and modernize the way we utilize power.
Predictive Maintenance
To create a process that solves the preventive maintenance related issues need to Incorporate, integrate or reuse Sensors including CTs, Vibrational, and Airflow for Key equipment’s such has heavy blower, large compressor which supply air for floor operation.
This help to derive a predictive maintenance on these equipment’s which includes optimal operation efficiency, motor deteriorating factors/failure rate, Current increase due to system vibration exceeding the threshold value.
An advanced hardware with high frequency metering, controller and Sub-Ghz Radio Frequency (RF) communication framework to log the energy data with sampling rate of 4-5Khz. The hardware which will be able to measure parameters including Voltage, Ampere, Power Factor, and Harmonics The equipment has embedded programming to deduct the sampling rate of 4-5Khz and using Sub-Ghz RF communication framework, that is able to send and receive signal up to 3 Miles.
Designing an algorithm to understand the pulse or signature of major building equipment (Heating Ventilation and Air-Conditioning (HVAC), Water heater, refrigerator, lighting, etc.) and compare the equipment’s signatures health (anomaly detection vs signature in normal operation)
An algorithm to separate major load consumption and its deterioration data based on the equipment’s signature. Creation of Json file with the comparison dataset OnDemand basis.
Preventive maintenance analytics framework
