Strojno učenje v pametnih omrežjih - Asian Utility Week 2019 · Strojno učenje v pametnih...

Quantifying the Future Impact of Demand Response: A Data Driven Approach

Miha GrabnerElectric Power Research Institute Milan Vidmar, Slovenia, Europe

Kuala Lumpur, 3. 9. 2019

Real Demand Response Project

Critical Peak Pricing - Peak shaving

Send notice one day before

DR event

Before DR Program

DR limited to 50 x 1 hour

SBS Data

Smart Metering Data

Substation Data Analytics

Substation Data Analytics

Clustering Substation Daily Profiles

50 hours of DR activations

Approx. 5 % annual peak demand decrease

Smart Meter Data Analytics

Targeting the Consumers using Clustering

Group similar daily profiles

Approx. 800 small consumers

Without equipment(SMS notification)

Installed equipment(Direct Load Control)

Estimating Baseline Load

Probabilistic Forecasting Backtesting

CONCLUSION

SMS Consumers: 0.25 kW/consumer

DLC Consumers: 2 kW/consumer

Mean Demand Flexibility per Consumer

DLC Consumers: 2300 EUR / consumer

Mean Annual Savings per Consumer

SMS Consumers: 6300 EUR / consumer

DLC Consumers: 23 EUR / consumer

Mean Annual Savings per Consumer

SMS Consumers: 9 EUR / consumer

Satisfied with the Project?

Very Satisfied Consumers!

Demand response is still for enthusiasts!

RECOMMENDATIONS

Hire a Trained Energy Data Scientist

RECOMMENDATIONS

Hire a Trained Energy Data Scientist

Evaluate Responses using ML

RECOMMENDATIONS

Hire a Trained Energy Data Scientist

Social Aspect is Most Important!

Evaluate Responses using ML

AI in Smart Grids