Quantum mechanics

Voltage regulator

Voltage reduction

Voltage

Engineering

Reliability engineering

Real-time computing

Operating system

Power (physics)

Computer science

Distributed generation

Physics

AC power

Volt

Simulation

Renewable energy

Electric power system

Leverage (statistics)

Voltage droop

Real Time Digital Simulator

Python (programming language)

Photovoltaic system

Machine learning

Electrical engineering

IEEE Transactions on Power Systems

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with a local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. Besides, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

Event-Driven Predictive Approach for Real-Time Volt/VAR Control With CVR in Solar PV Rich Active Distribution Network