Real-Time Optimal Power Flow under Wind Energy Penetration-Part II: Implementation

TL;DR

This paper presents a real-time optimal power flow method that dynamically updates operation strategies considering wind power variability, using parallel processing and short sampling intervals for improved grid management.

Contribution

It implements a prediction-updating approach for RT-OPF that efficiently handles rapid wind power changes with parallel computation and frequent updates.

Findings

Enhanced handling of wind power fluctuations in RT-OPF

Parallel processing reduces computation time

Improved economic and technical operation strategies

Abstract

In this paper (Part II) we implement the prediction-updating approach developed in Part I to address fast changes in wind power generation when solving a complex real-time optimal power flow (RT-OPF) problem. The approach considers essential scenarios around forecasted wind power values in a moving prediction horizon (120 seconds). The individual optimal power flow problems corresponding to these scenarios are solved in parallel using a multi-processor server. Then the operation strategy is updated in a short sampling time (every 20 seconds) considering real wind power values. The RT-OPF problem is formulated considering both technical and economic aspects simultaneously. The RT-OPF is implemented on a 41-bus medium-voltage distribution network with two wind stations. The results show the benefits of the proposed approach and highlight further challenges of RT-OPF.