Leveraging Microgrids for Capturing Uncertain Distribution Network Net Load Ramping

TL;DR

This paper introduces a robust optimization-based microgrid scheduling model that effectively manages distribution network load ramping caused by high solar PV penetration, reducing reliance on grid reinforcement.

Contribution

It presents a novel microgrid optimal scheduling model that captures load variability and uncertainties using mixed-integer and robust optimization techniques.

Findings

Model effectively mitigates load ramping issues.

Numerical simulations confirm model's efficiency.

Reduces need for grid reinforcement.

Abstract

In this paper, a flexibility-oriented microgrid optimal scheduling model is proposed to mitigate distribution network net load variability caused by large penetration distributed solar generation. The distributed solar generation variability, which is caused by increasing adoption of this technology by end-use consumers, is mainly addressed by electric utilities using grid reinforcement. Microgrids, however, provide viable and local solutions to this pressing challenge. The proposed model, which is developed using mixed-integer programming and employs robust optimization, not only can efficiently capture distribution network net load variations, mainly in terms of ramping, but also accounts for possible uncertainties in forecasting. Numerical simulations on a test distribution feeder with one microgrid and several consumers/prosumers indicate the effectiveness of the proposed model.