# Arbitrage with Power Factor Correction using Energy Storage

**Authors:** Md Umar Hashmi, Deepjyoti Deka, Ana Busic, Lucas Pereira, Scott, Backhaus

arXiv: 1903.06132 · 2020-01-14

## TL;DR

This paper presents a method for jointly optimizing energy storage to perform energy arbitrage and power factor correction, demonstrating that reactive power compensation can be achieved without sacrificing arbitrage profits, using real data and real-time control.

## Contribution

It introduces a non-convex joint optimization approach for energy arbitrage and power factor correction, solved efficiently with relaxation techniques, and develops a model predictive control policy for uncertain real-time operation.

## Key findings

- Energy storage can correct power factor locally without reducing arbitrage profit.
- Active and reactive power control are largely decoupled for arbitrage and power factor correction.
- Look-ahead in online control has limited impact on power factor correction, but affects arbitrage profits depending on battery ramp rates.

## Abstract

The importance of reactive power compensation for power factor (PF) correction will significantly increase with the large-scale integration of distributed generation interfaced via inverters producing only active power. In this work, we focus on co-optimizing energy storage for performing energy arbitrage as well as local power factor correction. The joint optimization problem is non-convex, but can be solved efficiently using a McCormick relaxation along with penalty-based schemes. Using numerical simulations on real data and realistic storage profiles, we show that energy storage can correct PF locally without reducing arbitrage profit. It is observed that active and reactive power control is largely decoupled in nature for performing arbitrage and PF correction (PFC). Furthermore, we consider a real-time implementation of the problem with uncertain load, renewable and pricing profiles. We develop a model predictive control based storage control policy using auto-regressive forecast for the uncertainty. We observe that PFC is primarily governed by the size of the converter and therefore, look-ahead in time in the online setting does not affect PFC noticeably. However, arbitrage profit are more sensitive to uncertainty for batteries with faster ramp rates compared to slow ramping batteries.

## Full text

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## Figures

14 figures with captions in the complete paper: https://tomesphere.com/paper/1903.06132/full.md

## References

48 references — full list in the complete paper: https://tomesphere.com/paper/1903.06132/full.md

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Source: https://tomesphere.com/paper/1903.06132