Capacity firming for wind generation using one-step model predictive control and battery energy storage system

Micro Daryl Robles, Jung Su Kim, Hwachang Song

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This paper presents two MPC (Model Predictive Control) based charging and discharging algorithms of BESS (Battery Energy Storage System) for capacity firming of wind generation. To deal with the intermittency of the output of wind generation, a single BESS is employed. The proposed algorithms not only make the output of combined systems of wind generation and BESS track the predefined reference, but also keep the SoC (State of Charge) of BESS within its physical limitation. Since the proposed algorithms are both presented in simple if-then statements which are the optimal solutions of related optimization problems, they are both easy to implement in a real-time system. Finally, simulations of the two strategies are done using a realistic wind farm library and a BESS model. The results on both simulations show that the proposed algorithms effectively achieve capacity firming while fulfilling all physical constraints.

Original languageEnglish
Pages (from-to)2043-2050
Number of pages8
JournalJournal of Electrical Engineering and Technology
Volume12
Issue number5
DOIs
StatePublished - Sep 2017

Keywords

  • BESS (Battery Energy Storage System)
  • Capacity firming
  • MPC (Model Predictive Control)
  • SoC (State of Charge)
  • Wind generation

Fingerprint

Dive into the research topics of 'Capacity firming for wind generation using one-step model predictive control and battery energy storage system'. Together they form a unique fingerprint.

Cite this