An MPC Based ESS Control Method for PV Power Smoothing Applications

Mingyu Lei, Zilong Yang, Yibo Wang, Honghua Xu, Lexuan Meng, Juan Carlos Vasquez Quintero, Josep M. Guerrero

Research output: Contribution to journalJournal articleResearchpeer-review

82 Citations (Scopus)
932 Downloads (Pure)

Abstract

Random fluctuation in photovoltaic (PV) power plants is becoming a serious problem affecting the power quality and stability of the grid along with the increasing penetration of PVs. In order to solve this problem, by the adding of energy storage systems (ESS), a grid-connected microgrid system can be performed. To make this system feasible, this paper proposes a model predictive control (MPC) based on power/voltage smoothing strategy. With the receding horizon optimization performed by MPC, the system parameters can be estimated with high accuracy, and at the same time the optimal ESS power reference is obtained. The critical parameters, such as state of charge, are also taken into account in order to ensure the health and stability of the ESSs. In this proposed control strategy, communication between PVs and ESS is not needed, since control command can be calculated with local measured data. At the same time, MPC can make a great contribution to the accuracy and timeliness of the control. Finally, experimental results from a grid-connected lab-scale microgrid system are presented to prove effectiveness and robustness of the proposed approach.

Original languageEnglish
Article number7900331
JournalI E E E Transactions on Power Electronics
Volume33
Issue number3
Pages (from-to)2136 - 2144
Number of pages9
ISSN0885-8993
DOIs
Publication statusPublished - Mar 2018

Keywords

  • Energy storage
  • Model predictive control (MPC)
  • Photovoltaic (PV)
  • Power quality
  • Power smoothing
  • power smoothing
  • photovoltaic (PV)
  • power quality
  • model predictive control (MPC)

Fingerprint

Dive into the research topics of 'An MPC Based ESS Control Method for PV Power Smoothing Applications'. Together they form a unique fingerprint.

Cite this