Optimal energy management via MPC considering photovoltaic power uncertainty

Toru Namerikawa, Shunsuke Igari

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

In this paper, we propose a method that uses model predictive control (MPC) to predict photovoltaic (PV) power generation, plan for the electricity demand in a building using the predicted value, and apply it online to correct the prediction error. First, we construct the regression model using a PV experimental unit and past data obtained from the Meteorological Agency. Next, we predict the PV power using grid point power (GPV) data of the next day. Second, the air conditioning or heating of the building is modeled to determine the electricity demand so that it increases the profits to the consumer and reduces the peak in time-varying electric cost. The error between the predicted and true value is considered via MPC. Finally, we show the advantages of the proposed method by performing simulations.

本文言語English
ホスト出版物のタイトル2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ57-62
ページ数6
ISBN(電子版)9781509040759
DOI
出版ステータスPublished - 2016 12月 8
イベント7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 - Sydney, Australia
継続期間: 2016 11月 62016 11月 9

Other

Other7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
国/地域Australia
CitySydney
Period16/11/616/11/9

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • エネルギー工学および電力技術
  • 制御と最適化
  • 信号処理

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