Scenario-Based Robust MPC for Energy Management Systems with Renewable Generators

Shotaro Sato, Toru Namerikawa

研究成果: Conference contribution

抜粋

This paper addresses photovoltaics (PV) power prediction and energy storage problem which are known to be a key technology in energy management systems (EMS). Extending results of the point prediction of PV power, we first describe a prediction interval (PI) method using a copula, which can express the relation between a multivariable joint distribution and each marginal distribution. Then, resorting to the PI method, the energy storage optimization problem in a building is developed. A scenario robust (SR) optimization theorem, which calculates the robustness of the optimal solution, is applied to the proposed PI method, and hence we obtain an optimal energy storage solution taking the robustness of the solution into account. Additionally, we propose a method which combines a model predictive control (MPC) technique and SR to reduce the total electricity costs. The simulation results finally illustrate the cost reduction and robustness of the proposed method.

元の言語English
ホスト出版物のタイトルProceedings of the 37th Chinese Control Conference, CCC 2018
編集者Xin Chen, Qianchuan Zhao
出版者IEEE Computer Society
ページ2304-2309
ページ数6
2018-July
ISBN(電子版)9789881563941
DOI
出版物ステータスPublished - 2018 10 5
イベント37th Chinese Control Conference, CCC 2018 - Wuhan, China
継続期間: 2018 7 252018 7 27

Other

Other37th Chinese Control Conference, CCC 2018
China
Wuhan
期間18/7/2518/7/27

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modelling and Simulation

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  • これを引用

    Sato, S., & Namerikawa, T. (2018). Scenario-Based Robust MPC for Energy Management Systems with Renewable Generators. : X. Chen, & Q. Zhao (版), Proceedings of the 37th Chinese Control Conference, CCC 2018 (巻 2018-July, pp. 2304-2309). [8483209] IEEE Computer Society. https://doi.org/10.23919/ChiCC.2018.8483209