### Abstract

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.

Original language | English |
---|---|

Title of host publication | Proceedings of the 37th Chinese Control Conference, CCC 2018 |

Editors | Xin Chen, Qianchuan Zhao |

Publisher | IEEE Computer Society |

Pages | 2304-2309 |

Number of pages | 6 |

Volume | 2018-July |

ISBN (Electronic) | 9789881563941 |

DOIs | |

Publication status | Published - 2018 Oct 5 |

Event | 37th Chinese Control Conference, CCC 2018 - Wuhan, China Duration: 2018 Jul 25 → 2018 Jul 27 |

### Other

Other | 37th Chinese Control Conference, CCC 2018 |
---|---|

Country | China |

City | Wuhan |

Period | 18/7/25 → 18/7/27 |

### Fingerprint

### Keywords

- Energy Management
- Prediction Intervals
- Robust Optimization

### ASJC Scopus subject areas

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

### Cite this

*Proceedings of the 37th Chinese Control Conference, CCC 2018*(Vol. 2018-July, pp. 2304-2309). [8483209] IEEE Computer Society. https://doi.org/10.23919/ChiCC.2018.8483209

**Scenario-Based Robust MPC for Energy Management Systems with Renewable Generators.** / Sato, Shotaro; Namerikawa, Toru.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 37th Chinese Control Conference, CCC 2018.*vol. 2018-July, 8483209, IEEE Computer Society, pp. 2304-2309, 37th Chinese Control Conference, CCC 2018, Wuhan, China, 18/7/25. https://doi.org/10.23919/ChiCC.2018.8483209

}

TY - GEN

T1 - Scenario-Based Robust MPC for Energy Management Systems with Renewable Generators

AU - Sato, Shotaro

AU - Namerikawa, Toru

PY - 2018/10/5

Y1 - 2018/10/5

N2 - 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.

AB - 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.

KW - Energy Management

KW - Prediction Intervals

KW - Robust Optimization

UR - http://www.scopus.com/inward/record.url?scp=85056115618&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056115618&partnerID=8YFLogxK

U2 - 10.23919/ChiCC.2018.8483209

DO - 10.23919/ChiCC.2018.8483209

M3 - Conference contribution

AN - SCOPUS:85056115618

VL - 2018-July

SP - 2304

EP - 2309

BT - Proceedings of the 37th Chinese Control Conference, CCC 2018

A2 - Chen, Xin

A2 - Zhao, Qianchuan

PB - IEEE Computer Society

ER -