Scenario-based robust MPC for energy management systems with renewable generators

被引:0
|
作者
Sato, Shotaro [1 ]
Namerikawa, Toni [1 ]
机构
[1] Keio Univ, Dept Syst Design Engn, Yokohama, Kanagawa, Japan
来源
2018 37TH CHINESE CONTROL CONFERENCE (CCC) | 2018年
关键词
Prediction Intervals; Robust Optimization; Energy Management;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:2304 / 2309
页数:6
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