TY - GEN
T1 - Scenario-Based Robust MPC for Energy Management Systems with Renewable Generators
AU - Sato, Shotaro
AU - Namerikawa, Toru
N1 - Publisher Copyright:
© 2018 Technical Committee on Control Theory, Chinese Association of Automation.
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
T3 - Chinese Control Conference, CCC
SP - 2304
EP - 2309
BT - Proceedings of the 37th Chinese Control Conference, CCC 2018
A2 - Chen, Xin
A2 - Zhao, Qianchuan
PB - IEEE Computer Society
T2 - 37th Chinese Control Conference, CCC 2018
Y2 - 25 July 2018 through 27 July 2018
ER -