TY - GEN
T1 - Charging and discharging control of plug-in electric vehicles with uncertainties via robust model predictive control method
AU - Wang, Peng
AU - Ran, Long
AU - Shao, Yunfeng
AU - Zou, Suli
AU - Ma, Zhongjing
N1 - Publisher Copyright:
© 2017 Technical Committee on Control Theory, CAA.
PY - 2017/9/7
Y1 - 2017/9/7
N2 - With the development of the Plug-in Electric Vehicles (PEVs), it has become a significant part of electric load. The optimal PEVs' charging and discharging scheduling is a vital problem when PEVs connect into the smart grid. In most literatures, the charging and discharging procedure is assumed idealized. In reality, many uncertainties are exist during the procedure, such as the conversion efficiency, temperature and other aspects, but they are not easy to be expressed as a fixed term. In this paper, we use a random but bounded uncertainties to describe the uncertainties. Meanwhile, based on robust model predictive control (RMPC) method, we introduce the disturbance invariant set to solve the PEVs scheduling problem with uncertainties and design a feedback control law to guarantee the feasibility of it. A distributed method to reduce the computation complexity of the uncertain problem. At last, some simulations demonstrate the feasibility of the proposed centralized and distributed methods.
AB - With the development of the Plug-in Electric Vehicles (PEVs), it has become a significant part of electric load. The optimal PEVs' charging and discharging scheduling is a vital problem when PEVs connect into the smart grid. In most literatures, the charging and discharging procedure is assumed idealized. In reality, many uncertainties are exist during the procedure, such as the conversion efficiency, temperature and other aspects, but they are not easy to be expressed as a fixed term. In this paper, we use a random but bounded uncertainties to describe the uncertainties. Meanwhile, based on robust model predictive control (RMPC) method, we introduce the disturbance invariant set to solve the PEVs scheduling problem with uncertainties and design a feedback control law to guarantee the feasibility of it. A distributed method to reduce the computation complexity of the uncertain problem. At last, some simulations demonstrate the feasibility of the proposed centralized and distributed methods.
KW - PEV
KW - RMPC
KW - disturbance invariant set
KW - uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85032195921&partnerID=8YFLogxK
U2 - 10.23919/ChiCC.2017.8027762
DO - 10.23919/ChiCC.2017.8027762
M3 - Conference contribution
AN - SCOPUS:85032195921
T3 - Chinese Control Conference, CCC
SP - 2644
EP - 2650
BT - Proceedings of the 36th Chinese Control Conference, CCC 2017
A2 - Liu, Tao
A2 - Zhao, Qianchuan
PB - IEEE Computer Society
T2 - 36th Chinese Control Conference, CCC 2017
Y2 - 26 July 2017 through 28 July 2017
ER -