TY - GEN
T1 - Peak power reduction in hybrid energy systems with limited load forecasts
AU - Pant, Yash V.
AU - Nghiem, Truong X.
AU - Mangharam, Rahul
PY - 2014
Y1 - 2014
N2 - Hybrid energy systems, which consist of a load powered by a source and a form of energy storage, find applications in many systems, e.g., the electric grid and electric vehicles. A key problem for hybrid energy systems is the reduction of peak power consumption to ensure cost-efficient operation as peak power draws require additional resources and adversely affect the system reliability and lifetime. Furthermore, in some cases such as electric vehicles, the load dynamics are fast, not perfectly known in advance and the on-board computation power is often limited, making the implementation of traditional optimal control difficult. We aim to develop a control scheme to reduce the peak power drawn from the source for hybrid energy systems with limited computation power and limited load forecasts. We propose a scheme with two control levels and provide a sufficient condition for control of the different energy storage/generation components to meet the instantaneous load while satisfying a peak power threshold. The scheme provides performance comparable to Model Predictive Control, while requiring less computation power and only coarse-grained load predictions. For a case study, we implement the scheme for a battery-supercapacitor-powered electric vehicle with real world drive cycles to demonstrate the low execution time and effective reduction of the battery power (hence temperature), which is crucial to the lifetime of the battery.
AB - Hybrid energy systems, which consist of a load powered by a source and a form of energy storage, find applications in many systems, e.g., the electric grid and electric vehicles. A key problem for hybrid energy systems is the reduction of peak power consumption to ensure cost-efficient operation as peak power draws require additional resources and adversely affect the system reliability and lifetime. Furthermore, in some cases such as electric vehicles, the load dynamics are fast, not perfectly known in advance and the on-board computation power is often limited, making the implementation of traditional optimal control difficult. We aim to develop a control scheme to reduce the peak power drawn from the source for hybrid energy systems with limited computation power and limited load forecasts. We propose a scheme with two control levels and provide a sufficient condition for control of the different energy storage/generation components to meet the instantaneous load while satisfying a peak power threshold. The scheme provides performance comparable to Model Predictive Control, while requiring less computation power and only coarse-grained load predictions. For a case study, we implement the scheme for a battery-supercapacitor-powered electric vehicle with real world drive cycles to demonstrate the low execution time and effective reduction of the battery power (hence temperature), which is crucial to the lifetime of the battery.
KW - Automotive
KW - Optimization
KW - Predictive control for linear systems
UR - http://www.scopus.com/inward/record.url?scp=84905687076&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905687076&partnerID=8YFLogxK
U2 - 10.1109/ACC.2014.6859145
DO - 10.1109/ACC.2014.6859145
M3 - Conference contribution
AN - SCOPUS:84905687076
SN - 9781479932726
T3 - Proceedings of the American Control Conference
SP - 4212
EP - 4217
BT - 2014 American Control Conference, ACC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 American Control Conference, ACC 2014
Y2 - 4 June 2014 through 6 June 2014
ER -