Optimal Energy Management Strategy of an Improved Elevator With Energy Storage Capacity Based on Dynamic Programming

Author

Bilbao, Enrique ; Barrade, Philipe ; Etxeberria-Otadui, I. ; Rufer, Alfred ; Luri, S. ; Gil, Iñigo

Author_Institution

Ind. Electron. Lab., Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland

Volume

50

Issue

2

fYear

2014

fDate

March-April 2014

Firstpage

1233

Lastpage

1244

Abstract

Efficiency and energy consumption reduction are becoming a key issue in elevation applications. Energy Storage Systems (ESS) can play a significant role in this field, together with their associated Energy Management Strategy (EMS) to optimize the overall behavior of the elevator. This paper presents an EMS based on Dynamic Programming (DP) for a stochastic application where the cost function is based on the stock management theory. For that purpose, an implementation methodology for DP-based EMS is also proposed. That methodology has been applied on an elevator where the system modeling has been carried out. Due to the stochastic behavior of the application, a novel representation method is also presented (General Energy and Statistical Description). The EMS has been implemented and validated experimentally on a real elevator with energy storage capability reducing grid power peaks by 65% and braking resistor energy losses up to 84%.

Keywords

dynamic programming; energy management systems; energy storage; lifts; power grids; resistors; stochastic programming; DP-based EMS; ESS; braking resistor energy losses; cost function; dynamic programming; efficiency consumption reduction; energy consumption reduction; energy storage capacity; general energy-and-statistical description; grid power peak reduction; optimal energy management strategy; overall elevator behavior optimization; stochastic application; stock management theory; system modeling; Cost function; Dynamic programming; Elevators; Energy management; Energy storage; Resistors; Dynamic programming (DP); elevators; energy management; energy storage; modeling; stochastic systems; supercapacitors;

fLanguage

English

Journal_Title

Industry Applications, IEEE Transactions on

Publisher

ieee

ISSN

0093-9994

Type

jour

DOI

10.1109/TIA.2013.2276015

Filename

6574271