Optimal maintenance planning for sustainable energy efficiency lighting retrofit projects by a control system approach. (April 2015)

• Record Type: Journal Article
• Authors: Ye, Xianming; Xia, Xiaohua; Zhang, Lijun; Zhu, Bing
• Is Part Of: Control engineering practice. Volume 37(2015)
• Page Start: 1
• Page End: 10
• Publication Date: 2015-04
• Subjects: Energy Efficiency -- Optimal Control -- Lighting -- Maintenance Planning -- MPC; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2014.12.014
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: The energy savings achieved by implementing energy efficiency (EE) lighting retrofit projects are sometimes not sustainable and vanish rapidly given that lamp population decays as time goes by if without proper maintenance activities. Scope of maintenance activities refers to replacements of failed lamps due to nonrepairable lamp burnouts. Full replacements of all the failed lamps during each maintenance interval contribute to a tight project budget due to the expense for the lamp failure inspections, as well as the procurement and installation of new lamps. Since neither "no maintenance" nor "full maintenance" is preferable to the EE lighting project developers (PDs), we propose to design an optimal maintenance plan that optimises the number of replacements of the failed lamps, such that the EE lighting project achieves sustainable performance in terms of energy savings whereas the PDs obtain their maximum benefits in the sense of cost–benefit ratio. This optimal maintenance planning (OMP) problem is aptly formulated as an optimal control problem under control system framework, and solved by a model predictive control (MPC) approach. An optimal maintenance plan for an EE lighting retrofit project is designed as a case study to illustrate the effectiveness of the proposed control system approach. Abstract : Highlights: Optimal lighting project maintenance plan is designed under control system framework. The optimal maintenance planning problem is solved by an MPC approach. The optimal maintenance plan brings sustainable energy savings and maximum profits.