Multi-process production scheduling with variable renewable integration and demand response

José Luis Ruiz Duarte, Neng Fan, Tongdan Jin

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Integrating renewable energy sources to power manufacturing facilities is one approach to achieve low carbon economy. The contribution of this paper is to propose a way to facilitate and assess renewable sources’ integration into manufacturing systems, by exploring an optimization model that obtains a production schedule adapted to match the onsite renewable energy supply, with energy storage systems and the power grid as backups. A multi-process production scheme as well as demand side management policies such as Time-and-Level-of-Use and power consumption reduction requests are considered. To capture renewable uncertainties, a two-stage robust optimization model is formulated to optimize the production scheduling under the worst-case scenario of renewable generation. A nested Column-and-Constraint Generation algorithm is applied to solve this formulation. Numerical experiments are performed on a benchmark case, and sensitivity analysis is conducted by modifying renewable integration, uncertainty, data granularity, scheduling horizon, switch of on-peak prices hours, and zero-inventory policy. Obtained results validate the proposed model and algorithm.

Original languageEnglish (US)
Pages (from-to)186-200
Number of pages15
JournalEuropean Journal of Operational Research
Volume281
Issue number1
DOIs
StatePublished - Feb 16 2020

Keywords

  • Demand response
  • OR in energy
  • Onsite renewables
  • Production scheduling
  • Robust optimization

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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