Onsite Generation System Sizing for Manufacturing Plant Considering Renewable Sources Towards Sustainability
Abstract
Onsite generation system with renewable sources for manufacturing plant is considered a critical alternative energy source that can improve the sustainability and resilience for manufacturers. The optimal sizing for all the components of the onsite generation system under the variations of the uncertain energy demand from manufacturing plant plays a critical role in achieving a cost-effective operational mode. In this paper, a Mixed Integer Non-Linear Programming optimization model is proposed for sizing the capacity of onsite generation system with renewable sources and battery energy storage system for the manufacturers considering the energy loads from both manufacturing system and HVAC system in a typical manufacturing plant. An integrated simulation model is used to capture the variations of the plant-level electricity demand including both manufacturing and HVAC systems so that it can be used as the input to the proposed optimization model. Both linearization and meta-heuristic solution strategies are discussed and compared when solving the proposed optimization model considering both solution quality and computational time. A case study employing the relevant data of a real auto component manufacturing plant as well as the data of the renewable sources in the Chicago area is implemented to illustrate the effectiveness of the proposed model.
Recommended Citation
M. M. Islam and Z. Sun, "Onsite Generation System Sizing for Manufacturing Plant Considering Renewable Sources Towards Sustainability," Sustainable Energy Technologies and Assessments, vol. 32, pp. 1 - 18, Elsevier, Apr 2019.
The definitive version is available at https://doi.org/10.1016/j.seta.2019.01.004
Department(s)
Engineering Management and Systems Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Climate control; Cost effectiveness; Digital storage; Electric energy storage; HVAC; Integer programming; Nonlinear programming; Particle swarm optimization (PSO); Sustainable development; Alternative energy source; Battery energy storage systems; Electricity demands; Integrated simulation models; Mixed-integer nonlinear programming; Onsite generation; Optimization modeling; Renewable sources; Manufacture; Manufacturing system; Onsite generation system; Sustainability
International Standard Serial Number (ISSN)
2213-1388
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Elsevier, All rights reserved.
Publication Date
01 Apr 2019