Application of new optimisation model for multi-chiller system consumption. Issue 16 (10th December 2021)

• Record Type: Journal Article
• Authors: Tian, Erlin; Ebadi, Abdol Ghaffar; Mavaluru, Dinesh; Kadyrov, Marsel; Ponomarev, Andrei; Druzhinin, Zumrat
• Is Part Of: International journal of ambient energy. Volume 42:Issue 16(2021)
• Page Start: 1851
• Page End: 1863
• Publication Date: 2021-12-10
• Subjects: Optimal chiller loading -- robust scheduling of electrical power consumption -- cooling demand uncertainty -- deterministic method -- robust optimisation approach; Power resources -- Periodicals; Renewable energy sources -- Periodicals; 621.04205
• DOI: 10.1080/01430750.2019.1621201
• Languages: English
• ISSNs: 0143-0750

Abstract

ABSTRACT: Obtaining of optimal electricity usage in a multi-chiller results in saving higher power in houses or industrial consumers. As well, this optimal problem has high importance in such plants. Moreover, considering the uncertain parameters such as cooling demand is essential because oscillation in this uncertain parameter must be remarked. So, a robust optimisation algorithm is suggested in the present work for formulating of the mentioned uncertainty for achieving robust loading in a chiller plant considering the uncertainty where the cooling requirement is procured by a multi-chiller plant. Optimising of power usage in the considered plant is remarked in the form of a cost function. Suggested robust optimisation algorithm of this plant is formalised in the form of nonlinear scheduling. This model is investigated in both deterministic and robust methods and achieved outputs are contrasted. In addition, impacts of variations in robust control coefficient are discussed in the optimum loading of chiller where decision-maker is able to make the decision without considering risk (risk-neutral method) through the deterministic approach. Also, decision can be made considering most robustness (risk-averse method) through a robust method. Contrasting of outputs confirms the ability of the suggested method in an uncertain situation.