LAPSE:2019.1569
Published Article
LAPSE:2019.1569
Multi-Objective Predictive Control Optimization with Varying Term Objectives: A Wind Farm Case Study
December 11, 2019
This paper introduces the incentive of an optimization strategy taking into account short-term and long-term cost objectives. The rationale underlying the methodology presented in this work is that the choice of the cost objectives and their time based interval affect the overall efficiency/cost balance of wide area control systems in general. The problem of cost effective optimization of system output is taken into account in a multi-objective predictive control formulation and applied on a windmill park case study. A strategy is proposed to enable selection of optimality criteria as a function of context conditions of system operating conditions. Long-term economic objectives are included and realistic simulations of a windmill park are performed. The results indicate the global optimal criterium is no longer feasible when long-term economic objectives are introduced. Instead, local sub-optimal solutions are likely to enable long-term energy efficiency in terms of balanced production of energy and costs for distribution and maintenance of a windmill park.
Keywords
distributed model predictive control, multi-objective optimization, sequential optimisation, wind speed estimator, windmill park
Suggested Citation
Ionescu CM, Caruntu CF, Cajo R, Ghita M, Crevecoeur G, Copot C. Multi-Objective Predictive Control Optimization with Varying Term Objectives: A Wind Farm Case Study. (2019). LAPSE:2019.1569
Author Affiliations
Ionescu CM: Research lab on Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium; EEDT—Core Lab Decisions and Controls, Flanders Make, Tech Lane Science Park 131, 9052 Ghent, Belgium; Department of Automatic Control, Tech [ORCID]
Caruntu CF: Department of Automatic Control and Applied Informatics, Gheorghe Asachi Technical University of Iasi, D. Mangeron Blvd 27, 700050 Iasi, Romania [ORCID]
Cajo R: Research lab on Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium; EEDT—Core Lab Decisions and Controls, Flanders Make, Tech Lane Science Park 131, 9052 Ghent, Belgium; Facultad de Ingeniería en Electricid [ORCID]
Ghita M: Research lab on Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium; EEDT—Core Lab Decisions and Controls, Flanders Make, Tech Lane Science Park 131, 9052 Ghent, Belgium [ORCID]
Crevecoeur G: EEDT—Core Lab Decisions and Controls, Flanders Make, Tech Lane Science Park 131, 9052 Ghent, Belgium; Electrical Energy Lab, Ghent University, Tech Lane Science Park 131, 9052 Ghent, Belgium [ORCID]
Copot C: Department of Electromechanics, Antwerp University, Op3Mech, Groenenborgerlaan 171, 2020 Antwerp, Belgium [ORCID]
Journal Name
Processes
Volume
7
Issue
11
Article Number
E778
Year
2019
Publication Date
2019-10-29
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr7110778, Publication Type: Journal Article
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LAPSE:2019.1569
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doi:10.3390/pr7110778
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Dec 11, 2019
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CC BY 4.0
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Dec 11, 2019
 
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Dec 11, 2019
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Original Submitter
Calvin Tsay
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