Multi-Objective Predictive Control Optimization with Varying Term Objectives: A Wind Farm Case Study

Processes

卷:7

ConstantinF. Caruntu¹  Cosmin Copot²  Guillaume Crevecoeur³  Ricardo Cajo⁴  ClaraM. Ionescu⁴  Mihaela Ghita⁴ 

[1] Department of Automatic Control and Applied Informatics, Gheorghe Asachi Technical University of Iasi, D. Mangeron Blvd 27, 700050 Iasi, Romania;

[2] Department of Electromechanics, Antwerp University, Op3Mech, Groenenborgerlaan 171, 2020 Antwerp, Belgium;

[3] EEDT—Core Lab Decisions and Controls, Flanders Make, Tech Lane Science Park 131, 9052 Ghent, Belgium;

[4] Research lab on Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium;

关键词: windmill park;    wind speed estimator;    multi-objective optimization;    sequential optimisation;    distributed model predictive control;   

DOI  :  10.3390/pr7110778

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown