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

Abstract

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.

Context Aware Control Systems: An Engineering Applications Perspective

“…Renewable energy integration remains challenging due to stochastic nature of supply and demand in smart grid systems [132]. Distributed control seem to cope well with variations in operating conditions of power systems [133], while multiobjective optimization may offer versatility in short-and long-term economic objectives [134]. Multi-agent artificial intelligence algorithms applied to wind farm throughput optimization seems to be better positioned when data and structural features are integrated [135].…”

A Low Computational Cost, Prioritized, Multi-Objective Optimization Procedure for Predictive Control Towards Cyber Physical Systems

“…1. This is a simplified approach compared to those proposed in literature [28], [29], [33], [49]- [51]. MO algorithms with artificial intelligence data processing methods such as in [52], [53] can deal with great amount of data.…”

“…These specifications are dominated by the requirement for safety operation (which includes stability), within limit intervals for the manipulated variables and controlled outputs of the involved processes. When multi-objective optimization is required, there exist a manifold of academic solutions with stability guaranteed [26]- [29]. Some of them have also been applied to specific industrial settings, although their number remains limited [30]- [33].…”

Recent Advances on Optimization for Control, Observation, and Safety

“…Ionescu et al [15] study the case of an optimization method that considers short-term and long-term cost objectives. The problem of cost-effective optimization of the system's output is studied in a multi-objective predictive control formulation and applied to a windmill park case study.…”