2019
DOI: 10.3390/app9061184
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Optimal Power Dispatch of an Offshore Wind Farm under Generator Fault

Abstract: For offshore wind farms, the power loss caused by the wake effect is large due to the large capacity of the wind turbine. At the same time, the operating environment of the offshore wind farm is very harsh, and the cost of maintenance is higher than that of the onshore wind farm. Therefore, it is worthwhile to study through reasonable control how to reduce the wake loss of the wind farm and minimize the losses caused by the fault. In this paper, the Particle Swarm Optimization (PSO) algorithm is used to optimi… Show more

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Cited by 9 publications
(7 citation statements)
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“…The objective of a wind turbine owner is to keep the wind turbine running. Hence, it is very important to minimize the downtime due to maintenance and repairs [12,13]. In the long-term, it is crucial to determine what is the most economical strategy to avoid short cuts, which can end up being a big expense, risking the business model of the electricity-generating wind turbine.…”
Section: Main Problem Statement Methods and Theory Reviewmentioning
confidence: 99%
“…The objective of a wind turbine owner is to keep the wind turbine running. Hence, it is very important to minimize the downtime due to maintenance and repairs [12,13]. In the long-term, it is crucial to determine what is the most economical strategy to avoid short cuts, which can end up being a big expense, risking the business model of the electricity-generating wind turbine.…”
Section: Main Problem Statement Methods and Theory Reviewmentioning
confidence: 99%
“…The third term can prevent the PSO from falling into a local optimum due to the factor mentioned above. The detail explanation of the objective function can be found in [29]. However, the difference between these two objective functions is that the power limitation of the faulty WT does not need to be calculated.…”
Section: Power Optimization At the Farm Level Under Itsc Faultmentioning
confidence: 99%
“…[16] Adaptive FTC using barrier Lyapunov function Active power control during actuator fault [17] Particle swarm optimization Accommodation of the generator fault effects at farm level [18,19] FTCC using fuzzy logic at farm level Accommodation of mild power-loss faults caused by turbine blade erosion and debris build-up on the blades [20,21] FTCC using adaptive PI control at turbine level and control reallocation at farm level Accommodation of mild and severe power loss faults caused by turbine blade erosion and debris build-up on the blades [22] It should be noted that the effective implementation of the presented scheme in [22] for a large-scale wind farm or WFC, where the number of wind turbines becomes quite large, turns to be complex or computationally expensive due to the increased number of modules required in the scheme (i.e., each module monitors the power consistency between two different turbines in the wind farm). To overcome these issues when dealing with very large-scale wind farms or WFCs, the present paper proposes a novel clustering approach to enable a computationally efficient multilayer FTCC scheme which provides effective fault identification and accommodation performance with simplified computer programming.…”
Section: Principal Component Analysismentioning
confidence: 99%
“…In [17], the problem of active power control in a wind farm is converted to the rotor speed tracking problem, and an adaptive FTC scheme is presented to track the power signal of each wind turbine with an acceptable transient performance and robustness to the actuator faults. The particle swarm optimization (PSO) approach is used in [18] for optimal active power dispatch in a wind farm during generator cooling system faults. A PSO-based active power dispatch method is introduced in [19] to accommodate the fault effects (i.e., inter-turn short circuit faults in wind turbines generators) at the farm level.…”
Section: Introductionmentioning
confidence: 99%