Extremum seeking for wind and solar energy applications

Krstić, Miroslav; Ghaffari, Azad; Seshagiri, Sridhar

doi:10.1109/wcica.2014.7053780

Cited by 14 publications

(6 citation statements)

References 25 publications

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“…ES has been applied in the automotive sector (Killingsworth et al, 2009), process engineering (Guay et al, 2004), formation flight and obstacle avoidance (Binetti et al, 2003;Montenbruck et al, 2014) and others. Further applications concern problems in renewable energy such as maximum power point tracking in photovoltaic (Ghaffari et al, 2015) or wind energy systems Ghaffari et al (2014); Krstic et al (2014), and Volt-VAR control in power systems (Arnold et al, 2016).…”

Section: Extremum Seekingmentioning

confidence: 99%

Optimization Algorithms as Robust Feedback Controllers

Hauswirth¹,

Bolognani²,

Hug³

et al. 2021

Preprint

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Mathematical optimization is one of the cornerstones of modern engineering research and practice. Yet, throughout all application domains, mathematical optimization is, for the most part, considered to be a numerical discipline. Optimization problems are formulated to be solved numerically with specific algorithms running on microprocessors. An emerging alternative is to view optimization algorithms as dynamical systems. While this new perspective is insightful in itself, liberating optimization methods from specific numerical and algorithmic aspects opens up new possibilities to endow complex real-world systems with sophisticated self-optimizing behavior. Towards this goal, it is necessary to understand how numerical optimization algorithms can be converted into feedback controllers to enable robust "closed-loop optimization". In this article, we review several research streams that have been pursued in this direction, including extremum seeking and pertinent methods from model predictive and process control. However, our primary focus lies on recent methods under the name of "feedback-based optimization". This research stream studies control designs that directly implement optimization algorithms in closed loop with physical systems. Such ideas are finding widespread application in the design and retrofit of control protocols for communication networks and electricity grids. In addition to an overview over continuous-time dynamical systems for optimization, our particular emphasis in this survey lies on closed-loop stability as well as the enforcement of physical and operational constraints in closed-loop implementations. We further illustrate these methods in the context of classical problems, namely congestion control in communication networks and optimal frequency control in electricity grids, and we highlight one potential future application in the form of autonomous reserve dispatch in power systems.

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Section: Extremum Seekingmentioning

confidence: 99%

Optimization Algorithms as Robust Feedback Controllers

Hauswirth¹,

Bolognani²,

Hug³

et al. 2021

Preprint

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“…The model-less extremum seeking control (ESC) method is an alternative application of the P&O algorithm at PSCs to improve transient response and convergence speed. However, its validation is limited near the MPP because an assumed function is used to test the stability performance [57]. To confirm high tracking speed during the transient period and minimum power oscillations in the steady state with less complexity, a modified beta method is designed.…”

Section: Other Mppt Techniquesmentioning

confidence: 99%

Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems

et al. 2018

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This paper elaborates a comprehensive overview of a photovoltaic (PV) system model, and compares the attributes of various conventional and improved incremental conductance algorithms, perturbation and observation techniques, and other maximum power point tracking (MPPT) algorithms in normal and partial shading conditions. Performance evaluation techniques are discussed on the basis of the dynamic parameters of the PV system. Following a discussion of the MPPT algorithms in each category, a table is drawn to summarize their key specifications. In the performance evaluation section, the appropriate PV module technologies, atmospheric effects on PV panels, design complexity, and number of sensors and internal parameters of the PV system are outlined. In the last phase, a comparative table presents performance-evaluating parameters of MPPT design criterion. This paper is organized in such a way that future researchers and engineers can select an appropriate MPPT scheme without complication.

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“…Thus, to avoid all of the above, the MPPT can use a scheme based on ESC [32,33], a methodology that consists of carrying out the process of maximizing a function by calculating the Hessian of a modulated signal, which is built in real-time and governs the movements of the actuators that are developed. The modulated signal corresponds to the dynamics of the current generated by the SC and its interaction with a sinusoidaltype signal (called dither) that allows obtaining an oscillating behavior around the real value [34,35]. This makes it possible to dispense with the use of more sensors and since the algorithm can be solved analytically, the use of reserved numerical methods is avoided.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Extremum-Seeking Control Based on MPPT for Dual-Axis Solar Tracker

Solís-Cervantes,

Palomino-Resendiz,

Flores-Hernández

et al. 2024

Mathematics

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The increase in the production efficiency of photovoltaic technology depends on its alignment in relation to the solar position. Solar tracking systems perform the tracking action by implementing control algorithms that help the reduction of tracking errors. However, conventional algorithms can reduce the life of actuators and mechanisms due to control action, significantly reducing operation times and profitability. In this article, an unconventional control scheme is developed to address the mentioned challenges, presenting the design and implementation of an extremum-seeking control to perform maximum power point tracking for a two-axis solar tracker instrumented with a solar module. The proposed controller is governed by the dynamics of a classic proportional-integral scheme and assisted by sensorless feedback. Also, it has an anti-wind-up-type configuration for the integral component and counts with a variable amplitude for the dither signal. The proposal is validated experimentally by comparison between a fixed system and a two-axis system in azimuth-elevation configuration. In addition, two performance indices are defined and analyzed, system energy production and tracking error. The results show that the proposal allows producing up to 27.75% more than a fixed system, considering the tracker energy consumption due to the tracking action and a pointing accuracy with ±1.8° deviation. Finally, an analysis and discussion are provided based on the results, concluding that the proposed algorithm is a viable alternative to increase the performance of tracked photovoltaic systems.

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Extremum seeking for wind and solar energy applications

Cited by 14 publications

References 25 publications

Optimization Algorithms as Robust Feedback Controllers

Optimization Algorithms as Robust Feedback Controllers

Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems

Design and Implementation of Extremum-Seeking Control Based on MPPT for Dual-Axis Solar Tracker

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