Model predictive control method to achieve maximum power point tracking without additional sensors in stand-alone renewable energy systems

Samani, Loghman; Mirzaei, Rahmatollah

doi:10.1016/j.ijleo.2019.04.067

Cited by 10 publications

(4 citation statements)

References 22 publications

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“…In this, DDM, SM, and the input of the distribution matrix in Equation ( 14) is expressed as Γ, X, and Y , respectively. The control vector as well as the disturbance vector involving load variations is depicted as v and k. In Equation (15), the distribution matrix of control output is stated as Z and the state vector is explicated as s. The arithmetic expression of the state vector s and n-state vector is given in Equations ( 16) and (17), respectively.…”

Section: Variables That Impact On Lfcmentioning

confidence: 99%

“…Among the control approaches in industrial applications, the model predictive control (MPC) is the most successful and popular technique used for complex process systems. Many of the industrial and academic researchers paid more attention to these MPC, [16][17][18][19] due to some outstanding characteristics like the parameters uncertainty, fast response, and robustness against load disturbance. Most of the literary works have defined the importance of distributed MPC approach for a complicated large-scale industrial system since it has better dealing with diverse kinds of constraints and therefore successfully evaluates the distributed decision-making tasks.…”

Section: Introductionmentioning

confidence: 99%

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Hysteresis modulation‐based sliding mode load frequency controller for multi‐area power system

Mahendran

Vijayan

2022

Adaptive Control & Signal

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Recently the raise in interconnection of the power system leads to vigorous change of power flow, as well as load in tie-line. Hence, there is a need of robust control in both tie-line power flows and systems frequency. This research work aims to design a dual-mode switch controller-based load frequency control in multi-area interconnected power system (MAIPS). In this, the incremental control action's influence is taken along with the constraints of the system dynamic such as Governor with Dead Band, Capacitive Energy Storage, and Generation Rate Constraint. This work on the proposed controller of the multisource-MAIPS (MS-MAIPS) is operated on the basis of dual mode switching function. For this purpose, a threshold value 𝜉 is evolved. The control on MPC and optimized hysteresis modulation based sliding mode control (HMSMC) is varied according to this switching function. For attaining the fascinating performance, the optimal tuning of switch threshold 𝜉 and the gain of HMSMC controller K is exploited by a new Self-Adaptive Sea Lion algorithm. To the end, variation of control parameters like T r , T rb , C g , as well as T CD for reducing unwanted variances in power flows among control areas is used to verify the effectiveness of the implemented scheme.

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Section: Variables That Impact On Lfcmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hysteresis modulation‐based sliding mode load frequency controller for multi‐area power system

Mahendran

Vijayan

2022

Adaptive Control & Signal

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“…Unfortunately, as in the previous cases, the load and PV model are simplified to a resistance and voltage source, respectively. PV systems based onĆuk converters have been also controlled using more complex control tech-Ì ISSN: 2088-8708 niques, such as the model predictive controller reported in [40]. The main problems of such a solution are the inaccurate PV source model (constant voltage) and the particular load model (constant resistance), which are not realistic for practical applications.…”

Section: Introductionmentioning

confidence: 99%

Sliding-mode controller for a photovoltaic system based on a Cuk converter

Ramos‐Paja

González-Motoya

Villegas-Ceballos

et al. 2021

IJECE

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The wide range of step-up and step-down input-output voltage characteristic of the Cuk converter makes it a good candidate to interface photovoltaic arrays in both classical and distributed maximum power point tracking systems. Because its two inductor structure, Cuk converters have continuous input and output currents, which reduce the additional filtering elements usually required for interfacing dc/dc converter topologies. However, PV systems based on Cuk converters usually do not provide formal proofs of global stability under realistic conditions, which makes impossible to ensure a safe operation of the PV installation. Therefore, this paper proposes a high performance sliding-mode controller for PV systems based on Cuk converters, which regulates the PV voltage in agreement with the commands imposed by a MPPT algorithm, rejecting both load and environmental perturbations, and ensuring global stability for real operation conditions. Finally, the performance of the regulated PV system is tested using both simulations and experiments.

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“…This information is used to find a fault condition. This way there are methods based in the AC condition [16], Predictive control [17], Bayesian Networks [18], and comparation methods [19,20].Cartesians robots make linear motion in direction of three axes X, Y and Z [21].…”

Section: Introductionmentioning

confidence: 99%

Application of A Computer Vision Method for Soiling Recognition in Photovoltaic Modules for Autonomous Cleaning Robots

Pivem¹,

Araujo²,

Araujo³

et al. 2019

SIPIJ

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It is well known that this soiling can reduce the generation efficiency in PV system. In some case according to the literature of loss of energy production in photovoltaic systems can reach up to 50%. In the industry there are various types of cleaning robots, they can substitute the human action, reducing cleaning cost, be used in places where access is difficult, and increasing significantly the gain of the systems. In this paper we present an application of computer vision method for soiling recognition in photovoltaic modules for autonomous cleaning robots. Our method extends classic CV algorithm such Region Growing and the Hough. Additionally, we adopt a pre-processing technique based on Top Hat and Edge detection filters. We have performed a set of experiments to test and validate this method. The article concludes that the developed method can bring more intelligence to photovoltaic cleaning robots.

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Model predictive control method to achieve maximum power point tracking without additional sensors in stand-alone renewable energy systems

Cited by 10 publications

References 22 publications

Hysteresis modulation‐based sliding mode load frequency controller for multi‐area power system

Hysteresis modulation‐based sliding mode load frequency controller for multi‐area power system

Sliding-mode controller for a photovoltaic system based on a Cuk converter

Application of A Computer Vision Method for Soiling Recognition in Photovoltaic Modules for Autonomous Cleaning Robots

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