ANFIS Based Frequency Control in an Autonomous Microgrid Integrated with PV and Battery Storage

Kaur, Sachpreet; Kaur, Tarlochan; Khanna, Rintu

doi:10.1109/icpes47639.2019.9105593

Cited by 6 publications

(8 citation statements)

References 12 publications

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“…The output of the trained ANFIS is the power reference (P MGRef ) to be supplied by the microgrid at time t. Eqs. (16), and ( 17) are rule sets used in the first-order Takagi-Sugeno interference system with two fuzzy layers [11,20]. The relation 𝑊 𝑖 = 𝑋 𝑖 (𝑎)𝑌 𝑖 (𝑏) was used to determine the activation levels in connection with fuzzy rules, with the logical operator "AND" being optimized by a permanent t-norm.…”

Section: Design Of the Proposed Anfis Controllermentioning

confidence: 99%

“…Other research was conducted on Artificial Intelligence-based control using ANFIS for optimal and stable operation of converter-dominated microgrids considering optimizing the virtual inertia, damping, current state feedback factor, and reactive power sharing [18], and minimizing the irregular frequency and power deviations within microgrid was done in Reference [19] considering a distributed generator. In Reference [20], frequency regulation using ANFIS controller in microgrid for coordinating the performance of charging and discharging storage system to enhance real power balance was investigated with the aim of increasing storage equipment lifespan. A synthesis procedure for an energy management system (EMS) based on ANFIS controller and hyperplane clustering was investigated in [21] to maximize the profit of energy exchange between a microgrid and the main grid.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent ANFIS-Based Distributed Generators Energy Control and Power Dispatch of Grid- Connected Microgrids Integrated into Distribution Network

Odonkor

2024

IJEETC

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Power supply management is a critical problem in the operation of a distribution network, considering the causes of large power losses and interruptions in the main grid caused by the unknown connection of loads and DGs that affect power delivery to customers downstream of a distribution network. The above-mentioned problems can be reduced by the integration of microgrids close to load centers and developing a controller using adaptive control techniques to enhance reliable power supply. For this reason, this paper presents an intelligent method for distributed generators' energy control and power dispatch of microgrids integrated into a distribution network employing an Adaptive Neuro- Fuzzy Inference System (ANFIS). The aim is to control distributed generators energy sources, loads, and power dispatch of grid-connected microgrids among multiconnected power sources to maintain a stable power supply without using any optimization techniques. The proposed intelligent ANFIS system is trained for power-sharing purposes and applied to the microgrid controllers. The mathematical modeling of distributed generators, system design, simulation, and testing of the proposed method were done using MATLAB/Simulink software. The results show that the proposed controller is capable of power dispatch and controls the energy harvest of distributed generators. Additionally, it can assign microgrid power source(s) to additional load(s) connected to the active distribution network without interruptions of power flow. The obtained results outperform similar works that used hybrid ANFISPID (Adaptive Neural Fuzzy Inference System-Proportional- Integral-Derivative), PSO-ANFIS (Particle Swarm Optimization-Adaptive Neural Fuzzy Inference System), and GA-ANFIS (Genetic Algorithm-Adaptive Neuro-Fuzzy Inference System) by automatically connecting and controlling distributed generators energy sources with effective power dispatch in mitigating downtime of grid power operations.

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Section: Design Of the Proposed Anfis Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent ANFIS-Based Distributed Generators Energy Control and Power Dispatch of Grid- Connected Microgrids Integrated into Distribution Network

Odonkor

2024

IJEETC

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“…In addition, it achieves a fast response and minimises steady-state error. Many methods of hybrid control are proposed in [193,197,198] and the literature ref [232][233][234][235][236].…”

Section: Hybrid Controlmentioning

confidence: 99%

Voltage Lifting Techniques for Non-isolated DC/DC Converters

Al-Khaldi¹,

Elkhateb²,

Laverty³

2023

Preprint

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This paper presents a comprehensive review that highlights the characteristics of non-isolated step-up converters based on high boost voltage lifting techniques. The paper categorises the high boost techniques: multistage/multilevel, switched capacitor, voltage multiplier, voltage lift, switched inductor, and magnetic coupling. The paper also discusses in detail the advantages and disadvantages for each category such as cost, complexity, power density, reliability and efficiency. The number of passive and active components, voltage gain, voltage stress, switching frequency, efficiency and power rating are also compared. Although the paper considers coupling inductors in the context of the non-isolated converter, the focus of the entire article is on the non-isolated high voltage step-up techniques. The key contribution in this paper is the review of high boosting techniques rather than the DC /DC converters. This allows divergence of new ideas and new power converters that will help provide highly efficient and flexible power converters for several applications where the sending end voltage is very low as photovoltaic systems. In addition, many applications and control techniques of DC/DC converters are summarised in this paper.

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“…This way of weight tuning is generally termed as backpropagation while the stages included in the process are precondition tuning (first layer) and consequent tuning (fourth layer). Figure 12 illustrates the corresponding layer architecture of the ANFIS controller 89,90 …”

Section: Microgrid: Issues and Controllermentioning

confidence: 99%

A comprehensive review on control techniques for stability improvement in microgrids

Mehta

Basak

2021

Int Trans Electr Energ Syst

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In recent times, with the increase in the penetration of various renewable energy sources (RESs) into power systems, the complications related to the stability issues have increased. The main contribution of this paper is an in‐depth analysis of research in microgrid based on small‐signal, transient, and voltage stability. The small‐signal stability has been discussed based on uncertain load, limitation in power generation capacity, and nature of sluggish feedback observed in few microgrid systems. Instability caused by a transient phenomenon in microgrid has been thoroughly analyzed for losses in distributed energy resources (DERs), islanding and transition modes of operation, load shedding, and faults causing instability. The voltage fluctuations are duly considered in the perspective of load shedding, type of loads, power unbalancing, and different types of faults in microgrid systems. The existing controllers have been compared based on steady‐state error, response time, and robustness etc. The voltage, frequency, and active/reactive power control are analyzed based on centralized, decentralized, hierarchal/distributed control schemes aiming stabilization of microgrid systems. Finally, stability improvement features have been explored in detail, finding the implementation of microgrid stabilizers, energy storage devices, FACTS devices, load balancing, resource forecasting including the adaptive controller. Hence, the uniqueness of this paper can be considered as a state‐of‐the‐art review of the abovementioned stability components in the microgrid system which is not available in the published literature with a similar amount of vastness.

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ANFIS Based Frequency Control in an Autonomous Microgrid Integrated with PV and Battery Storage

Cited by 6 publications

References 12 publications

Intelligent ANFIS-Based Distributed Generators Energy Control and Power Dispatch of Grid- Connected Microgrids Integrated into Distribution Network

Intelligent ANFIS-Based Distributed Generators Energy Control and Power Dispatch of Grid- Connected Microgrids Integrated into Distribution Network

Voltage Lifting Techniques for Non-isolated DC/DC Converters

A comprehensive review on control techniques for stability improvement in microgrids

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