Optimum Modified Fractional Order Controller for Future Electric Vehicles and Renewable Energy-Based Interconnected Power Systems

Ahmed, Emad M.; Mohamed, Emad A.; Elmelegi, Ahmed; Aly, Mokhtar; Elbaksawi, Osama

doi:10.1109/access.2021.3058521

Cited by 58 publications

(32 citation statements)

References 53 publications

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“…Fractional order controllers have been gaining attention with the added ability to better tune than traditional integral order controllers due to the fractional order terms. One drawback is in determining the optimal parameters for such controller, and research such as [22] - [24] have proposed variants of fractional order controllers using different tuning methods. Unlike PID controllers, which are simple to tune, the current state of tuning fractional order controllers relies on metaheuristic methods.…”

Section: B Literature Reviewmentioning

confidence: 99%

Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control

Kirihara

Kawabe

2022

IEEE Access

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This research proposes a power system frequency control architecture which leverages a rising open protocol for charge rate control of electric vehicles: Open Charge Point Protocol. Unlike conventional research that focused on building a high-performance controller, this research puts emphasis on the architecture. Specifically, this research explores the design of the frequency control architecture around a basic functionality of an open protocol while allowing substantial performance to mitigate the need for a well-tuned specialized protocol. As the usage of open protocols cannot provide a quick response, the proposed architecture alleviates this limitation by (a) utilizing a hierarchical and asynchronous structure to emulate a faster control interval and (b) providing a model predictive controller with system integrity protection scheme behavior to have sufficient performance under both large and small disturbances. The overall architecture is tested against an aggregated power system frequency response model on Simulink for both large and small disturbances. Compared to a tuned proportional integral derivative controller on the same architecture, the proposed architecture observed an average reduction of 21.77% in nadir in the step disturbance test and an average reduction of 36.27% in standard deviation from the nominal frequency in the load variation test.

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Section: B Literature Reviewmentioning

confidence: 99%

Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control

Kirihara

Kawabe

2022

IEEE Access

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“…The control of EVs using TID controller has been designed and optimized using artificial-bee-colony optimizer (ABC) in [15]. Also, in [16], the authors have presented optimum modified FO controller for EVs based on two-area interconnected power systems. Furthermore, virtual inertial controllers have been optimized using the particle swarm optimizer (PSO) algorithm [17].…”

Section: B Literature Reviewmentioning

confidence: 99%

“…The detailed dynamic model of EVs is shown in Fig. 4, which has been applied in this paper for the frequency response analysis as in [44].…”

Section: B Ev Modellingmentioning

confidence: 99%

“…In addition, the Nernst equation is commonly utilized for expressing the relation among the open circuit voltage (V oc ) and the state of charge (SOC) of connected EVs as follows [44]:…”

Section: B Ev Modellingmentioning

confidence: 99%

“…Z i " Elite i`P .CFˆS i (16) where, CF " p1´t t max q 2 t tmax (17) where, t and t max represent the current and the maximum iterations numbers.…”

Section: ) Phase No 1 At High Ratio Of Speedmentioning

confidence: 99%

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Frequency Regulation of Electric Vehicle-Penetrated Power System Using MPA-Tuned New Combined Fractional Order Controllers

et al. 2021

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Energy transition from traditional generation sources into new renewable energy generation has become essential for facing climate changes. However, increased penetration levels of renewable energy sources (RESs) make power systems subjected to low inertia problems. Moreover, the continuously growing numbers of electric vehicles (EVs) have made the substantial need for their contribution in power systems. Therefore, this paper proposes a combined fractional-order controller using the parallel combination of tiltintegral-derivative with filter (TIDF) and hybrid fractional-order (HybFO) controllers for robust frequency regulation in interconnected power systems. The proposed controller is advantageous in combining the merits of two fractional-order controllers that result in more robust and effective load frequency control (LFC) at wide range and different types of disturbances. Furthermore, a new application of marine predator optimization algorithm (MPA) is proposed for simultaneously determining the optimum controller parameters in the different power system areas. The existing EVs contribute in performing additional functionality in power systems. EVs help in damping out the frequency and tie-line power oscillations in the proposed work. The two-area interconnected power system is selected as a case study with the installed photovoltaic (PV), and wind generations in addition to distributed EVs among areas. The obtained results show the superiority and suitability of the proposed controller over the traditional controllers in the literature. Additionally, the effectiveness of the MPA is validated and compared with recent meta-heuristic optimization algorithms.INDEX TERMS Electric vehicles (EVs), interconnected power systems, load frequency control (LFC), marine predator optimization algorithm (MPA), renewable energy sources (RESs).

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Renewable Energy‐Based Load Frequency Controller and Model with a Reduced Order for a Large‐Scale Power System

Singh,

Kumar,

Singh

et al. 2023

Energy Tech

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Power system stability relies heavily on load frequency control (LFC) because it ensures that the power generated in a grid matches the load demand. The conventional LFC methods are no longer adequate with the rising use of renewable energy sources like wind and solar power. These resources are intermittent, and their power output varies depending on weather conditions. As a result, incorporating renewable energy resources (RERs) into the LFC system necessitates a different approach. One method is to use advanced control algorithms that can respond quickly to changes in power output. Hence, this article proposes an autoencoder‐based jellyfish optimization developed in this framework to reduce the power outage and control voltage and frequency fluctuations. The LFC system can be optimized by combining autoencoder and jellyfish optimization techniques to effectively handle the variability and unpredictability of RERs while maintaining the power system's stability and reliability. This approach may also result in more efficient and cost‐effective power system operation by reducing the need for conventional power generation and minimizing the impact of RERs on the system.

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Optimum Modified Fractional Order Controller for Future Electric Vehicles and Renewable Energy-Based Interconnected Power Systems

Cited by 58 publications

References 53 publications

Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control

Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control

Frequency Regulation of Electric Vehicle-Penetrated Power System Using MPA-Tuned New Combined Fractional Order Controllers

Renewable Energy‐Based Load Frequency Controller and Model with a Reduced Order for a Large‐Scale Power System

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