A Novel Hybridized Fuzzy PI-LADRC Based Improved Frequency Regulation for Restructured Power System Integrating Renewable Energy and Electric Vehicles

Sharma, Prateek; Mishra, Abhishek; Saxena, Abhishek; Shankar, Ravi

doi:10.1109/access.2020.3049049

Cited by 42 publications

(10 citation statements)

References 40 publications

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“…According to the analysis method of other scholars [23,24], seven independent variables are selected among numerous influencing factors according to the seismic liquefaction data set provided by reference [25,26]. Based on seven characteristic indexes, including intensity𝐼 ′ (𝑋 1 ), groundwater level 𝑑 𝑤 (𝑋 2 ), effective overburden pressure𝜎 0 ′ (𝑋 3 ), blow counts of SPT 𝑁 63.5 (𝑋 4 ), average grain size 𝑑 50 (𝑋 5 ), nonuniformity coefficient 𝐶 𝑢 (𝑋 6 ) and shear-to-stress ratio 𝜏 𝑑 /𝜎 0 ′ (𝑋 7 ), the liquefaction of sandy soil is divided into three grades according to the field conditions.…”

Section: Several Common Assessment Methods Of Sand Liquefactionmentioning

confidence: 99%

Improved artificial electric field algorithm based on multi-strategy and its application

Tian

Liu

Wang

et al. 2022

IJCAI

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Artificial electric field algorithm is a new swarm bionic optimization algorithm, which uses the interaction force of charged particles to create a mathematical model to solve the problem. To improve the global exploration ability and local development ability of artificial electric field algorithms, an artificial electric field algorithm based on opposition learning is proposed. The chaos strategy is used to strengthen the quality of the initial population, and the opposition learning strategy is used to increase the diversity of the population and the development ability of the algorithm. The excellent performance of the algorithm is proved by simulation experiments. The improved artificial electric field algorithm is combined with SVM to construct the sand liquefaction identification model by selecting seven measured indexes, including intensity, underground water level, overlying effective pressure, standard penetration hit number, average particle size, non-uniformity coefficient, and shear stress ratio. Compared with traditional methods such as the standard method and seed simplification method, the results show that the IAEFA-SVM model has high prediction accuracy and provides an effective method for sand liquefaction identification.Povzetek: Predstavljen je izboljšan algoritem umetnega električnega polja na osnovi mnogoterih strategij.

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Section: Several Common Assessment Methods Of Sand Liquefactionmentioning

confidence: 99%

Improved artificial electric field algorithm based on multi-strategy and its application

Tian

Liu

Wang

et al. 2022

IJCAI

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“…This method blends proportional‐integral control with fuzzy logic to create an optimized control approach for power electronics systems that increases effectiveness and minimizes power quality problems. [ 76 ] A control method that may be used to enhance power quality in electrical systems, particularly those that contain EV chargers, is hybrid fuzzy‐PI control. To improve the efficiency of power conditioning equipment and reduce power quality problems, this control method combines the advantages of proportional‐integral (PI) control with fuzzy logic.…”

Section: Techniques Used To Improve Power Qualitymentioning

confidence: 99%

Review of Power Quality and Stability of EV Charging with Grid and PV Solar

Bishla,

Khosla

2023

Energy Tech

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As a sustainable mode of transportation, electric vehicles (EVs) are gaining popularity, and their integration with the power grid and photovoltaic (PV) solar systems is essential for their widespread adoption. Solar PV and EV systems have improved based on the generation and demands of the power grid. However, incorporating EV chargers with the grid and PV solar systems can cause power quality issues and stability problems that can impact the charger's performance and affect the charging procedure. EV technologies are divided into two major components: electric propulsion systems and EV charging systems. The electric propulsion system delivers the necessary energy for the EV motor in an EV system. In addition, with higher penetration, EVs and PVs are anticipated to emerge as new participants in the energy market operation and can play a crucial role in redefining the market. Many have integrated into the electricity network to reach renewable energy sources (RES), such as wind and solar PV. The study concludes that continued research and development are necessary to upgrade the power quality and solidness of EV charging frameworks, to ensure the seamless integration of PV solar systems and electric vehicles into the grid, and to promote sustainable transportation.

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“…All three subsets of intelligent controllers (fuzzy, neural, and others according to [22]) are still researched. For instance, [25], [26] proposed variants of fuzzy PI controllers. Furthermore, with the recent advancements in artificial intelligence led to the introduction of reinforcement learning based controllers [27], [28], and long-short term memory (LSTM) and deep neural network (DNN) based controllers [29].…”

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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A Novel Hybridized Fuzzy PI-LADRC Based Improved Frequency Regulation for Restructured Power System Integrating Renewable Energy and Electric Vehicles

Cited by 42 publications

References 40 publications

Improved artificial electric field algorithm based on multi-strategy and its application

Improved artificial electric field algorithm based on multi-strategy and its application

Review of Power Quality and Stability of EV Charging with Grid and PV Solar

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

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