Central Tunicate Swarm NFOPID-Based Load Frequency Control of the Egyptian Power System Considering New Uncontrolled Wind and Photovoltaic Farms

Fayek, Hady H.; Kotsampopoulos, Panos

doi:10.3390/en14123604

Cited by 8 publications

(4 citation statements)

References 26 publications

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“…The size and location of ESSs are the variables needed to be optimal in a multi-objective optimization problem consisting of many cost objectives [ 49 ]. The objective of this optimization issue is to minimize the total cost of the system comprising Power Losses Cost (PLC), Voltage Variation Cost ( VVC ), and Peak Demand Cost (PDC) [ 50 ].…”

Section: The Proposed Optimization Problemmentioning

confidence: 99%

Optimal allocation of distributed energy storage systems to enhance voltage stability and minimize total cost

Hany,

Mahmoud,

Osman

et al. 2024

PLoS ONE

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The enhancement of energy efficiency in a distribution network can be attained through the adding of energy storage systems (ESSs). The strategic placement and appropriate sizing of these systems have the potential to significantly enhance the overall performance of the network. An appropriately dimensioned and strategically located energy storage system has the potential to effectively address peak energy demand, optimize the addition of renewable and distributed energy sources, assist in managing the power quality and reduce the expenses associated with expanding distribution networks. This study proposes an efficient approach utilizing the Dandelion Optimizer (DO) to find the optimal placement and sizing of ESSs in a distribution network. The goal is to reduce the overall annual cost of the system, which includes expenses related to power losses, voltage deviation, and peak load damand. The methods outlined in this study is implemented on the IEEE 33 bus distribution system. The outcomes obtained from the proposed DO are contrasted with those of the original system so as to illustrate the impact of ESSs location on both the overall cost and voltage profile. Furthermore, a comparison is made between the outcomes of the Ant Lion Optimizer (ALO) and the intended Design of Experiment DO, revealing that the DO has obtained greater savings in comparison to the ALO. The recommended methodology’s simplicity and efficacy in resolving the researched optimization issue make the acquired locations and sizes of ESSs favorable for implementation within the system.

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Section: The Proposed Optimization Problemmentioning

confidence: 99%

Optimal allocation of distributed energy storage systems to enhance voltage stability and minimize total cost

Hany,

Mahmoud,

Osman

et al. 2024

PLoS ONE

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“…This study assumed the PV generating system operates in a maximum power point tracking mode. The PV output power can be represented as [37]:…”

Section: E Photovoltaic Power Generatormentioning

confidence: 99%

A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System

Fadheel,

Wahab,

Manoharan

et al. 2024

IEEE Access

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This paper introduces a robust approach, integrating a Virtual Inertia Controller (VIC) with a modified demand response controller for an islanded Multi-Microgrid (MMG) system, accommodating high levels of Renewable Energy Sources (RESs). In these MGs, the low inertia in the system has an undesirable impact on the stability of MG frequency. As a result, it leads to a weakening of the MGs overall performance. A novel fractional derivative virtual inertia is integrated into the VIC loop to address this issue. This enhancement aims to fortify the MG's stability and robust performance, particularly when facing contingencies. Furthermore, a modified demand response controller has been incorporated into the proposed inertia control technique to mitigate the frequency fluctuations and reduce stress on the energy storage system (ESS). Fractional Order Proportional Integral Derivative (FOPID) controllers have been employed to regulate the active power output of the biodiesel generators and the Geothermal station in the MG. The hybrid sparrow search and mountain gazelle optimizer algorithm (SSAMGO) optimizes the parameters for the three-loop controller. Time-domain simulations assess the effectiveness of proposed controllers in enhancing system frequency stability. SSAMGO's performance was comprehensively evaluated, comparing it to various optimization algorithms in diverse scenarios. The results obtained from the MMG system demonstrate that utilizing the proposed controller technique, optimized with hybrid SSAMGO parameters, yields notable improvements in settling time by 24.68%, 46.20%, 7.52%, and 61.01%, steady-state error values by 72.56%, 98.18%, 98.73%, and 6.67%, undershoot by 105.76%, 144.23%, 19.23%, and 7.69% compared to other stateof-the-art algorithms presented in the literature. Finally, the proposed control technique's effectiveness and robustness are assessed in comparison to conventional inertia control across various system scenarios. These scenarios encompass random load demand fluctuations, real-time changes in RES, and a wide spectrum of system operations, including situations with reduced damping and inertia and high levels of load variation.INDEX TERMS Virtual inertia control, Load frequency control, Renewable energy resources, Hybrid optimization algorithm, Demand response control, Power system stability, Microgrid system.

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“…Most historical blackouts resulted from under/over-frequency events. LFC schemes gives the chance to minimize frequency oscillations and deviations from spreading among power system areas [8].…”

Section: Introductionmentioning

confidence: 99%

Novel Combined Load Frequency Control and Automatic Voltage Regulation of a 100% Sustainable Energy Interconnected Microgrids

Fayek

Rusu

2022

Sustainability

Self Cite

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Frequency and voltage deviations are two main problems in microgrids, especially with the increase in the penetration level of renewable energies. This paper presents novel techniques to apply combined the load frequency control and automatic voltage regulation of two interconnected microgrids. The two microgrids are operated by solar energy and bioenergy technologies and include energy-storage facilities. The control is applied using a novel accelerating PID controller (PIDA), which is compared to state-of-the-art control schemes. The controllers are designed using a new doctor and patient optimization technique (DPO), which is compared to state-of-the-art techniques. The combined design of load frequency controllers and automatic voltage regulators is also compared to a standalone design. The comparisons are carried out by testing the system performance at each operation condition in addition to indicators such as integral absolute error for frequency and voltage and integral time absolute error for frequency and voltage. The results show that a combined DPO–PIDA design of LFC–AVR schemes for fully sustainable microgrids has better performance than other standalone designs and other control and optimization alternatives.

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Central Tunicate Swarm NFOPID-Based Load Frequency Control of the Egyptian Power System Considering New Uncontrolled Wind and Photovoltaic Farms

Cited by 8 publications

References 26 publications

Optimal allocation of distributed energy storage systems to enhance voltage stability and minimize total cost

Optimal allocation of distributed energy storage systems to enhance voltage stability and minimize total cost

A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System

Novel Combined Load Frequency Control and Automatic Voltage Regulation of a 100% Sustainable Energy Interconnected Microgrids

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