Techno-economic multi-objective reactive power planning in integrated wind power system with improving voltage stability

Eladl, Abdelfattah A.; Basha, Mohamed I.; ElDesouky, Azza A.

doi:10.1016/j.epsr.2022.108917

Cited by 17 publications

(7 citation statements)

References 30 publications

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“…In the proposed PDOMPA, the marine predator algorithm (MPA) is applied to the PDO to sharpen the exploration and exploitation stages so that they are more valid and accurate as well as avoiding local optimal traps and preventing premature convergence. In this article, the PDO and MPA methods are integrated by replacing equation (11) with equation ( 16). The advantage of the PDOMPA hybrid algorithm is that the individuals in the top layer are not only affected by each individual in the PDO, but also have an effect on the global optimal solution.…”

Section: Proposed Hybrid Pdo-mpamentioning

confidence: 99%

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A Novel Hybrid Prairie Dog Optimization Algorithm - Marine Predator Algorithm for Tuning Parameters Power System Stabilizer

Aribowo,

Rohman,

Baskoro

et al. 2023

Journal of Robotics and Control

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The article presents the parameter tuning of the Power System Stabilizer (PSS) using the hybrid method. The hybrid methods proposed in this article are Praire Dog Optimization (PDO) and Marine Predator Algorithm (MPA). The proposed method can be called PDOMPA. In the PDOMPA method, the marine predator algorithm (MPA) is able to search around optimal individuals when updating population positions. MPA is used to make the exploration and exploitation stages of PDO more valid and accurate. PDO is an algorithm inspired by the life of prairie dogs. Prairie dogs are adapted to colonizing in burrows underground. Prairie dogs have daily habits of eating, observing for predators, establishing fresh burrows, or preserving existing ones. Meanwhile, MPA is a duplication of marine predator life which is modeled mathematically. In order to validate the performance of the PDOMPA method, this article presents a comparative simulation of the objective function and the transient response of PSS. This research uses validation by comparing with conventional methods, Whale Optimization Algorithm (WOA), Grasshopper Optimization Algorithm (GOA), Marine Predator Algorithm (MPA), and Praire Dog Optimization (PDO). Based on the simulation results, PDOMPA presents fast convergence in some cases and shows optimal results compared to competitive algorithms. From the simulation results using load variations, it was found that the proposed method has the ability to reduce the average undershoot and overshoot of speed by 42.2% and 85.37% compared to the PSS-Lead Lag method. Meanwhile the average settling time value of speed is 50.7%.

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Section: Proposed Hybrid Pdo-mpamentioning

confidence: 99%

“…Demand for electrical energy from consumers has increased rapidly [5] [6][7][8][9]. In addition, the remote location of the plant and away from the load increases the complexity of the power system [10][11][12][13][14]. The important keys in distributing electric power systems are stability and consistency [15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Prairie Dog Optimization Algorithm - Marine Predator Algorithm for Tuning Parameters Power System Stabilizer

Aribowo,

Rohman,

Baskoro

et al. 2023

Journal of Robotics and Control

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“…Amongst those, the efficiently authenticated model was the Weibull probability density function [34,35], which is capable of actual wind speed distribution because its adaptability is feasible and soothes operation. DFIG-WECS [36] could generate and absorb the reactive power and coordinate the terminal voltage of the bus-accordingly, the DFIG-WECS stator integrated into the transmission system, as the rotor connected to the transmission system through a variable converter. The wind speed distribution represented by the Weibull probability density function as:…”

Section: A Wind Power Modelmentioning

confidence: 99%

Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

Valuva,

Chinnamuthu

2023

Energies

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Transmission line losses are a crucial and essential issue in stable power system operation. Numerous methodologies and techniques prevail for minimizing losses. Subsequently, Flexible Alternating Current Transmission Systems (FACTSs) efficiently reduce transmission losses, and the Unified Power Flow Controller (UPFC) is a reactive power compensation controller. The parameter strength of the proportional–integral (PI) controller was calibrated with the Marine Predator Algorithm (MPA), a recent metaheuristic algorithm. An MPA-based optimum PI controller with a UPFC evaluates the optimal location of the UPFC and PI controller parameters to accomplish the desired research objective. The power rating of the UPFC was determined depending on the voltage collapse rating and power loss and an evaluated performance analysis of the MPA–PI-controlled UPFC on a modified IEEE-30 bus transmission network in MATLAB Simulink code. The Newton–Raphson method was used to perform the load flow analysis. Hence, the proposed MPA–PI controller was examined in contrast to preferred heuristic algorithms, the Artificial Bee Colony (ABC) and Moth Flame Optimization algorithms (MFO); the results showed that the MPA–PI controller exhibited better performance with an improved voltage profile and surpasses active power losses with the optimal placement of the UPFC device under different loading conditions. The active power loss, considering a UPFC with the proposed algorithm, reduced from 0.0622 p.u to 0.0301 p.u; consequently, the voltage profile was improved in the respective buses, and the loss percentage reduction during a 100% base load was 68.39%, which was comparatively better than the ABC and MFO algorithms.

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“…During peak load demand periods, if there is unexpected load consumption, the higher current drawn from the distribution and transmission line decreases the grid voltage. A higher grid voltage occurs when the estimated load demand is not met and during the higher wind speed period [7,8]. In most cases, the voltage regulator allows the grid voltage to be maintained within the allowable range.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Thailand’s 8 MW Wind Farm Feeder Trip, Energy Generation, and Loss Using 5 MWh BESS—A Statistical and Economic Approach

Ngoenmeesri,

Chindaruksa,

Wangkeeree

et al. 2024

IEEE Access

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In this study, an operational 8 MW wind farm was analyzed through a statistical approach to determine the wind speed and feeder trip correlation with energy loss and energy production. In December, a higher wind potential was recorded; however, a higher feeder trip was recorded during the low wind potential period of October, with a maximum duration of 1800 min. The box plot and histogram show that a higher feeder trip occurred at a wind speed of 4-6 m/s which indicates that grid voltage and load consumption were the major causes of the feeder trip. The Pearson Correlation method expressed a similar trend for feeder trips associated with energy losses that had a very strong positive correlation compared to feeder trip time.To improve the stability of the wind farm's power generation, a 1-5 MWh battery energy storage system was studied to determine its impact on the grid voltage at the wind farm and the load terminals. It was found that 411071.84 kWh is enhanced for a 5 MWh battery energy storage system compared to the conventional wind farm. This enhancement in power production shows a positive correlation of grid voltage at the factory, village 1, wind farm, village 2, and village 3 with a range of 0.703, 0.873, 0.665, 0.894, and 0.896, respectively. Further, the economic analysis of the 5 MWh battery incorporation increased the annual revenue to 2825585 baht with a payback period of 7.79 years and a return on investment of 0.10 years.

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Techno-economic multi-objective reactive power planning in integrated wind power system with improving voltage stability

Cited by 17 publications

References 30 publications

A Novel Hybrid Prairie Dog Optimization Algorithm - Marine Predator Algorithm for Tuning Parameters Power System Stabilizer

A Novel Hybrid Prairie Dog Optimization Algorithm - Marine Predator Algorithm for Tuning Parameters Power System Stabilizer

Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

Performance Evaluation of Thailand’s 8 MW Wind Farm Feeder Trip, Energy Generation, and Loss Using 5 MWh BESS—A Statistical and Economic Approach

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