Optimal Siting and Sizing of Battery Energy Storage: Case Study Seventh Feeder at Nakhon Phanom Substation in Thailand

Boonluk, Panyawoot; Khunkitti, Sirote; Fuangfoo, Pradit; Siritaratiwat, Apirat

doi:10.3390/en14051458

Cited by 10 publications

(6 citation statements)

References 60 publications

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“…Step 5: Evaluate the leader's position based on the parameters c 1 , c 2 , and c 3 obtained from Step 4 using Equation (5). Then, the follower's position based on the existing leader position is determined using Equation (8).…”

Section: Inputmentioning

confidence: 99%

“…Electricity is widely regarded as a critical factor in economic growth, as increased usage is required to serve a diverse range of load types, including industrial, commercial, and residential customers [1][2][3][4]. Renewable energy sources have been widely used to improve the capacity of electrical generation, particularly in the last few decades [5][6][7]. Power quality disturbance (PQD) has been a highly concerning problem in power systems since it can essentially degrade the system's performance.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Salp Swarm Algorithm as Optimal Feature Selection for Power Quality Disturbance Classification

et al. 2021

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Power quality disturbance (PQD) is an influential situation that significantly declines the reliability of electrical distribution systems. Therefore, PQD classification is an important process for preventing system reliability degradation. This paper introduces a novel algorithm called “adaptive salp swarm algorithm (SSA)” as an optimal feature selection algorithm for PQD classification. Feature extraction and classifier of the proposed classification system were based on the discrete wavelet and the probabilistic neural network, respectively. The classification was focused on the 13 types of power quality signals. The optimal number of selected features for the proposed classification system was firstly determined. Then, it demonstrated that the optimally selected features resulted in the highest classification accuracy of 98.77%. High performance of the proposed classification system in the noisy environment, as well as based on the real dataset was also verified. Furthermore, the proposed SSA indicates a very high convergence rate compared to other well-known algorithms. A comparison of the proposed classification system’s performance to existing works was also carried out, revealing that the proposed system’s accuracy is on a high-range scale. Hence, the adaptive SSA becomes another efficient optimal feature selection algorithm for PQD classification.

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Section: Inputmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Salp Swarm Algorithm as Optimal Feature Selection for Power Quality Disturbance Classification

et al. 2021

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“…However, RESs such as photovoltaics (PV) and wind turbines (WT) are from natural sources which cannot be controlled resulting in power fluctuations caused by the difference in voltage and frequency of different RESs, especially in systems with high DG penetration levels [4][5][6][7]. Energy storage system (ESS) is increasingly being incorporated into distribution systems to solve the aforementioned problems and provide different technical and economic benefits [8][9][10][11][12]. Moreover, ESS also reduces power losses [13][14][15][16], improves voltage profile or alleviates voltage deviation [17,18], achieves peak shaving [19], mitigates reverse power flow [20], and decreases system cost [21].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, the adopted algorithms in this work which are GA and PSO are very traditional, although several new efficient optimization algorithms have been proposed, and the statistical analysis of the considered algorithms has not been investigated. In [12], an optimal siting and sizing of BESSs are proposed to improve performance, in terms of voltage regulation, real loss, and peak demand reductions, of a distribution network in ailand. However, this work only considers one PV as a DG in a 56-bus distribution network.…”

Section: Introductionmentioning

confidence: 99%

Optimal Location and Sizing of BESS for Performance Improvement of Distribution Systems with High DG Penetration

Khunkitti

Boonluk

Siritaratiwat

2022

International Transactions on Electrical Energy Systems

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This work proposes an optimal location and sizing of battery energy storage system (BESS) installation for performance improvement of distribution systems with high distributed generation (DG) penetration level where the DGs comprise photovoltaics (PV) and wind turbines (WT). The installation of the BESS can reduce costs incurred in the systems, alleviate reverse power flow when the systems are in the high DG penetration level, and also achieve peak shaving during high demand. To find the optimal location and sizing of the BESS, three optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), and salp swarm algorithm (SSA), are applied, and their performances are compared. The considered objective function is the system costs consisting of transmission loss cost, peak power cost, and voltage deviation cost. The system performance improvement is compared in terms of transmission loss, peak demand, and voltage regulation reductions. IEEE 33- and 69-bus distribution systems with high DG penetration are tested to investigate the performance improvement of the BESS installation. The results found that the installation of the BESS could successfully decrease system cost, improve voltage profile, reduce power losses, alleviate reverse power flow, and achieve peak shaving where PSO and SSA are found to be the best competitive algorithms. So, the proposed method can be further applied to find the optimal location and sizing of the BESS to improve the performance of practical systems in the future.

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“…Based on the configuration of DSPM, this machine indicates low inertia and light rotor weight; therefore it is suitable for low-speed operation (Cheng et al, 2001a;Cheng et al, 2001b). Many previous studies have attempted to develop the DSPM aiming to be used for electric vehicle applications as well as electrical generation from renewable energy which is a clean energy source (Fan et al, 2006;Boonluk et al, 2020;Srithapon et al, 2020;Boonluk et al, 2021;Okedu and Barghash, 2021;Srithapon et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic Torque Improvement of Doubly Salient Permanent Magnet Machine Using Pole Ratio Adjustment Technique

et al. 2021

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This paper introduces the pole ratio adjustment technique to improve the torque characteristics of the doubly salient permanent magnetic machine (DSPM). The electrical characteristics of the machine, namely the magnetic field distribution, flux linkage, back-electromotive force (EMF), and cogging torque, were obtained under open-circuit conditions. The electromagnetic torque and ripple torque were examined under the loaded condition. The simulations, based on the 2D-finite element method, show that the optimal pole ratio for the DSPM structure is with 18 stator teeth and 15 rotor poles. This optimal structure achieves a larger phase back-EMF than the conventional structure, as well as had a better magnetic flux path with a reasonable cogging torque. The on-load test also confirmes that the proposed optimal structure can produce a significantly higher electromagnetic torque than the conventional machine while maintaining a satisfactory torque ripple. Furthermore, an experimental prototype of the DSPM structure having 18/15 stator/rotor poles was fabricated and tested to verify the simulations. The experimental results were in good agreement with the simulations. The design technique and the fabricated prototype demonstrate the DSPM utilization for low-speed/high torque applications.

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Optimal Siting and Sizing of Battery Energy Storage: Case Study Seventh Feeder at Nakhon Phanom Substation in Thailand

Cited by 10 publications

References 60 publications

Adaptive Salp Swarm Algorithm as Optimal Feature Selection for Power Quality Disturbance Classification

Adaptive Salp Swarm Algorithm as Optimal Feature Selection for Power Quality Disturbance Classification

Optimal Location and Sizing of BESS for Performance Improvement of Distribution Systems with High DG Penetration

Electromagnetic Torque Improvement of Doubly Salient Permanent Magnet Machine Using Pole Ratio Adjustment Technique

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