Multi-objective Binary Particle Swarm optimization Algorithm for Optimal Distribution System Reconfiguration

El‐Ela, Adel A. Abou; El‐Sehiemy, Ragab A.; El-Ayaat, Nora K.

doi:10.1109/mepcon47431.2019.9008170

Cited by 7 publications

(4 citation statements)

References 32 publications

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“…Proses pengubahan juga diterapkan pada rentang kecepatan serta posisi. Pada rekonfigurasi jaringan distribusi, individu yang bernilai "1" menandakan switch yang terbuka, sedangkan yang bernilai "0" menandakan switch yang tertutup [18].…”

Section: E Binary Partticle Swarm Opttimization (Bpso)unclassified

Rekonfigurasi Dinamis Jaring Distribusi Radial 20 kV Teluk Betung untuk Meningkatkan Profil Tegangan dengan Mempertimbangkan Gangguan Saluran dan Injeksi Renewable Energy

Fayumi¹,

Putra²,

Aryani³

2022

JTITS

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Print) B90 Abstrak-Sistem distribusi tenaga listrik semakin berkembang yang ditandai dengan meningkatnya permintaan energi listrik. Terlebih lagi, keberadaan pembangkit listrik dengan sumber terbarukan semakin berkembang dan meluas. Pada kenyataannya, nilai beban dan pembangkitan sumber energi terbarukan selalu berubah. Semakin meningkatnya permintaan energi listrik serta nilai beban yang selalu berubah menyebabkan permasalahan seperti kerugian daya dan penurunan tegangan. Permasalahan ini dapat diselesaikan dengan melakukan rekonfigurasi dinamis yang memperhatikan energi terbarukan dan dinamika perubahan beban. Rekonfigurasi dinamis dilakukan pada jaringan distribusi radial 20 kV ULP Teluk Betung kota Bandar Lampung dengan metode Binary Particle Swarm Optimization (BPSO) untuk mengurangi kerugian daya dan meningkatkan nilai tegangan pada jaringan distribusi. Metode Newton-Raphson digunakan sebagai metode aliran daya pada studi rekonfigurasi dinamis ini. Berdasarkan hasil simulasi dan analisis pada sistem distribusi yang terjadi gangguan pemutusan saluran dan terpasang sistem PV, setelah dilakukan rekonfigurasi dinamis pada sistem distribusi didapatkan bahwa dalam waktu 24 jam terjadi pengurangan kerugian daya aktif adalah sebesar 47,001% dan pengurangan kerugian daya reaktif adalah sebesar 46,866%. Nilai tegangan rata-rata pada sistem distribusi dalam 24 jam adalah sebesar 0, 98947 p.u dan dengan nilai tegangan minimum adalah sebesar 0,95444 p.u. Dari hasil simulasi dan analisis, rekonfigurasi dinamis dengan metode BPSO mampu meningkatkan nilai tegangan dan menurunkan kerugian daya pada sistem distribusi yang terjadi gangguan saluran dan terpasang sistem PV.

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Section: E Binary Partticle Swarm Opttimization (Bpso)unclassified

Rekonfigurasi Dinamis Jaring Distribusi Radial 20 kV Teluk Betung untuk Meningkatkan Profil Tegangan dengan Mempertimbangkan Gangguan Saluran dan Injeksi Renewable Energy

Fayumi¹,

Putra²,

Aryani³

2022

JTITS

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“…Basically, the PSO is stimulated by the attitude of swarming through the process of finding food sources. Several applications with a number of modified versions of the PSO were presented in the literature as in [39][40][41][42][43]. The proposed CLPSO is a modified version of the standard PSO algorithm.…”

Section: Closed-loop Particle Swarm Optimizationmentioning

confidence: 99%

Assessment of an Improved Three-Diode against Modified Two-Diode Patterns of MCS Solar Cells Associated with Soft Parameter Estimation Paradigms

et al. 2021

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Recently, the use of multi-crystalline silicon solar cells (MCSSCs) has been increasing worldwide. This work proposes a novel MCSSC pattern for achieving a more accurate emulation of the electrical behavior of solar cells. Specifically, this pattern is dependent on the modification of the double diode model of MCSSCs. Importantly, the proposed pattern has an extra diode compared to the previously modified double-diode model (MDDM) described in the literature for considering the defect region of MCSSC to form a modified three diode model (MTDM). For estimating the parameters of the proposed MTDM, two metaheuristic algorithms called closed-loop particle swarm optimization (CLPSO) and elephant herd optimization (EHO) are developed, which have superior convergence rates. The competitive algorithms are executed on experimental data based on a MCSSC of area 7.7 cm2 from Q6-1380 and CS6P-240P solar modules under different irradiance and temperature levels for both MDDM and MTDM. Also, the proposed elephant herd optimization soft paradigm is extended for a high irradiance level at 1000 W/m2 on an R.T.C. France Solar cell. The proposed new optimization models are more efficient in dealing with the natural characteristics of the MCSSC. The simulation results show that the MTDM gives more accurate solutions as a model to the MCSSC compared with the results reported in the literature. From the viewpoint of soft computing paradigms, the EHO outperforms CLPSO in terms of the solution quality and convergence rates.

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“…3. Moreover, a comparative analysis is conducted between the proposed ISHO, the basic SHO, BPSO [27], two differential evaluation variants (DE1 [28]) and (DE2 [25]). This comparative analysis is carried out and tabulated for Case 1 in Table 2, Case 2 in Table 3 and Case 3 in Table 4, respectively.…”

Section: Figmentioning

confidence: 99%

Optimal Allocation of DGs with network reconfiguration using Improved Spotted Hyena Algorithm

El‐Ela

Shaheen

El‐Sehiemy

et al. 2020

Wseas Transactions on Power Systems

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Several studies of distribution network enhancement focused only on the optimization of either the integration of distributed generations (DGs) or system reconfiguration (SRC). However, very few researches have been exerted for incorporating both where this merge represents further complexities in searching for maximizing their benefits and minimizing the investments. This paper sheds light on the simultaneous allocation of DGs with SRC in distribution systems. It suggests a multi-objective formulation considering multiple objectives: active power loss minimization, total cost reduction, and voltage profile improvement. For solving this problem, an improved spotted hyena optimizer (ISHO) is developed. The SHO demonstrates a good feature in finding the optimal or nearly optimal subset with simple structure to minimize the given fitness function. To support the exploration characteristics of the proposed ISHO, it augments a switch strategy in the updating mechanism of the spotted hyena’s positions and random positions are generated instead of the violated spotted hyenas. The simulations are investigated for the integration of a single and multiple DGs with SRC for two standard systems, which are IEEE 33 and 69-node test systems. The obtained results prove the efficiency of the suggested method for the network manager to find the optimal DGs allocation with SRC considering multiple criteria. These results are compared with previous literatures to demonstrate the effectiveness of the proposed algorithm.

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Multi-objective Binary Particle Swarm optimization Algorithm for Optimal Distribution System Reconfiguration

Cited by 7 publications

References 32 publications

Rekonfigurasi Dinamis Jaring Distribusi Radial 20 kV Teluk Betung untuk Meningkatkan Profil Tegangan dengan Mempertimbangkan Gangguan Saluran dan Injeksi Renewable Energy

Rekonfigurasi Dinamis Jaring Distribusi Radial 20 kV Teluk Betung untuk Meningkatkan Profil Tegangan dengan Mempertimbangkan Gangguan Saluran dan Injeksi Renewable Energy

Assessment of an Improved Three-Diode against Modified Two-Diode Patterns of MCS Solar Cells Associated with Soft Parameter Estimation Paradigms

Optimal Allocation of DGs with network reconfiguration using Improved Spotted Hyena Algorithm

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