Power Loss Minimization for Distribution Networks with Load Tap Changing Using Genetic Algorithm and Environmental Impact Analysis

Gümüş, Talha Enes; Tırmıkçı, Ceyda Aksoy; Yavuz, Cenk; Yalçın, Mehmet Ali; Turan, Mustafa

doi:10.17559/tv-20200813105532

Cited by 3 publications

(2 citation statements)

References 38 publications

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“…Let us find the average values within the variable change ranges. The rule base in the fuzzy logic inference system, taking into account the description of the input variable ∆𝜃 -the error signal, and the output parameter 𝐹 -the control action Figure 4, is presented in Table 1 [28], [29].…”

Section: Methodsmentioning

confidence: 99%

Synthesis of the neuro-fuzzy regulator with genetic algorithm

Siddikov,

Porubay,

Rakhimov

2024

IJECE

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Real-acting objects are characterized by the presence of various types of random perturbations, which significantly reduce the quality of the control process, which determines the use of modern methods of intellectual technology to solve the problem of synthesis of control systems of structurally complex dynamic objects, allowing to compensate the influence of external factors with the properties of randomness and partial uncertainty. The article considers issues of synthesis of the automatic control system of dynamic objects by applying the theory of intelligent control. In this case, a neural network based on radial-basis functions is used at each discrete interval for neuro-fuzzy approximation of the control system, allowing real-time adjustment of the regulator parameters. The radial basis function is designed to approximate functions defined in the implicit form of pattern sets. The neuro-fuzzy regulator's parameter configuration is accomplished using a genetic algorithm, enabling more efficient computation to determine the regulator's set parameters. The regulator's parameters are represented as a vector, facilitating their application to multidimensional objects. To determine the optimal tuning parameters of the neuro-fuzzy regulator, characterized by high convergence and the possibility of determining global extrema, a genetic algorithm was used. The effectiveness of the neuro-fuzzy regulator is explained by the possibility of providing quality control of the dynamic object under random perturbations and uncertainty of input data.

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Section: Methodsmentioning

confidence: 99%

Synthesis of the neuro-fuzzy regulator with genetic algorithm

Siddikov,

Porubay,

Rakhimov

2024

IJECE

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“…In the optimization of power system line loss, the research and application of artificial intelligence algorithms are currently research hotpots. Tirmikçi et al [20] studies the advantages of using distribution static compensators and distributed power sources in reducing power losses in the IEEE 34-bus test system, and uses GA to optimize power losses. Wu et al [21] applies a charging system search algorithm to determine the optimal PV capacity, minimizing line losses under relevant constraints, and studies the impact of increasing PV installed capacity on system steady-state and dynamic performance.…”

Section: Introductionmentioning

confidence: 99%

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

2024

Teh. vjesn.

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With the increasing integration of distributed photovoltaic (PV) generation into distribution networks, challenges such as power reverse flow and high line losses have emerged, leading to greater uncertainty in power systems. To address these issues, this paper presents an analytical model for calculating line losses in low-voltage distribution networks with PV generation, utilizing power flow calculations. A simulation model of a 15 node low-voltage network is developed using SIMULINK to validate the accuracy of the analytical model under the scenario of uniform load distribution (ULD). Additionally, a line loss optimization algorithm based on quantum genetic algorithms (QGA) is proposed for low-voltage distribution networks with distributed PV generation, along with an optimization model. The objective function of the optimization model is based on the reduction in line losses resulting from the integration of the PV system. The example results demonstrate the consistency between the line loss optimization using QGA and the analytical results, highlighting the significant advantages of QGA in terms of speed and accuracy. This research provides valuable insights for line loss optimization in low-voltage distribution networks with distributed PV generation and serves as a theoretical reference for future studies in this field.

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Kuzeybatı Anadolu Güç Sisteminde Yenilenebilir Enerji Kaynaklarının Optimal Boyutlandırılması ve Yerleşimi

B.AYMAZ>

Yalçın

Gümüş

2023

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

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Dağıtık üretim birimleri (DG), son yıllarda güç sistemlerinde elektrik enerjisi üretiminde önemli ölçekte pay sahibi haline gelmiştir. Dağıtık üretimlerin sisteme eklenmesi, güç sisteminin üretim kapasitesini arttırırken ayrıntılı araştırma yapılmadan mertebe ve yerleşim seçimi durumunda sistemde güç kayıplarını arttırdığı gibi sistem kararlılığını da olumsuz etkileyebilmektedir. Bu nedenle ortaya çıkabilecek olumsuzları engellemek için dağıtık üretim kaynaklarının sisteme en uygun yer ve güç değerinde seçilmesi gerekmektedir. Bu çalışmada Kuzey Batı Anadolu (KBA) 114 baralı güç sistemine eklenecek dağıtık üretim kaynaklarının yer ve güç değerlerinin belirlenmesi problemi, genetik algoritmalar (GA) optimizasyon yöntemi kullanılarak incelenmiştir. Önerilen yöntem ile belirlenen yerlere yine yöntemle belirlenen kapasitede dağıtık üretim kaynaklarının eklenmesi durumunda güç sisteminin ağ topolojisini değiştirmeksizin aktif güç kayıplarının azaldığı ve bara gerilim profilinin iyileştiği gözlenmiştir.

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Power Loss Minimization for Distribution Networks with Load Tap Changing Using Genetic Algorithm and Environmental Impact Analysis

Cited by 3 publications

References 38 publications

Synthesis of the neuro-fuzzy regulator with genetic algorithm

Synthesis of the neuro-fuzzy regulator with genetic algorithm

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

Kuzeybatı Anadolu Güç Sisteminde Yenilenebilir Enerji Kaynaklarının Optimal Boyutlandırılması ve Yerleşimi

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