Impact of distributed generation on radial distribution network with various load models

Hizarci, Halime; Türkay, Belgin Emre

doi:10.1109/upec.2017.8231905

Cited by 7 publications

(4 citation statements)

References 20 publications

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“…In this paper, load models with DG integration is divided into two types, first one is theoretical load model which varies linearly and with square of the voltage (Constant Current Load & Constant Impedance Load) [10][11][12][13] and the other type is termed as practical load model i.e., loads which are majorly used in practical distribution system (Residential, Commercial and Industrial) [15][16][17][18][19][20][21][22][23][24].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Whereas, Payasi et al [20] & Swetha [21] used different types of DGs other than PV, which injects only active power into the system in planning studies. Hizarci and Turkay [24] studied the effect of DG with both theoretical & practical load models for different indices such as Qualified Load Index, System Loadability Index, and Voltage Deviation Index. Khan and Malik [22][23] used only practical load model in planning studies to reduce the losses.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Khan and Malik [22][23] used only practical load model in planning studies to reduce the losses. From the above literature [15][16][17][18][19][20][21][22][23][24], it is evident that some research has been carried out on practical load model with DG integration to minimize the losses in distribution network. However, optimization of DG on inappropriate load model with large test bus systems has not been covered in the literature.…”

Section: Literature Reviewmentioning

confidence: 99%

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Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System

Manikanta

Mani

Singh

et al. 2020

mjee

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Distribution system supplies power to variety of load depending upon the consumer's demand, which is increasing day by day and lead to high power losses and poor voltage regulation. The increase in demand can be met by integrating Distributed Generators (DG) into the distribution system. Optimal location and capacity of DG plays an important role in distribution network to minimize the power losses. Some researchers have studied this important optimization problem with constant power load which is independent of voltage. However, majority of consumers at load center uses voltage dependent load models, which are primarily dependent on magnitude of supply voltage. In practical distribution network, the assumption of constant power load can significantly affect the location and size of DG, which in turn can lead to higher power losses and poor voltage regulation. In this study, an investigation has been performed to find the increase in power loss due to the use of inappropriate load models, while solving the optimization problem. Furthermore, an attempt has been made in this study to reduce power losses occurring in large test bus systems with loads being dependent on voltage rather than the constant power load. Different test cases are created to analyse the power losses with appropriate load model and in-appropriate load model (constant power load model). The load at distribution network is not mainly dependent on any single type of load model, it is a combination of all load models. In this study, a class of mix load viz., combination of residential, industrial, constant power, and commercial load, is also considered. In order to solve this critical combinatorial optimization problem with voltage dependent load model, which requires an extensive search, Adaptive Quantum inspired Evolutionary Algorithm (AQiEA) is used. The proposed algorithm uses entanglement and superposition principles, which does not require an operator to avoid premature convergence and tuning parameters for improving the convergence rate. A Quantum Rotation inspired Adaptive Crossover operator has been used as a variation operator for a better convergence. The effectiveness of AQiEA is demonstrated and computer simulations are carried out on two standard benchmark large test bus systems viz., 85 bus system and 118 bus system. In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. Tabulated results show that the location and size of DGs determined using in-appropriate load model (constant power load model) has significantly high power losses when applied in distribution system with different load model (other voltage dependent load models) as compared with the location and size of DGs determined using the appropriate load model. Experimental results indicate that AQiEA has a better pe...

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System

Manikanta

Mani

Singh

et al. 2020

mjee

View full text Add to dashboard Cite

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“…O método de busca Cuco foi aplicado por (Samal et al, 2016) para determinação da dimensão e posicionamento dos REDs a fim de avaliar um método ótimo de planejamento para alocação e dimensionamento dos recursos. Em (Hizarci and Turkay, 2017), os autores utilizam inicialmente um método analítico para determinação do posicionamento dos REDs com base em fatores de sensibilidade de perdas para, posteriormente, utilizarem um algoritmo de enxame de partículas para determinação do dimensionamento das instalações. O método proposto pelos autores em (Zhang et al, 2016) introduz uma classificação composta por fatores de sensibilidade de tensão e de perdas para atuar na função objetivo de otimização.…”

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Distribuição de Recursos Energéticos para Análise dos Impactos da Geração Distribuída

Alvaro R. Albertini,

Vítor T. Yabe,

Silvio G. Di Santo

2022

Proceedings IX Simpósio Brasileiro De Sistemas Elétricos

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The increasing penetration of Distributed Energy Resources (DERs) and Distributed Generation (DG) means a paradigm change in planning and operation of power systems around the world. In order to understand and circumvent the possible challenges arising from the growing energy injection at this grid level, new modeling and analysis tools are required. This paper presents a methodology for the distribution of energy resources for power system analysis. In this method, the feeder is divided into regions and probabilities of DG occurrence are determined for each of the delimited zones. The energy resources are allocated in a random and iterative fashion, according to the established application goals, described through boundary conditions. In terms of results, the method presented the capability to estimate the occurence of load shifting, losses reduction, and changes on voltage fluctuations once the integration of DER increases. The procedure proved to be flexible and efficient in the development of case study scenarios and it may be applied, among others, in the analysis of DER penetration impacts', hosting capacity studies. Resumo: O aumento da penetração dos Recursos Energéticos Distribuítos (REDs) e da Geração Distribuída (GD) significa uma mudança nos paradigmas de planejamento e operação do sistema elétrico ao redor do mundo. Para entender e contornar os possíveis desafios decorrentes da crescente injeção energética nesse nível de rede, é necessária a criação de novas ferramentas de modelagem e análise. Este trabalho apresenta uma metodologia de distribuição dos recursos energéticos para análises do sistemas de potência. Nele, o alimentador é dividido em regiões e são determinadas probabilidades de ocorrência de geração distribuída em cada uma das zonas delimitadas. Os recursos energéticos são alocados de maneira aleatória e iterativa, de acordo com objetivos de aplicação estipulados, descritos através das condições de contorno da metodologia. Em relação aos resultados obtidos, observou-se a capacidade do modelo em estimar a ocorrência de deslocamento da demanda de pico, diminuição das perdas totais do alimentador e alteração nos índices de variação de tensão com a crescente penetração de REDs. O procedimento mostrouse flexível e eficiente na criação de cenários de estudo e pode ser aplicado, entre outros, em análises dos impactos e penetração de REDs e estudos capacidade de alocação de recursos energéticos.

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Intra-minutes technical impacts of PV grid integration on distribution network operation of a rural community under extreme PV power delivery

Azab

2018

Energy Syst

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Impact of distributed generation on radial distribution network with various load models

Cited by 7 publications

References 20 publications

Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System

Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System

Distribuição de Recursos Energéticos para Análise dos Impactos da Geração Distribuída

Intra-minutes technical impacts of PV grid integration on distribution network operation of a rural community under extreme PV power delivery

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