An analytical approach for optimal placement and sizing of Distributed Generation based on a combined voltage stability index

Distribution grids are being transformed from passive to active networks by integrating distributed generation (DG). In this paper, a Strength Pareto Evolutionary Algorithm (SPEA) has been used to estimate the best type of DGs and their optimal capacity and location in a 33-node radial distribution network. In order to improve the voltage stability, expressed by its index, and to reduce the active and reactive power losses, multiple scenarios have been proposed and compared. The backward/forward sweep method of distribution load flow was used to evaluate the three objective functions. The same distribution network has been also used to show the effect of the capacity and location of the DGs on the objective functions.

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“…Make sure that the voltages | | along the feeder are well within the tolerable range, ± 5 % of the nominal value [26].…”

Section: Voltage Limits On Each Busmentioning

confidence: 99%

Optimal Placement and Sizing of Distributed Generation Sources in Distribution Networks Using SPEA Algorithm

Mohamed¹,

Mohamed²,

Kansab³

2019

IJEEI

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Modelling, applications, and evaluations of optimal sizing and placement of distributed generations: A critical state‐of‐the‐art survey

Yang

Chen

et al. 2020

Int J Energy Res

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Summary Distributed generation (DG) has attracted significant attention due to its great potential for enhancing economical and technical performance of power systems and reducing dependence on fossil fuels. Optimal sizing and placement are critical for stimulating such potential, about which a considerable number of models and algorithms have been proposed in past literature. This paper attempts to undertake a comprehensive review on optimal sizing and placement of DG via a systematic methodology procedure, including definition and classifications of DG, modelling and problem formulation with different technical and economic criteria, and summary of optimization algorithms. Common features and distinctive characteristics of both models and methods are identified, followed by evaluations and comparisons based on their practical performance in various test systems. Selection of DG techniques with respect to application scenarios, indispensable and optional considerations in DG planning models, and pros and cons of algorithms are listed in tables for a clearer understanding. Lastly, a total of 107 algorithms are addressed, which are classified into five categories. Particular, hybrid methods can deal with complex engineering problems with multiple objective functions and constraints most effectively and robustly. Future research trends are also highlighted with the aim of providing a comprehensive and state‐of‐the‐art survey for researchers, engineers, and other stakeholders.

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Application of Distributed Generation for Reduction of Power Losses and Voltage Deviation in Electric Distribution System by Using AI Techniques

Agajie

Rao

Hailu

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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An analytical approach for optimal placement and sizing of Distributed Generation based on a combined voltage stability index

Cited by 13 publications

References 20 publications

Optimal Placement and Sizing of Distributed Generation Sources in Distribution Networks Using SPEA Algorithm

Optimal Placement and Sizing of Distributed Generation Sources in Distribution Networks Using SPEA Algorithm

Modelling, applications, and evaluations of optimal sizing and placement of distributed generations: A critical state‐of‐the‐art survey

Application of Distributed Generation for Reduction of Power Losses and Voltage Deviation in Electric Distribution System by Using AI Techniques

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