Integration of Distributed Generation and Electric vehicles in a distribution network using Political Optimizer

Dharavat, Nagaraju; Sudabattula, Suresh Kumar; Suresh, Velamuri

doi:10.1109/rdcape52977.2021.9633448

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…The reduction of losses in the power system in the presence of EVCSs is achieved in different ways. A large number of papers can be found in the literature that treat the problem of reducing energy losses in the presence of electric vehicles, e.g., optimal operation of vehicles with distributed generators [19][20][21][22][23], optimal reconfiguration of the distribution network [24][25][26][27][28], optimal operation of the battery storage, [29,30], optimal charging strategies [31][32][33][34] and optimal location and size of reactive power compensators [35,36].…”

Section: Introductionmentioning

confidence: 99%

Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses

Pavlićević

Mujović

2022

Energies

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Climate change at the global level has accelerated the energy transition around the world. With the aim of reducing CO2 emissions, the paradigm of using electric vehicles (EVs) has been globally accepted. The impact of EVs and their integration into the energy system is vital for accepting the increasing number of EVs. Considering the way the modern energy system functions, the role of EVs in the system may vary. A methodology for analyzing the impact of reactive power from public electric vehicle charging stations (EVCSs) on two main indicators of the distribution system is proposed as follows: globally, referring to active power losses, and locally, referring to transformer aging. This paper indicates that there is an optimal value of reactive power coming from EV chargers at EVCSs by which active energy losses and transformer aging are reduced. The proposed methodology is based on relevant models for calculating power flows and transformer aging and appropriately takes into consideration the stochastic nature of EV charging demand.

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Section: Introductionmentioning

confidence: 99%

Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses

Pavlićević

Mujović

2022

Energies

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Socio-inspired evolutionary algorithms: a unified framework and survey

2023

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Evolutionary computation has gone through vast and diverse research endeavors in the past few decades. Although the initial inspiration came from Darwin's ideas of biological evolution, the field has moved thereon to ideas from the collective intelligence of insects, birds, and fish, to name a few. A variety of algorithms have been proposed in the literature based on these ideas and have been shown to perform well in various applications. More recently, inspiration from human behavior and knowledge exchange and transformation has given rise to a new evolutionary computing paradigm. It is well recognized that human societies and problem-solving capabilities have evolved much faster than biological evolution. Many research endeavors have been reported in the literature inspired by diverse aspects of human societies with corresponding terminologies to describe the algorithm. These endeavors have resulted in a plethora of algorithms worded differently from each other, but the underlying mechanisms could be more or less similar, causing immense confusion for a new reader. This paper presents a generalized framework for these Socio-inspired Evolutionary Algorithms (SIEAs) or Socio-inspired Metaheuristic Algorithms. A survey of various SIEAs is provided to highlight the working of these algorithms on a common framework, their variations and improved versions proposed in the literature, and their applications in various fields of search and optimization. The algorithmic description of each SIEA enables a clearer understanding of the similarities and differences between these methodologies. Efforts have been made to provide an extensive list of references with due context. In that sense, this paper could become an excellent reference as a starting point for anyone interested in this fascinating field of research.

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Optimal integration of renewable distributed generators and electric vehicles in a radial distributed network

Kumar

Sudabattula

Dharavat

2022

J. Phys.: Conf. Ser.

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With the rising interest in sustainable transportation efforts, the optimal integration of Electric Vehicles (EVs) in the transportation business has come into existence very drastically. However, because of the increased power consumption, their impact on the electric power market might result in more enormous losses in the active power, a reduced voltage profile, as well as reduced voltage stability limits. In Radial Distribution System (RDS), getting the reduced effect of EVs load is crucial. It is significantly important to build charging stations for EVs and Distributed Generators (DGs) at the best locations. This article presents a combined approach to solve the optimal integration of DGs and EVs problem. First, the desired locations of DGs and EVs are found using the Voltage Stability Index (VSI) method. Further, the resource ratings are obtained by the Firefly algorithm (FA) method. EVs charging dump and smart charging strategies are used, and comparison is done with both systems. Furthermore, the main objective of this work is to reduce the power loss and maintain a good voltage profile at each bus in the RDS. Finally, the developed approach is tested on IEEE 69 bus system.

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Integration of Distributed Generation and Electric vehicles in a distribution network using Political Optimizer

Cited by 3 publications

References 16 publications

Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses

Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses

Socio-inspired evolutionary algorithms: a unified framework and survey

Optimal integration of renewable distributed generators and electric vehicles in a radial distributed network

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