ATLA: A novel metaheuristic optimization algorithm inspired by the mating search behavior of longicorn beetles in the nature

Han, Xiaokuang; Du, Xianjun; Yu, Ping

doi:10.1088/1757-899x/782/5/052028

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…In this scheduling process, majorly the scheduling of shiftable electric devices is considered by using the real time pricing signal. Due to the scheduling process of residential electric devices, the proposed approach utilized the waiting time threshold 33,52‐54 . The detailed description of the proposed approach is given below.…”

Section: Optimal Energy Management System Of Iot‐enabled Residential ...mentioning

confidence: 99%

A hybrid approach for optimal energy management system of internet of things enabled residential buildings in smart grid

Vanitha

Vallimurugan²

2022

Intl J of Energy Research

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Nowadays, a large number of smart devices in residential buildings is integrated with the evolution of internet of things (IoT), where it is necessary to effectively manage energy to meet the increase in demand. Therefore, in this paper, an optimal energy management strategy using the hybrid Gradient Boosting Decision Tree ‐Artificial Transgender Longicorn Algorithm (GBDT‐ALTA) is proposed for IoT‐enabled residential buildings. The main objective of the proposed approach is to minimize the electricity bill of customer, thereby Peak‐to‐Average Ratio (PAR) is reduced. Due to the scheduling process of residential electric devices, the proposed approach utilizes the waiting time threshold. Here, three types of appliances, such as shiftable electrical devices, thermostatically controlled electrical devices, and generally operated electrical devices are considered. Related to real‐time price signals (RTPS) in utilities, scheduling the shiftable electrical devices is processed. The cost minimization with less acceptable time of waiting is achieved by GBDT‐ATLA method, which considers the trade‐off between the electricity cost and waiting time. Moreover, the proposed approach maintains the stability of the grid, because the stability of grid depends on the PAR. The proposed method is carried out in MATLAB/Simulink site and the simulated results prove that the better performance of GBDT‐ATLA approach compared to the existing approaches, like Slime Mould Optimization (SMO), Chaos Game Optimization Algorithm (CGO), and Side‐Blotched Lizard Optimization Algorithm (SBLO). The efficiency of the proposed approach under 100, 200, 500, and 1000 trails are 99.7300%, 99.6513%, 99.8363%, and 99.7916% respectively.

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Section: Optimal Energy Management System Of Iot‐enabled Residential ...mentioning

confidence: 99%

A hybrid approach for optimal energy management system of internet of things enabled residential buildings in smart grid

Vanitha

Vallimurugan²

2022

Intl J of Energy Research

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“…If not, they perform the Lévy flight search movement in space. 47 In this manuscript, the ATL algorithm is utilized to break down the original optimization method as a major issue including numerous subproblems. The major issue optimizes the IES, when the subproblems optimize EVCS operation in parallel.…”

Section: Proposed Atla Strategy For Optimizing Energy Trading Problemmentioning

confidence: 99%

“…Male longicorn individuals have been attracted as well as affected through the sex pheromone while they attempt to approach the female longicorn and walking in the range. If not, they perform the Lévy flight search movement in space 47 . In this manuscript, the ATL algorithm is utilized to break down the original optimization method as a major issue including numerous subproblems.…”

Section: Proposed Energy Management Strategymentioning

confidence: 99%

Optimally manage the energy between electric vehicle charging stations and electricity distribution system: A hybrid technique

Venkatakrishnan

Rengaraj

Prakash³

2021

Int J Numerical Modelling

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In this manuscript, the energy trading model is proposed for investigating the cooperative benefits between several electric vehicle charging stations (EVCSs) and integrated energy systems (IES) based on hybrid system. The proposed hybrid system is combination of Radial‐Basis Function Neural Network (RBFNN) and artificial transgender longicorn algorithm (ATLA), hence it is called RBFNN‐ATLA technique. Initially, the RBFNN approach manages the energy between IES and EVCSs. After that, the original issue breaks down into the main energy trade and payment negotiation issue. The energy trading issue and payment negotiation problem can be solved using ATLA approach. This proposed structure may not only diminish the IES cost, however also enlarge the EVCS profit. The uncertainties in electricity and renewable energy prices are modeled using a robust optimization technique. Additionally, the integrated demand response is modeled for maximizing operational performance. The distributed algorithm depends on the proposed technique is evolved for solving the issue of energy trading, ensuring the privacy of players. The proposed algorithm may obtain the global optimal solutions devoid of adjusting the parameter compared with existing algorithm. The proposed system is performed by the matrix laboratory (MATLAB)/Simulink and the performance is evaluated with other existing methods. The RBFNN‐ATLA method reduces the cost up to 3.76%, 7.793%, 8.210% and 9.01% for independent and cooperative mode. The experimental outcomes demonstrate that the proposed system can accurately detect that optimal global solution.

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“…[3][4][5] At present, the stage of development EV industry is still developing because of lack of charging infrastructure. [6][7][8] Even though the drivers charge their cars in home, but the longer time of charge may affects the vehicles. 9 The fast EV charging stations are most required to help the EV industry development.…”

Section: Introductionmentioning

confidence: 99%

“…Reduction in the China's dependence on oil resources and improvement in the environmental pollution is tackled by developing electric vehicles (EV) 3‐5 . At present, the stage of development EV industry is still developing because of lack of charging infrastructure 6‐8 . Even though the drivers charge their cars in home, but the longer time of charge may affects the vehicles 9 .…”

Section: Introductionmentioning

confidence: 99%

An optimization framework for capacity allocation and energy management of fast electric vehicle charging stations‐wind photovoltaic energy using artificial transgender longicorn algorithm

Arivalahan

Balaji

2022

Intl J of Energy Research

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Summary This paper proposes the optimal design for fast electric vehicle charging stations for the capacity configuration of components and the power scheduling strategy. The proposed approach is the artificial transgender longicorn algorithm, which is a simple and powerful controller. The optimal capacity of the system components and the optimal power scheduling approach are determined. First, an electric vehicle charging simulation model is built considering the demand response, which dynamically modified the charging expectation based on the electricity price at the time of use. Second, based on the system design, a multi‐objective optimization model is proposed with minimal objectives for the electricity cost and polluting emissions. Finally, a scenario analysis is carried out and it is concluded that renewable energy supplies, connection to the utility grid and demand response may help improve the performance of the optimization objectives. By then, the performance of the proposed technique is implemented in the MATLAB platform and compared with several existing approaches.

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ATLA: A novel metaheuristic optimization algorithm inspired by the mating search behavior of longicorn beetles in the nature

Cited by 8 publications

References 11 publications

A hybrid approach for optimal energy management system of internet of things enabled residential buildings in smart grid

A hybrid approach for optimal energy management system of internet of things enabled residential buildings in smart grid

Optimally manage the energy between electric vehicle charging stations and electricity distribution system: A hybrid technique

An optimization framework for capacity allocation and energy management of fast electric vehicle charging stations‐wind photovoltaic energy using artificial transgender longicorn algorithm

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