Renewable energy inclusion on economic power optimization using thunderstorm algorithm

Afandi, Arif Nur; Sulistyorini, Yunis; Fujita, Goro; Khai, Nguyen Phuc; Tutkun, Nedim

doi:10.1109/eecsi.2017.8239141

Cited by 18 publications

(7 citation statements)

References 17 publications

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“…A model can also be also used to plan the amount of evaluation required to meet desired levels in various fields [1]- [5]. In addition, the model is used to find the optimal allocation of the UC among the various generators available to serve the load [8]- [11], [34], [36]- [38]. Recently, many strategies are developed to explore a UC considering the fuel cost, emission, transmission line losses, weighting factors, and others [5], [23]- [25].…”

Section: Methods and Approachmentioning

confidence: 99%

See 1 more Smart Citation

Combined Computational Intelligence Approach for the Power System Optimization Problem

Afandi¹,

Fadlika²,

Gumilar³

et al. 2018

EECSI

Self Cite

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A power system optimization is one of the major problems in the operating performances of the existing system. This problem takes place on the various technical cases to get optimal conditions of the system. Moreover, many approaches have been implemented to carry out the solution under operational constraints. This paper presents Thunderstorm Algorithm (TA) and Artificial Salmon Tracking Algorithm (ASTA) for defining the optimal strategy of the power system optimization based on the unit commitment. Both algorithms are tested on the IEEE-62 bus system, whereas, results show that ASTA and TA can be combined together to solve the power system problem. These algorithms have been applied to predict the power consumption and it has good performances while searching for the optimal solution. These results also show that the economic dispatch problem is conducted to the power production while the algorithm is performed in good characteristics.

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Section: Methods and Approachmentioning

confidence: 99%

“…In detail, the Thunderstorm Algorithm (TA) is depicted in Fig. 1 with transforming structures in computation processes are Cloud Phase: Streamer Phase; and Avalanche Phase [8], [11], [34]. This figure illustrated a striking propagation from the sky to earth as a charge moving direction.…”

Section: Algorithms Overviewmentioning

confidence: 99%

Combined Computational Intelligence Approach for the Power System Optimization Problem

Afandi¹,

Fadlika²,

Gumilar³

et al. 2018

EECSI

Self Cite

View full text Add to dashboard Cite

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“…In general, the system operation is carried out within 24 hours, and this period considers the power output scheduled for 24 hours to meet energy consumption where the consumption changes load demand from this hour to the next according to technical and environmental requirements. In detail, this relation covers all possible combinations of suitable energy producers associated with reasonable power production [27], [28], which is presented as given in Equation ( 4) to Equation (6).…”

Section: Energy Mixed Approachmentioning

confidence: 99%

Optimization of Power Balance Transaction Based on Renewable Energy Sources Using Artificial Salmon Tracking Algorithm for Modeling the Interconnected Grid Development

Afandi¹,

Aripriharta²,

Rahmawati³

2019

Adv. sci. technol. eng. syst. j.

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Since environmental requirements penetrate engineering processes to keep global warming and to reduce pollutant emissions, the system operation should be designed based on environmentally approach friendly. Operationally, the system processes are supported by energy suppliers to meet continuously energy transaction while clean and green energies are also targeted to keep the environmental conditions. In other word, the renewable energy source becomes an opportunity integration of a potential natural source inclusion into conventional energy producers. Technically, the energy balance is also important to optimize to get an optimal power portion during the operating period. These works are prioritized to search the balanced combination of the integrated energy mix composition. The works also present the novel computational intelligence to find out the energy portion using Artificial Salmon Tracking Algorithm. By considering technical requirements and tested on the integrated renewable energy plants, this algorithm is applied to optimize the economic power production. The works show dynamically the total power for feeding the energy consumption through local loads. The power production is also balanced in various combination portions of energy sources in accordance with the power demand as similar as discharged pollutants. Moreover, the computation has been obtained clearly for optimal solutions within 24 hours using a proposed algorithm.

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“…As in many previous works, the behavior learning presents natural mechanisms for searching suitable models and understanding the phenomena [5], [8], [9]. Many behaviors of entities or species have been selected as inspirations for developing certain approaches based on mechanisms of processes.…”

Section: Introductionmentioning

confidence: 99%

Natural Behavior Learning for Developing an Innovation of Computational Intelligence Applied to a Technical Quadratic Problem

Afandi¹,

Handayani²,

Lestari³

et al. 2019

Proceedings of the 2nd International Conference on Vocational Education and Training (ICOVET 2018)

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Recently, many algorithms have been presented for new approaches based on natural inspirations as introduced in this paper is explored from the migrating Salmon mechanism. This approach is Artificial Salmon Tracking Algorithm (ASTA) which is tested on a standard system model for carrying out a dynamic economic dispatch. In these studies, ASTA is also used to optimize the system and to get an optimal portion of the balanced combination. The results show that the solution is produced dynamically to make the optimal operation for 24 hours. The system model can be balanced based on the quadratic model while ASTA has been demonstrated clearly to search for optimal solutions.

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Renewable energy inclusion on economic power optimization using thunderstorm algorithm

Cited by 18 publications

References 17 publications

Combined Computational Intelligence Approach for the Power System Optimization Problem

Combined Computational Intelligence Approach for the Power System Optimization Problem

Optimization of Power Balance Transaction Based on Renewable Energy Sources Using Artificial Salmon Tracking Algorithm for Modeling the Interconnected Grid Development

Natural Behavior Learning for Developing an Innovation of Computational Intelligence Applied to a Technical Quadratic Problem

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