Application of firefly algorithm for multi-stage transmission expansion planning with adequacy-security considerations in deregulated environments

Rastgou, Abdollah; Moshtagh, Jamal

doi:10.1016/j.asoc.2016.01.018

Cited by 21 publications

(8 citation statements)

References 47 publications

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“…The proposed TEP model with renewable energy sources [38][39][40] such as wind turbine and PV array using GWGA method has been simulated in MATLAB, tested in IEEE 24 bus system and the results obtained are analysed. The performance of the proposed model has been compared with traditional algorithms such as GA [23][24][25][26], PSO [41][42][43][44][45][46], ABC [47][48], FF [49][50] and GWO [22][23][24][25][26][27][28] based on cost function and load shedding function. The corresponding outcomes were evaluated to certify the performance of the proposed model.…”

Section: Resultsmentioning

confidence: 99%

A Multi-objective Hybrid Optimization for renewable energy integrated Electrical Power Transmission Expansion Planning

Gaffoor

Chacko

2022

Int. j. electr. comput. eng. syst. (Online)

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Due to the large size of conventional electrical power transmission systems and the large number of uncertainties involved, achieving the most favourable Transmission Expansion Planning solution turns out to be almost impossible. The proposed method intends to develop a novel method to solve Transmission Expansion Planning problems in electric power systems incorporating renewable energy sources like wind turbines and Photo Voltaic array using IEEE 24 Reliability Test System. For enhancing the efficiency of search processes and to make its use easier on diverse networks and operations, the hybridization of two renowned meta-heuristic algorithms known as Grey Wolf Optimization (GWO) and Genetic Algorithm (GA) termed as Grey Wolf with Genetic Algorithm (GWGA) is adopted. A novel distance factor based on the best position and current position of the solution in Grey wolf optimization is introduced and proposed for the hybridization technique and gives a quick and promising solution with reduced computational time. The GWO and GA algorithms are combined suitably to achieve the advantages of both algorithms. With this proposed model, the investment cost of the transmission line and the maximum amount of power that can be distributed to the consumer is optimized with an objective of minimum load shedding. Among the state-of-the-art optimization techniques considered, a remarkable performance percentage improvement in the expansion plan in terms of cost reduction and load shedding minimization has been obtained in GWO, but when hybridized with GA, an improvement of 13.42% in cost function and 18.65% in load shedding is achieved for a population size of 60. Hence, the proposed method guarantees to generate the best solution with a faster convergence resulting in reduced computational time.

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Section: Resultsmentioning

confidence: 99%

A Multi-objective Hybrid Optimization for renewable energy integrated Electrical Power Transmission Expansion Planning

Gaffoor

Chacko

2022

Int. j. electr. comput. eng. syst. (Online)

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“…In [35], a PSO algorithm was used in order to solve market-based TEP problems along with reactive power planning. Application of Firefly algorithm (FA) was introduced in [36] for solving multi-stage TEP problems in a restructured environment while considering investment cost, congestion cost, as well as reliability criterion. An improved PSO algorithm was presented in [37] for finding the optimal expansion plan of smart transmission networks in which a load shedding model and shunt compensation planning were considered in the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

Naderi

Pourakbari‐Kasmaei²,

Lehtonen³

2020

International Journal of Electrical Power & Energy Systems

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This paper develops a novel hybrid algorithm for solving transmission expansion planning (TEP) problems in electric power networks. Raising the awareness about immense contaminants produced by fossil fuels as well as depleting these resources, have pushed energy companies toward considering more renewable energy resources (RERs). The RESs are beneficial for the society and the power system utility, however, taking into account the uncertainties, which are inherent in RERs, increase the complexity of the optimization problems. In this work, a Monte-Carlo simulation (MCS) is used to address the intermittent nature of wind energy. To handle the resulted model, by modifying and combining three wellknown evolutionary algorithms such as shuffled frog leaping algorithm (SFLA), particle swarm optimization (PSO), and teaching learning-based optimization (TLBO), a potent hybrid MSFLA-MPSO-MTLBO, namely combinatorial heuristic-based profound-search algorithm (CHPSA), is proposed. A self-adaptive probabilistic mutation operator (SAPMO) is employed to enhance the effectiveness and computational efficiency of the CHPSA. Ten commonly-used benchmark problems are introduced to corroborate the performance of the CHPSA, while the IEEE RTS 24-bus test system is used to validate the model. Results show that the proposed CHPSA is capable of obtaining better solutions than other algorithms, either implemented in this paper or borrowed from the literature.

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“…da-Silva developed [434] MOEA technique for generation expansion planning. Rastgou and Moshtagh [435] introduced Firefly algorithm technique. Sisodia et al [436] applied hybrid algorithm model for resolving TEP problems.…”

Section: Rajesh Et Al [349] Established a Multi-stage Mixedmentioning

confidence: 99%

Recent Updates on Energy Planning Models - A Review

Hafeez

Gulshan

Tahira

2020

Journal of Mechanical and Energy Engineering

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Energy is the most important part for community and financial growth of any country. Energy planning models play a vital role in strategy formulation and power sector progress. In this paper a systematic review and comparison of energy planning models developed and applied from 1977-2019 has been presented. The review indicates that most of the energy planning models has been presented and applied in developed nations. Only few numbers of energy planning models have been presented and applied in under developing countries. The review also shows the comparison of energy planning models applied in developed and under-developed countries. This review article will assistance the energy managers, scholars and strategy makers broadly.

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Application of firefly algorithm for multi-stage transmission expansion planning with adequacy-security considerations in deregulated environments

Cited by 21 publications

References 47 publications

A Multi-objective Hybrid Optimization for renewable energy integrated Electrical Power Transmission Expansion Planning

A Multi-objective Hybrid Optimization for renewable energy integrated Electrical Power Transmission Expansion Planning

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

Recent Updates on Energy Planning Models - A Review

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