Modified Artificial Bee Colony algorithm for non-convex economic dispatch problems

Nagur, P N; Raj, Shubham; Jadhav, H. T.

doi:10.1109/icgt.2012.6477982

Cited by 6 publications

(4 citation statements)

References 22 publications

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“…3. Lebah penonton menunggu di sarang dan menonton tarian petunjuk lokasi sumber-sumber makanan yang menguntungkan dan memilih situs sumber makanan tergantung pada frekuensi tarian yang sebanding dengan kualitas sumbernya [6][7] [8]. Dalam algoritma ABC yang diusulkan oleh Karaboga, posisi sumber makanan merupakan solusi optimasi dan jumlah nektar sumber makanan merupakan profitabilitas (kebugaran) dari solusi yang terkait.…”

Section: A Artificial Bee Colonyunclassified

Dynamic Economic Dispatch Mempertimbangkan Prohibited Operating Zones Menggunakan Algoritma Improved Artificial Bee Colony

Gumelar

Wibowo

Soeprijanto

2017

JTITS

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B199Abstrak-Dynamic Economic Dispatch (DED) adalah solusi untuk menekan biaya produksi pembangkitan listrik dan efisiensi biaya bahan bakar dengan melakukan optimisasi biaya pembangkitan pada unit pembangkit. Perubahan permintaan beban tiap waktunya mengakibatkan berubahnya biaya pembangkitan per satuan waktu.Fungsi Dynamic Economic Dispatch (DED) untuk mendapatkan pembangkitan daya yang optimal dengan biaya seekonomis mungkin sambil tetap melayani kebutuhan daya ke konsumen selama 24 jam. Beberapa karakteristik dan batasan operasi yang terdapat pada Dynamic Economic Dispatch antara lain kerugian transmisi, batasan ramp rate, permintaan beban dinamis, Prohibited Operating Zones, dan spinning reserve. Pada studi ini menunjukkan implementasi algoritma Improved Artificial Bee Colony (IABC) pada perhitungan Dynamic Economic Dispatch. Beberapa batasan operasi yang dipertimbangkan dalam perhitungan studi antara lain, Prohibited Operating Zones dan batasan operasi ramp rate. Pengujian simulasi Dynamic Economic Dispatch dilakukan dengan menggunakan sistem 6 unit generator dan sistem 15 unit generator. Hasil simulasi menunjukkan batasan ramp rate dan Prohibited Operating Zones berdampak pada biaya pembangkitan. Pada sistem 6 unit generator dengan mempertimbangkan Prohibited Operating zones menggunakan algoritma Improved Artificial Bee Colony (IABC) total biaya pembangkitan sebesar $ 313404/h atau lebih murah 1.002% dibandingkan dengan metode Improved Bee Algorithm (IBA).Kata Kunci-Dynamic economic dispatch, prohibited operating zones, improved artificial bee colony.

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Section: A Artificial Bee Colonyunclassified

Dynamic Economic Dispatch Mempertimbangkan Prohibited Operating Zones Menggunakan Algoritma Improved Artificial Bee Colony

Gumelar

Wibowo

Soeprijanto

2017

JTITS

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“…Hence, more time is required to reach the global solution. The computer technology has been developed many new population based heuristic optimization techniques like differential evolution (DE) [8], evolutionary programming (EP) [9], hybrid evolutionary programming (HEP) [10], particle swarm optimization (PSO) [11], civilized swarm optimization (CSO) [12], craziness based PSO (CRPSO) [13], hybrid PSO (HPSO) [14], modified PSO (MPSO) [15], genetic algorithm (GA) [16], hybrid GA (HGA) [17], adaptive real coded GA (ARCGA) [18], bacteria foraging optimization (BFO) [19], modified BFO (MBFO) [20], modified artificial bee colony (ABC) [21], seeker optimization algorithm (SOA) [22], ant colony optimization (ACO) [23], tabu search (TS) [24], biogeography based optimization (BBO) [25], and quasi oppositional BBO (QOBBO) [26] , oppositional BBO (OBBO) [27], harmony search algorithm (HSA) [28] for solving ELD problems. Other optimization algorithms have been proposed to solve the ELD problem, like the opposition based harmony search algorithm (OHSA) which was introduced by Chatterjee et al [29].…”

Section: Introductionmentioning

confidence: 99%

A comparative study of Economic Load Dispatch with complex non-linear constraints using Salp Swarm Algorithm

Bhattacharjee

Patel

2020

Scientia Iranica

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Economic Load Dispatch (ELD) is an important part of cost minimization procedure in power system operation. Different derivative and probabilistic methods are used to solve ELD problems. This paper proposes a powerful Salp Swarm Algorithm (SSA) to explain the ELD issue including equality and inequality restrictions. The main aim of ELD is to satisfy the entire electric load at minimum cost. The SSA is a population based probabilistic method which guides its search agents that are randomly placed in the search space, towards an optimal point using their fitness function and also keeps a track of the best solution achieved by each search agent. SSA is being used to solve the ELD problem with their high exploration and local optima escaping technique. This algorithm confirms that the promising areas of the search space are exploited to have a smooth transition from exploration to exploitation using the movement of Salps in the sea. Simulation results prove that the proposed algorithm surpasses other existing optimization techniques in terms of quality of solution obtained and computational efficiency. The final results also prove that SSA is more robust when compared to other techniques in the paper.

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“…So they prove to be a bit slow in their approach towards the global optimum solution. With the development in the computer technology, many new population based heuristic optimization techniques have been introduced, like differential evolution (DE) [8], hybrid evolutionary programming (HEP) [9], evolutionary programming (EP) [10], civilized swarm optimization (CSO) [11], particle swarm optimization (PSO) [12], craziness based PSO (CRPSO) [13], hybrid PSO (HPSO) [14], modified PSO (MPSO) [15], hybrid GA (HGA) [16], genetic algorithm (GA) [17],adaptive real coded GA (ARCGA) [18], bacteria foraging optimization (BFO) [19], modified artificial bee colony (ABC) [20], modified biogeography based optimization (BBO) [21], seeker optimization algorithm (SOA) [22], ant colony optimization (ACO) [23], tabu search (TS) [24], and quasi oppositional BBO (QOBBO) [25] , oppositional BBO (OBBO) [26], harmony search algorithm (HSA) [27] for solving ELD problems. Other optimization algorithms have been proposed to solve the ELD problem, like the opposition based harmony search algorithm (OHSA) which was introduced by [28].…”

Section: Introductionmentioning

confidence: 99%

An experimental study regarding Economic Load Dispatch using Search Group Optimization

Bhattacharjee

Patel

2019

Scientia Iranica

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Power System network is formed mainly to generate power from all the generators to fulfil total load demand and transmission line losses. The Economic Load Dispatch (ELD) problem is considered to be one of the most important problems of cost minimization in power system operations. Various approaches have been taken to solve the ELD problem. In this paper a powerful Search Group Optimization (SGO) technique is implemented to solve the ELD problem. SGO maintains a good balance between the exploitation and the exploration phases of the technique. This optimization technique tends to find the promising regions of the search space from the first iteration onwards. The algorithm uses five important steps to reach the optimal solution of the ELD problem. Namely, initial population, initial selection of search group, search group mutation, family generation and new search group selection. Using these five steps, the SGO tends to make a smooth transition towards the optimized solution. The SGO is applied to five test systems and the final results obtained have been compared to various other recently developed optimization techniques. The results prove the robustness, feasibility, effectiveness and efficiency of SGO in terms of computational time and proximity to the global optimum solution.

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Modified Artificial Bee Colony algorithm for non-convex economic dispatch problems

Cited by 6 publications

References 22 publications

Dynamic Economic Dispatch Mempertimbangkan Prohibited Operating Zones Menggunakan Algoritma Improved Artificial Bee Colony

Dynamic Economic Dispatch Mempertimbangkan Prohibited Operating Zones Menggunakan Algoritma Improved Artificial Bee Colony

A comparative study of Economic Load Dispatch with complex non-linear constraints using Salp Swarm Algorithm

An experimental study regarding Economic Load Dispatch using Search Group Optimization

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