Security constrained optimal power flow solution using new adaptive partitioning flower pollination algorithm

Mahdad, Belkacem; Srairi, K.

doi:10.1016/j.asoc.2016.05.027

Cited by 75 publications

(31 citation statements)

References 52 publications

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“…FACTS components have a very important role in further enhancing the impact of the power systems solution on the OPF problem. Mahdad and Srairi [5] used the adaptive flower pollination algorithm combined with SVC to resolve the OPF in the case of failures in the generating units. UPFC is a better FACTS tool that has been used to mitigate transmission losses and network operating costs [6][7], power system loadability, congestion management and various other applications.…”

Section: Introductionmentioning

confidence: 99%

Optimal Reallocation of Generators using Line Utilization Factor and L-Index with UPFC

2019

IJITEE

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In the electrical industry, globalization and privatization have greatly increased competition. Therefore, it has become completely necessary to make full use of existing power assets. In this paper, a technique was proposed in the presence of UPFC to optimize the sizing of generators with Krill Herd algorithm. The UPFC is based on an index incorporating both the L-index and the LUF index. For tuning the generators, a multi-objective function has been selected. The multi-objective feature consists of deviation of voltage, cost of active generation of power and loss of transmission line. This approach was tested and implemented for regular loading and extreme network conditions due to line failure on an IEEE 30 bus system.

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Section: Introductionmentioning

confidence: 99%

Optimal Reallocation of Generators using Line Utilization Factor and L-Index with UPFC

2019

IJITEE

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“…krill herd algorithm, 15 moth swarm algorithm (MSA), 16 hybrid differential evolution-harmony search algorithm, 17 and adaptive partitioning flower pollination algorithm 18 to solve classical OPF problem.…”

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confidence: 99%

Optimal power flow of power systems with controllable wind‐photovoltaic energy systems via differential evolutionary particle swarm optimization

Duman

Rivera

et al. 2019

Int Trans Electr Energ Syst

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Summary The produced energy from varied sources in modern power systems is to be optimally planned for planning and operating of power system under the determined limit conditions. Recently, the rising overall people population of the world, the increasing of people requirements, improvements of technology, and ecosystem and global climate changes have caused with the increasing of electric energy demand. One of the most important solution methods to meet this energy demand is considered as utilization of renewable energy sources (RESs) in power systems. The structure of power systems has become with the usage of RESs more complex. The optimal power flow (OPF) from planning and operation problems has converted to difficult problem with RESs integrated into modern power systems. This paper presents the OPF problem of power systems with a high penetration of controllable renewable sources. These kinds of sources are able to inject a determined power since they have a back‐up unit (storage). Uncertain solar irradiance and wind speed are simulated via log‐normal and Rayleigh probability distributions, respectively. The proposed OPF problem with controllable renewable sources is solved by the differential evolutionary particle swarm optimization (DEEPSO) algorithm. Simulations conducted on various test systems illustrate the effectiveness and efficiency of DEEPSO as compared with other algorithms including moth swarm algorithm, backtracking search algorithm, and differential search algorithm. In addition, the Wilcoxon signed‐rank test is applied to show the supremacy, effectiveness, and robustness of DEEPSO algorithm.

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“…Valve point effect of generator are taken into account in other studies [9] whose objective function is to get the minimal fuel costs. Furthermore, the addition of Static VAR Compensator (SVC) as a control variable and the addition of the influence of valve-point loading effect on the fuel function is shown in other studies [10].…”

Section: Introductionmentioning

confidence: 99%

“…The use of FPA methods to solve OPF problems has been done by previous researchers [7] - [10]. Researchers use Flexible AC Transmission System (FACTS) to get minimum line power losses and fuel costs with active power generator as control variables [7].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Power Flow Using Flower Pollination Algorithm: A Case Study of 500 kV Java-Bali Power System

Sakti

Sarjiya

Hadi

2017

IJITEE

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Security constrained optimal power flow solution using new adaptive partitioning flower pollination algorithm

Cited by 75 publications

References 52 publications

Optimal Reallocation of Generators using Line Utilization Factor and L-Index with UPFC

Optimal Reallocation of Generators using Line Utilization Factor and L-Index with UPFC

Optimal power flow of power systems with controllable wind‐photovoltaic energy systems via differential evolutionary particle swarm optimization

Optimal Power Flow Using Flower Pollination Algorithm: A Case Study of 500 kV Java-Bali Power System

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