Performance comparison of evolutionary programming and differential evolution approaches for social welfare maximization by placement of multi type FACTS devices in pool electricity market

Balamurugan, K.; Muralisachithanandam, R.; Dharmalingam, V.

doi:10.1016/j.ijepes.2014.12.007

Cited by 32 publications

(17 citation statements)

References 14 publications

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“…S. T. Suganthi et al [66] Improved DE To mitigate congestion through the installation of new wind farms in transmission lines and generator rescheduling. K. Balamurugan, et al [67] Evolutionary Programming(EP) & Differential Evolution (DE)…”

Section: Distributed Generationmentioning

confidence: 99%

A survey on recent advances in transmission congestion management

Gajjala

Ahmad

2021

IRASE

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For the last few decades, the power sector has been restructuring throughout the world, and because of this, congestion is bound to take place in the network. Congestion can lead to market failure, violate transmission capability limits and high electricity prices, and end up threatening the power systems’ reliability and security. Increased congestion may also lead to unexpected price differences in power markets leading to market power. In a deregulated power market (DPM), the independent system operator (ISO)’s fundamental challenge is to preserve the power market’s reliability and safety by improving market efficiency when the network is congested. Therefore, congestion management (CM) is essential in DPM and is the key to the power system. This paper carries out a congestion management methods survey to bring together all recent publications in the DPM. It aims to help readers summarize progressive CM methods, along with traditional CM methods that have been discussed so far. In this paper, we have carried out a comparative survey of the various well-known CM methods.

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Section: Distributed Generationmentioning

confidence: 99%

A survey on recent advances in transmission congestion management

Gajjala

Ahmad

2021

IRASE

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“…In [25], a GA for finding the optimal location and size of this device was proposed for congestion management with the aim of increasing social welfare. A novel efficient differential evolution and evolutionary programming technique for social welfare maximization by optimal location of various FACTS devices in pool electricity market based on contingency analysis was introduced in [26].…”

Section: Introductionmentioning

confidence: 99%

An Effective Method for Maximizing Social Welfare in Electricity Market via Optimal TCSC Installation

Long¹,

Nguyen²,

Nguyen³

et al. 2019

Eng. Technol. Appl. Sci. Res.

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The evolving electricity market has increased power demand and has brought many social benefits. Meanwhile, the transmission systems are not developed to the same extent because building new lines is difficult for environmental and political reasons. Hence, the systems are driven close to their limits resulting in congestions and critical situations endangering the system’s security. Due to this, the study of enhancing the transfer capability of existing power networks to satisfy the increased power demand, maximum social welfare, and ensure its secure operation has become one of the challenges the Independent System Operator faces in the electricity market. In order to solve this problem without building more transmission lines, the installation of FACTS devices can be a better alternative. Among FACTS devices, thyristor-controlled series compensator (TCSC) is one that can redistribute power flow in the network to improve the transfer capability of the existing system effectively. However, it is very difficult to implement. This paper presents the implementation of the Cuckoo Optimization Algorithm (COA) to solve the OPF problem which is formulated as a nonlinear optimization problem with equality and inequality constraints in a power system for social welfare maximization via the optimal installation of TCSC devices. As Cuckoo Search Algorithm (CSA), the COA also starts with an initial population-based metaheuristic optimization inspired by the nature of brood parasitism of some cuckoo species. However, unlike CSA, COA uses the cuckoo’s style for egg-laying to optimize the local search instead of using Lévy flights. This model is tested in IEEE 14 and IEEE 30 bus systems. Simulations results are compared with GA and GWO and show that the COA is one useful method for TCSC installation to maximize social welfare.

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“…The various optimisation techniques offered as solution as for the placement of FACTS has been suggested in recent decades [4–18]. The solution techniques may be classified as conventional, intelligent searches and fuzzy set applications.…”

Section: Introductionmentioning

confidence: 99%

“…An EP and DE techniques‐based economic dispatch has been developed to improve the social welfare. In this paper FACTS devices have been considered to minimise the cost and to reduce the overloads [18]. The bacteria foraging algorithm has been proposed to optimise the real power loss (RPL) and voltage stability limit [19].…”

Section: Introductionmentioning

confidence: 99%