Self‐adaptive firefly algorithm based multi‐objectives for multi‐type FACTS placement

Ranganathan, S.; Kalavathi, M. Surya; Rajan, C.

doi:10.1049/iet-gtd.2015.0905

Cited by 47 publications

(40 citation statements)

References 24 publications

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“…In recent years there has been growing interest in the employment of AI to this kind of problems. Actually, AI techniques such as PSO, GA, GSA or DE have inspired researchers to develop several algorithms ( [21][22][23]). Alternatively, the Pareto approach, combined with FDMs, is also employed to determine the optimal FACTS devices allocation [24].…”

Section: Introductionmentioning

confidence: 99%

A FACTS Devices Allocation Procedure Attending to Load Share

2020

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Power system stability is a topic which is attracting considerable interest due to the increase of both electrical demand and distributed variable generation. Since Flexible AC Transmission Systems (FACTS) devices are an increasingly widespread solution to these issues, it is important to study how their allocation procedure should be done. This paper seeks to assess the influence of load share in FACTS devices allocation. Despite this interest, researchers, as well as system planners, have mainly focused on studying single power system configuration rather than using a wider approach. Keeping this in mind, we have iteratively created several load share scenarios based on an IEEE 14-bus test system. Subsequently, we have applied an heuristic procedure in order to demonstrate how load share may affect the results of the FACTS devices allocation procedure. Additionally, we have compared results from two different objective functions so as to evaluate our proposal. Finally, we have proposed a solution to FACTS allocation which takes load share into account. Our tests have revealed that, depending on the distribution of load within the power system, the optimal location for a FACTS device may change. Furthermore, we have also found some discrepancies and similarities between results from distinct objective functions.

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Section: Introductionmentioning

confidence: 99%

A FACTS Devices Allocation Procedure Attending to Load Share

2020

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“…References [14][15][16][17] present the effects of different types of FACTS devices on system voltage stability, power flow entropy or loadability. In addition, multi-objective optimization placement of multi-type FACTS devices is investigated in [18][19][20] based on intelligent optimization algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimal configuration of distributed power flow controller to enhance system loadability via mixed integer linear programming

Dai

Tang

Liu

et al. 2019

J. Mod. Power Syst. Clean Energy

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Increasing energy consumption has caused power systems to operate close to the limit of their capacity. The distributed power flow controller (DPFC), as a new member of distributed flexible AC transmission systems, is introduced to remove this barrier. This paper proposes an optimal DPFC configuration method to enhance system loadability considering economic performance based on mixed integer linear programming. The conflicting behavior of system loadability and DPFC investment is analyzed and optimal solutions are calculated. Thereafter, the fuzzy decision-making method is implemented for determining the most preferred solution. In the most preferred solution obtained, the investment of DPFCs is minimized to find the optimal number, locations and set points. Simulation results on the IEEE-RTS79 system demonstrate that the proposed method is effective and reasonable.

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“…An adaptive DE algorithm is proposed for allocating the TCSC incorporated with the reactive power management problem [36]. In [37], the self-adaptive firefly algorithm (SAFA) is presented to optimize the placement of TCSCs, SVCs and UPFCs for improving the power system performance through minimizing real power loss, improving voltage profiles and enhancing the voltage stability. In [38], the imperialistic competitive algorithm (ICA) is employed for solving TCPST and TCSC allocation problem in a way that low values of overloads and voltage deviations result both during line outage contingencies and demand growth.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach for Power System Security Enhancement via Optimal Installation of Flexible AC Transmission System (FACTS) Devices

et al. 2017

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Abstract:Increasing demand for electricity has placed heavy stress on power system security. Therefore, this paper focuses on the problem of how to maximize power system static security in terms of branch loading and voltage level under normal operation and even the most critical single line contingency conditions. This paper proposes a hybrid approach to find out the optimal locations and settings of two classical types of flexible AC transmission system (FACTS) devices, namely thyristor-controlled series compensators (TCSCs) and static var compensators (SVCs) for solving this problem. Our proposed approach requires a two-step strategy. Firstly, the min cut algorithm (MCA) and tangent vector technique (TVT) are applied to determine the proper candidate locations of TCSC and SVC respectively so as to reduce the search scope for a solution to the problem, and then the cuckoo search algorithm (CSA) is employed to solve this problem by simultaneously optimizing the locations and settings for TCSC and SVC installation. The proposed hybrid approach has been verified on the IEEE 6-bus and modified IEEE 14-bus test systems. The results indicate that CSA outperforms particle swarm optimization (PSO), proving its effectiveness and potential, and they also show that our proposed hybrid approach can find the best locations and settings for TCSC and SVC devices as an effective way for enhancing power system static security by removing or alleviating the overloads and voltage violations under normal operation and even the most critical single line contingency conditions. Using this hybrid approach, the search space for solution to the problem becomes limited hence the computational burden will be decreased.

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Self‐adaptive firefly algorithm based multi‐objectives for multi‐type FACTS placement

Cited by 47 publications

References 24 publications

A FACTS Devices Allocation Procedure Attending to Load Share

A FACTS Devices Allocation Procedure Attending to Load Share

Optimal configuration of distributed power flow controller to enhance system loadability via mixed integer linear programming

A Hybrid Approach for Power System Security Enhancement via Optimal Installation of Flexible AC Transmission System (FACTS) Devices

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