FACTS Devices Allocation With Control Coordination Considering Congestion Relief and Voltage Stability

Wibowo, Rony Seto; Yorino, Naoto; Eghbal, Mehdi; Zoka, Yoshifumi; Sasaki, Yuya

doi:10.1109/tpwrs.2011.2106806

Cited by 117 publications

(81 citation statements)

References 23 publications

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“…SVC and TCSC FD types only are used in [3]. It is noted that the FD locations reported in [3] are compatible with the results obtained in this work.…”

Section: Comparative Evaluationsupporting

confidence: 85%

“…SVC and TCSC FD types only are used in [3]. It is noted that the FD locations reported in [3] are compatible with the results obtained in this work. But the FD sizes and number in [3] tend to be less than their counterparts in this work.…”

Section: Comparative Evaluationsupporting

confidence: 85%

“…This paper presents an approach to optimally allocate multiple FD in deregulated electricity market Series FD Line (6-11), (2-4), (3)(4), (9)(10)(11)(12)(13)(14), and (7-9) (4-5), (9)(10)(11)(12)(13)(14), (13)(14), (1-2), (2-3), (10-11), …”

Section: Resultsmentioning

confidence: 99%

“…A polynomial cost function of FD is derived and used for FACTS allocation study as in [3], [11]. The investment costs of TCSC, SVC and UPFC can be formulated as follows: …”

Section: Facts Devices Investment Costmentioning

confidence: 99%

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Long‐term economic model for allocation of FACTS devices in restructured power systems integrating wind generation

Elmitwally

Eladl

Morrow

2016

IET Generation, Transmission & Distribution

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Abstract-This paper proposes an approach to optimally allocate multiple types of flexible AC transmission system (FACTS) devices in market-based power systems with wind generation. The main objective is to maximize profit by minimizing device investment cost, and the system's operating cost considering both normal conditions and possible contingencies. The proposed method accurately evaluates the long-term costs and benefits gained by FACTS devices installation to solve a large-scale optimization problem. The objective implies maximizing social welfare as well as minimizing compensations paid for generation rescheduling and load shedding. Many technical operation constraints and uncertainties are included in problem formulation. The overall problem is solved using both Particle Swarm Optimizations (PSO) for attaining optimal FACTS devices allocation as main problem and optimal power flow as sub optimization problem. The effectiveness of the proposed approach is demonstrated on modified IEEE 14-bus test system and IEEE 118-bus test system.

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“…SVC and TCSC FD types only are used in [3]. It is noted that the FD locations reported in [3] are compatible with the results obtained in this work.…”

Section: Comparative Evaluationsupporting

confidence: 85%

Section: Comparative Evaluationsupporting

confidence: 85%

Section: Resultsmentioning

confidence: 99%

“…A polynomial cost function of FD is derived and used for FACTS allocation study as in [3], [11]. The investment costs of TCSC, SVC and UPFC can be formulated as follows: …”

Section: Facts Devices Investment Costmentioning

confidence: 99%

See 2 more Smart Citations

Long‐term economic model for allocation of FACTS devices in restructured power systems integrating wind generation

Elmitwally

Eladl

Morrow

2016

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

show abstract

“…Alternatively, evolutionary algorithms (EAs) are able to account for this purpose in system planning areas [16]. In [17][18][19][20][21][22][23], related applications of the evolutionary techniques, such as genetic, hybrid tabu search, simulated annealing and PSO algorithms, were indentified with high efficiency to achieve the optimal solution.…”

Section: Introductionmentioning

confidence: 99%

Fitness Sharing Particle Swarm Optimization Approach to FACTS Installation for Transmission System Loadability Enhancement

Chang¹

2013

Journal of Electrical Engineering and Technology

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-Proper installation of Flexible AC Transmission Systems (FACTS) devices in existing transmission networks can enable power systems to accommodate more power transfer with less network expansion cost. The problem to maximize transmission system loadability by determining optimal locations and settings for installations of two types of FACTS devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), is formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). For solving the MDCP, in the paper, the proposed method with fitness sharing technique involved in the updating process of the particle swarm optimization (PSO) algorithm, can diversify the particles over the search regions as much as possible, making it possible to achieve the optimal solution with a big probability. The modified IEEE-14 bus network and a practical power system are used to validate the proposed method.

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A novel approach for optimal allocation of series FACTS device for transmission line congestion management

Sarwar

Siddiqui

2020

Engineering Reports

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The reformed electricity market structure has forced the transmission network to operate near its operational limits. Due to competition in electricity market and with increasing demand, the probability of occurrence of congestion in transmission network has also increased. This resulted in insecure operation of power system and inefficient operation of the electricity market. The main aim of this article is to achieve efficient management of congestion in terms of minimum cost of electricity. This is accomplished by optimally allocating thyristor‐controlled series capacitor (TCSC) in the system. Since flexible alternating current transmission system (FATCS) devices involve heavy installation cost, its proper allocation plays a vital role in achieving the electricity market economics. Therefore, in this article, a new sensitivity index called line flow sensitivity factor is proposed to find the optimal location of TCSC while its control parameter setting is optimally obtained with particle swarm optimization algorithm. The obtained results are validated through implementation of TCSC based on its minimum installation cost. Further, two different penalty factors for violation of system constraints are also introduced in the problem formulation to effectively consider the competitive nature of the electricity market. The proposed method is tested on IEEE 30‐bus system, IEEE 118‐bus system, and 33‐bus Indian network and the results are found to be encouraging. The performance of the optimization algorithm on different systems is also analyzed in this article.

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FACTS Devices Allocation With Control Coordination Considering Congestion Relief and Voltage Stability

Cited by 117 publications

References 23 publications

Long‐term economic model for allocation of FACTS devices in restructured power systems integrating wind generation

Long‐term economic model for allocation of FACTS devices in restructured power systems integrating wind generation

Fitness Sharing Particle Swarm Optimization Approach to FACTS Installation for Transmission System Loadability Enhancement

A novel approach for optimal allocation of series FACTS device for transmission line congestion management

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