Optimal Allocation and Size of FACTS Devices Using Several Optimizers: a Comprehensive Study

Awad, Ayman; Kamel, Salah; Hassan, Mohamed H.; Ibrahim, Abdalla Ahmed; Jurado, Francisco

doi:10.1109/mepcon55441.2022.10021743

Cited by 3 publications

(2 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, in Khan et al, 9 multiobjective multiverse optimization algorithm was developed to explore the optimal allocation of SVC and TCSC in an IEEE 57-bus system for voltage profile enhancement and power losses minimization. Furthermore, many studies [10][11][12][13][14][15][16] introduce other optimization problems and problemsolving approaches for various systems.…”

Section: Motivationmentioning

confidence: 99%

Optimal allocation of flexible AC transmission system (FACTS) for wind turbines integrated power system

Awad,

Kamel,

Hassan

et al. 2023

Energy Science & Engineering

Self Cite

View full text Add to dashboard Cite

The importance of flexible alternating current transmission system (FACTS) devices is increasing day by day as they provide compensation for power systems. The installation of such devices solves many issues regarding the stability and power transferability of power systems. However, for optimizing the performance of FACTS devices, the location and sizes of FACTS devices must be selected very carefully. On the other side, the utilization of optimization techniques is increasing daily, as it is capable of solving nonlinear, random problems by its stochastic nature. As a result, it became a reliable tactic for solving stochastic problems almost in every aspect of our lives. Therefore, it is adopted for solving power system problems, like, FACTS devices allocation, distributed generators allocation, determining component's parameters, and more. In this paper, the optimal size and location of several FACTS devices are selected to achieve the following single objective functions separately: fuel cost minimization and power losses minimization, then combining the mentioned objective function into one multiobjective function for gross cost minimization. The power system optimized is the Institute of Electrical and Electronics Engineers 30‐bus standard system, and the FACTS devices installed are static VAR compensator, thyristor control series compensator, and thyristor‐controlled phase shifter, while the optimization is performed using different conventional and recent optimization algorithms, including a newly developed algorithm, typically Leader Walrus Optimization Algorithm “LWaOA,” making a comparison among such algorithms to investigate the algorithm that possesses the best performance. The results of the optimization processes show the superiority of LWaOA.

show abstract

Section: Motivationmentioning

confidence: 99%

Optimal allocation of flexible AC transmission system (FACTS) for wind turbines integrated power system

Awad,

Kamel,

Hassan

et al. 2023

Energy Science & Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…As per [33,34], FACTS device placement and rating is optimized to minimize transmission losses and prevent transmission line overloading. Additionally, [35,36] leverages FACTS devices to improve the loadability characteristics of the system being studied.…”

Section: Literature Reviewmentioning

confidence: 99%

CAVOA: A chaotic optimization algorithm for optimal power flow with facts devices and stochastic wind power generation

Mohamed,

Kamel,

Hassan

et al. 2023

IET Generation Trans & Dist

Self Cite

View full text Add to dashboard Cite

The study proposes a modified version of African Vultures Optimization Algorithm (AVOA) to address the optimal power flow (OPF) issue. The developed optimizer is called Chaotic AVOA (CAVOA). Prior to applying CAVOA to the problem at hand, its accuracy is evaluated using 23 benchmark functions. The production powers of WTs that are interrupted are predicted using Weibull probability density functions (PDFs). Two additional costs, namely penalty cost and reserve cost, are incorporated into the goal function of the OPF. The simulation results of CAVOA are compared with those of the original AVOA to solve the OPF. The proposed OPF technique and its solution methodology are verified on the IEEE 30‐bus test system, taking into account the flexible alternating current transmission systems (FACTS) devices, which have several benefits such as reducing active power transmission loss, regulating power flow, and improving voltage stability/profile. The research's simulation results demonstrate that CAVOA is more effective in identifying the OPF's optimal solution by reducing the overall power cost and power losses. The results indicate that the CAVOA algorithm outperforms AVOA as a metaheuristic optimization algorithm due to its superior capability in addressing challenging OPF problems with a minimal convergence rate. For example, when comparing the two algorithms, CAVOA achieved a significant improvement. It successfully reduced the cost function by approximately 0.023% in Case I and 0.035% in Case II, while also decreasing power loss by 2.57% in Case II and 0.57% in Case I. Additionally, CAVOA exhibited a remarkable reduction of 5.36% in voltage deviation compared to AVOA in Case I. Furthermore, in Case III, CAVOA demonstrated a decrease of 0.64% in gross cost when compared to AVOA.

show abstract

Wind/PV Allocation Applying Whale Optimization Algorithm Versus System Uncertainties

Eissa,

Swief,

Salam

2023

2023 24th International Middle East Power System Conference (MEPCON)

View full text Add to dashboard Cite

Optimal Allocation and Size of FACTS Devices Using Several Optimizers: a Comprehensive Study

Cited by 3 publications

References 23 publications

Optimal allocation of flexible AC transmission system (FACTS) for wind turbines integrated power system

Optimal allocation of flexible AC transmission system (FACTS) for wind turbines integrated power system

CAVOA: A chaotic optimization algorithm for optimal power flow with facts devices and stochastic wind power generation

Wind/PV Allocation Applying Whale Optimization Algorithm Versus System Uncertainties

Contact Info

Product

Resources

About