A Gradient-Based Approach for Solving the Stochastic Optimal Power Flow Problem with Wind Power Generation

Souza, Rafael Ramos de; Balbo, Antônio Roberto; Martins, André; Soler, Edilaine Martins; Baptista, Edméa Cássia; Silva, Diego Nunes da; Nepomuceno, Leonardo

doi:10.1016/j.epsr.2022.108038

Cited by 6 publications

(3 citation statements)

References 42 publications

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“…This phase expresses a lower velocity ratio (v = 0.1); hence, the motion of the predator is quicker than the prey. Depending on the Levy movement, the mathematical representation of this phase is as Equations ( 33) and (34).…”

Section: Phasementioning

confidence: 99%

“…Various investigations focused on obtaining desirable data on wind speed considering the special distributions. Amongst those, the efficiently authenticated model was the Weibull probability density function [34,35], which is capable of actual wind speed distribution because its adaptability is feasible and soothes operation. DFIG-WECS [36] could generate and absorb the reactive power and coordinate the terminal voltage of the bus-accordingly, the DFIG-WECS stator integrated into the transmission system, as the rotor connected to the transmission system through a variable converter.…”

Section: A Wind Power Modelmentioning

confidence: 99%

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Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

Valuva,

Chinnamuthu

2023

Energies

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Transmission line losses are a crucial and essential issue in stable power system operation. Numerous methodologies and techniques prevail for minimizing losses. Subsequently, Flexible Alternating Current Transmission Systems (FACTSs) efficiently reduce transmission losses, and the Unified Power Flow Controller (UPFC) is a reactive power compensation controller. The parameter strength of the proportional–integral (PI) controller was calibrated with the Marine Predator Algorithm (MPA), a recent metaheuristic algorithm. An MPA-based optimum PI controller with a UPFC evaluates the optimal location of the UPFC and PI controller parameters to accomplish the desired research objective. The power rating of the UPFC was determined depending on the voltage collapse rating and power loss and an evaluated performance analysis of the MPA–PI-controlled UPFC on a modified IEEE-30 bus transmission network in MATLAB Simulink code. The Newton–Raphson method was used to perform the load flow analysis. Hence, the proposed MPA–PI controller was examined in contrast to preferred heuristic algorithms, the Artificial Bee Colony (ABC) and Moth Flame Optimization algorithms (MFO); the results showed that the MPA–PI controller exhibited better performance with an improved voltage profile and surpasses active power losses with the optimal placement of the UPFC device under different loading conditions. The active power loss, considering a UPFC with the proposed algorithm, reduced from 0.0622 p.u to 0.0301 p.u; consequently, the voltage profile was improved in the respective buses, and the loss percentage reduction during a 100% base load was 68.39%, which was comparatively better than the ABC and MFO algorithms.

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Section: Phasementioning

confidence: 99%

Section: A Wind Power Modelmentioning

confidence: 99%

Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

Valuva,

Chinnamuthu

2023

Energies

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“…The authors of [21] proposed the modified Cuckoo Search (CS) approach as a solution to the OPF problem with wind energy, including costs associated with wind. The Gradient‐Based Optimizer (GBO) was introduced in [22] to examine the impact of wind power on the economic operation of the electricity system and bus voltages and transmission power loss. The Equilibrium Optimization (EO) proposed in [23] is a unique technique for solving the OPF problem that considers uncertainties caused by not only wind generation but also other components in the power grid.…”

Section: Introductionmentioning

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

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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.

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Identifying critical nodes in power grids containing renewable energy based on electrical spreading probability

Li,

Lin,

2023

International Journal of Electrical Power & Energy Systems

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A Gradient-Based Approach for Solving the Stochastic Optimal Power Flow Problem with Wind Power Generation

Cited by 6 publications

References 42 publications

Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

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

Identifying critical nodes in power grids containing renewable energy based on electrical spreading probability

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