“…3 . The following mathematical formula is used to update the particle's position and velocity [1] : Figure 3 Flowchart of Particle Swarm Optimization (PSO). …”
Section: Bench-marking Modelmentioning
confidence: 99%
“…For example, the Wind Energy Technologies Office of the Department of Energy in the United States has been actively promoting the development of wind energy systems in microgrids to improve energy reliability and resiliency. In Europe, countries such as Denmark, Germany, and Spain have been at the forefront of the development and adoption of wind energy systems in microgrids [1] , [2] . Moreover, countries in Asia, including China and India, have been increasing their investments in wind energy and microgrid technologies.…”
“…3 . The following mathematical formula is used to update the particle's position and velocity [1] : Figure 3 Flowchart of Particle Swarm Optimization (PSO). …”
Section: Bench-marking Modelmentioning
confidence: 99%
“…For example, the Wind Energy Technologies Office of the Department of Energy in the United States has been actively promoting the development of wind energy systems in microgrids to improve energy reliability and resiliency. In Europe, countries such as Denmark, Germany, and Spain have been at the forefront of the development and adoption of wind energy systems in microgrids [1] , [2] . Moreover, countries in Asia, including China and India, have been increasing their investments in wind energy and microgrid technologies.…”
The supply-demand-based optimization (SDO) is among the recent stochastic approaches that have proven its capability in solving challenging engineering tasks. Owing to the non-linearity and complexity of the real-world IEEE optimal power flow (OPF) in modern power system issues and like the existing algorithms, the SDO optimizer necessitates some enhancement to satisfy the required OPF characteristics integrating hybrid wind and solar powers. Thus, a SDO variant namely leader supply-demand-based optimization (LSDO) is proposed in this research. The LSDO is suggested to improve the exploration based on the simultaneous crossover and mutation mechanisms and thereby reduce the probability of trapping in local optima. The LSDO effectiveness has been first tested on 23 benchmark functions and has been assessed through a comparison with well-regarded state-of-the-art competitors. Afterward, Three well-known constrained IEEE 30, 57, and 118-bus test systems incorporating both wind and solar power sources were investigated in order to authenticate the performance of the LSDO considering a constraint handling technique called superiority of feasible solutions (SF). The statistical outcomes reveal that the LSDO offers promising competitive results not only for its first version but also for the other competitors.
“…Several studies have used different types of devices to improve power oscillations in power systems. Among the most common devices are FACTS [20,21], static VAR compensators (SVCs) [22], and STATCOMs [23]. A clustering technique combined with catastrophe theory and multi-objective particle swarm optimization was presented in [20] with the purpose of optimally placing controlled series capacitors (TCSCs).…”
Section: Introductionmentioning
confidence: 99%
“…Aiming to improve transient stability, [21] analyzed the implementation of a unified power flow controller, a static synchronous series compensator, and an SVC. In [22], an SVC was employed to stabilize the power system under transient stability events, and, [23] described combined genetic and PSO algorithms to optimize STATCOM-POD in a wind-PV-thermal-bundled power system.…”
This paper presents an integrated methodology applied to photovoltaic (PV) plants for improving the dynamic performance of electric power systems. The proposed methodology is based on primary frequency control, which adds an ancillary signal to the voltage reference of the DC-link for the voltage source converter (VSC) in order to reduce power oscillations. This ancillary signal is computed by relating the energy stored in the VSC of the DC-link and the energy stored in the synchronous machine’s shaft. In addition, the methodology considers the operating limits of the VSC, which prioritizes active power over reactive power. Furthermore, the VSC control is assessed with interconnection and damping assignment passivity-based control (IDA-PBC), as well as compared to conventional PI control. IDA-PBC is employed to design a Lyapunov asymptotically stable controller using the Hamiltonian structural properties of the open-loop model of the VSC. A 12-bus test system that considers PV plants is employed to compare the proposed IDA-PBC control with a classical proportional-integral control approach. The impact of the proposed methodology is analyzed in four scenarios with different PV penetration levels (10%, 30%, 50%, and 80%) and four large disturbances in the test power system. In addition, a decrease in the inertia of the synchronous machines from 100 to 25% is analyzed. The time-domain simulation results show that the frequency oscillations are reduced by 16.8%, 38.43%, 37.53%, and 76.94% in comparison with the case where the proposed methodology was not implemented. The simulations were conducted using the SimPowerSystems toolbox of the MATLAB/Simulink software.
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