Part of the widely discussed problem in electrical power systems is the optimal reactive power dispatch (ORPD) due to its reliability and economical operation of electrical power systems. The ORPD is a complex and non...
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Part of the widely discussed problem in electrical power systems is the optimal reactive power dispatch (ORPD) due to its reliability and economical operation of electrical power systems. The ORPD is a complex and nonlinear optimization problem. The pathfinderalgorithm (PFA) is a newly developed algorithm that inspires the group movement of prey with a leader called a pathfinder when hunting for food. The inertia weight is added to the PFA and is called an improved pathfinder algorithm (IPFA) to support the proper random work of the swarm to avoid the decrease in searchability of the PFA. The IPFA was proposed in this work to diminish the active power loss while improving the voltage profile. The IPFA was validated on the IEEE 30 and 118 bus systems along with particle swarm optimization (PSO) and the teaching-learning-based optimizer (TLBO). The proposed IPFA provides the best result as the losses of the IEEE 30 and 118 test systems were reduced to 16.035 and 115.048 MW from the initial base of 17.89 and 132.86 MW, respectively. The losses of PSO and the TLBO were 16.1568 and 16.1607 MW for the IEEE 30 bus system, respectively, while for the IEEE 118 bus system, the PSO provided 117.9129 MW and the TLBO provided 118.0524 MW. The two test systems' reduction percentages (%) were 10.37% and 13.41%, respectively. The results were compared with those of other algorithms in the literature, and the IPFA provided a superior result, thereby suggesting the superiority of IPFA methods in diminishing the power loss and improving the system's voltage profile.
This paper proposes a new optimization methodology for presenting an efficient result of the hydrogen consumption and speed trajectory in a PEM fuel cell (PEMFC)-based locomotive energy system for transportation appli...
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This paper proposes a new optimization methodology for presenting an efficient result of the hydrogen consumption and speed trajectory in a PEM fuel cell (PEMFC)-based locomotive energy system for transportation applications. After modeling the system, it has been linearized for simplification. The efficiency of the hydrogen consumption is maximized based on a new version of the pathfinder (IPF) algorithm and the speed trajectory. The reason for designing IPF is to resolve the local optimum and fast convergence shortcomings during the maximization. Two scenarios including normal and extreme characteristics are performed to the system. The simulation results specified that the total traction en-ergy for the normal mode and the extreme mode is 4.27 MJ and 4.80 MJ, respectively, and the optimal hydrogen consumption for these two modes are 0.0764 kg and 0.0628 kg, respectively. The final results showed that the locomotive improves significantly the efficiency of the system for hydrogen saving. (C) 2020 Elsevier Ltd. All rights reserved.
This study proposes a hybrid static economic dispatch (HSED) model that incorporates multiple constraints specific to power systems to enhance the economic efficiency of power dispatch following the integration of win...
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This study proposes a hybrid static economic dispatch (HSED) model that incorporates multiple constraints specific to power systems to enhance the economic efficiency of power dispatch following the integration of wind energy. Wind energy integration in power systems can effectively reduce operational costs and energy consumption. However, the significant influx of renewable energy sources can introduce system instability and complicate power dispatch procedures. An improved pathfinder algorithm (IPFA) is proposed to address the cost minimization problem associated with power dispatch involving wind energy. The HSED model contains constraints related to wind energy penetration rate, operating area limitations, and slope rate, thereby ensuring its applicability in real-world power dispatch scenarios. The IPFA incorporates three measures such as Kent mapping initialization, nonlinear adaptation factor, and following correction strategy. The result indicates that the IPFA achieves a reduction of up to 95.86($/h) and 606.24($/h) in operating costs compared to alternative methods when wind energy is not considered. The IPFA reduces operating costs by up to 9.3% and 7.5% compared to scenarios without wind energy when wind energy is integrated. The proposed model and method contribute to enhance renewable energy utilization while simultaneously ensuring the power system economic feasibility and stability.
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