In this paper, the design of a hybrid renewable energy PV/wind/battery system is proposed for improving the load supply reliability over a study horizon considering the Net Present Cost (NPC) as the objective function to minimize. The NPC includes the costs related to the investment, replacement, operation, and maintenance of the hybrid system. The considered reliability index is the deficit power-hourly interruption probability of the load demand. The decision variables are the number of PV panels, wind turbines and batteries, capacity of transferred power by inverter, angle of PV panels, and wind tower height. To solve the optimization problem, a new algorithm named improved crow search algorithm (ICSA) is proposed. The design of the system is done for Zanjan city, Iran based on real data of solar radiation and wind speed of this area. The performance of the proposed ICSA is compared with crow search algorithm (CSA) and particle swarm optimization methods in different combinations of system. This comparison shows that the proposed ICSA algorithm has better performance than other methods.

Designing of stand-alone hybrid PV/wind/battery system using improved crow search algorithm considering reliability index

Siano P.
2019

Abstract

In this paper, the design of a hybrid renewable energy PV/wind/battery system is proposed for improving the load supply reliability over a study horizon considering the Net Present Cost (NPC) as the objective function to minimize. The NPC includes the costs related to the investment, replacement, operation, and maintenance of the hybrid system. The considered reliability index is the deficit power-hourly interruption probability of the load demand. The decision variables are the number of PV panels, wind turbines and batteries, capacity of transferred power by inverter, angle of PV panels, and wind tower height. To solve the optimization problem, a new algorithm named improved crow search algorithm (ICSA) is proposed. The design of the system is done for Zanjan city, Iran based on real data of solar radiation and wind speed of this area. The performance of the proposed ICSA is compared with crow search algorithm (CSA) and particle swarm optimization methods in different combinations of system. This comparison shows that the proposed ICSA algorithm has better performance than other methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4734667
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