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In this paper, optimal designing and energy management of hybrid photovoltaic/wind/fuel cell (PV/WT/FC) system is presented with cost of hybrid system life span (CHSLS) minimizing and considering loss of load interruption probability (LOLIP) for Recreational Center of Gonbad (RCOG), a remote area region in Iran country using actual irradiance and wind speed data of this region. A meta-heuristic improved sine–cosine algorithm (ISCA) is used based on nonlinearly decreasing inertia weight strategy (NDIWS) for improving global and local search of the conventional SCA to find the optimal combination of hybrid system. In designing problem the optimal size of hybrid system components is determined using ISCA considering CHLS and LOLIP to satisfy the RCOG load demand in most cost-effective way. The performance of the proposed ISCA is compared with conventional SCA and well-known PSO methods in different combinations and under LOLIP changing conditions. Simulation results showed that the ISCA finds easily the optimal combination as PV/WT/FC system with lower CHSLS and better LOLIP. Also WT/FC system is not economical due to high CHSLS for RCOG. The results demonstrated that the average cost of per kW RCOG load supply using the PV/WT/FC for maximum LOLIP of 1% is equal to 0.87$ and for maximum LOLIP of 5% is 0.76$. The results showed the contribution and management of PV, WT and fuel cell together as PV/WT/FC is made a reliable and cost-effective energy system to supply the remote area application like RCOG. Moreover superiority of the ISCA than the SCA and PSO is proved with better convergence speed and accuracy. Also, the effect of some effective factors on the system designing is evaluated. • Hybrid system designing for RCOG load supply using ISCA, case study for Iran. • Optimal sizing of PV/WT/FC with minimizing the CHSLS and respect to the LOLIP. • Determination of reliable and cost-effective system combination to supply RCOG load. • Superiority of the ISCA performance compared to SCA and well-known PSO method. • Investigating the effect of some economic and technical factors on system designing. [ABSTRACT FROM AUTHOR]

Similar to any other geophysical method, seismic refraction method faces non-uniqueness in the estimation of model parameters. Recently, different nonlinear seismic processing techniques have been introduced, particularly for seismic inversion. One of the recently developed metaheuristic algorithms is bat optimization algorithm (BA). Standard BA is usually quick at the exploitation of the solution, while its exploration ability is relatively poor. In order to improve exploration ability of BA, in the current study, a hybrid metaheuristic algorithm by inclusion a mutation operator into BA, socalled mutation based bat algorithm (MBA), is introduced to inversion of seismic refraction data. The efficiency and stability of the proposed inversion algorithm were tested on different synthetic cases. Finally, the MBA inversion algorithm was applied to a real dataset acquired from Leylanchay dam site at East-Azerbaijan province, Iran, to determine alluvium depth. Then, the performance of MBA on both synthetic and real datasets was compared with standard BA. Moreover, the dataset was further processed following a tomographic approach and the results were compared to the results of the proposed MBA inversion method. In general, the MBA inversion results were superior to standard BA inversion and results of MBA were in good agreement with available boreholes data and geological sections at the dam site. The analysis of the seismic data showed that the studied site comprises three distinct layers: a saturated alluvial, an unsaturated alluvial, and a dolomite bedrock. The measured seismic velocity across the dam site has a range of 400 to 3,500 m/s, with alluvium thickness ranging from 5 to 19 m. Findings showed that the proposed metaheuristic inversion framework is a simple, fast, and powerful tool for seismic data processing. [ABSTRACT FROM AUTHOR]