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Hybrid renewable energy systems (HRES) should be designed appropriately with an adequate combination of different renewable sources and various energy storage methods to overcome the problem of intermittency of renewable energy resources. A multi-criteria approach is proposed in this study to design an HRES including wind turbine, photovoltaic panels, fuel cell, electrolyser, hydrogen tank, and battery storage unit with an intermittent load. Three design criteria including loss of power supply probability, total energy loss (TEL), and the power difference between generation and storing capacity (as TELSUB) are taken into account in minimising the total cost of the system considering the interest rate and lifetime. The justifications and advantages of using these criteria are thoroughly discussed along with appropriate presentation of the results. The purpose of considering TEL and TELSUB is discussed thoroughly. The ɛ-constraint method is used to handle practical constraints of the proposed multi-criteria problem to construct a multi-objective fitness function. Shuffled frog leaping algorithm is implemented to achieve better optimal results. The proposed approach is implemented using real wind speed and solar irradiance data for a specific location with an intermittent load demand. The results verify performance of the proposed multicriteria design procedure.

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PurposeThe purpose of this paper is to implement a simple, fast and accurate heuristic method for parameter determination of Jiles‐Atherton (JA) hysteresis model for representing magnetization in electrical steel sheets. The performance of the method is validated using measured data and comparison with previous methods.Design/methodology/approachJA model requires five parameters to represent the hysteretic behavior of ferromagnetic materials. In order to determine these parameters, measured hysteresis loop is used here to calculate a fitness function which is defined by comparing the measured and simulated magnetization loops. This fitness function is minimized by optimization algorithms.FindingsIn total, four different measured hysteresis loops are studied in this paper. Each optimization algorithm is executed 50 times to investigate the convergence, speed, and accuracy of six methods. All methods begin with the same randomly generated initial parameters. Physical boundaries are used for parameters to avoid unaccepted results. Thorough examination of results shows that the proposed method is more appropriate than previously implemented methods for the parameter determination of Jiles‐Atherton model in all studied cases. The required parameters for each optimization method are also presented.Originality/valueShuffled frog leaping algorithm (SFLA) is implemented for the first time for JA model parameter determination. The results show that SFLA is faster and more accurate in comparison with other methods. Furthermore, this algorithm is easy to implement and tune.