Renewable Energy Sources and Battery Forecasting Effects in Smart Power System Performance

Mehdi Bagheri, Venera Nurmanova, Oveis Abedinia, Mohammad Salay Naderi, Noradin Ghadimi and Mehdi Salay Naderi
Additional contact information
Mehdi Bagheri: Department of Electrical and Computer Engineering, Nazarbayev University, Astana 010000, Kazakhstan
Venera Nurmanova: Department of Electrical and Computer Engineering, Nazarbayev University, Astana 010000, Kazakhstan
Oveis Abedinia: Department of Electric Power Eng., Budapest University of Technology and Economics, Budapest 1111, Hungary
Mohammad Salay Naderi: Electrical and Computer Engineering Department, Tehran North Branch, Islamic Azad University, Tehran 1651153311, Iran
Noradin Ghadimi: Young Researchers and Elite Club, Islamic Azad University, Ardabil Branch, Ardabil 5615731567, Iran
Mehdi Salay Naderi: Iran Grid Secure Operation Research Center, Amirkabir University of Technology, Tehran 158754413, Iran

Energies, 2019, vol. 12, issue 3, 1-18

Abstract: In this study, the influence of using acid batteries as part of green energy sources, such as wind and solar electric power generators, is investigated. First, the power system is simulated in the presence of a lead–acid battery, with an independent solar system and wind power generator. In the next step, in order to estimate the output power of the solar and wind resources, a novel forecast model is proposed. Then, the forecasting task is carried out considering the conditions related to the state of charge (SOC) of the batteries. The optimization algorithm used in this model is honey bee mating optimization (HBMO), which operates based on selecting the best candidates and optimization of the prediction problem. Using this algorithm, the SOC of the batteries will be in an appropriate range, and the number of on-or-off switching’s of the wind turbines and photovoltaic (PV) modules will be reduced. In the proposed method, the appropriate capacity for the SOC of the batteries is chosen, and the number of battery on/off switches connected to the renewable energy sources is reduced. Finally, in order to validate the proposed method, the results are compared with several other methods.

Keywords: renewable energy sources; lead–acid battery; state of charge; feature selection; forecasting (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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