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In recent years, with the rapid economic development, the development speed of all walks of life has entered a new level, and the power industry has also developed rapidly. Driven by market demand, China's power transmission range and power transmission capacity will enter a new level. At the same time, the problems brought about by the development of the power system are equally severe. Due to the large load density in individual areas, the detection of short-circuit current must be improved as an important issue. The purpose of this paper is to study how to improve the practical model of short-circuit current calculation of photovoltaic power plants, so that it can be well applied to the current high-density current detection in China. Therefore, this paper improves the recursive least squares (RLS) algorithm and applies it to the practical model of short-circuit current calculation of photovoltaic power plants and describes the improvement process of the algorithm in detail. At the same time, this paper designs relevant experiments and analysis to count the data of the improved RLS algorithm in the short-circuit current calculation of the actual photovoltaic power station and combines the data of this part to test and analyze the ability of the algorithm. The experimental results in this paper show that the improved RLS algorithm has a very good improvement in the calculation accuracy of the short-circuit current calculation of photovoltaic power plants in the actual model calculation. At the same time, the calculation efficiency is also improved, and the current tracking effect is also improved by 7%. [ABSTRACT FROM AUTHOR]

Summary: The present paper describes a new optimal design for an autonomous renewable energy‐based CHP system for a remote area in Zhidoi county, China. The configuration contains different parts of the electric heater (EH), photovoltaic‐thermal (PV/T), wind turbines (WTs), thermal energy storage (TES), and electrical energy storage (EES). The total annual cost (TAC) is utilized as a cost function of the system configuration and the idea is to minimize this function to access an optimal configuration. Due to the complicated nonlinear nature of this system, a metaheuristic‐based method, called Improved Marine Predators Algorithm (IMPA) has been introduced and designed. The reason for using this new algorithm is to cover the main drawbacks of most metaheuristics like better accuracy and higher convergence speed. To show the capability of the designed IMPA, it is validated by some different new metaheuristics from the literature. Afterward, the algorithm is used for system configuration optimization. Some sensitivity analysis is also investigated to shoe the method capability and the final results confirm the high ability of the proposed method for providing an optimal renewable energy‐based CHP system. The final results show a $56 307.74 value of TAC. The total efficiency of the system for the winter and the summers are 66% and 61%, respectively and the minimum total annual cost happens at AD = 0.8983. Finally, the minimum value of the total annual cost is achieved by the proposed method with 922.4 kWh. [ABSTRACT FROM AUTHOR]