# Determination of Effective Parameters for Hydropower Plants' Energy Generation: A Case Study
## 5 Conclusions  
The energy generation of hydropower plants may be influenced by several variables, which can differ according to the particular design and geographical placement of the plant, including fluctuations that occur during the seasons. The understanding and efficient management of seasonal variations are crucial for optimizing the performance of hydropower plants and ensuring a consistent and sufficient energy supply throughout the year. This study thoroughly examined the key factors influencing the energy generation of a selected hydroelectric plant, taking into account the daily data pertaining to flow rate, precipitation, and temperature in relation to energy generation. Furthermore, a novel correlation has been proposed for the estimation of energy generation in the case of the availability of only flow rate data.  
Based on the comprehensive investigation that was carried out in the current study, the following deductions can be made:  
1. There exists an apparent relationship between flow rate and energy generation. However, in the presence of high flow rates that exceed the design flow rate of 31.24 m\({}^{3}\)/s, the energy generation of hydropower plants reaches its highest limit.
2. The peak value of flow rate occurs during the spring season, composed of March-June, after the existence of the peak value of precipitation, which has a shifting pattern, and then energy generation likewise attains its maximum value during the same time interval. However, in the rest of the months, these exhibit distinct behaviors.
3. The effect of air temperature variation on energy generation can be divided into three sections: the effect of cold-low temperatures, warmer temperatures, and high temperatures. While cold-low and high temperatures have adverse effects on energy generation in terms of freezing and evaporation of water stored in the regulator or flowing in the river, respectively, warm temperatures support an increase in the snowmelt rate occurring in the mountains, which results in an augmentation in the flow rate of the river.
4. There is no discernible correlation between daily precipitation and daily energy output. This finding does not imply the absence of a relationship between precipitation and energy output; as it was mentioned previously, monthly mean data trends of energy generation and precipitation have a strict relationship. The year with the greatest energy generation, as shown in this study, was 2019, coinciding with the year in which the highest precipitation levels were recorded.
5. A novel linear correlation with an R\({}^{2}\) value of 0.89 has been obtained between the long-term daily flow rate data and the daily energy output of the hydropower plant under investigation. The energy generation values generated via the implementation of the suggested correlation were compared to the actual energy generation values, and we observed that the equation's deviation band falls within the range of \(\pm\)20%.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The author declares no conflicts of interest.