Hydroelectric Energy Generation Research Articles

Estimates of hydroelectric energy generation in BRICS-T countries using a new hybrid model

ABSTRACT Realistic energy production and consumption projections are needed by national governments that are developing policies to reduce greenhouse gas emissions and ensure energy supply security. In this study, four types of artificial neural network (ANN) models – including a back propagation (BP) model, ANN-BP, and three Rao algorithm models, namely ANN-Rao_1, ANN_Rao2 and ANN-Rao_3 were developed to determine hydroelectric power (HEP) generation projections for Brazil, Russia, India, China, South Africa, and Turkey (BRICS-T) countries. Gross domestic product (GDP), population, import, and export data were inputted as independent variables into the models. Data from the period of 1990‒2014 were used for ANN model development. Data from the period of 2015‒2020 were used as reference data to test the models’ predictive power. According to the error values calculated for the training and test sets, the ANN-Rao_3 model predicted HEP generation values for BRICS-T countries more accurately than the other models. The results obtained from this study predict that the HEP generation value of the BRICS-T countries will increase by 28.1% by 2040. According to the RMSE values obtained for the test datasets, compared to the BP algorithm, the Rao_3 algorithm increased ANN performance by 34.1% for Brazil, 24.1% for Russia, 3% for India, 13% for South Africa, and 12.1% for Turkey. The total HEP generation value of the BRICS-T countries in 2040 was projected to be 2815.69 TWh. Current BRICS-T countries’ HEP investments are not sufficient to achieve their renewable energy targets. In light of this research, relevant policy implications may be derived.

Hydrological and Precipitation Extremes and Trends over the Paraiba do Sul River Basin, Brazil

The Paraiba do Sul River Basin (PSRB) is a vital source of water resources in Brazil, providing water for human consumption, industry, agriculture, and hydroelectric energy generation. As part of one of the most developed areas of the country, in the Southeast of Brazil, the region is vulnerable to the impacts of climate change, with evidence of extreme events such as droughts and floods affecting the availability and quality of water. Hence, this study analyzes precipitation and streamflow rates data from the PSRB between 1939–2020 to investigate the spatial variability of average patterns and extreme events, trends, and their relationship with urban growth and socioeconomic development. The analysis reveals significant spatial variations in precipitation and runoff rates, with higher altitude areas, such as the Serra da Mantiqueira, exhibiting higher average values. Moreover, the Mann–Kendall trend results showed in most of the sites no significant trend regarding precipitation data; however, about 50% of the sites in the PSRB presented a decreasing trend of runoff rates. Since the precipitation does not explain identified changes in the hydrological patterns, the evaluation of the area’s urban growth and socioeconomic development throughout the decades suggested that human activities, such as those associated with urbanization, have played a significant role in altering the runoff patterns in the basin. These findings highlight the importance of sustainable land-use planning and water resource-management practices in the PSRB to mitigate the negative impacts of urbanization on the hydrological cycle and to enhance the resilience of the region’s water resources.

Power Generation Sources and Carbon Dioxide Emissions in BRICS Countries: Static and Dynamic Panel Regression

Purpose: The threat of global warming has escalated as a result of industrialization, urbanization, population growth, and lifestyle changes in Brazil, Russia, India, China, and South Africa (BRICS). The amount of electricity generated by various sources is directly influenced by their respective carbon dioxide (CO2
 ) emissions. This study’s primary goal is to determine which sources are bad for the environment and which are not.
 Methodology: Examining the impact of different energy generation sources on CO2
 emissions using data from the BRICS. To analyze the data, pooled OLS and Generalized Method of Moments (GMM) are used, as well as Quantile Regression (QR).
 Findings: We found that coal and gas power generation had a positive and large influence on CO2
 emissions regardless of the method used. As compared to other emissions, coal-fired energy production has a more significant impact. In all regression models, hydroelectric and renewable energy generation can reduce CO2
 emissions.
 Originality: Identifying an empirical link between CO2
 emissions and energy production sources is the study’s most significant accomplishment. To obtain solid results, the paper used a combination of QR and GMM techniques. The conclusions presented in this article have important environmental policy consequences. CO2 emissions can be reduced by reducing the consumption of fossil fuels and promoting the development of alternative energy sources such as hydroelectric, wind, and solar power.

Climate Change Migration and the Economic Rebirth of Central Appalachia

This research examines the potential economic rebirth of the Central Appalachian Region as persons from the southwestern and southeastern parts of the United States seek a safe and livable environment for their families and businesses. Central Appalachia is projected to be the largest habitable area in the continental United States by the year 2050. However, mined land remediation, water control efforts, and hydro-electric energy generation units will be required to support the incoming population.

Poly(phthalazinone ether ketone) – Poly(3,4-ethylenedioxythiophene) fiber for thermoelectric and hydroelectric energy harvesting

A kind of thermoelectric and hydroelectric energy harvesting fiber made of poly(phthalazinone ether ketone) (PPEK) and poly(3,4-ethylenedioxythiophene) (PEDOT) was prepared by wet-spinning PPEK fiber and in-situ polymerization of PEDOT on PPEK fiber. The crystallinity of the PEDOT component in PPEK-PEDOT fibers increased from 28.2 % to 42.1 % with the molar ratio of 3,4-ethoxylenedioxythiophene (EDOT) and FeCl3 increased from 0.75:1 to 3:1, and the electrical conductivity of PPEK-PEDOT fiber increase from around 0.3 × 10-3 S cm−1 to almost 25.4 × 10-3 S cm−1. Benefiting from the high crystallinity, good electrical conductivity of PPEK-PEDOT fibers and the porous structure inherited from PPEK fibers, PPEK-PEDOT fibers have good thermoelectric and hydroelectric energy harvesting capabilities. PPEK-PEDOT fiber has a tree-like structure with a radial distribution of pores on the fiber cross-section, forming pore channels along the fiber axis direction, which enhanced the hydroelectric energy harvesting properties. PPEK-0.66PEDOT fiber that treated by 2wt% poly(ethylenimine) (PEI) ethanol solution would generate about 1.6 mV thermoelectric voltage with only 2 cm fiber length under the temperature gradient of 21 ℃ and produce ∼ 260 mV hydroelectric voltage under 99 % humidity at 30 ℃. As a whole, the compact and flexible PPEK-PEDOT fiber prepared in this work showed great potential in the field of thermoelectric and hydroelectric energy generation for wearable electronic devices.

Symmetric and Asymmetric Impacts of Commercial Energy Distribution from Key Sources on Economic Progress in Pakistan

This paper aims to determine the interaction of commercial energy distribution, including the installed capacity of hydroelectric energy, hydroelectric energy generation, the installed capacity of thermal energy, thermal energy generation, the installed capacity of nuclear energy, and nuclear energy generation, with economic progress in Pakistan over the 1970–2019 period. Both linear and non-linear autoregressive distributed lag models were used to ascertain the symmetric and asymmetric short- and long-run effects. The findings from the linear autoregressive distributed lag model analysis revealed evidence that increases in the installed capacity of nuclear energy, alongside higher levels of hydroelectric energy generation and thermal energy generation, have positively affected economic growth in the short run, while a greater installed capacity of nuclear energy has positively affected economic growth in the long run. The findings from the non-linear autoregressive distributed lag model analysis showed that negative shocks to installed capacities related to hydroelectric, thermal, and nuclear energy reduced economic growth, while positive shocks to hydroelectric energy generation and the installed capacity of nuclear energy boosted economic growth in the short run. Furthermore, in the long run, negative shocks to the installed capacities of hydroelectric and thermal energy reduced economic growth, negative shocks to the installed capacity of nuclear energy enhanced economic growth, and positive shocks to hydroelectric energy generation and the installed capacity of nuclear energy have stimulated economic growth in Pakistan.

Estimates of hydroelectric energy generation in Turkey with Jaya algorithm-optimized artificial neural networks

The main purpose of this study was to establish an artificial neural network (ANN) model trained by a Jaya algorithm, and use the model to predict Turkey’s future hydroelectric energy generation (HEG). Population, gross domestic product (GDP), installed capacity, energy consumption, gross electricity energy demand (GEED), and average yearly temperature (AYT) data were inputted as independent variables in the model. ANN-Jaya was compared with ANN models trained by the other two high performance optimization methods, namely back-propagation (BP) and artificial bee colony (ABC) algorithms, to test its accuracy. The ANN-Jaya model converged to smaller error values than were obtained with the ANN-BP and ANN-ABC models for both the training and test datasets. When the average relative error (RE) values calculated for the test set are taken into account, ANN-Jaya performs 19.3% better than ANN-ABC and 31.2% better than ANN-BP. Therefore, Turkey’s HEG projections were made out to the year 2030 using an ANN-Jaya model in a low and a high energy demand scenario. According to the developed projections, HEG values in Turkey in 2030 will be in the range of 104.81–124.66 TWh. The present results affirm that HEG can be modeled accurately with an ANN-Jaya technique and this method was shown to be advantageous for predicting future HEG.

Water Rights Analysis Package Modeling System

The water rights analysis package simulates surface water development, allocation, management, and use and performs reliability and frequency analyses of simulation results. The computer modeling system facilitates assessments of hydrologic and institutional water availability and reliability in satisfying requirements for reservoir storage, water supply diversions, environmental instream flows, and hydroelectric energy generation. Reservoir system operations for flood control can be simulated. Capabilities are also provided for tracking salinity concentrations. Basin-wide impacts of water resources development projects and management practices are modeled. The modeling system is generalized for application anywhere, with input datasets being developed for particular river systems of concern. The water availability modeling system maintained by the Texas Commission on Environmental Quality and routinely applied by the professional water management community consists of the water rights analysis package and simulation input datasets for all of the river basins of Texas. Model-users modify the input datasets as appropriate to evaluate alternative water use scenarios, development projects, and management strategies of interest. This paper explores concepts and methodologies incorporated in the water rights analysis package and other comparable modeling systems, implementation of water availability modeling in Texas, and contributions to effective water management.

Numerical Study of Discharge Adjustment Effects on Reservoir Morphodynamics and Flushing Efficiency: An Outlook for the Unazuki Reservoir, Japan

The Unazuki Reservoir is located on the Kurobe River, which is influenced by a catchment with one of the highest sediment yields in Japan. Due to a sufficiently available discharge during flood events, annual sediment flushing with full water-level drawdown (i.e., free-flow sediment flushing) is conducted to preserve the effective storage capacity of the reservoir. Nevertheless, the upstream half of the reservoir (i.e., study segment) suffers from the excessive deposition of coarser sediments. Remobilization of these coarser materials and their transportation further downstream of the reservoir is a priority of reservoir owners for sustainable reservoir functions, such as flood-risk management and hydroelectric energy generation. In this paper, an already conducted sediment-flushing operation in the Unazuki Reservoir is simulated, and its effects on sediment scouring from the study segment of the reservoir together with changes in bed morphodynamics are presented. A fully 3D numerical model using the finite volume approach in combination with a wetting/drying algorithm was utilized to reproduce the hydrodynamics and bed changes using the available onsite data. Afterwards, the effects of discharge adjustment on the morphological bed changes and flushing efficiency were analysed in the study segment using an additional single-discharge pulse supplied from upstream reservoirs. Simulation results showed that an approximately 75% increase in the average discharge during the free-flow stage changed the dominant morphological process from deposition into an erosive mode in the study segment. If the increase in discharge reaches up to 100%, the flushed volume of sediments from the target segment can increase 2.9 times compared with the initiation of the erosive mode.

Basin-scale and seasonal evaluation of automated threshold methods for surface water detection

ABSTRACT Estimating surface water using satellite data can improve estimates and predictions for hydroelectric energy generation. The goal of this research is to identify the best threshold method and image band combination to detect seasonal surface water at the basin scale. This paper explores Otsu, Minimum Entropy, and average of Otsu-Minimum Entropy threshold algorithms using Sentinel-2 narrow near-infrared band 8A (N-NIR), shortwave infrared bands 11 and 12 (SWIR-11 or SWIR-12) images for the Assiniboine River Basin (ARB). The highest precision (0.87) of surface water detection was obtained in autumn using Minimum Entropy (N-NIR & SWIR-11) threshold values for the ARB, however, the Minimum Entropy also had poor detection of surface water (low recall). Use of the naïve Bayesian classifier did not improve detection of surface water compared to using threshold values alone, and the use of threshold values generated for one basin was not transferable to another basin. We concluded that threshold methods should be assessed seasonally, at a per-tile scale before combining surface water products at a watershed scale, and products should be evaluated using non-balanced statistical measures for watersheds with high land-to-water ratios. Accuracy assessment is hampered by validation data which represents static hydrologic conditions, not contemporary, seasonal conditions.

Optimizing Current and Future Hydroelectric Energy Production and Water Uses of the Complex Multi-Reservoir System in the Aliakmon River, Greece

In this work we study long-term maximization of hydroelectric energy generation from complex multi-purpose reservoir systems, using the reservoir system of the Aliakmon River, Greece, as an application example. This system serves various purposes, like urban water supply, irrigation, hydroelectric energy production, cooling thermoelectric power plants and flood control, while preserving environmental flow. The system operator uses institutional rules for the annual scheduling of the outflows of the 2 largest reservoirs (Ilarion and Polyfyto) for additional safety and smooth distribution of energy production through the year. In this work, we focus on maximization of energy production. We have considered three different hydrological scenarios (dry, average and wet), both for the current and for anticipated future water demand. The multi-reservoir system’s operation was simulated and then optimized using a rather simple form of genetic algorithms, in order to maximize hydro energy production. All other water uses were taken into account as constraints. Our conceptual and computational approach succeeded to identify and quantify hydro energy production increase and to indicate necessary changes to the operating rule curves of the reservoirs. The methodology can be easily adapted to other large-scale multi reservoir systems.

Energy Efficiency Policies to Face Buildings’ Climate Change Effects in Paraguay

Nowadays, the importance of implementing energy efficiency (EE) measures is growing significantly worldwide, based on its potential to reduce energy demands and mitigate climate change effects. Paraguay is a developing country with the highest per capita hydroelectric energy generation in the world, but only 18% of local consumption is hydroelectric and 41% of its energy matrix corresponds to oil products. This paper aims to analyse the importance the Country places on EE as a strategy towards sustainable development and to highlight as EE is an effective pathway to mitigate the climate changes and contrast their effects. The authors initially provide an insight into the climate scenarios for Paraguay and underline the effects of the climate changes on the buildings’ comfort. Subsequently, the authors provide, by resourcing a bibliographic review, a description of the Paraguayan sectors of greater energy consumption, its policies and targets set for increasing EE. Besides, the main EE projects developed by other neighbouring South American countries are analysed to show the level of development of each one in the scope of EE and to offer a reference basis of potential virtuous solutions to be adopted in Paraguay. A focus on the building sector is also made to provide a foundation for policy analyses to enhance EE in this sector. As a result of this review, evidence that EE is beginning to take part in Paraguay’s public policies was found, with the leaders becoming aware of its importance. Nevertheless, many concrete results could not be achieved as of yet and overcoming these barriers still involve a great challenge. Regarding the building sector, few advances have been noticed regarding the regulations of buildings’ thermal performance, a reason for which the National objectives set need to be more specific to achieve greater collective awareness to enforce them. Finally, key actions are recommended for Paraguay aiming to improve EE levels to face the climate change phenomenon.

Prihodnje potrebe po shranjevanju energije v Alpskem prostoru

In this paper we discuss energy storage requirements for EUSALP region in Europe. EUSALP is an Alpine region that includes the entirety Switzerland, Austria, Slovenia, and Lichtenstein, as well as parts of France, Germany, and Italy. A model is presented that facilitates the estimation of the required technical amounts of energy storage and installed power of pumped storage hydropower plants. The aim of the model is to estimate the requirements of energy storage to assist in setting guidelines for stable and reliable future electric energy supply in the EUSALP region. The model is based on currently known patterns of energy consumption and generation and available information on the future increase of renewable electric generation capacity, energy consumption, and the introduction of electromobility within all EUSALP regions. The hourly balance of generation, demand, and storage within a selected future year is assumed. The results are presented such that a mix of scenarios is addressed. Among them are installed generation capacity, installed pumped hydro storage power, selection of photovoltaic and wind electric energy generation ratio, the charging of a selected percentage of electric cars, flexible run-of-river hydro electric energy generation, import/export, generation by nuclear and backup fossil fuel sources, and a selection of disturbances. Results show that energy storage capacities must be increased by a large margin regardless of the choice of demand site management strategies or flexible electric car charging. Around a requisite 10-fold increase in pumped storage hydropower capacity is estimated, while the estimated increase in required energy storage is even higher. Daily and seasonal variations are also discussed. Further, the amount of surplus electric energy generation is presented and discussed.

Estimation of Sediment Deposition at Nausehri Reservoir by Using Multiple Linear Regression and Assessment of its Effect on Hydropower Generation Capacity

This article presents investigation of the inflow of sediments depending upon the stream flow, density and kinematic viscosity of water. The process involves Multiple Linear Regression (MLR) technique for estimation of sediment load and volume, by using UNISTAT software (Version 5.6). A general equation is developed for a specific flow rate while considering density and kinematic viscosity of water as other parameters. The developed equation can be applied in future for determining the sediment concentration when the flow rate is known. The daily stream flow and suspended sediment data belonging to the station Nausehri operated by the Water and Power Development Authority, Pakistan is used as case study. The results indicate that the dam site experiences a mean annual sediment load of 3.74mst. With this much incoming sediment load the reservoir life comes out to be 45 years when no flushing is done. The impact of this sediment deposition on hydro-electric energy generation is also determined, which shows a decrease of 113MW (12%) in the production capacity of the power plant over the life of the reservoir.

INVESTIGATION OF HYDROPOWER GENERATION FROM IRRIGATION DAMS

Evaluation of renewable energy resource is very important for Turkey. As geodetic and fossil energy that Turkey owns is insufficient and do not meet the demand. For this reason, tending towards hydro-electric power is an applicable option and is one of the most important energy resource for the country. From water resources point of view, water potential of large and small streams, for the purpose of energy production is vital for the country. Thereby, the existing deficit gap relevant to the energy, is reduceable. Within this paper, Seydisuyu basin has been selected as the research area. Precipitation in the basin is drained by Seydisuyu stream. Only two dams named as Kunduzlar and Çatören , were constructed and are currently in operation in the basin. These dams were built for the purposes of only irrigation and flood control, in the basin. Water potential of the basin is very small, due to the slight amount of precipitation within that area. Accordingly, planning of only small-scale hydro-electric energy potential is considerable over these dams, for region/national economic advantage of the country. In this study, the hydro-electric power potential of these two existing dams, were investigated. For this purpose, using 19 years of monthly data discharging from six existing flow gauging stations in the basin, the amount of hydroelectric energy generation of these dams was analyzed individually. As the result of these analysis, the calculation of the annual energy production capacity, the installed power production, and the annual economic contribution for both Çatören and Kunduzlar dams were estimated as 4.14 GWh ( 2.15 GWh (Çatören) + 1.99 GWh (Kunduzlar)) , 0.843 MW ( 0.273 MW (Çatören) + 0.57 MW (Kunduzlar)) , and 495000 USD ( 257000 USD (Çatören) + 238000 USD (Kunduzlar)), respectively .

Greenhouse gas emissions from two hydroelectric reservoirs in Mediterranean region.

Water reservoirs are used for many purposes, such as water supply, irrigation, flood mitigation, and hydroelectric energy generation. Although hydroelectric energy is considered "green," many studies show that the construction of a reservoir enhances greenhouse gas (GHG) emissions at the transformed area. These emissions, mainly of CO2, CH4, and N2O gases, depend on the age of the reservoir, landscape and soil composition, fauna and flora remnants of the impounded area, climatic conditions, and basin runoffs. Consequently, GHG emissions significantly vary between reservoirs and depending on local specificities. Several studies have investigated GHG emissions from reservoirs around the world, focusing mainly on reservoirs located in cold regions, temperate regions, and tropical regions. Research is lacking for reservoirs in Mediterranean countries, like Greece, and similar regions. This work initially assesses the net GHG emissions of a newly created reservoir (Ilarion est. 2012) in Western Macedonia, Greece. The methodology for net GHG emission calculation was based on the use of literature data concerning pre-impoundment emission factors and local specificities of the reservoir (terrain type, canopy cover), as well as on the 2-year measurement data that were collected using a "static floating chamber." Furthermore, in this work, the gross GHG emissions of an older, in-line reservoir (Polyfytos est. 1974) were also calculated, based on 2-year measurement data. The results show that the global warming potential (GWP) of the reservoirs is dictated by methane emissions; it minimizes during winter and spring and maximizes during summer and autumn. Hydroelectric energy production at Ilarion Reservoir results in 32 to 97 times less total CO2 equivalent emissions in comparison to fossil fuels, while at Polyfytos Reservoir only 8 to 24 times less (based on gross emissions). It appears that the impact of a reservoir's morphology on GHG emissions is more significant than that of a reservoir's age.

Statistical Model for the Forecast of Hydropower Production in Ecuador

The main sources of electricity generation are hydroelectric and thermo-fossil type in Ecuador. Gross hydroelectric production have sometimes exceeded 50% of national production. However, this type of hydroelectric is often threatened by droughts and their effect on the water reservoirs which our country has experienced on some occasions, such as in 2009. On the other hand, the National Plan for Good Living 2013-2017, in conjunction with the National Master Plan for Electrification 2013-2022, has planned new hydroelectric generation projects, which are expected to exceed 90% of the national balance. The objective of this article is to model the monthly production of hydroelectric energy for prediction purposes, by implementing five stochastic process models on a historical series of monthly hydroelectric energy production in Ecuador, during the period 2000-2015. The results show that the model that best fit the data of this time series is the ARIMA model (1, 1, 1)x(0, 0, 1) 12 with seasonality. This model shows that the energy monthly production can be forecasted to one and twelve months. The range used was from 2000 to 2014 and it was validated with data from January to December of 2015. With this model, the forecast is made for the year 2020, proving an increase of monthly production. The real values are in the confidence interval of the predicted values of the ARIMA model with annual seasonality. This model will help to describe and predict hydroelectric energy generation of Ecuador. In other words, it could be used in future planning studies of the electric sector.

Comparison of the water footprint of two hydropower plants in the Tocantins River Basin of Brazil

The purpose of this study was to characterize the water footprint of the Tucuruí and Lajeado hydropower plants (HPPs), located in the Tocantins River Basin, Brazil. The water footprint of hydropower was evaluated by three different methods based on the electricity production of the HPP and the monthly and annual evaporation rates estimated according to Penman's method. The first water footprint method (WF-1) considers only the gross water consumption by the HPPs; the second method (WF-2) considers the net water consumption, discounting what would be lost by evapotranspiration in the area previous to the construction of the reservoir; and the third method (WF-3) accounts for the net water balance. The results demonstrated that the estimates of average annual water footprint for the Tucuruí reservoir, using the WF-1, WF-2 and WF-3 methods, were, respectively, 49 m3/GJ, 26 m3/GJ and −21 m3/GJ, while for Lajeado, these estimates were 95 m3/GJ, 48 m3/GJ and 21 m3/GJ. The flooded area of the reservoir per unit of installed capacity of Tucuruí HPP is 34 ha/MW, while for Lajeado, this value reaches 70 ha/MW, which explains Tucuruí's greater water efficiency. Confirming this result, the normalized WFs based on the reservoir area and the installed capacity were approximately 100% higher for the Lajeado HPP than for the Tucuruí HPP through all water footprint methods analyzed. The WF-2 method is the most appropriate to account for the consumption of water directly related to hydroelectric energy generation since it considers the change in evaporation caused by the construction of the reservoir.

Optimization of Multiple and Multipurpose Reservoir System Operations by Using Matrix Structure (Case Study: Karun and Dez Reservoir Dams).

Optimal operation of water resources in multiple and multipurpose reservoirs is very complicated. This is because of the number of dams, each dam’s location (Series and parallel), conflict in objectives and the stochastic nature of the inflow of water in the system. In this paper, performance optimization of the system of Karun and Dez reservoir dams have been studied and investigated with the purposes of hydroelectric energy generation and providing water demand in 6 dams. On the Karun River, 5 dams have been built in the series arrangements, and the Dez dam has been built parallel to those 5 dams. One of the main achievements in this research is the implementation of the structure of production of hydroelectric energy as a function of matrix in MATLAB software. The results show that the role of objective function structure for generating hydroelectric energy in weighting method algorithm is more important than water supply. Nonetheless by implementing ε- constraint method algorithm, we can both increase hydroelectric power generation and supply around 85% of agricultural and industrial demands.

Total Electricity and Hydroelectric Energy Generation in Turkey: Projection and Comparison

The main goal of this study is to forecast total electricity and hydroelectricity energy generation using historical electricity energy production data in order to determine the future level of electricity and hydroelectricity energy generation in Turkey. For this purpose, Turkey's electricity energy sector was reviewed during the period of 1940–2005. The total electricity and hydroelectricity energy generation were then modelled using historical energy generation data as years with regression analysis. Additionally, the portion that hydroelectric energy generation of Turkey has within total electricity energy production and probable meeting capacity of Turkey's hydroelectric potential of its future total demand was determined. According to the results, it is deduced that hydropower energy will have portion of 13.6% within the total electricity energy generation in 2030. In addition, it is concluded that the whole of Turkey's technical and economical hydroelectric energy potential that is equal 129.9 billion kWh will be used in the year of 2102 if the current trend continues.