scholarly journals Method of calculation of water-diverting structures of low-head hydroelectric power plant for power supply of small power consumers

2022 ◽  
Vol 1211 (1) ◽  
pp. 012012
Author(s):  
Y Y Zakharov ◽  
A R Lepeshkin

Abstract In recent years and in many countries the economic development of distant regions is increasingly dependent on energy resources. This fact makes the world scientific community pay more attention to the renewable energy sources. Special attention is paid to the solar, wind and small hydropower for electrical consumers who have no possibility to connect to the central power supply lines. In the countries that have water resources the financial support is given to the development of small and micro hydropower stations. The present work presents the results of the research on the improved method of calculation of water-diverting structures of low-head hydroelectric power plant with an installed cross-jet hydro turbine that is actual for the power supply of small power consumers. The presented method can be used for the preliminary analysis of morphometric characteristics of water course as well as the basic parameters of a cross-jet hydro turbine.

Author(s):  
M. I. Balzannikov ◽  
E. G. Vyshkin

The paper presents the analysis of different types of impact the hydroelectric power plants’ reservoirs could make on the environment. Hydroelectric power plants (HPP) produce ecologically safe energy and correspond to the modern striving for sustainability because they are operated on renewable energy sources. At the same time they can provoke various potential dangers for the environment. The objective of the investigation is to demonstrate the interrelation between the type and structure of a hydroelectric power plant and the way its reservoir may impact on the nature surrounding the plant. These effects may be direct and indirect, positive and negative and vary from insignificant that can be easily fixed to those that are irreversible and catastrophic. The latter should be taken into account during the design of HPP.


2018 ◽  
Vol 1 (2) ◽  
pp. 293-303
Author(s):  
Diego Fernando Rodríguez-Galán ◽  
Andrés Escobar-Díaz

In this study a presentation is made of the Small Hydroelectric Power Plant (PCH) located in Usaquén (Bogota), the work is based on an engineering project carried out by the Aqueduct and Sewer Company of Bogotá (EAAB). It is addressed first of all the environmental problems considered in this project and the business context that propitiates it, taking into account the technical background of the operation of the aqueduct system of the city. In second instance, the technical generalities and the scopes that were estimated in the formulation of the project are exposed to finally contrast them with the results obtained after five years of operation of the project.


Forecasting ◽  
2020 ◽  
Vol 2 (4) ◽  
pp. 410-428
Author(s):  
Emanuele Ogliari ◽  
Alfredo Nespoli ◽  
Marco Mussetta ◽  
Silvia Pretto ◽  
Andrea Zimbardo ◽  
...  

The increasing penetration of non-programmable renewable energy sources (RES) is enforcing the need for accurate power production forecasts. In the category of hydroelectric plants, Run of the River (RoR) plants belong to the class of non-programmable RES. Data-driven models are nowadays the most widely adopted methodologies in hydropower forecast. Among all, the Artificial Neural Network (ANN) proved to be highly successful in production forecast. Widely adopted and equally important for hydropower generation forecast is the HYdrological Predictions for the Environment (HYPE), a semi-distributed hydrological Rainfall–Runoff model. A novel hybrid method, providing HYPE sub-basins flow computation as input to an ANN, is here introduced and tested both with and without the adoption of a decomposition approach. In the former case, two ANNs are trained to forecast the trend and the residual of the production, respectively, to be then summed up to the previously extracted seasonality component and get the power forecast. These results have been compared to those obtained from the adoption of a ANN with rainfalls in input, again with and without decomposition approach. The methods have been assessed by forecasting the Run-of-the-River hydroelectric power plant energy for the year 2017. Besides, the forecasts of 15 power plants output have been fairly compared in order to identify the most accurate forecasting technique. The here proposed hybrid method (HYPE and ANN) has shown to be the most accurate in all the considered study cases.


2015 ◽  
Vol 21 (4) ◽  
pp. 470-477 ◽  
Author(s):  
Murat Gunduz ◽  
Haci Bayram Sahin

Energy is increasingly becoming more important in today’s world, whereas energy sources are drastically decreasing. One of the most valuable energy sources is hydro energy. Because of limited energy sources and excessive energy usage, cost of energy is rising. Among the electricity generation units, hydroelectric power plants are very important, since they are renewable energy sources and they have no fuel cost. To decide whether a hydroelectric power plant investment is feasible or not, project cost and amount of electricity generation of the investment should be precisely estimated. In this paper, fifty four hydroelectric power plant projects are analysed by using multiple regression and artificial neural network tools. As a result, two cost estimation models have been developed to estimate the hydroelectric power plant project cost in early stages of the project.


2021 ◽  
pp. 267-279
Author(s):  
Manuel Ayala-Chauvin ◽  
Henrry Rojas-Asuero ◽  
Genís Riba-Sanmartí ◽  
Jaime Ramón-Campoverde

2002 ◽  
Vol 122 (6) ◽  
pp. 989-994
Author(s):  
Shinichiro Endo ◽  
Masami Konishi ◽  
Hirosuke Imabayashi ◽  
Hayami Sugiyama

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