2014
Stoppato, Anna; Cavazzini, Giovanna; Ardizzon, Guido; Rossetti, Antonio
In: Energy, vol. 76, pp. 168-174, 2014, ISSN: 03605442.
Abstract | Links | BibTeX | 标签: Energy storage, Particle swarm theory, Photovoltaic pumping systems, Pump as Turbine, Water cooling, Water saving
@article{Stoppato2014a,
title = {A PSO (particle swarm optimization)-based model for the optimal management of a small PV(Photovoltaic)-pump hydro energy storage in a rural dry area},
author = {Anna Stoppato and Giovanna Cavazzini and Guido Ardizzon and Antonio Rossetti},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0360544214006999},
doi = {10.1016/j.energy.2014.06.004},
issn = {03605442},
year = {2014},
date = {2014-01-01},
journal = {Energy},
volume = {76},
pages = {168-174},
abstract = {In developing countries, the exploitation of renewable sources is an opportunity to increase the number of people who have simple access to electricity and to water. Among other technologies, stand-alone photovoltaic pumping systems are often installed in remote areas where the grid is not available: they are used for irrigation and/or other local water needs and can supply also electricity to small consumers. In this paper, by means of an optimization model based on the Particle Swarm Theory, the managing strategy of a system aimed at supplying electricity and water to an isolated small village in Nigeria has been optimized in order to fulfill the requirement of the users and to improve the system efficiency. Ground water is pumped into a storage reservoir and can be used both for irrigation and domestic use. The system is composed by a photovoltaic plant, a pump as turbine, a pack of batteries and a diesel internal combustion engine for integration purposes. A simultaneous optimization of both devices size and plant management has been performed in order to achieve the best economic performances or to fulfil the requirement only by renewable sources. In the first case, the use of a pump as turbine permits to save about 4% of diesel oil, even if the low cost of fuel makes it convenient to use the engine. In the latter case the optimum size of photovoltaic plant is about 16 times higher than in the first one, while the batteries' and pump's optimum sizes are strictly connected to the maximum allowable value for the water storage volume. © 2014 Elsevier Ltd. All rights reserved.},
keywords = {Energy storage, Particle swarm theory, Photovoltaic pumping systems, Pump as Turbine, Water cooling, Water saving},
pubstate = {published},
tppubtype = {article}
}
In developing countries, the exploitation of renewable sources is an opportunity to increase the number of people who have simple access to electricity and to water. Among other technologies, stand-alone photovoltaic pumping systems are often installed in remote areas where the grid is not available: they are used for irrigation and/or other local water needs and can supply also electricity to small consumers. In this paper, by means of an optimization model based on the Particle Swarm Theory, the managing strategy of a system aimed at supplying electricity and water to an isolated small village in Nigeria has been optimized in order to fulfill the requirement of the users and to improve the system efficiency. Ground water is pumped into a storage reservoir and can be used both for irrigation and domestic use. The system is composed by a photovoltaic plant, a pump as turbine, a pack of batteries and a diesel internal combustion engine for integration purposes. A simultaneous optimization of both devices size and plant management has been performed in order to achieve the best economic performances or to fulfil the requirement only by renewable sources. In the first case, the use of a pump as turbine permits to save about 4% of diesel oil, even if the low cost of fuel makes it convenient to use the engine. In the latter case the optimum size of photovoltaic plant is about 16 times higher than in the first one, while the batteries' and pump's optimum sizes are strictly connected to the maximum allowable value for the water storage volume. © 2014 Elsevier Ltd. All rights reserved.
