Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation

In this paper we show a multi-objective evolutionary algorithm (MOEA) for the optimisation of stand-alone (off-grid) hybrid systems (photovoltaic-wind-diesel-battery) to minimise total net present cost (NPC) and maximise human development index (HDI) and job creation (JC). Optimisation of this kind...

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Vydáno v:	Renewable energy Ročník 94; s. 280 - 293
Hlavní autoři:	Dufo-López, Rodolfo, Cristóbal-Monreal, Iván R., Yusta, José M.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.08.2016
Témata:	algorithms Communities Cost engineering Electricity emissions energy Energy consumption Human human development Human development index Hybrid systems Job creation Multi-objective evolutionary algorithms Net present cost Optimization Refugees renewable energy sources Renewable stand-alone systems Renewable stand-alone systems Multi-objective evolutionary algorithms Job creation Human development index Net present cost
ISSN:	0960-1481, 1879-0682
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Abstract	In this paper we show a multi-objective evolutionary algorithm (MOEA) for the optimisation of stand-alone (off-grid) hybrid systems (photovoltaic-wind-diesel-battery) to minimise total net present cost (NPC) and maximise human development index (HDI) and job creation (JC). Optimisation of this kind of system is usually performed considering only the minimisation of cost (NPC or the levelised cost of energy), as well as the emissions and the unmet load in some cases. In this paper, for the first time, we consider the maximisation of HDI and JC as part of optimisation. HDI depends on the consumption of electricity, so the extra energy that can supply the hybrid system can improve the HDI index. JC is different for each technology, obtaining different values for each combination of components in the system. The three objectives are often opposed, so a Pareto-optimisation MOEA is a good option to obtain a set of possible solutions in which no solution is better than another one for all three objectives (optimal Pareto set). We provide an example in the optimisation of a hybrid system to supply electricity to a small community in the Sahrawi refugee camps of Tindouf. •Multi-objective evolutionary algorithm for the optimisation of stand-alone systems.•Applied in the optimisation of photovoltaic-wind-diesel-battery hybrid systems.•Minimise total net present cost and maximise human development index and job creation.•Obtain the optimal Pareto set in which no solution is better than another one.
AbstractList	In this paper we show a multi-objective evolutionary algorithm (MOEA) for the optimisation of stand-alone (off-grid) hybrid systems (photovoltaic-wind-diesel-battery) to minimise total net present cost (NPC) and maximise human development index (HDI) and job creation (JC). Optimisation of this kind of system is usually performed considering only the minimisation of cost (NPC or the levelised cost of energy), as well as the emissions and the unmet load in some cases. In this paper, for the first time, we consider the maximisation of HDI and JC as part of optimisation. HDI depends on the consumption of electricity, so the extra energy that can supply the hybrid system can improve the HDI index. JC is different for each technology, obtaining different values for each combination of components in the system. The three objectives are often opposed, so a Pareto-optimisation MOEA is a good option to obtain a set of possible solutions in which no solution is better than another one for all three objectives (optimal Pareto set). We provide an example in the optimisation of a hybrid system to supply electricity to a small community in the Sahrawi refugee camps of Tindouf. In this paper we show a multi-objective evolutionary algorithm (MOEA) for the optimisation of stand-alone (off-grid) hybrid systems (photovoltaic-wind-diesel-battery) to minimise total net present cost (NPC) and maximise human development index (HDI) and job creation (JC). Optimisation of this kind of system is usually performed considering only the minimisation of cost (NPC or the levelised cost of energy), as well as the emissions and the unmet load in some cases. In this paper, for the first time, we consider the maximisation of HDI and JC as part of optimisation. HDI depends on the consumption of electricity, so the extra energy that can supply the hybrid system can improve the HDI index. JC is different for each technology, obtaining different values for each combination of components in the system. The three objectives are often opposed, so a Pareto-optimisation MOEA is a good option to obtain a set of possible solutions in which no solution is better than another one for all three objectives (optimal Pareto set). We provide an example in the optimisation of a hybrid system to supply electricity to a small community in the Sahrawi refugee camps of Tindouf. •Multi-objective evolutionary algorithm for the optimisation of stand-alone systems.•Applied in the optimisation of photovoltaic-wind-diesel-battery hybrid systems.•Minimise total net present cost and maximise human development index and job creation.•Obtain the optimal Pareto set in which no solution is better than another one.
Author	Dufo-López, Rodolfo Cristóbal-Monreal, Iván R. Yusta, José M.
Author_xml	– sequence: 1 givenname: Rodolfo orcidid: 0000-0002-1490-6423 surname: Dufo-López fullname: Dufo-López, Rodolfo email: rdufo@unizar.es organization: Electrical Engineering Department, University of Zaragoza, Calle María de Luna, 3, 50018 Zaragoza, Spain – sequence: 2 givenname: Iván R. surname: Cristóbal-Monreal fullname: Cristóbal-Monreal, Iván R. email: icristob@unizar.es organization: Centro Universitario de la Defensa, Academia General Militar, Ctra. de Huesca s/n, 50.090 Zaragoza, Spain – sequence: 3 givenname: José M. surname: Yusta fullname: Yusta, José M. email: jmyusta@unizar.es organization: Electrical Engineering Department, University of Zaragoza, Calle María de Luna, 3, 50018 Zaragoza, Spain
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Snippet	In this paper we show a multi-objective evolutionary algorithm (MOEA) for the optimisation of stand-alone (off-grid) hybrid systems...
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SubjectTerms	algorithms Communities Cost engineering Electricity emissions energy Energy consumption Human human development Human development index Hybrid systems Job creation Multi-objective evolutionary algorithms Net present cost Optimization Refugees renewable energy sources Renewable stand-alone systems
Title	Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation
URI	https://dx.doi.org/10.1016/j.renene.2016.03.065 https://www.proquest.com/docview/1808719074 https://www.proquest.com/docview/1825442162 https://www.proquest.com/docview/2116905375
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