An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization

Hydropower is one of the significant renewable energy resources. It is regularly requested at peak time steps to meet the load requirements of power systems resources allocation. Therefore, modeling the optimal operation of hydropower systems to maximize the entire energy production of reservoir sys...

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Autores principales:	Yin Fang, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee, Reza Azarsa, Miklas Scholz, Zaher Mundher Yaseen
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Multi-reservoir optimization Hydropower Accelerated gradient Sequential quadratic programming Water resources management Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/feb23c1c3fbd440fa8bc1ae147ad827b
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id	oai:doaj.org-article:feb23c1c3fbd440fa8bc1ae147ad827b
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spelling	oai:doaj.org-article:feb23c1c3fbd440fa8bc1ae147ad827b2021-11-28T04:34:23ZAn accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization2352-484710.1016/j.egyr.2021.11.010https://doaj.org/article/feb23c1c3fbd440fa8bc1ae147ad827b2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352484721011549https://doaj.org/toc/2352-4847Hydropower is one of the significant renewable energy resources. It is regularly requested at peak time steps to meet the load requirements of power systems resources allocation. Therefore, modeling the optimal operation of hydropower systems to maximize the entire energy production of reservoir systems can be a vital task for energy investment. Deriving optimal unknown decision parameters of these reservoir systems is a nonlinear, nonconvex, and complex optimization problem. Herein, a novel optimization algorithm, called an accelerated version of gradient-based optimization (AGBO), is developed to solve a complex multi-reservoir hydropower system. This advised technique uses an efficient adaptive control parameters mechanism to stabilize the global and local search; utilizing an enhanced local escaping operator (ELEO) to extend the chances of getting away from local optima; expanding the exploitation search by applying the sequential quadratic programming (SQP) technique. At first, the developed AGBO algorithm is employed to solve the optimal operation of a complex 10-reservoir hydropower system. Secondly, the possibility of the AGBO algorithm within the global optimization problems is illustrated by numerical tests of 23 mathematical benchmark functions. Optimal results show that the proposed AGBO can approach to 0.9999% of the optimal global solution. As a result, the advised method is the most superior one compared to the other advanced optimization algorithms for maximizing the load demands in hydropower system. In conclusion, this offers a productive tool to solve the complex hydropower multi-reservoir optimization systems.Yin FangIman AhmadianfarArvin Samadi-KoucheksaraeeReza AzarsaMiklas ScholzZaher Mundher YaseenElsevierarticleMulti-reservoir optimizationHydropowerAccelerated gradientSequential quadratic programmingWater resources managementElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENEnergy Reports, Vol 7, Iss , Pp 7854-7877 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Multi-reservoir optimization Hydropower Accelerated gradient Sequential quadratic programming Water resources management Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Multi-reservoir optimization Hydropower Accelerated gradient Sequential quadratic programming Water resources management Electrical engineering. Electronics. Nuclear engineering TK1-9971 Yin Fang Iman Ahmadianfar Arvin Samadi-Koucheksaraee Reza Azarsa Miklas Scholz Zaher Mundher Yaseen An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization
description	Hydropower is one of the significant renewable energy resources. It is regularly requested at peak time steps to meet the load requirements of power systems resources allocation. Therefore, modeling the optimal operation of hydropower systems to maximize the entire energy production of reservoir systems can be a vital task for energy investment. Deriving optimal unknown decision parameters of these reservoir systems is a nonlinear, nonconvex, and complex optimization problem. Herein, a novel optimization algorithm, called an accelerated version of gradient-based optimization (AGBO), is developed to solve a complex multi-reservoir hydropower system. This advised technique uses an efficient adaptive control parameters mechanism to stabilize the global and local search; utilizing an enhanced local escaping operator (ELEO) to extend the chances of getting away from local optima; expanding the exploitation search by applying the sequential quadratic programming (SQP) technique. At first, the developed AGBO algorithm is employed to solve the optimal operation of a complex 10-reservoir hydropower system. Secondly, the possibility of the AGBO algorithm within the global optimization problems is illustrated by numerical tests of 23 mathematical benchmark functions. Optimal results show that the proposed AGBO can approach to 0.9999% of the optimal global solution. As a result, the advised method is the most superior one compared to the other advanced optimization algorithms for maximizing the load demands in hydropower system. In conclusion, this offers a productive tool to solve the complex hydropower multi-reservoir optimization systems.
format	article
author	Yin Fang Iman Ahmadianfar Arvin Samadi-Koucheksaraee Reza Azarsa Miklas Scholz Zaher Mundher Yaseen
author_facet	Yin Fang Iman Ahmadianfar Arvin Samadi-Koucheksaraee Reza Azarsa Miklas Scholz Zaher Mundher Yaseen
author_sort	Yin Fang
title	An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization
title_short	An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization
title_full	An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization
title_fullStr	An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization
title_full_unstemmed	An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization
title_sort	accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/feb23c1c3fbd440fa8bc1ae147ad827b
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An accelerated gradient-based optimization development for multi-reservoir hydropower systems optimization

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