A flexible-reliable operation optimization model of the networked energy hubs with distributed generations, energy storage systems and demand response

This paper presents a novel optimization model for the flexible-reliable operation (FRO) of energy hubs (EHs) in electricity, natural gas, and district heating networks. To achieve flexible EH in the presence of renewable energy sources (RESs) and combined heat and power (CHP) system, energy storage...

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Vydáno v:	Energy (Oxford) Ročník 239; s. 121923
Hlavní autoři:	Dini, Anoosh, Hassankashi, Alireza, Pirouzi, Sasan, Lehtonen, Matti, Arandian, Behdad, Baziar, Ali Asghar
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 15.01.2022 Elsevier BV
Témata:	algorithms Cogeneration Distributed generation District heating Electric power demand electricity energy Energy costs Energy management Energy storage Flexibility Flexibility sources Flexible-reliable operation heat Hubs Hybrid evolutionary algorithm hybrids Machine learning Mixed integer Natural gas Network reliability Networked energy hub Nonlinear programming Optimization Optimization models Power flow power generation Renewable energy sources Scenario-based stochastic programming Search algorithms standard deviation Stochastic programming Storage systems Flexible-reliable operation Flexibility sources Hybrid evolutionary algorithm Networked energy hub Scenario-based stochastic programming
ISSN:	0360-5442, 1873-6785
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Abstract	This paper presents a novel optimization model for the flexible-reliable operation (FRO) of energy hubs (EHs) in electricity, natural gas, and district heating networks. To achieve flexible EH in the presence of renewable energy sources (RESs) and combined heat and power (CHP) system, energy storage systems (ESS) and incentive-based demand response program (IDRP) are used. The proposed problem minimizes the total expected costs of operation, reliability, and flexibility of the energy networks including EHs. The optimization scheme is constrained to the optimal power flow (OPF) equations and the reliability requirements of these networks and the EH model in the presence of sources and active loads, namely ESS and IDRP. Scenario-based stochastic programming (SBSP) is utilized to model uncertainties of load, energy cost, power generation of RES, and network equipment availability. The problem has a mixed-integer nonlinear programming (MINLP) nature. Consequently, a hybrid teaching-learning-based optimization (TLBO) and crow search algorithm (CSA) is used to obtain a reliable optimal solution with a low standard deviation. Finally, by simulating the proposed scheme on a sample test system, the capabilities of this scheme in improving the reliability, operation, and flexibility of energy networks in accordance with the optimal scheduling for EHs are confirmed. •Modeling flexible-reliable operation in the electricity, gas, and heating networks.•Operation, reliability, flexibility, and economic indices for energy management.•Use of ESS and IDRP to improve EH flexibility in the presence of RES and CHP.•Solving FRO problem of energy networks with EH using hybrid TLBO and CSA.
AbstractList	This paper presents a novel optimization model for the flexible-reliable operation (FRO) of energy hubs (EHs) in electricity, natural gas, and district heating networks. To achieve flexible EH in the presence of renewable energy sources (RESs) and combined heat and power (CHP) system, energy storage systems (ESS) and incentive-based demand response program (IDRP) are used. The proposed problem minimizes the total expected costs of operation, reliability, and flexibility of the energy networks including EHs. The optimization scheme is constrained to the optimal power flow (OPF) equations and the reliability requirements of these networks and the EH model in the presence of sources and active loads, namely ESS and IDRP. Scenario-based stochastic programming (SBSP) is utilized to model uncertainties of load, energy cost, power generation of RES, and network equipment availability. The problem has a mixed-integer nonlinear programming (MINLP) nature. Consequently, a hybrid teaching-learning-based optimization (TLBO) and crow search algorithm (CSA) is used to obtain a reliable optimal solution with a low standard deviation. Finally, by simulating the proposed scheme on a sample test system, the capabilities of this scheme in improving the reliability, operation, and flexibility of energy networks in accordance with the optimal scheduling for EHs are confirmed. This paper presents a novel optimization model for the flexible-reliable operation (FRO) of energy hubs (EHs) in electricity, natural gas, and district heating networks. To achieve flexible EH in the presence of renewable energy sources (RESs) and combined heat and power (CHP) system, energy storage systems (ESS) and incentive-based demand response program (IDRP) are used. The proposed problem minimizes the total expected costs of operation, reliability, and flexibility of the energy networks including EHs. The optimization scheme is constrained to the optimal power flow (OPF) equations and the reliability requirements of these networks and the EH model in the presence of sources and active loads, namely ESS and IDRP. Scenario-based stochastic programming (SBSP) is utilized to model uncertainties of load, energy cost, power generation of RES, and network equipment availability. The problem has a mixed-integer nonlinear programming (MINLP) nature. Consequently, a hybrid teaching-learning-based optimization (TLBO) and crow search algorithm (CSA) is used to obtain a reliable optimal solution with a low standard deviation. Finally, by simulating the proposed scheme on a sample test system, the capabilities of this scheme in improving the reliability, operation, and flexibility of energy networks in accordance with the optimal scheduling for EHs are confirmed. •Modeling flexible-reliable operation in the electricity, gas, and heating networks.•Operation, reliability, flexibility, and economic indices for energy management.•Use of ESS and IDRP to improve EH flexibility in the presence of RES and CHP.•Solving FRO problem of energy networks with EH using hybrid TLBO and CSA.
ArticleNumber	121923
Author	Dini, Anoosh Lehtonen, Matti Arandian, Behdad Baziar, Ali Asghar Hassankashi, Alireza Pirouzi, Sasan
Author_xml	– sequence: 1 givenname: Anoosh surname: Dini fullname: Dini, Anoosh email: a.dini@ieee.org organization: Department of Electrical and Electronics Engineering, Iran University of Science and Technology, Tehran, Iran – sequence: 2 givenname: Alireza surname: Hassankashi fullname: Hassankashi, Alireza email: a_hasankashi@alumni.iust.ac.ir organization: Department of Electrical and Electronics Engineering, Iran University of Science and Technology, Tehran, Iran – sequence: 3 givenname: Sasan surname: Pirouzi fullname: Pirouzi, Sasan email: s.pirouzi@sutech.ac.ir organization: Power System Group, Semirom Branch, Islamic Azad University, Semirom, Iran – sequence: 4 givenname: Matti orcidid: 0000-0002-9979-7333 surname: Lehtonen fullname: Lehtonen, Matti email: matti.lehtonen@aalto.fi organization: Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland – sequence: 5 givenname: Behdad surname: Arandian fullname: Arandian, Behdad email: b.arandian@yahoo.com organization: Department of Electrical Engineering, Dolatabad Branch, Islamic Azad University, Isfahan, Iran – sequence: 6 givenname: Ali Asghar surname: Baziar fullname: Baziar, Ali Asghar email: aliasghar.baziar@yahoo.com organization: Department of Electrical Engineering, Missouri University of Science and Technology, Rolla, Missouri, USA
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Keywords	Flexible-reliable operation Flexibility sources Hybrid evolutionary algorithm Networked energy hub Scenario-based stochastic programming
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Snippet	This paper presents a novel optimization model for the flexible-reliable operation (FRO) of energy hubs (EHs) in electricity, natural gas, and district heating...
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SubjectTerms	algorithms Cogeneration Distributed generation District heating Electric power demand electricity energy Energy costs Energy management Energy storage Flexibility Flexibility sources Flexible-reliable operation heat Hubs Hybrid evolutionary algorithm hybrids Machine learning Mixed integer Natural gas Network reliability Networked energy hub Nonlinear programming Optimization Optimization models Power flow power generation Renewable energy sources Scenario-based stochastic programming Search algorithms standard deviation Stochastic programming Storage systems
Title	A flexible-reliable operation optimization model of the networked energy hubs with distributed generations, energy storage systems and demand response
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