Coordinated expansion planning problem considering wind farms, energy storage systems and demand response

During the recent years, the power system has entered a new technological era. The trends associated with increased commitment to wind farms (WFs) and energy storage systems (ESSs) as well demand side flexibility require disruptive changes in the existing power system structures and procedures. Bein...

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Veröffentlicht in:	Energy (Oxford) Jg. 239; S. 122321
Hauptverfasser:	Hamidpour, Hamidreza, Aghaei, Jamshid, Pirouzi, Sasan, Niknam, Taher, Nikoobakht, Ahmad, Lehtonen, Matti, Shafie-khah, Miadreza, Catalão, João P.S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 15.01.2022 Elsevier BV
Schlagworte:	Availability Demand response programs Electric power systems energy energy costs Energy management Energy storage Energy storage systems Expansion planning Flexibility Integer programming Linear programming Mixed integer Network reliability Nonlinear programming Optimization Parameter uncertainty Performance assessment Power flow Robust optimization Stochastic programming Storage systems Uncertainty wind Wind farms Wind power Expansion planning Uncertainty Robust optimization Energy storage systems Demand response programs
ISSN:	0360-5442, 1873-6785
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Abstract	During the recent years, the power system has entered a new technological era. The trends associated with increased commitment to wind farms (WFs) and energy storage systems (ESSs) as well demand side flexibility require disruptive changes in the existing power system structures and procedures. Being at the heart of a paradigm shift from passive users of the grid to active prosumers, storage owners and demand responsive actors, this paper expresses a flexible coordinated power system expansion planning (CPSEP) while considering local WFs, ESSs and incentive-based demand response programs (DRPs). This model minimizes the summation of the expansion planning, operation and reliability costs while taking the network model based on AC optimal power flow constraints, and the reliability and flexibility considerations into account. The proposed framework is firstly formulated by mixed integer non-linear programming (MINLP), then to have a well-handed optimization model it is converted to mixed-integer linear programming (MILP). Additionally, the uncertainties of load, energy price, maximum WF generation and availability/unavailability of the network equipment are included in the proposed model where the first three parameters are modeled based on the bounded uncertainty-based robust optimization (BURO), and the scenario-based stochastic programming (SBSP) is used to model the last uncertain parameter. Finally, the proposed method is examined on several test networks to assess the performance of the proposed framework for flexi-reliable transmission network operation and planning. •This paper expresses a reliable, flexible coordinated power system expansion planning.•Local wind farms, energy storage system and demand response programs are considered.•The model minimizes the summation of the expansion planning, operation and reliability costs.•The performance of the strategy efficiency is assessed for enhancing network operational indices.
AbstractList	During the recent years, the power system has entered a new technological era. The trends associated with increased commitment to wind farms (WFs) and energy storage systems (ESSs) as well demand side flexibility require disruptive changes in the existing power system structures and procedures. Being at the heart of a paradigm shift from passive users of the grid to active prosumers, storage owners and demand responsive actors, this paper expresses a flexible coordinated power system expansion planning (CPSEP) while considering local WFs, ESSs and incentive-based demand response programs (DRPs). This model minimizes the summation of the expansion planning, operation and reliability costs while taking the network model based on AC optimal power flow constraints, and the reliability and flexibility considerations into account. The proposed framework is firstly formulated by mixed integer non-linear programming (MINLP), then to have a well-handed optimization model it is converted to mixed-integer linear programming (MILP). Additionally, the uncertainties of load, energy price, maximum WF generation and availability/unavailability of the network equipment are included in the proposed model where the first three parameters are modeled based on the bounded uncertainty-based robust optimization (BURO), and the scenario-based stochastic programming (SBSP) is used to model the last uncertain parameter. Finally, the proposed method is examined on several test networks to assess the performance of the proposed framework for flexi-reliable transmission network operation and planning. •This paper expresses a reliable, flexible coordinated power system expansion planning.•Local wind farms, energy storage system and demand response programs are considered.•The model minimizes the summation of the expansion planning, operation and reliability costs.•The performance of the strategy efficiency is assessed for enhancing network operational indices. During the recent years, the power system has entered a new technological era. The trends associated with increased commitment to wind farms (WFs) and energy storage systems (ESSs) as well demand side flexibility require disruptive changes in the existing power system structures and procedures. Being at the heart of a paradigm shift from passive users of the grid to active prosumers, storage owners and demand responsive actors, this paper expresses a flexible coordinated power system expansion planning (CPSEP) while considering local WFs, ESSs and incentive-based demand response programs (DRPs). This model minimizes the summation of the expansion planning, operation and reliability costs while taking the network model based on AC optimal power flow constraints, and the reliability and flexibility considerations into account. The proposed framework is firstly formulated by mixed integer non-linear programming (MINLP), then to have a well-handed optimization model it is converted to mixed-integer linear programming (MILP). Additionally, the uncertainties of load, energy price, maximum WF generation and availability/unavailability of the network equipment are included in the proposed model where the first three parameters are modeled based on the bounded uncertainty-based robust optimization (BURO), and the scenario-based stochastic programming (SBSP) is used to model the last uncertain parameter. Finally, the proposed method is examined on several test networks to assess the performance of the proposed framework for flexi-reliable transmission network operation and planning. 1 During the recent years, the power system has entered a new technological era. The trends associated with increased commitment to wind farms (WFs) and energy storage systems (ESSs) as well demand side flexibility require disruptive changes in the existing power system structures and procedures. Being at the heart of a paradigm shift from passive users of the grid to active prosumers, storage owners and demand responsive actors, this paper expresses a flexible coordinated power system expansion planning (CPSEP) while considering local WFs, ESSs and incentive-based demand response programs (DRPs). This model minimizes the summation of the expansion planning, operation and reliability costs while taking the network model based on AC optimal power flow constraints, and the reliability and flexibility considerations into account. The proposed framework is firstly formulated by mixed integer non-linear programming (MINLP), then to have a well-handed optimization model it is converted to mixed-integer linear programming (MILP). Additionally, the uncertainties of load, energy price, maximum WF generation and availability/unavailability of the network equipment are included in the proposed model where the first three parameters are modeled based on the bounded uncertainty-based robust optimization (BURO), and the scenario-based stochastic programming (SBSP) is used to model the last uncertain parameter. Finally, the proposed method is examined on several test networks to assess the performance of the proposed framework for flexi-reliable transmission network operation and planning.
ArticleNumber	122321
Author	Shafie-khah, Miadreza Nikoobakht, Ahmad Aghaei, Jamshid Pirouzi, Sasan Catalão, João P.S. Lehtonen, Matti Hamidpour, Hamidreza Niknam, Taher
Author_xml	– sequence: 1 givenname: Hamidreza surname: Hamidpour fullname: Hamidpour, Hamidreza organization: Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran – sequence: 2 givenname: Jamshid surname: Aghaei fullname: Aghaei, Jamshid organization: Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran – sequence: 3 givenname: Sasan surname: Pirouzi fullname: Pirouzi, Sasan organization: Power System Group, Semirom Branch, Islamic Azad University, Semirom, Iran – sequence: 4 givenname: Taher surname: Niknam fullname: Niknam, Taher organization: Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran – sequence: 5 givenname: Ahmad surname: Nikoobakht fullname: Nikoobakht, Ahmad organization: Higher Education Center of Eghlid, Eghlid, Iran – sequence: 6 givenname: Matti surname: Lehtonen fullname: Lehtonen, Matti organization: Aalto University, Espoo, Finland – sequence: 7 givenname: Miadreza surname: Shafie-khah fullname: Shafie-khah, Miadreza organization: School of Technology and Innovations, University of Vaasa, 65200, Vaasa, Finland – sequence: 8 givenname: João P.S. orcidid: 0000-0002-2105-3051 surname: Catalão fullname: Catalão, João P.S. email: catalao@fe.up.pt organization: Faculty of Engineering of University of Porto and INESC TEC, 4200-465, Porto, Portugal
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Keywords	Expansion planning Uncertainty Robust optimization Energy storage systems Demand response programs
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Snippet	During the recent years, the power system has entered a new technological era. The trends associated with increased commitment to wind farms (WFs) and energy...
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SubjectTerms	Availability Demand response programs Electric power systems energy energy costs Energy management Energy storage Energy storage systems Expansion planning Flexibility Integer programming Linear programming Mixed integer Network reliability Nonlinear programming Optimization Parameter uncertainty Performance assessment Power flow Robust optimization Stochastic programming Storage systems Uncertainty wind Wind farms Wind power
Title	Coordinated expansion planning problem considering wind farms, energy storage systems and demand response
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