Investigating the impacts of energy storage systems on transmission expansion planning

Mazaheri, Hesam; Abbaspour, Ali; Fotuhi‐Firuzabad, Mahmud; Farzin, Hossein; Moeini‐Aghtaie, Moein

doi:10.1109/iraniancee.2017.7985224

Cited by 9 publications

(14 citation statements)

References 16 publications

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“…The limit on the load curtailment power is supposed to be 10 MW. To evaluate the Master investment problem, the annual discount rate is set to 0.12 in a 30‐year planning horizon by considering hourly scale of operation sub‐problem in each day [40]. Finally, the operation sub‐problem is optimized for one target year via the discount factor to determine the winter/summer days in the proposed static co‐planning structure.…”

Section: The Garver Case Studymentioning

confidence: 99%

“…In many of the above-mentioned literature, authors have employed non-linear and linear optimization models to assess the impacts of ESS integration on TEP, in which some solution techniques have been offered such as the genetic algorithm [14], the Benders decomposition scheme [9,16], and direct optimization method [21]. However, none has concentrated on the joint TEP and ESS planning in order to primarily improve metrics of system flexibility considering the ESS impacts.…”

Section: Introductionmentioning

confidence: 99%

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A linearized transmission expansion planning model under N − 1 criterion for enhancing grid‐scale system flexibility via compressed air energy storage integration

Mazaheri

Moeini‐Aghtaie

Fotuhi‐Firuzabad

et al. 2021

IET Generation Trans & Dist

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The concept of flexibility is defined as the power systems' ability to effectively respond to changes in power generation and demand profiles to maintain the supply-demand balance. However, the inherent flexibility margins required for successful operation have been recently challenged by the unprecedented arrival of uncertainties, driven by constantly changing demand, failure of conventional units, and the intermittent outputs of renewable energy sources (RES). Tackling these challenges, energy storage systems (ESS) as one important player of the new power grids can enhance the system flexibility. It, therefore, calls for an efficient planning procedure to ensure flexibility margins by considering ESS's role in modern power systems. This paper proposes a novel mixed integer linear programming (MILP) model for transmission expansion planning (TEP) framework taking into account the role of compressed air energy storage (CAES) integration on improvements in system flexibility. The proposed framework is housed with a quantitative metric of gridscale system flexibility, while a new offline repetitive mechanism is suggested to account for the N − 1 reliability criterion. The model is applied to different test systems, where the numerical results demonstrate the impacts of CAES units on system flexibility, investment plans, and the total costs.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: The Garver Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A linearized transmission expansion planning model under N − 1 criterion for enhancing grid‐scale system flexibility via compressed air energy storage integration

Mazaheri

Moeini‐Aghtaie

Fotuhi‐Firuzabad

et al. 2021

IET Generation Trans & Dist

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“…The power balance of generation, load, and CAESs charging/discharging power is enforced in (16). Moreover, linear formulation of D.C. power flow for online as well as installed transmission lines, transmission line power flow limits, and power generation limits linearised by Big-M approach are specified in (10), (17)(18)(19). According to the CAESs constraints, the hourly CAESs status is presented in (11).…”

Section: Linearised Es-tep Model-normal Operating Statementioning

confidence: 99%

“…The natural gas cost, heat rate, and energy ratio are 3.5 $/GJ, 4185 MJ/MWh, and 0.75, respectively, [40] and the average value of curtailed load is 39228 $/MWh [7]. In this paper, the annual discount rate is defined as the "return rate earned on an investment" [41] and is taken 0.12 [42]. The probability of contingency scenarios is supposed to be the same for all transmission line outages in outage hours and is considered 0.004 [6], [39].…”

Section: Test System Data and Main Assumptionsmentioning

confidence: 99%

“…On the other hand, some researchers have progressively tried to introduce models for deployment of ESS technologies in TEP studies. In this vein, authors in [19] investigate the impacts of ESSs on TEP problem through a non‐linear optimisation model decomposed to investment and operation sub‐problems. In [7], utilisation of flexible system technologies such as phase‐shifting transformers, ESSs, and demand‐side management programs are incorporated in a long‐term stochastic planning formulation.…”

Section: Introductionmentioning

confidence: 99%

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An online method for MILP co‐planning model of large‐scale transmission expansion planning and energy storage systems considering N‐1 criterion

Mazaheri

Abbaspour

Fotuhi‐Firuzabad

et al. 2020

IET Generation Trans & Dist

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In recent years, increased integration of renewable energy sources (RES) calls for extensive and costly investments in transmission networks. In response, power system decisionmakers try to apply alternative solutions aimed to decrease the imposed investment costs. In this context, the presence of large-scale energy storage systems (ESSs) in transmission network can be a practical option for deferring investment in expansion plans of transmission lines, alleviating system congestions, and attaining higher flexibility. In this paper, an efficient model is proposed for co-planning expansion studies of compressed air energy storage (CAES) units and transmission networks. The associated optimisation formulation of co-planning problem is expressed as a MILP model, which can be efficiently solved. The proposed model is applied on the Garver as well as RTS test systems and N-1 criterion is considered to address the system reliability performance in expansion studies. The results demonstrate that the proposed co-planning framework has a superior performance in expansion plans of transmission systems. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Transmission Expansion Planning Considering Storage and Intraday Time Constraints to Integrate Wind Power

Huanca,

Falcão

2024

J. Electr. Eng. Technol.

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Investigating the impacts of energy storage systems on transmission expansion planning

Cited by 9 publications

References 16 publications

A linearized transmission expansion planning model under N − 1 criterion for enhancing grid‐scale system flexibility via compressed air energy storage integration

A linearized transmission expansion planning model under N − 1 criterion for enhancing grid‐scale system flexibility via compressed air energy storage integration

An online method for MILP co‐planning model of large‐scale transmission expansion planning and energy storage systems considering N‐1 criterion

Transmission Expansion Planning Considering Storage and Intraday Time Constraints to Integrate Wind Power

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