Reliability‐based model for generation and transmission expansion planning

Ahmadi, Abdollah; Mavalizadeh, Hani; Zobaa, Ahmed F.; Shayanfar, Heidarali

doi:10.1049/iet-gtd.2016.1058

Cited by 22 publications

(17 citation statements)

References 33 publications

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“…Variable ξ indicates the extent of the variations and implicates the model robustness. Higher values of ξ imply larger model Ahmadi et al 55 The multiyear generation and transmission expansion planning…”

Section: Robust Igdt-based Model Descriptionmentioning

confidence: 99%

Robust optimal energy and reactive power management in smart distribution networks: An info‐gap multi‐objective approach

Samimi

Rezaei

2019

Int Trans Electr Energ Syst

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Summary Distributed energy resources (DERs) are main components for smart distribution networks (SDNs). Generally, energy and reactive power dispatch scheduling problems are managed separately in SDNs. In this paper, a robust simultaneous active/reactive scheduling framework is presented for SDNs. In order to handle the uncertainties of wind power generation, upstream grid prices, and load demand forecasting in a robust framework, information gap decision theory (IGDT) technique is proposed. The proposed robust model considers the minimization of the energy and reactive power cost, carbon taxes of CO2 emission of all distributed resources along with the cost of implementation of demand response program. Numerical results based on a 22‐bus distribution system validate the effectiveness of the proposed method from determining boundaries of uncertainties viewpoint. The obtained results verify that through the proposed IGDT‐based model, the distribution system operator (DSO) can effectively schedule the all DERs while considering the possibility of problem with a specific uncertainty budget.

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Section: Robust Igdt-based Model Descriptionmentioning

confidence: 99%

Robust optimal energy and reactive power management in smart distribution networks: An info‐gap multi‐objective approach

Samimi

Rezaei

2019

Int Trans Electr Energ Syst

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“…The constraints on the operation of the FACTS devices are presented in (14) and (15), which limit the series FACTS capacity and parallel FACTS susceptance, respectively. The series-parallel FACTS include two constraints given by (14) and (15). Also, the binary variable FA is equal to 1 if the FACTS device is built and 0 otherwise, and this variable is equal to 1 for the existing FACTS devices.…”

Section: Facts Constraintsmentioning

confidence: 99%

“…Application of the heuristic algorithms such as differential evolution algorithm and particle swarm optimization (PSO) to solve the problem has been widely addressed . Moreover, reliable renewable G&TEP, N ‐ k constrained composite G&TEP, and reliability‐based model for G&TEP are expressed in the works of Moreira et al, Hong et al, and Ahmadi et al, respectively. In these references, the power system planning is based on a direct current (DC) power flow.…”

Section: Introductionmentioning

confidence: 99%

Advanced model for joint generation and transmission expansion planning including reactive power and security constraints of the network integrated with wind turbine

Khob

Moazzami

Hemmati

2018

Int Trans Electr Energ Syst

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Summary This paper presents coordinated generation and transmission expansion planning (G&TEP) considering environmental pollutions and reliability in the presence of wind‐generating units and Flexible Alternating Current Transmission System (FACTS) devices. The proposed problem is expressed as a constrained optimization programming that aims at maximizing profit of generation and transmission owners as an objective function. The constraints of the problem include security constraints of alternating current (AC) power flow, wind unit operation, FACTS device operation, and reliability equations. Moreover, the produced power by wind turbines is modeled by probability function, and stochastic programming is adopted to cope with such uncertainty. The planning also calculates the expected energy not supplied (EENS) as a part of the objective function (ie, planning cost). The problem is expressed by means of mixed‐integer nonlinear programming (MINLP) and then linearized as a mixed‐integer linear programming (MILP) to confirm the optimal solution. The linear model is implemented in the Generalized Algebraic Modeling System (GAMS) software. Simulation results are carried out on a large‐scale electrical network, emphasizing the capability and efficiency of the introduced planning to expand the network under uncertainty. Also, the impacts of pollution, FACTS devices, and reliability on planning are demonstrated by numerous analyses and discussions, and it is confirmed that considering such items improves planning.

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“…Various research works in the literature have been focused on the CSEP problem during recent years. Although the accuracy of AC power flow equations is higher than DC ones, most of previous CSEP, generation expansion planning (GEP), and transmission expansion planning (TEP) models have utilised DC power flow equations [4][5][6]. The main reason is that GEP, TEP, and CSEP problems with AC power flow equations are mixed-integer nonlinear programming (MINLP) problems, and consequently, any mathematical solution technique demands a considerable computation time to solve these MINLP problems.…”

Section: Introductionmentioning

confidence: 99%

Flexible, reliable, and renewable power system resource expansion planning considering energy storage systems and demand response programs

Hamidpour¹,

Aghaei²,

Pirouzi

et al. 2019

IET Renewable Power Generation

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This study presents a flexible, reliable, and renewable power system resource planning approach to coordinate generation, transmission, and energy storage (ES) expansion planning in the presence of demand response (DR). The flexibility and reliability of the optimal resource expansion planning are ensured by means of appropriate constraints incorporated into the proposed planning tool where thermal generation units, ES systems, and DR programs are considered as flexibility resources. The proposed planning tool is a mixed-integer non-linear programming (MINLP) problem due to the non-linear and non-convex constraints of AC power flow equations. Accordingly, to linearise the proposed MINLP problem, the AC nodal power balance constraints are linearised by means of the first-order expansion of Taylor's series and the line flow equations are linearised by means of a polygon. Additionally, the stochastic programming is used to characterise the uncertainty of loads, a maximum available power of wind farms, forecasted energy price, and availability/unavailability of generation units and transmission lines by means of a sufficient number of scenarios. The proposed planning tool is implemented on the IEEE 6-bus and the IEEE 30bus test systems under different conditions. Case studies illustrate the effectiveness of the proposed approach based on both flexibility and reliability criteria.

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Reliability‐based model for generation and transmission expansion planning

Cited by 22 publications

References 33 publications

Robust optimal energy and reactive power management in smart distribution networks: An info‐gap multi‐objective approach

Robust optimal energy and reactive power management in smart distribution networks: An info‐gap multi‐objective approach

Advanced model for joint generation and transmission expansion planning including reactive power and security constraints of the network integrated with wind turbine

Flexible, reliable, and renewable power system resource expansion planning considering energy storage systems and demand response programs

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