A linearized formulation of AC multi-year transmission expansion planning: A mixed-integer linear programming approach

Akbari, Tohid; Bina, Mohammad Tavakoli

doi:10.1016/j.epsr.2014.04.013

Cited by 84 publications

(47 citation statements)

References 18 publications

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“…To surmount this shortcoming, some more sophisticated models of TEP have been introduced recently. 10,11 To work with real-world conditions of power systems, some studies analyzed the TEP problem based on the AC power flow, known as AC-TEP. 8,9,12 The algorithm presented by Rider et al 13 is an incipient attempt to solve AC-TEP in traditional power systems in which the single objective function is the capital cost of installing new transmission lines and MVAr sources.…”

Section: Discussionmentioning

confidence: 99%

“…Based on the decision-maker judgment, the desired (satisfaction) level (μ di ) of each objective is determined. The final solution will be found by solving the optimization problem in Equation 10.…”

Section: Final Decision-makingmentioning

confidence: 99%

“…The real transmission network operates in AC, and thus the obtained transmission expansion plans based on DC power flows may be unable to satisfy real operation conditions. To surmount this shortcoming, some more sophisticated models of TEP have been introduced recently …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multiobjective transmission expansion planning problem based on ACOPF considering load and wind power generation uncertainties

Abbasi

Abdi

2016

Int. Trans. Electr. Energ. Syst.

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SummaryThis article tackles the transmission expansion planning (TEP) problem in a deregulated environment with the objective functions of investment, congestion, and load curtailment costs. The proposed TEP approach is a mixed-integer nonlinear optimization problem with a nonconvex structure and noncommensurable objective function. Until now, the research efforts on this problem have been mostly based on the DC power flow, which has the disadvantage of neglecting reactive load, power losses, and voltage constraints. However, a realistic transmission network operates based on AC power flow conditions. Therefore, the obtained transmission expansion plans based on DC power flow may be unable to satisfy the real conditions of power systems. In this article, the effects of different transmission network models on the objective functions of TEP are analyzed. Furthermore, different uncertainties especially associated with load and wind power generation are considered as the major concerns in TEP studies for each of the previously mentioned models. The point estimation method that enjoys from proper accuracy and low computational efforts is used for modeling the uncertainties. The nondominated sorting genetic algorithm II (NSGA II) is performed to obtain the Pareto optimal solutions of the TEP objectives and the final optimal solution is searched by applying the fuzzy decision-making approach based on decision-maker preferences. The models are simulated on the case studies of IEEE 24-bus reliability test system as well as the Iranian 400 kV transmission grid. The obtained results show that the type of power flow and uncertainties can change the TEP optimal solutions and objectives significantly.

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Section: Discussionmentioning

confidence: 99%

Section: Final Decision-makingmentioning

confidence: 99%

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Multiobjective transmission expansion planning problem based on ACOPF considering load and wind power generation uncertainties

Abbasi

Abdi

2016

Int. Trans. Electr. Energ. Syst.

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“…Therefore, a linear model for line losses should be considered. Several methods have been proposed to represent a linear model for the line losses in the TEP problem [33,34,2]. One approach is to approximate (Â i − Â j ) 2 using piecewise linear functions and the other is to approximate (Pf The formulation of the TEP problem is indicated by Eqs.…”

Section: Multiyear Tep Problem Formulationmentioning

confidence: 99%

Transmission expansion planning using multivariate interpolation

Mortaz

Fuerte-Ledezma

Gutiérrez-Alcaraz

et al. 2015

Electric Power Systems Research

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“…In this regard, two main mathematical and Meta-heuristic optimization methods are used to solve these problems. TEP has been widely solved by using mathematical methods such as linear programming [3], nonlinear programming [4], mixed integer programming [5]; and Meta-heuristic methods such as ant colony [6], chaos [7], genetic algorithms [8], harmony search [9] and PSO [10,11]. GEP has also been solved by using mathematical methods such as dynamic programming [12], mixed integer programming [13], linear programming [14]; and Meta-heuristic methods such as ant colony [15], Tabu search [15], genetic algorithms [16] and PSO [17].…”

Section: Introductionmentioning

confidence: 99%

Coordinated generation and transmission expansion planning in deregulated electricity market considering wind farms

2016

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a b s t r a c tThis paper deals with a coordinated generation expansion planning (GEP)etransmission expansion planning (TEP) in competitive electricity market. In the proposed method, GEP and TEP are performed at the same time, with consideration of wind farm uncertainty. The uncertainty is modeled by normal probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to include the uncertainty into the problem. The planning is managed for two master and slave levels. At slave level, all generation company (GENCO) and transmission company (TRANSCO) maximize their profit and then at master level, the system constraints are checked by independent system operator (ISO). In other words, the proposed planning aims at maximizing the expected profit of all GENCOs and TRANSCOs, while considering security and reliability constraints such as reserve margin and loss of load expectation (LOLE). The proposed problem is a constrained, nonlinear, mixed-integer optimization programming and solved by using particle swarm optimization (PSO) method. Simulation results verify the effectiveness and validity of the proposed planning for maximizing GENCOs and TRANSCOs profit in the presence of wind farm uncertainty under electricity market.

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A linearized formulation of AC multi-year transmission expansion planning: A mixed-integer linear programming approach

Cited by 84 publications

References 18 publications

Multiobjective transmission expansion planning problem based on ACOPF considering load and wind power generation uncertainties

Multiobjective transmission expansion planning problem based on ACOPF considering load and wind power generation uncertainties

Transmission expansion planning using multivariate interpolation

Coordinated generation and transmission expansion planning in deregulated electricity market considering wind farms

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