A mixed integer disjunctive model for transmission network expansion

Summary One ultimate goal of power network planning is to construct power systems that are environmentally friendly. However, it is still a challenging issue to efficiently consider environmental factors in power network planning problems due to the complexity and the diversity of environment. This paper presents a nonlinear approach to formulate the multi‐dimensional spatial power network planning problem based on raster map in geographic information systems. With the objective of minimizing investment and operation costs, the proposed model integrates five dimensions: the substation location, the substation sizing, the line type selection, the optimal electric line routing, and the power network evaluation in terms of the ac power flow calculation. Furthermore, the branch capacity constraints and the node voltage limitations at peak load hours are examined to ensure the operational security of power systems. To overcome difficulties in solving the mixed‐integer nonlinear optimization problem, an enhanced ant colony optimization with the four‐search‐space structure and the improved state transition rule is introduced. The case results validate the proposed model and the algorithms. Copyright © 2014 John Wiley & Sons, Ltd.

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“…Variable costs are the costs of technical energy losses. Thus, the objective function is modeled as (4)- (9).…”

Section: Objective Functionmentioning

confidence: 99%

“…A coordination of transmission and generation capacity planning was proposed in [5][6][7]. Based on a linear disjunctive model, power transmission network design problems were solved via a Benders decomposition approach [8,9].…”

Section: Introductionmentioning

confidence: 99%

Enhanced multi-dimensional power network planning based on ant colony optimization

Shu

Han

et al. 2014

Int. Trans. Electr. Energ. Syst.

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“…These optimization problems have been solved using LP methods, [17][18][19] nonlinear programming (NLP), 20 and MIP methods. 21,22 LP was first used to solve the TEP problem 15 in 1997 by Garver, where the transmission losses were neglected and the constraints were all linear. It is noted that this method was associated with low accuracy and high convergence speed.…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective, multi‐year dynamic generation and transmission expansion planning‐ renewable energy sources integration for Iran's National Power Grid

Javadi

Nezhad

2018

Int Trans Electr Energ Syst

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Summary The paper presents a multi‐year, multi‐objective framework for integrating Renewable Energy Sources (RESs) into the high voltage transmission network of Iran's National Power Grid (INPG). The objective functions in this study are the total cost, including the investment cost and operating cost for the planning horizon, and the system reliability. The first objective function is stated from the economic point of view, while the second objective function is considered as a security index in the expansion planning issue. The main purpose of this paper is to increase the RES penetration into the generation mix of INPG. Since the mentioned 230 to 400‐kV INPG is a large‐scale power system, the problem formulation is investigated in a mixed‐integer programming, and then, the developed multi‐objective problem has been solved using the augmented epsilon‐constraint optimization method. In order to select the executive plan for installation, the fuzzy satisfying decision‐making procedure is adopted in this study.

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“…The names DC and AC refers to the nature of the load flow modeling. The optimization techniques for solving such models include linear programming (LP) [9,14,15], dynamic programming [16], non-LP [17], mixed-integer programming [18][19][20], and Benders decomposition [21,22], among others.…”

Section: Introductionmentioning

confidence: 99%

Enhanced multiobjective algorithm for transmission expansion planning consideringN − 1 security criterion

Correa

Bolaños

Garcés

2014

Int. Trans. Electr. Energ. Syst.

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SUMMARYPower system deregulation and the high penetration of renewable energies have introduced new challenges for the transmission expansion planning (TEP), which is a high complex mixed-integer non-linear problem. The search space and the computational effort increase if these constraints are included; therefore, efficient methods for solving the problem are needed. This paper presents an enhanced NSGA-II multiobjective algorithm for solving the security-constrained TEP problem, taking into account the N À 1 security criterion. This new methodology takes advantage of the NSGA-II crowded distance features and the Chu-Beasley genetic algorithm. The performance of the proposed algorithm is validated using three test systems. A set of optimal non-dominated solutions for each test system is thoroughly analyzed from the power systems and computational standpoint. The analysis of the obtained results and the comparison with others from the specialized literature show the robustness and the advantages of using this algorithm.

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A mixed integer disjunctive model for transmission network expansion

Cited by 12 publications

References 0 publications

Enhanced multi-dimensional power network planning based on ant colony optimization

Enhanced multi-dimensional power network planning based on ant colony optimization

Multi‐objective, multi‐year dynamic generation and transmission expansion planning‐ renewable energy sources integration for Iran's National Power Grid

Enhanced multiobjective algorithm for transmission expansion planning consideringN − 1 security criterion

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