A mixed integer disjunctive model for transmission network expansion

Bahiense, Laura; Oliveira, G.C.; Pereira, M.V.F.; Granville, S.

doi:10.1109/59.932295

Cited by 268 publications

(136 citation statements)

References 5 publications

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“…(9). The total emission cost decreased to 0.20012 t/h (43.89%) in Case 3 in comparison to 0.365141 t/h in Case 1.…”

Section: Case 3: Emission Minimizationmentioning

confidence: 80%

“…Four branches, (6,9), (6,10), (4,12) and (27,28), are under load tap setting transformer branches within the interval (0.9, 1.1). The possible 9 reactive power sources within the interval (0, 0.05) are installed at bus numbers 10, 12, 15, 17, 20, 21 23, 24 and 29.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The EPD problem is a large-scale highly constrained nonlinear non-convex optimization problem [2]. To solve it, a number of conventional optimization techniques such as nonlinear programming (NLP) [3], quadratic programming (QP) [4], linear programming (LP) [5,6], and interior point methods [7], Newton-based method [8], mixed integer programming [9], dynamic programming [10], and branch and bound [11] have been applied. All of these mathematical methods are fundamentally based on the convexity of objective function to find the global minimum.…”

Section: Introductionmentioning

confidence: 99%

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A new technique for solving the multi-objective optimization problem using hybrid approach

2014

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Energy efficiency, which consists of using less energy or improving the level of service to energy consumers, refers to an effective way to provide overall energy. But its increasing pressure on the energy sector to control greenhouse gases and to reduce CO 2 emissions forced the power system operators to consider the emission problem as a consequential matter besides the economic problems. The economic power dispatch problem has, therefore, become a multi-objective optimization problem. Fuel cost, pollutant emissions, and system loss should be minimized simultaneously while satisfying certain system constraints. To achieve a good design with different solutions in a multi-objective optimization problem, fuel cost and pollutant emissions are converted into single optimization problem by introducing penalty factor. Now the power dispatch is formulated into a bi-objective optimization problem, two objectives with two algorithms, firefly algorithm for optimization the fuel cost, pollutant emissions and the real genetic algorithm for minimization of the transmission losses. In this paper the new approach (firefly algorithm-real genetic algorithm, FFA-RGA) has been applied to the standard IEEE 30-bus 6-generator. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multiobjective optimization algorithms. Simulation results show the validity and feasibility of the proposed method.

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“…(9). The total emission cost decreased to 0.20012 t/h (43.89%) in Case 3 in comparison to 0.365141 t/h in Case 1.…”

Section: Case 3: Emission Minimizationmentioning

confidence: 80%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A new technique for solving the multi-objective optimization problem using hybrid approach

2014

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“…A new disjunctive formulation, hopefully tighter than the standard one, and requiring additional continuous variables, was considered in [4]. Each flow is rewritten by using two positive flow variables, as follows:…”

Section: Improved Disjunctive Formulationmentioning

confidence: 99%

“…In general, the transmission expansion planning problem is solved in two variants, considering or not generation redispatch; see [4,14,16]. The case without redispatch requires the planned transmission network to operate correctly for a given set of generation values, computed a priori for each generation plant.…”

Section: Introductionmentioning

confidence: 99%

Transmission expansion planning with re-design

2010

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Expanding an electrical transmission network requires heavy investments that need to be carefully planned, often at a regional or national level. We study relevant theoretical and practical aspects of transmission expansion planning, set as a bilinear programming problem with mixed 0-1 variables. We show that the problem is NP-hard and that, unlike the so-called Network Design Problem, a transmission network may become more efficient after cutting-off some of its circuits. For this reason, we introduce a new model that, rather than just adding capacity to the existing network, also allows for the network to be re-designed when it is expanded. We then turn into different reformulations of the problem, that replace the bilinear constraints by using a "big-M" approach. We show that computing the minimal values for the "big-M" coefficients involves finding the shortest and longest paths between two buses. We assess our theoretical results by making a thorough computational study on real electrical networks. The comparison of various models and reformulations shows that our new model, allowing for re-design, can lead to sensible cost reductions.

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2016

Power System Optimization

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A mixed integer disjunctive model for transmission network expansion

Cited by 268 publications

References 5 publications

A new technique for solving the multi-objective optimization problem using hybrid approach

A new technique for solving the multi-objective optimization problem using hybrid approach

Transmission expansion planning with re-design

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