Power system transmission network expansion planning using AC model

Univ. of Campinas, Campinas
IET Generation Transmission & Distribution (Impact Factor: 1.31). 10/2007; 1(5):731 - 742. DOI: 10.1049/iet-gtd:20060465
Source: IEEE Xplore

ABSTRACT An optimisation technique to solve transmission network expansion planning problem, using the AC model, is presented. This is a very complex mixed integer nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. An interior point method is employed to solve nonlinear programming problems during the solution steps of the algorithm. Results of the tests, carried out with three electrical energy systems, show the capabilities of the method and also the viability of using the AC model to solve the problem.

    • "Such approaches include, among others, multistage dynamic planning [7] [8] [9], demand uncertainty [10] [11] [12], and the inclusion of security constraints (N À 1 criterion) [9,13–15]. Solutions for these mathematical models have been proposed in the literature using different optimization techniques such as metaheuristics [7,16–20], and mathematical programming, [4] [6] [15] [21] [22]. Despite of the great number of model adaptations and solution approaches applied to the TEP problem, there is not reference in 0142-0615/Ó 2015 Elsevier Ltd. "
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    ABSTRACT: Transmission expansion planning (TEP) is a classic problem in electric power systems. In current optimization models used to approach the TEP problem, new transmission lines and two-winding transformers are commonly used as the only candidate solutions. However, in practice, planners have resorted to non-conventional solutions such as network reconfiguration and/or repowering of existing network assets (lines or transformers). These types of non-conventional solutions are currently not included in the classic mathematical models of the TEP problem. This paper presents the modeling of necessary equations, using linear expressions, in order to include non-conventional candidate solutions in the disjunctive linear model of the TEP problem. The resulting model is a mixed integer linear programming problem, which guarantees convergence to the optimal solution by means of available classical optimization tools. The proposed model is implemented in the AMPL modeling language and is solved using CPLEX optimizer. The Garver test system, IEEE 24-busbar system, and a Colombian system are used to demonstrate that the utilization of non-conventional candidate solutions can reduce investment costs of the TEP problem.
    International Journal of Electrical Power & Energy Systems 07/2015; 69:213-221. DOI:10.1016/j.ijepes.2015.01.008 · 3.43 Impact Factor
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    • "Given the computational complexity of modelling AC power flow a linear direct current (DC) approximation model is usually sufficient for the purposes of long term expansion network planning. However, recent research has also considered AC power models [15] [19]. An extension to the disjunctive TEP formulation that considers the location of ESS is developed by Hu et. "
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    ABSTRACT: In electricity transmission networks, energy storage systems (ESS) provide a means of upgrade deferral by smoothing supply and matching demand. We develop a mixed integer programming (MIP) extension to the transmission network expansion planning (TEP) problem that considers the installation and operation of ESS as well as additional circuits. The model is demonstrated on the well known Garver's 6-bus and IEEE 25-bus test circuits for two 24 hour operating scenarios; a short peak, and a long peak. We show optimal location and capacity of storage is sensitive not only to cost, but also variability of demand in the network.
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    • "The typical AC power flow formulation can be found in [10]. During the formulation of the problem, the number of circuits added in branch ij, and PG (the resizing value of the generation units) are considered as the most important decision variables. "
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    ABSTRACT: This work proposes a method based on a mixed integer nonlinear non-convex programming model to solve the multistage transmission expansion planning (TEP). A metaheuristic algorithm by the means of differential evolution algorithm (DEA) is employed as an optimization tool. An AC load flow model is used in solving the multistage TEP problem, The proposed technique is tested on the Colombian 93 bus system and has shown high capability in considering the active and reactive power in the same manner and solving the TEP problem. The method produced improved good results in a faster convergence time for the test systems.
    3rd IET International Conference on Clean Energy and Technology (CEAT) 2014, Kuching, Malaysia; 11/2014
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