A New Distribution System Reconfiguration Approach Using Optimum Power Flow and Sensitivity Analysis for Loss Reduction

Gomes, Felipe V.; Carneiro, S.; Pereira, J.L.R.; Vinagre, M.P.; Garcia, P.A.N.; Araujo, Leandro Ramos de

doi:10.1109/tpwrs.2006.879290

Cited by 173 publications

(118 citation statements)

References 18 publications

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“…In this Reference [25], the voltage profile has not been reported. The comparison can be observed in Table I, which has been extracted from Reference [25]. To this table has been added the execution time of the methodology proposed in this paper.…”

Section: Examplementioning

confidence: 99%

“…In References [25] and [36] the load conditions of the test case are 5058.25 kW and 2547.32 kvar, which are different from the original values of the Reference [7], from where the test case has been extracted. In this case, the initial losses are 202.68 kW.…”

Section: Examplementioning

confidence: 99%

“…Gomes et al [25] have elaborated a methodology and compared their method with References [4,35,36] and [37]. In this Reference [25], the voltage profile has not been reported. The comparison can be observed in Table I, which has been extracted from Reference [25].…”

Section: Examplementioning

confidence: 99%

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Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

Khodr¹,

Martínez-Crespo

Vale³

et al. 2009

Int Trans Elec Energy Syst

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SUMMARYThis paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.Supporting information may be found in the online version of this article.

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Section: Examplementioning

confidence: 99%

Section: Examplementioning

confidence: 99%

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Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

Khodr¹,

Martínez-Crespo

Vale³

et al. 2009

Int Trans Elec Energy Syst

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“…The thermal limit constraint of distribution lines and cables is guaranteed by (4). Radiality of the reconfigured system is preserved by satisfying (6).…”

Section: A Mip-based Dsrmentioning

confidence: 99%

Robust Reconfiguration of A Distribution System

Moradzadeh

Liu

Tomsovic

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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Abstract-In this paper, a robust reconfiguration approach based on Mixed Integer Programming (MIP) is proposed to minimize loss in distribution systems. A Depth-First Search (DFS) algorithm to enumerate possible loops provides radiality constraint. This provides a general solution to the radiality constraint for distribution system reconfiguration/expansion problems. Still, imprecision and ambiguity in net loads, i.e. load minus renewable generation, due to lack of sufficient measurements and high utilization of demand response programs and renewable resources, creates challenges for effective reconfiguration. Deterministic optimization of reconfiguration may no lead to optimal/feasible results. Two methods to address these uncertainties are introduced in this paper: one, based on a stochastic MIP (SMIP) formulation and two, based on a fuzzy MIP (FMIP) formulation. Case studies demonstrate the robustness and efficiency of the proposed reconfiguration methods.

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“…The decision variables are tied to the state of switches. We use the binary code 0 (OFF) and 1 (ON) different from Gomes, F. V., et al [8] who use continuous functions. We apply this algorithm on IEEE 33 bus.…”

Section: Introductionmentioning

confidence: 99%

Optimal Reconfiguration of Power Distribution Systems Based on Symbiotic Organism Search Algorithm

Boum¹,

Ndjependa²,

Bisse³

2017

JPEE

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This paper presents a reconfiguration of electric power distribution network based on the symbiotic organism search algorithm (SOS). The goal here is to come out with an optimal reconfiguration of a power distribution network that minimises the active power losses for a good power flow. This method is applied to IEEE 33 bus and the results show a significant reduction of active power losses. The execution time for this algorithm is found to be smaller compared to other metaheuristic algorithms.

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A New Distribution System Reconfiguration Approach Using Optimum Power Flow and Sensitivity Analysis for Loss Reduction

Cited by 173 publications

References 18 publications

Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

Robust Reconfiguration of A Distribution System

Optimal Reconfiguration of Power Distribution Systems Based on Symbiotic Organism Search Algorithm

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