A new 0–1 integer programming method of feeder reconfiguration for loss minimization in distribution systems

Sarma, N.D.R.; Rao, K. Sambasiva

doi:10.1016/0378-7796(95)00934-a

Cited by 48 publications

(20 citation statements)

References 13 publications

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“…Moreover, Fig. 41 shows that the optimal configuration introduced by the proposed methodology and other models with the same switching scenario (7,13,34,39,42,55,62,72,83,86,89,90,92) enhances the voltage profile and therefore network power quality better than configurations proposed by other formulations of Table XI. These facts show higher efficiency of the proposed model compared to other methods for reconfiguration of the TPC system.…”

Section: K Case 11: Distribution Network Of Taiwan Power Company (Tpc)mentioning

confidence: 99%

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An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL

et al. 2021

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Distribution network is an essential part of electric power system, which however has higher power losses than transmission system. Distribution losses directly affect the operational cost of the system. Therefore, power loss reduction in distribution network is very important for distribution system users and connected customers. One of the commonly used ways for reducing losses is distribution system reconfiguration (DSR). In this process, configuration of distribution network changes by opening and closing sectional and tie switches in order to achieve the lowest level of power losses, while the network has to maintain its radial configuration and nodal voltage limits, and supply all connected loads. The DSR aiming loss reduction is a complex mixed-integer optimization problem with a quadratic term of power losses in the objective function and a set of linear and non-linear constraints. Accordingly, distribution network researchers have dedicated their efforts to developing efficient models and methodologies in order to find optimal solutions for loss reduction via DSR. In this paper, an efficient mathematical model for loss minimization in distribution network reconfiguration considering the system voltage profile is presented. The model can be solved by commercially available solvers. In the paper, the proposed model is applied to several test systems and real distribution networks showing its high efficiency and effectiveness for distribution systems reconfiguration.INDEX TERMS Efficient mathematical model, electric power distribution systems, loss reduction, network reconfiguration, voltage profile.

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Section: K Case 11: Distribution Network Of Taiwan Power Company (Tpc)mentioning

confidence: 99%

“…Sarma and Rao [13] introduced a new model for network reconfiguration, allocating distribution feeders to different circuits, by representing network losses in terms of circuits' currents. The status of each bus was defined by binary numbers, in which number 1 indicates connection between bus and related circuit.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL

et al. 2021

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“…In recent years, several studies have been implemented to investigate the DFR problem deeply. In [8], a new method based on integer programming is proposed to utilise the DFR strategy as a tool to reduce the total power losses. Similar study is implemented by ant colony algorithm in [9] to use the DFR and capacitor placement techniques for reducing the active power losses.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent stochastic framework to solve the reconfiguration problem from the reliability view

Kavousi‐Fard¹,

Niknam²,

Khooban³

2014

IET Science, Measurement & Technology

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This study proposes a new method to employ the distribution feeder reconfiguration as a reinforcement strategy to enhance the reliability of the distribution systems. Also, several wind power sources are considered to assess their effects on the reliability indices. In order to make the final results more dependable, a stochastic framework based on the probabilistic power flow is utilised to consider the uncertainty of forecast/measurement error of the active and reactive loads, failure rate, repair rate and output generation of wind units, concurrently. The objective functions to be investigated are (i) system average interruption frequency index, (ii) average energy not supplied, (iii) active power losses and (iv) total cost. Moreover, a new modified optimisation method based on harmony search algorithm is proposed to improve the total ability of the algorithm to explore the problem search space globally. The effectiveness and efficiency of the proposed method are examined through two radial distribution test systems.

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“…A great deal of work has been done on network reconfiguration (also known as feeder reconfiguration) in distribution systems mainly in the context of active power loss reduction because the cost of MW loss occupies considerable amount of operating cost in the system and therefore small amount achieved from loss reduction is still attractive for electric power utilities. A number of methods have been proposed to solve feeder reconfiguration for loss minimization, such as integer programming (Sarma & Prakasa Rao, 1995) and artificial neural network (Kashem et al, 1998) and simulated annealing (Chang & Kuo, 1994). The reconfiguration problem in this case are normally subject to power balance equations, bus voltage upper and lower limits, line carrying capability of the feeders and radial topology of the network.…”

Section: Introductionmentioning

confidence: 99%

Network Reconfiguration for Reliability Worth Enhancement in Distribution Systems by Simulated Annealing

Sirisumrannukul¹

2010

Simulated Annealing, Theory With Applications

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A new 0–1 integer programming method of feeder reconfiguration for loss minimization in distribution systems

Cited by 48 publications

References 13 publications

An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL

An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL

Intelligent stochastic framework to solve the reconfiguration problem from the reliability view

Network Reconfiguration for Reliability Worth Enhancement in Distribution Systems by Simulated Annealing

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