New Multiobjective Tabu Search Algorithm for Fuzzy Optimal Planning of Power Distribution Systems

Ramírez-Rosado, I.J.; Domínguez-Navarro, José A.

doi:10.1109/tpwrs.2005.860946

Cited by 143 publications

(68 citation statements)

References 18 publications

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“…Equations (18) and (19) show that the active and reactive power flow is the sum of the discretised variables of the non-linear curve function. Equations (20) and (21) (22) shows the relationship between the apparent power supply, slope and discretised variables of the nonlinear curve function.…”

Section: List Of Symbolsmentioning

confidence: 99%

“…This heuristic based technique is derived from the annealing process, which usually involves reduction of the overall network capital cost of the system stepwisely, by removing the most capital cost effective branch, among the available set, as long as the feasible solution arrived at, satisfies the technical constraints and connectivity of the network. Other heuristic methods used are the Ant colony algorithm used in [18], the Tabusearch algorithm used in [19]and [20]. In [21] Artificial Neural Network (ANN) was used in addressing power quality problems prevalent in power distribution network.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and optimization of an electric power distribution network planning system using mixed binary integer programming

Ogunwolu¹,

Ero²,

Ibidapo-Obe³

2017

Nig. J. Tech.

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In this paper, the electric distribution network expansion planning problem (EDNEPP) was solved by a mixed binary integer programming (MBIP) formulation of the network, where the steady-state operation of the network was modelled with non-linear mathematical expressions. The non-linear terms are linearized, using piecewise linearization of the nonlinear expressions, so as to ensure the model computational compatibility with existing commercial optimization solvers. The linearized formulation is verified to ensure its solution optimality and degree of error deviation. The proposed network model formulation considers the alternatives of installation of new transformers of various capacities to reinforce already existing ones at substations of the network, choosing and construction of new substations given feasible locations, re-conductoring of existing feeders in the network, construction of new feeders given various conductor types alternatives, cost lost as a result of power interruption, and changes in the overall network topology. The cost of interruption would contain a cost term called 'cost of goodwill', which was brought into the model formulation, to measure the loss in confidence of consumers to distributors of power as a result of interrupted power supply, which is prevalent in developing nations. Two test systems of 23 and 54 nodes was used in showing the efficiency of the proposed network model formulation.

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Section: List Of Symbolsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and optimization of an electric power distribution network planning system using mixed binary integer programming

Ogunwolu¹,

Ero²,

Ibidapo-Obe³

2017

Nig. J. Tech.

View full text Add to dashboard Cite

show abstract

“…A new multi-objective Tabu search (NMTS) algorithm is proposed in [17]. The work in [17] is a development of the method presented in [24].…”

Section: B Phase 2: Optimization Algorithms Applied To Distribution mentioning

confidence: 99%

“…The work in [17] is a development of the method presented in [24]. Reference [24] applies a multiobjective fuzzy model for distribution network planning.…”

Section: B Phase 2: Optimization Algorithms Applied To Distribution mentioning

confidence: 99%

“…This NMTS algorithm determines the optimal solution for maximizing the network reliability at the lowest cost for a given level of risk. The main advantages of this search algorithm as stated in [17] are: (i) it obtains multi-objective non-dominated solutions to the three objective functions, (ii) it intensifies the search by ranking lists of the best network nodes of the distribution and stores visited network nodes avoiding unwanted movements, (iii) it diversifies the search to obtain a proper distribution of solutions. An immune-based evolutionary optimization algorithm proposed in [15] considers the uncertainties in the evolution of load and energy tax in each node in a time horizon.…”

Section: B Phase 2: Optimization Algorithms Applied To Distribution mentioning

confidence: 99%

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Regulation impact on distribution systems with distributed generation

Huang

Alvehag

Söder

2012

2012 9th International Conference on the European Energy Market

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Abstract-Distribution system operators (DSOs) are facing new challenges when more distributed generation (DG) is connected to the network. In this new operating environment the DSO has to be able to plan an efficient network topology, which consists of reinforcement and extensions. In addition, the DSO has to finance the investment from tariffs. The methods to solve network planning problems are reviewed in this paper. The studied network planning problem is the case when the DSO has no influence on the location of DG due to the unbundling between DSOs and production. Furthermore, the regulation for how the DSOs are allowed to design the tariffs in systems with DG vary between countries, a comparison of how the DSOs design their tariffs under different regulations is presented. This paper ends with a case study on methods that Swedish DSOs use to plan the networks when considering the uncertainties caused by wind power and the regulation impact on distribution network planning and network tariffs in Sweden.

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A hybrid heuristic and learning automata-based algorithm for distribution substations siting, sizing and defining the associated service areas

Mazhari

Monsef

Falaghi

2012

Int. Trans. Electr. Energ. Syst.

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This paper presents a new solution approach for optimal substation expansion planning (SEP) within electric power distribution networks. A modified fuzzy membership matrix as well as a memorable cost index vector is introduced to find the optimal substation service areas. Besides these, a Learning Automata-based algorithm is introduced for simultaneous determination of optimal service areas and capacities of the distribution substations. Electrical constraints such as voltage drops, power flow, radial flow constraints, as well as all prevalent cost indices are taken into consideration. The developed method is conducted to solve the distribution substation allocation problem for an actual distribution network with about 200 000 customers, and obtained results are compared to those of other methods. Detailed numerical results and comparisons presented in the paper show that the proposed solution approach could noticeably improve the quality of problem solutions with low computational burden and can be used as an effective tool for SEP in large distribution networks.

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New Multiobjective Tabu Search Algorithm for Fuzzy Optimal Planning of Power Distribution Systems

Cited by 143 publications

References 18 publications

Modeling and optimization of an electric power distribution network planning system using mixed binary integer programming

Modeling and optimization of an electric power distribution network planning system using mixed binary integer programming

Regulation impact on distribution systems with distributed generation

A hybrid heuristic and learning automata-based algorithm for distribution substations siting, sizing and defining the associated service areas

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