Restoration of power network - a bibliographic survey

Sudhakar, T. D.; Srinivas, K.N.

doi:10.1002/etep.467

Cited by 32 publications

(21 citation statements)

References 82 publications

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“…In part, this assumption is justified by the fact that in emergency situations the operational requirements of the network are not strictly the same as in normal operation. Thus, some constraints such as voltage levels and overloads may be relaxed during the restoration process [5].…”

Section: B Restoration Constraintsmentioning

confidence: 99%

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Multiobjective MILP model for optimal allocation of automated switching devices in electric power distribution systems

Ferreira

Gazzana²,

Bretãs

et al. 2015

2015 IEEE Eindhoven PowerTech

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This paper presents an analytical mixed-integer linear programming model to improve reliability of distribution networks through the optimal allocation of automated switching devices. Optimal reliability is formulated as a multi-objective problem of minimizing customers' interruptions and the investment costs related to devices' acquisition, relocation and operation. In order to establish the optimal trade-off between these conflicting objectives the Goal Programming approach is proposed. The presented model considers post-fault restoration constraints which limit load transfers and thereby the system reconfiguration capability. Restoration feasibility is ensured by a linear formulation of power flow equations as functions of geographical locations of automated switching devices in the feeder. Therefore, the model's solutions provide a more effective and economic application of automated switching devices, so that voltage and system capacity constraints are taken into account in selecting optimal locations of devices. The proposed methodology was validated using the IEEE 123-bus test feeder.Index Terms--Allocation of automated switching devices, Distribution systems reliability, Load restoration, Mixed-integer linear programming.I.

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Section: B Restoration Constraintsmentioning

confidence: 99%

“…Designing a flexible distribution network that is able to self-heal is accomplished by a suitable restoration planning [5]. It includes selecting number and locations of ASDs to be installed along the network, so that restoration of out-ofservice loads is carried out with a minimum load shedding.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective MILP model for optimal allocation of automated switching devices in electric power distribution systems

Ferreira

Gazzana²,

Bretãs

et al. 2015

2015 IEEE Eindhoven PowerTech

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“…Power system restoration after a complete or partial blackout is becoming much more important because of the increasing demand of customers for reliable power supply. 1,2 The restoration decision making is a multiobjective, multistage, multiconstraint, highly complex optimization problem, according to the system characteristics and tasks of different restoration stages. The restoration process can be generally divided into 3 stages-black start, network reconfiguration, and full load restoration.…”

Section: Introductionmentioning

confidence: 99%

Decision-making optimization of power system extended black-start coordinating unit restoration with load restoration

Wang

Zhou

et al. 2017

Int Trans Electr Energ Syst

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Summary The extended black‐start strategy is new exploration for black‐start restoration of power systems, in which more than one non–black‐start unit can be restored simultaneously during the black‐start stage. This paper presents a multiobjective optimization method coordinating unit restarting with load restoration for extended black‐start decision making. The objective functions of the black‐start restoration optimization are defined as restoring non–black‐start units and unserved loads as much as possible under steady‐state and transient system operation constraints. A hybrid algorithm combining the lexicographic method with the improved bacterial foraging algorithm is used to solve the defined optimization model. The proposed method has been tested on the IEEE 118‐bus system and the southern Hebei power system of China, and the test results verify the effectiveness of the proposed decision‐making method.

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“…Evolutionary algorithms (EAs) have been used extensively for solving multi-objective optimization problems in several areas [6,16] and in particular obtaining the Paretooptimal solutions for DSR problems [9].…”

Section: Introductionmentioning

confidence: 99%

A Self-Adaptive Multi-Resources Suppliers System

2017

IJCSI

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Dealing with a suppliers/demands system with functional transportation cost is usually considered as a classical transportation problem and can be solved with normal linear programming processes, but what adds to it, when the cost in the supply points is to be taken into consideration, demands at each demand point varies with time, and complexity of the whole system grows. Furthermore, introducing a constant cost to services and/or transportations, which is the case in several real distributed systems, makes the model more sophisticated to be solved. In this case, additional measures prevent us from treating the model as a classical transportation problem; instead, we have to search another technique to grant satisfactory results. This paper proposes an approach that enables a system to autoreconfigure itself at runtime whenever environmental variables vary, with the goal of minimizing costs while satisfying the demands, while taking into consideration the different type of costs (constant/functional, service/transportation, etc.). Furthermore, this work aims to build a framework to find the optimal configuration of services/transportations in a multiresources suppliers system requiring an auto adaptation facing the variation of demands. Our proposed framework, called GATRA, is a combination of the Genetic Algorithms and the Transportation problem techniques.

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Restoration of power network - a bibliographic survey

Cited by 32 publications

References 82 publications

Multiobjective MILP model for optimal allocation of automated switching devices in electric power distribution systems

Multiobjective MILP model for optimal allocation of automated switching devices in electric power distribution systems

Decision-making optimization of power system extended black-start coordinating unit restoration with load restoration

A Self-Adaptive Multi-Resources Suppliers System

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