Optimal reconfigurattion of distribution systems by considering switch and wind turbine placements to enhance reliability and efficiency

The continuous variation and dispersion of the load demand during a 24-h day are uncontrolled aspects that affect the efficiency, operational conditions, and total cost of the power distribution network. The cost of the network is strongly related to the peak of demand, but the available capacity of the network is not used efficiently during the day because feeders and branches usually work under 70% of their full capacity. In this way, it is necessary to measure how efficiently the distribution network capacity is used and to identify the aspects that can be modified to improve it. This article proposes a new exploitation capacity index to measure the efficiency of a/the whole distribution network throughout the day in relation to the total available capacity of the branches that compose the network. The paper presents the mathematical formulation and the validation process of the index, and then it provides a planning case study in which the index and the total cost of the planning problem are calculated and compared in four different scenarios in which the peak of the load demand changes. The results show a direct relation between the exploitation capacity and the peak of demand, so lower exploitation capacities are strongly related to higher peaks of demand. As for the capital investments for the network planning, it is found that higher peaks of demand involve more upgrade necessities and higher capital investments compared to the other cases.

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“…The active and reactive power supplied for the power substation (SS) are described by Equation (16) and Equation (17), respectively:…”

Section: Ssz=1mentioning

confidence: 99%

Low-Capacity Exploitation of Distribution Networks and Its Effect on the Planning of Distribution Networks

et al. 2020

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“…A further study is also proposed to investigate the effect of DER presence in the problem. In [23], by considering DERs an objective function is presented to enhance the reliability by minimising the expected customer interruption costs and the power losses. To solve the presented multi-objective problem, modified artificial bee colony (ABC) optimisation technique is used.…”

Section: Literature Surveymentioning

confidence: 99%

Co‐optimising distribution network adequacy and security by simultaneous utilisation of network reconfiguration and distributed energy resources

Ahmadi

Vahidinasab

Ghazizadeh

et al. 2019

IET Generation, Transmission & Distribution

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“…Optimal reconfiguration along with DG integration in the distribution system was presented in [48] using an evolutionary algorithm to minimise power loss and annual operational cost. Optimal placement of wind turbines and reconfiguration in the distribution system addressed in [49] using ABC. The objective function modelled as minimisation of power loss, voltage deviation index, switch cost and reliability cost.…”

Section: Introductionmentioning

confidence: 99%

“…This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/) have discussed distribution system analysis with DG and reconfiguration simultaneously [46][47][48][49]. Furthermore, many authors have used sensitivity methods [9,10,13,14,17,28,46] to find the location to install DG units.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the literature survey, it is noted that most of the researchers focused on DG integration only and ignored the impact of network reconfiguration [6–21, 25–34]. A few research studies have discussed distribution system analysis with DG and reconfiguration simultaneously [46–49]. Furthermore, many authors have used sensitivity methods [9, 10, 13, 14, 17, 28, 46] to find the location to install DG units.…”

Section: Introductionmentioning

confidence: 99%

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Optimal DG integration and network reconfiguration in microgrid system with realistic time varying load model using hybrid optimisation

Murty

Kumar

2019

IET Smart Grid

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The potential availability of renewable energy sources is unquestionable and the government is setting steep targets for renewable energy usage. Renewable-based DGs, reduce dependence on fossil fuels, mitigate global climate change, ensure energy security, and reduce emissions of CO 2 and other greenhouse gases. This study addresses microgrid system analysis with hybrid energy sources and reconfiguration simultaneously for efficient operation of the system. Microgrid zones are formulated categorically with the existing distribution system. In this study, wind, solar and small hydro-based DGs are considered. Uncertainties of renewable power generation and load are also taken care in the optimization problem. A multiobjective optimisation method proposed in this paper for optimal integration of renewable-based DGs and reconfiguration of the network to minimise power loss and maximise annual cost savings. Optimal location and sizes of DG units are determined using gravitational search algorithm and general algebraic modelling system respectively. Optimal reconfiguration of the microgrid system is obtained using genetic algorithm. Simulation results are obtained for the IEEE 33-bus system and compared with existing methods as available in the literature. Furthermore, this study has been carried out with a 24-hr time-varying distribution system. The simulation results show the efficiency and accuracy of the proposed technique.

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Optimal reconfigurattion of distribution systems by considering switch and wind turbine placements to enhance reliability and efficiency

Cited by 26 publications

References 27 publications

Low-Capacity Exploitation of Distribution Networks and Its Effect on the Planning of Distribution Networks

Low-Capacity Exploitation of Distribution Networks and Its Effect on the Planning of Distribution Networks

Co‐optimising distribution network adequacy and security by simultaneous utilisation of network reconfiguration and distributed energy resources

Optimal DG integration and network reconfiguration in microgrid system with realistic time varying load model using hybrid optimisation

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