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    Loss Sensitivity and Voltage Deviation Index Based Intelligent Technique for Optimal Placement and Operation of Distributed Generators

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    Date
    2019-04-09
    Author
    Bhatt, D.V.;
    Bhatt, Y.H.;
    Pakka, V. H.
    Metadata
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    Abstract
    Distribution system is the crucial part of the power system which needs to be monitored for quality since it is the last stage in delivering electricity to consumers. The main aim of suppliers is therefore to maintain excellent quality of supply with minimal support at the network level. This includes dealing with issues around voltage regulation and minimization of real power losses on the network which are reflected in a uniform voltage profile through various load points on the feeders. However, with increase in decentralization, Distributed Generation (DG) becomes the focal point of distribution networks and can be used to achieve the above mentioned objectives. DGs are used in this paper to minimize the losses along with an improvement in the voltage profile. The location of these DG units on the network is addressed as an optimization problem using the loss sensitivity index and voltage deviation index. The size of power injected by DG units is obtained with using an intelligent approach that combines Genetic Algorithm (GA) with neural networks. Different cases of DG in terms of real and reactive power injected are considered resulting in an improvement in voltage profile. The loss sensitivity and voltage deviation indices show the best result for the location of DG needed to minimize the power loss along with improvement in voltage regulation. This approach is tested on a 13-bus distribution network with different types of loads placed throughout the feeder.
    Description
    The Publisher's final version can be found by following the DOI link.
    Citation : Bhatt, D.V., Bhatt, Y.H., and Pakka, V.H. (2019) Loss Sensitivity and Voltage Deviation Index Based Intelligent Technique for Optimal Placement and Operation of Distributed Generators. Proceedings of 2018 IEEE 7th International Conference on Power and Energy (PECon), Kuala Lumpur, Malaysia, 2018, pp. 310-315.
    URI
    https://ieeexplore.ieee.org/document/8684177
    https://www.dora.dmu.ac.uk/handle/2086/17811
    DOI
    https://doi.org/10.1109/PECON.2018.8684177
    ISBN : 9781538654316
    Research Institute : Institute of Energy and Sustainable Development (IESD)
    Peer Reviewed : Yes
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    • School of Engineering and Sustainable Development [1941]

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