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Research Publications (Engineering and Built Environment)

Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/215

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Author: search.filters.author.Khumalo, PhilaniSubject: search.filters.subject.Smart grid

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    A lightweight based data aggregation scheme for smart grid power systems
    (2022-08-20) Khumalo, Philani; Nleya, Bakhe
    To accomplish data aggregation securely and efficiently, it is necessary to design a scheme that is low in both computational as well as communication overheads. Thus in this paper, we propose and analyze a novel secured data aggregation scheme that ensures both privacy preservation as well as data integrity. The scheme is centered on forecasting power consumption demands for a particular neighborhood, and overall, because most attacks occur, during the transmission of data across the ICT subsystem, it thus focuses on limiting that. It does so by first forecasting its demands, and only links with the utility operator when adjustments have become necessary. The scheme utilizes a lightweight efficient noninteractive authentication mechanism in the generation and sharing of session keys. Overall, both the security analysis and performance evaluation demonstrate its efficacy in guaranteeing both privacy and security in addition to minimizing computational and communication overheads.
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    Balancing between demand and trading in microgrids
    (IEEE, 2020-01) Gomba, Masimba; Chidzonga, Richard; Nleya, Bakhe; Khumalo, Philani
    The envisaged future generation power or smart grid (SG) will incorporate ICT technologies as well as innovative ideas for advanced integrated and automated power systems. The bidirectional information and energy flows within the envisaged advanced SG together with other aiding devices and objects, promote a new vision to energy supply and demand response. Meanwhile, the gradual shift to the next generation fully fledged SGs will be preceded by individual isolated microgrids voluntarily collaborating in the managing of all the available energy resources within their control to optimally serve both demand and distribution. In so doing, innovative applications will emerge that will bring numerous benefits as well as challenges in the SG. This paper introduces a power management approach that is geared towards optimizing power distribution, trading, as well as storage among cooperative microgrids (MGs). The initial task is to formulate the problem as a convex optimization problem and ultimately decompose it into a formulation that jointly considers user utility as well as factors such as MG load variance and associated transmission costs. It is deduced from obtained analytical results that the formulated generic optimization algorithm characterizing both aggregated demand and response from the cooperative microgrids assist greatly in determining the required resources hence enabling operational cost viability of the entire system.