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Faculty of Engineering and Built Environment

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Now showing 1 - 7 of 7
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    Towards a hierarchical and distributed power management framework for SGs
    (IEEE, 2023-11-16) Nleya, Bakhe; Shezi, Nokwanda
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    A D2D communication based lightweight customer side data securing scheme in smart grids
    (2022-08-20) Nleya, Bakhe; Khumalo, Phlani
    With the emergence of modernized power grids into smart equivalents referred to as smart grids (SGs) the bulk generation, transmission, distribution, and end-user infrastructures must be appropriately long-term planned concurrently with the required privacy and security. Notably, the objectives of modern SGs are to minimize power energy losses through theft or physical dissipation. The embedded device-to-device (D2D) communication technology in 5G networks will enable an affordable fail-safe ICT subsystem platform for the SGs. However, Privacy preservation is necessary for D2D services in SGs. In this paper, we propose an anonymity privacy-preserving, and data aggregation scheme. We carry out both security and performance and obtained theoretical analysis and simulation results the privacy algorithm is effective and at the same time, fewer communication overheads are exchanged.
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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.
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    Optimal allocation and control of EV energy storage in microgrids
    (Karadeniz Technical University, 2021-04-28) Nleya, Bakhe
    Next Generation smart grid (SG) systems blend legacy power system networks and the latest state-of-the-art ICT technologies to ensure the efficiency, robustness as well as reliability of the former (power systems). The duplex flow of both information and energy enhances energy supply and de-mand response, as well as SG-related innovative business-oriented applications and services. Renewable generators (RGs) and Electric Vehicles (EVs) are becoming prominent in any SG setup as they promote environmental friendliness. The presence of both necessitates the optimal allocation of dis-tributed renewable generation (DRG) and energy storage sys-tems (ESS) at both SG and microgrid (MG) levels. In that way, grid stability will be always ensured. The paper describes and discusses an optimized ESS deployment approach for serving EVs (as they are one of the largest consumers of stored energy) and DRGs. Careful consideration of the state of the ESS is also considered by developing and applying a dynamic capacity adjustment algorithm to deal with the none-smooth cost func-tions. The proposed cost function takes into consideration the operation as well as investment cost minimization concurrently. The matrix real-coded genetic algorithm (MRCGA) is used to minimize the cost function of the system while constraining it to meet the customer demand, as well as the security of the system overall. The computational simulation results are presented to verify the effectiveness of the proposed method. The electricity network model is simplified using a virtual subnode concept to alleviate the computational load burden of a node's agent. Simulation results demonstrate the feasibility and stability of this dispatch strategy. Overall, our proposed framework and obtained results set a benchmark for the realization of agent-based coordination algorithms to solve the optimal dispatch problem
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    Power planning for a smart integrated African super-grid
    (IEEE, 2022-01-25) Ndlela, Nomihla Wandile; Davidson, Innocent E.
    Africa's population has increased sharply from 364 million in 1970 to 1.3 billion in 2020 and is expected to reach 2.0 billion by 2050, representing the world's largest labor pool. Rapid growth in African population, generation capacity constraints, belated investment in new electricity infrastructure, load growth in unplanned areas, poor maintenance of existing power assets are some of Africa's critical challenges. These have resulted in demand outstripping available power generation capacity, leading to electricity shortages, load shedding, a huge backlog of unserved customers, and low economic growth. This paper presents the concept of a Smart Integrated African Super Grid, designed to energize Africa's emerging economy. In this paper, the five African Power pools are discussed, and the schemes for harnessing Africa's untapped renewable energy resources. A methodology is proposed to use highly complex power system controllers to integrate the African power pools, into a super-grid that absorbs large penetration of renewable powers using dispersed interconnected low voltage micro-grids, without compromising on power quality, stability, technical loss reduction, sustainability, and system reliability.
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    A smart grid based algorithm for improving energy efficiency of large scale cooperating distributed systems
    (IEEE, 2016) Nleya, Bakhe; Mutsvangwa, Andrew; Dewa, Mendon
    A smart grid (SG) is a sophisticatedly integrated hybrid power generating system which allows bidirectional energy as well as management data exchanges. In this paper we look at improving energy efficiency in large scale cooperating power consuming as well as power generating systems. We discuss a clustered as well as hierarchical power scheduling algorithms that are geared towards optimizing the management of power tariffs, storage and distribution in a cooperative environment. From a generation perspective, solar intensity prediction is proposed for power generation forecasting and whereas from a power consumption perspective, we evaluate and model the power consumed by these distributed systems (consumers) and propose improving resource allocation, scheduling and network traffic management so as to make network and computing resources more power efficient.