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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.Chidzonga, Richard

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Now showing 1 - 6 of 6
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    Power demand and supply optimization in islanded microgrids with distributed generation
    (IEEE, 2022-01-25) Chidzonga, Richard; Nleya, Bakhe; Khumalo, Philani
    In the power sector, a shift from the present fossildominated generation to renewable as well as energy-efficient generation and distribution is firmly underway. The transition is mostly driven by the digitalization of the energy systems to what has been coined ENERNET meaning energy network. Numerous benefits for both utility and consumers accrue. Digitalization enables more activity in the power trading market and a large amount of consumer data becomes available in the sector. Overall, strides are being made in the integration of Demand-Side Management (DSM) in the planning of Isolated/Islanded Microgrids (IMGs) as these will potentially reduce total OPEX costs at both customer and utility levels as well as increase renewable energy utilization. However, there is paucity in literature regarding distributed generators (DGs) non-convex cost function. Notably, not much has been covered regarding microgrid optimal load-dispatching especially with regards to optimizing algorithms. In this paper, we focus on formulating the day-ahead dispatch problem of microgrids with DGs subject to non-convex cost function and load dynamics. We first propose an operational framework that addresses the DG's 'valve point' loading effect as well as optimizing its performance. The impact of DSM on convex and non-convex EMS problems with different load participation levels is investigated. Further, the day-ahead scheduling horizon of fifteen-minute resolution time is considered to examine the effect of load dynamics in the microgrid. A Quantum Particle Swarm based approach is employed to solve non-convex DGs cost optimization. It is demonstrated that the proposed algorithm efficiently solves the non-convex EMS problem. Simulation results yield a 5% reduction in OPEX costs without compromising customer satisfaction.
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    An energy efficient resources allocation scheme for flexible translucent optical transport networks
    (Psychology and Education, 2021-03-02) Nleya, Bakhe; Molefe, Mlungisi; Chidzonga, Richard
    The present study attempts to explore how academic streams and learning styles play role in the preferences of coping strategies among prospective teachers. A quantitative approach was selected to explore the relationship. A survey was conducted with 300 prospective teachers (150 of science stream and 150 of humanities stream). A multi-stage random sampling technique was used to collect relevant information. Research instrument to measure coping strategies was developed by the researcher himself and Learning Style Inventory (LSI) by Ritu Dangwal & Sugata Mitra, 1997 was used to measure learning styles of prospective teachers. Statistical techniques i.e. mean, S.D., multivariate ANOVA were applied. Results revealed an essential significant effect of academic streams and learning styles on preference of coping strategies among prospective teachers. It is recommended that teacher training institutions should establish guidance or counseling centers to provide counseling to prospective teachers regarding coping skills and learning styles
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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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    On demand and supply management in domestic microgrids
    (Turkish Online Journal of Qualitative Inquiry (TOJQI), 2021-12-01) Chidzonga, Richard; Nleya, Bakhe; NLEYA
    Standalone or residential microgrids (MG) are becoming increasingly common. Their success is premised on optimal operational strategies like demand side management (DSM). It is not uncommon in optimization problems to deal with competing objectives in the context of multi-objective optimization. In a domestic MG, optimization objectives may encompass minimization of OPEX, maximization of consumers’ utility, and minimization of CO2 emissions etc. This article employs a technique which transforms a bi-objective energy optimization problem into a single objective problem, then solving the problem using the heuristic technique of binary particle swarm optimization (B PSO). The random phenomena associated with the statistical load profiles and multiple renewable energy sources (RESs) are modelled using established statistical approaches. Results obtained using simulation show that the pro-posed model can minimize the OPEX of isolated MG whilst simultaneously meeting the utility expectations of the consumer.
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    Quality of transmsision aware routing and wavelength assignment algorithm for blocking minimization in translucent optical networks
    (IEEE, 2020-08) Khumalo, Philani; Nleya, Bakhe; Mutsvangwa, Andrew; Chidzonga, Richard
    In Optical Transport networks, the optical reach is defined as the maximum distance (number of hops) a lightpath connection can span before the intelligence of the sig-nal it is carrying to unrecoverable state as a result of the degra-dation in the signal to noise power ratios. When the signal to noise ratio has degraded below a certain acceptable threshold, regeneration is necessary. Optical Transport networks will nor-mally incorporate optical repeaters throughout to facilitate sig-nal reach for all the lightpath connection establishments. Such networks are classified as being Translucent. The role of the sparsely spaced optical repeaters is to refresh the degraded op-tical signals so that an acceptable quality of transmission (QoT) can be guaranteed by the network operator. The deployment of such units where necessary throughout the network leads to an escalation to both capital as well as operational expenditures. It is however necessary that network designers strike a balance be-tween the network operating costs versus renderable quality of service (QoS) to end users. In light of this challenge, in this pa-per we propose and analyze a QoT-Aware routing and wave-length assignment algorithm (QARWA) that seeks to minimize blocking of data bursts traversing the network. The QoT block-ing considers the effects of various linear as well as nonlinear impairments. The proposed model can be infused with other al-gorithms that attempt to calculate wavelength blocking per route and also per available layer. We also further enhance the same algorithm’s efficacy by introducing its QoT aware guar-anteed RWA (QGRWA) equivalent. The novelty of the scheme is in taking into account physical layer impairments, as well as signal quality when computing candidate routes for a given source to destination pair. The proposed algorithm’s overall promising performance is validated via analytical and simula-tion means.
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    Energy demand and trading optimization in isolated microgrids
    (IEEE, 2020-04-30) Chidzonga, Richard; Gomba, Masimba; Nleya, Bakhe
    Future generation 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 achieve optimality in 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 overall demand and response by the cooperative microgrids assist greatly in determining the required resources hence leading to cost effectiveness of the entire system.