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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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Subject: search.filters.subject.Energy storage system

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Now showing 1 - 3 of 3
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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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    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.