Cost Optimal Hybrid Communication Model for Smart Distribution Grid
There have been significant changes and dynamic growth in power grids since the inception of the smart grid. To ensure a self-sustainable grid, the power grid should facilitate the real-time sharing of the dynamic attributes of the power grid between the spatially distributed power grid elements. Th...
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Veröffentlicht in: | IEEE transactions on smart grid 2022-11, Vol.13 (6), p.4931-4942 |
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Sprache: | eng |
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Zusammenfassung: | There have been significant changes and dynamic growth in power grids since the inception of the smart grid. To ensure a self-sustainable grid, the power grid should facilitate the real-time sharing of the dynamic attributes of the power grid between the spatially distributed power grid elements. This demands a flawless design of the overlay communication network for a smart grid. However, instrumenting the entire grid with intelligent communication devices would be prohibitively expensive. A cost-optimal model is necessary to select the actual cardinality of intelligent communication devices required for the data transmission by ensuring its Quality of Service (QoS) metrics. This research work presents a smart distribution grid architecture with a network of microgrids and details the need for hybrid communication for intra-microgrid communication. A cost-optimal model is proposed to offer an optimal combination of technologies for intelligent devices in the hybrid communication overlay network. The formulation considers QoS metrics such as data packet latency, bandwidth requirement, link reliability, packet drops, and communication range of the technology to derive a cost-optimal solution. Based on this model, a Recursive Algorithm for Cost Optimal Combination of Communication Technology (RACOCCT) for a power grid topology is presented in this work. The simulation study performed on selected power grid topology based on the Standard IEEE 33 bus network reveals the cost-optimal combination of hybrid wireless communication technologies for the varying probability of link unreliability. |
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ISSN: | 1949-3053 1949-3061 |
DOI: | 10.1109/TSG.2022.3185740 |