Journal
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 13, Issue 3, Pages 1471-1481Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2017.2681105
Keywords
Demand response (DR); dynamic programming (DP); evolved multimedia broadcast and multicast (eMBMS); greedy; 5G; multicast broadcast single frequency network (MBSFN); NP-complete; smart grids (SGs); radio resource management (RRM)
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Funding
- Basic Science Research Program through National Research Foundation of Korea - Ministry of Education [NRF-2016R1D1A1B03935633]
- National Research Foundation of Korea [2016R1D1A1B03935633] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Smart Grids (SGs) are emerging cyber-physical systems, equipped with sophisticated communication and information technologies, for efficient and large-scale power supply and management. SGs demand advanced communication technologies between energy providers and consumers, for enabling a control-feedback loop, by using time-dependent pricing. In this paper, we propose an efficient planning of 5G small cells, with evolved multimedia broadcast and multicast communication, between aggregators (small cells) and SG consumers, for efficient demand-response (DR) programs. After pointing out that optimal multicast scheduling and radio resource management problem is NP-complete, we propose two different solutions, based on dynamic programming (DP) and greedy heuristics, for minimizing the energy cost for DR customers. We also analyze the performance of SG user capacity for 5G single cell multicast and multicast broadcast single frequency network. Extensive OPNET simulation results, over actual energy data and real wireless trace, demonstrate that our proposed 5G small cell planning and multicast solutions are capable of reducing energy production cost by 30%, with up to 35% shift in peak energy load, low latency and packet drop.
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