Dynamic Energy Management for Smart-Grid-Powered Coordinated Multipoint Systems

Xin Wang; Yu Zhang; Tianyi Chen; Georgios B. Giannakis

doi:10.1109/JSAC.2016.2520220

Dynamic Energy Management for Smart-Grid-Powered Coordinated Multipoint Systems

Xin Wang, Yu Zhang, Tianyi Chen, Georgios B. Giannakis

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

49 Scopus citations

Abstract

Due to increasing threats of global warming and climate change concerns, green wireless communications have recently drawn intense attention toward reducing carbon emissions. Aligned with this goal, the present paper deals with dynamic energy management for smart-grid powered coordinated multipoint (CoMP) transmissions. To address the intrinsic variability of renewable energy sources, a novel energy transaction mechanism is introduced for grid-connected base stations that are also equipped with an energy storage unit. Aiming to minimize the expected energy transaction cost while guaranteeing the worst-case users' quality of service, an infinite-horizon optimization problem is formulated to obtain the optimal downlink transmit beamformers that are robust to channel uncertainties. Capitalizing on the virtual-queue-based relaxation technique and the stochastic dual-subgradient method, an efficient online algorithm is developed yielding a feasible and asymptotically optimal solution. Numerical tests with synthetic and real data corroborate the analytical performance claims and highlight the merits of the novel approach.

Original language	English (US)
Article number	7389362
Pages (from-to)	1348-1359
Number of pages	12
Journal	IEEE Journal on Selected Areas in Communications
Volume	34
Issue number	5
DOIs	https://doi.org/10.1109/JSAC.2016.2520220
State	Published - May 2016

Bibliographical note

Funding Information:
This work was supported by the China Recruitment Program of Global Young Experts, the Program for New Century Excellent Talents in University, the Innovation Program of ShanghaiMunicipal Education Commission, the National Science and Technology Major Project of the Ministry of Science and Technology of China under Grant 2012ZX03001013; and by the U.S. NSF under Grant 1509040, Grant 1508993, Grant 1442686, Grant 1423316, and Grant 1343248.

Publisher Copyright:
© 2016 IEEE.

Keywords

Co MP systems
Lyapunov optimization
downlink beamforming
high-penetration renewables
smart grids
stochastic optimization

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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abstract = "Due to increasing threats of global warming and climate change concerns, green wireless communications have recently drawn intense attention toward reducing carbon emissions. Aligned with this goal, the present paper deals with dynamic energy management for smart-grid powered coordinated multipoint (CoMP) transmissions. To address the intrinsic variability of renewable energy sources, a novel energy transaction mechanism is introduced for grid-connected base stations that are also equipped with an energy storage unit. Aiming to minimize the expected energy transaction cost while guaranteeing the worst-case users' quality of service, an infinite-horizon optimization problem is formulated to obtain the optimal downlink transmit beamformers that are robust to channel uncertainties. Capitalizing on the virtual-queue-based relaxation technique and the stochastic dual-subgradient method, an efficient online algorithm is developed yielding a feasible and asymptotically optimal solution. Numerical tests with synthetic and real data corroborate the analytical performance claims and highlight the merits of the novel approach.",

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Dynamic Energy Management for Smart-Grid-Powered Coordinated Multipoint Systems

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Bibliographical note

Keywords

UN SDGs

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