Joint Demand-Side Management in Smart Grid for Green Collaborative Mobile Operators Under Dynamic Pricing and Fairness Setup

被引:36
作者
Ghazzai, Hakim [1 ]
Kadri, Abdullah [1 ]
机构
[1] Qatar Univ, Qatar Mobil Innovat Ctr, Doha 2713, Qatar
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2017年 / 1卷 / 01期
关键词
Demand-side management; collaborative mobile operators; dynamic pricing; green heterogeneous networks; smart grid;
D O I
10.1109/TGCN.2016.2646818
中图分类号
TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构];
摘要
In this paper, the interactions between multiple mobile operators, owning heterogeneous cellular networks, and energy retailers existing in the smart grid are investigated. Energy procurement decisions of the cellular networks sharing common energy sources are jointly optimized while considering both dynamic energy pricing and varying pollution levels of energy sources. The objective is to enable collaboration among mobile operators in their demand-side management (DSM) to achieve economical and environmental goals. This is performed by solving a unified optimization problem aiming at maximizing a metric based on mobile operators' profits while limiting the amount of carbon dioxide (CO2) emitted by all networks. In this paper, three utility metrics, namely, Sum, Max-min, and Proportional Fair utilities, are considered to reflect the degree of fairness among mobile operators in the optimized DSM. Closed-form expressions of the optimal procured energy from each retailer used to power the marcocell and active small cell base stations (BSs) are derived for pricing profiles and utility metrics. Furthermore, the BS sleeping strategy is applied, in a centralized or a decentralized manner, in order to reduce the network energy consumption during low traffic periods. Finally, the impact of renewable energy generation uncertainty on the energy procurement decision is examined. The behavior of the different actors in the energy procurement decision is investigated through simulations. Results show that significant CO2 emissions reduction can be achieved thanks to the optimized DSM and the BS sleeping strategy.
引用
收藏
页码:74 / 88
页数:15
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