Nov 15, 2016 - The solar radiation variation during different portion of the day, and different season of ... saves a significant fraction of the total cost, compared.
Prospects of Green Cellular Base Stations in IoT-Enabled Smart and Connected Communities POPOOLA Segun Isaiah (160000343) M.Eng Information and Communication Engineering Covenant University Ota, Nigeria 15th November, 2016.
International Peer-Reviewed Journal Article Published by Springer
Faran Ahmed, Muhammad Naeem, and Muhammad Iqbal (2016). ICT and Renewable Energy: A Way Forward to the Next Generation Telecom Base Stations. Telecommunication Systems. DOI 10.1007/s11235-016-0156-4
Introduction • According to Cisco Visual Networking Index (2016), cellular networks support about 8 billion mobile users. • More than half a billion were added in 2015.
• With the advent of Internet of Things (IoT) and smart city applications
• At least 100 billion devices are expected to be connected, leading to an exponential increase in energy requirements.
Energy Issues in IoT Communication Network
• Cellular macro-base stations are integral parts of the communication network layer of IoT architecture. • As shown in Fig. 1, telecommunication industry made 31% contribution to carbon footprint in 2007. • In the third and fourth generation of cellular network (3G and 4G), base station accounts for 75-80% of the overall energy requirements (Hassan, Nuaymi, and Pelov, 2013).
Energy Issues in IoT Communication Network
Fig. 1: Percentage Contribution of ICT Sector to Carbon Footprint in 2007
Fig. 2: Proportion of Energy Sources in Electricity Generation
(Source: Ahmed, Naeem and Iqbal, 2016)
(Source: Ahmed et al., 2016)
Energy Issues in IoT Communication Network
•As of today, fossil fuels constitute about 80% of the energy generated to meet this energy demand (MacLean, 2008). •Meanwhile, over-dependence on fossil fuel is mainly responsible for the adverse climate change due to greenhouse gas emission, and the continuously rising financial burden that currently bedevil the world.
Renewable Energy in IoT Communication Network
•In order to combat these, cellular network technology need to embrace a green and sustainable approach for energy provision. •Unfortunately, renewable energy merely account for 5% of electricity generation worldwide. This is shown in Fig. 2.
Green Cellular Base Stations •Ahmed et al (2016) proposed a bidimensional approach: Innovation of SMART systems and processes; and Incorporation of renewable energy sources.
Green Cellular Base Stations •The SMART approach involves: • Standardization of energy measurement techniques; • Monitoring energy consumption; • Accounting for energy at every stage; • Rethinking innovation to reduce greenhouse emissions; and • Transformation of ICT sector into a low carbon technology.
Green Cellular Base Stations •On the other hand, the carbon footprint due to electricity consumption of cellular base stations can be effectively reduced by installing renewable energy sources on cell sites.
Case Study: Solar Power Systems for LTE Macro Base Stations • Zhang, Meo, Gerboni, and Marsan (2017) evaluated the costeffectiveness of powering LTE macro-base station using a PV solar systems, unreliable power grid, or a small diesel generator. • Related Works • Several works focused on the allocation of resources in a portion of a network comprising a few base stations, some of which are powered by renewable energy sources (Gong, Thompson, Zhou and Niu, 2014; Han and Ansari, 2013; Mereia, Berger and Sauer, 2013). • However, previous works do not consider in details: • How energy is captured from renewable energy sources (RES), stored and consume; • How RES can be combined with power grid use. • The solar radiation variation during different portion of the day, and different season of a year.
Case Study: Solar Power Systems for LTE Macro Base Stations • Literature Gap • However, previous works do not consider in details: • How energy is captured from renewable energy sources (RES), stored and consume; • How RES can be combined with power grid use. • The solar radiation variation during different portion of the day, and different season of a year.
Case Study: Solar Power Systems for LTE Macro Base Stations • Zhang, Meo, Gerboni, and Marsan (2017) evaluated the costeffectiveness of powering LTE macro-base station using a PV solar systems, unreliable power grid, or a small diesel generator.
• Methodology Mixed Integer Programming (MIP) optimization. Amount of energy produced was obtained using PVWatts. A heuristic algorithm was used to decrease the computational complexity of the optimization. A ten-year period was investigated for Torino (Europe), and Aswan (Africa).
Case Study: Solar Power Systems for LTE Macro Base Stations
Case Study: Solar Power Systems for LTE Macro Base Stations • Results A hybrid solar-grid (or solar-diesel) power system saves a significant fraction of the total cost, compared to a pure solar system, and to the traditional powergrid system. The developed heuristic algorithm can be used to obtain a solution within 10-20% of the optimum, at a computational speed 200 times faster than the MIP solution.
Challenges of Renewable Energy Harvesting and Storage • Energy harvested from solar and wind is unstable and unpredictable by nature. Therefore, maximum amount of energy should be harvested, and adequate provision should be made for efficient storage to support regulated reuse.
• Large number of solar panels (efficiency of commercial PV panels are about 15%) and large scale wind turbines are required to produce sufficient amount of energy. • Use of renewable energy in cellular base stations requires large scale storage.
Research Directions • Harvesting from other ambient energy sources like RF, vibrations, and thermal. • Wireless power transfer for energy sharing and energy harvesting. • High density low cost batteries for renewable energy applications. • Dynamic power allocation for maximizing throughput in energy-harvesting systems.
Research Directions • Renewable hybrid stand-alone telecommunication power system modeling and analysis. • Optimal adaptive modulation for QoS constrained wireless networks with renewable energy sources. • Optimal routing and scheduling in multihop wireless renewable energy networks.
References Andrea Zanella, Nicola Bui, Angelo Castellani, Lorenzo Vangelista, and Michele Zorzi, “Internet of Things for Smart Cities,” IEEE Internet Of Things Journal, Vol. 1, No. 1, February 2014, pp. 22-32. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2015-2020, White Paper, February 2016, pp. 1-39. Faran Ahmed, Muhammad Naeem, Muhammad Iqbal. ICT and Renewable Energy: A Way Forward to the Next Generation Telecom Base Stations. Telecommunication Systems. March, 2016. DOI 10.1007/s11235-016-0156-4 Hassan, H. A. H., Nuaymi, L., & Pelov, A. (2013). Classification of renewable energy scenarios and objectives for cellular networks. In IEEE 24th international symposium on personal indoor and mobile radio communications (PIMRC) 2013 (pp. 2967–2972). IEEE.
References L. Atzori, A. Iera, and G. Morabito, “The internet of things: A survey,” Comput. Netw., Vol. 54, No. 15, pp. 2787–2805, 2010. MacLean, D. (2008). ICTs, adaptation to climate change, and sustainable development at the edges. In International telecommunication union symposium on ICTs and climate change. Yi Zhang, Michela Meo, Raffaella Gerboni, Marco Ajmone Marsan, Minimum cost solar power systems for LTE macro base stations, Computer Networks, Volume 112, 15 January 2017, Pages 12-23
