Traditionally we highly rely on fossil fuels for our energy provisioning, but there are drawbacks on using these fossil fuels: the risk for depletion in the future; the increased in cost as already observed during the last few years, and the high impact on the climate change. One virtually carbon-neutral alternative to fossil fuels are renewable energy sources, like solar energy. In this paper, we investigate the energy and network performance of a wireless access network powered by the traditional electricity grid and a PV (PhotoVoltaic) panel system. An energy-aware management system for the future wireless access networks is proposed. This system consists of the management of the energy provisioning and storage system and the application of the proposed energy-saving strategies which aim to reduce the energy footprint through the traditional grid in case a renewable energy shortage occurs. To evaluate the network's performance, this paper proposes a deployment tool with the above described energy-aware management system. The results show that it is promising to further investigate a more evolved and complex energyaware management system.
Being cheap and easy to deploy, dense WLANs are becoming the most popular solution to provide Internet access in locations in which the population of users is large, as in Campuses, large enterprises, etc. The large density of access points (APs) comes from the need to have enough capacity to carry the traffic generated at peak hours although, in these scenarios, traffic varies a lot on a daily, weekly or seasonal basis. During low or no traffic periods, APs are underutilized, even if they are consuming energy almost in the same amount as if they were fully loaded. Promising solutions to reduce this form of energy waste consist in activating only the number of APs that is strictly needed to carry the actual traffic; in other words, to make capacity dynamically adaptive through Resource on-Demand (RoD) strategies. In this paper, we investigate the case of a portion of the dense WLAN in our Campus. Through real trace analysis, we investigate users behavior in accessing the WLAN and formulate a stochastic characterization of it. We propose a simple model that describes RoD strategies and use it to study the system performance that is evaluated in terms of AP activity and inactivity periods, AP switching frequency, and energy saving. Finally, we present some results obtained by experimenting RoD strategies in a portion of the WLAN. Our results show that RoD strategies for dense WLANs are feasible and effective in trading-off the opposite needs to save some energy and to guarantee a smooth network operation and high quality of service.
Three factors make power supply one of the most urgent and challenging issues for the future of mobile networks. First, the expected fast growth of mobile traffic raises doubts about the sustainability of mobile communications, that already account for 0.5% of the woldwide energy consumption. Second, power supply has become far the largest component of the operational costs of running a network. Third, the deployment of network infrastructures in emerging countries is strategic, but, in these countries, the power grid is not always reliable. Renewable energy sources can help to cope with these issues. However, one of their main drawbacks is the intermittent and difficult to predict energy generation profile. The feasibility of renewable power supply for base station (BS) powering depends then by the possibility to reduce the BS consumption and to adapt it to the amount of available energy. In this paper, we consider a cluster of BSs powered with photovoltaic (PV) panels and equipped with energy storage units. Resource on Demand (RoD) strategies are implemented to reduce the cluster energy consumption and to adapt it to energy availability. The results show that resource of demand can effectively be applied to make off-grid BS deployment feasible.
In this paper we focus on the design of the power system for off-grid cellular base stations powered by a photovoltaic (PV) solar panel and a battery. Several papers already tackled this problem, with different approaches, modeling either the day-to-day behavior, or the hourly dynamics. In addition, the meteorological characteristics were modeled using a variable number of levels. Different approaches produced different results, hardly comparable. In this paper, we discuss the choice of parameter quantization for time, weather, and energy storage, with the objective of deriving guidelines for the development of accurate and credible models that can support the power system design. Our investigation shows that quantization has an important impact on the mathematical model outputs. Hence, quantization must be carefully taken into account, to achieve a correct dimensioning of the power system.
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