Water harvesting for young trees using Peltier plates powered by photovoltaic solar energy

Young trees transplanted from nursery into open field require a minimum amount of soil moisture to successfully root in their new location, especially in dry-climate areas. One possibility is to obtain the required water from air moisture. This can be achieved by reducing the temperature of a surface below the air dew point temperature, inducing water vapor condensation on the surface. The temperature of a surface can be reduced by applying the thermoelectric effect, with Peltier modules powered by electricity. Here, we present a system that generates electricity with a solar photovoltaic module, stores it in a battery, and finally, it uses the electricity at the moment in which air humidity and temperature are optima to maximize water condensation while minimizing energy consumption. Also, a method to reduce the evaporation of the condensed water is proposed. The objective of the system, rather than irrigating young plants in such a degree as to boost their growth, is to maintain them alive in the dryer periods.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks (WSNs) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of WSNs facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers (DCs). The high economical and environmental impact of the energy consumption in DCs requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of WSNs: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of DCs: energy-optimal workload assignment policies in heterogeneous DCs, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

Leveraging heterogeneity for energy minimization in data centers

Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

On track for solar grade silicon through a siemens process-type laboratory reactor: operating conditions and energy savings

Polysilicon cost impacts significantly on the photovoltaics (PV) cost and on the energy payback time. Nowadays, the besetting production process is the so called Siemens process, polysilicon deposition by chemical vapor deposition (CVD) from Trichlorosilane. Polysilicon purification level for PV is to a certain extent less demanding that for microelectronics. At the Instituto de Energía Solar (IES) research on this subject is performed through a Siemens process-type laboratory reactor. Through the laboratory CVD prototype at the IES laboratories, valuable information about the phenomena involved in the polysilicon deposition process and the operating conditions is obtained. Polysilicon deposition by CVD is a complex process due to the big number of parameters involved. A study on the influence of temperature and inlet gas mixture composition on the polysilicon deposition growth rate, based on experimental experience, is shown. Moreover, CVD process accounts for the largest contribution to the energy consumption of the polysilicon production. In addition, radiation phenomenon is the major responsible for low energetic efficiency of the whole process. This work presents a model of radiation heat loss, and the theoretical calculations are confirmed experimentally through a prototype reactor at our disposal, yielding a valuable know-how for energy consumption reduction at industrial Siemens reactors.

Analyzing energy-efficient configurations in hexapod robots for demining applications

Purpose – Reducing energy consumption in walking robots is an issue of great importance in field applications such as humanitarian demining so as to increase mission time for a given power supply. The purpose of this paper is to address the problem of improving energy efficiency in statically stable walking machines by comparing two leg, insect and mammal, configurations on the hexapod robotic platform SILO6. Design/methodology/approach – Dynamic simulation of this hexapod is used to develop a set of rules that optimize energy expenditure in both configurations. Later, through a theoretical analysis of energy consumption and experimental measurements in the real platform SILO6, a configuration is chosen. Findings – It is widely accepted that the mammal configuration in statically stable walking machines is better for supporting high loads, while the insect configuration is considered to be better for improving mobility. However, taking into account the leg dynamics and not only the body weight, different results are obtained. In a mammal configuration, supporting body weight accounts for 5 per cent of power consumption while leg dynamics accounts for 31 per cent. Originality/value – As this paper demonstrates, the energy expended when the robot walks along a straight and horizontal line is the same for both insect and mammal configurations, while power consumption during crab walking in an insect configuration exceeds power consumption in the mammal configuration.

Water harvesting for young trees using Peltier modules powered by photovoltaic solar energy

Young trees transplanted from nursery into open field require a minimum amount of soil moisture to successfully root in their new location, especially in dry-climate areas. One possibility is to obtain the required water from air moisture. This can be achieved by reducing the temperature of a surface below the air dew point temperature, inducing water vapor condensation on the surface. The temperature of a surface can be reduced by applying the thermoelectric effect, with Peltier modules powered by electricity. Here, we present a system that generates electricity with a solar photovoltaic module, stores it in a battery, and finally, uses the electricity at the moment in which air humidity and temperature are optimal to maximize water condensation while minimizing energy consumption. Also, a method to reduce the evaporation of the condensed water is proposed. The objective of the system is to sustain young plants in drier periods, rather than exclusively irrigating young plants to boost their growth.

An energy efficient adaptive HELLO algorithm for mobile ad hoc networks

HELLO protocol or neighborhood discovery is essential in wireless ad hoc networks. It makes the rules for nodes to claim their existence/aliveness. In the presence of node mobility, no fix optimal HELLO frequency and optimal transmission range exist to maintain accurate neighborhood tables while reducing the energy consumption and bandwidth occupation. Thus a Turnover based Frequency and transmission Power Adaptation algorithm (TFPA) is presented in this paper. The method enables nodes in mobile networks to dynamically adjust both their HELLO frequency and transmission range depending on the relative speed. In TFPA, each node monitors its neighborhood table to count new neighbors and calculate the turnover ratio. The relationship between relative speed and turnover ratio is formulated and optimal transmission range is derived according to battery consumption model to minimize the overall transmission energy. By taking advantage of the theoretical analysis, the HELLO frequency is adapted dynamically in conjunction with the transmission range to maintain accurate neighborhood table and to allow important energy savings. The algorithm is simulated and compared to other state-of-the-art algorithms. The experimental results demonstrate that the TFPA algorithm obtains high neighborhood accuracy with low HELLO frequency (at least 11% average reduction) and with the lowest energy consumption. Besides, the TFPA algorithm does not require any additional GPS-like device to estimate the relative speed for each node, hence the hardware cost is reduced.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

A cyber-physical approach to combined HW-SW monitoring for improving energy efficiency in data centers

High-Performance Computing, Cloud computing and next-generation applications such e-Health or Smart Cities have dramatically increased the computational demand of Data Centers. The huge energy consumption, increasing levels of CO2 and the economic costs of these facilities represent a challenge for industry and researchers alike. Recent research trends propose the usage of holistic optimization techniques to jointly minimize Data Center computational and cooling costs from a multilevel perspective. This paper presents an analysis on the parameters needed to integrate the Data Center in a holistic optimization framework and leverages the usage of Cyber-Physical systems to gather workload, server and environmental data via software techniques and by deploying a non-intrusive Wireless Sensor Net- work (WSN). This solution tackles data sampling, retrieval and storage from a reconfigurable perspective, reducing the amount of data generated for optimization by a 68% without information loss, doubling the lifetime of the WSN nodes and allowing runtime energy minimization techniques in a real scenario.

Leakage and temperature aware server control for improving energy efficiency in data centers

Reducing the energy consumption for computation and cooling in servers is a major challenge considering the data center energy costs today. To ensure energy-efficient operation of servers in data centers, the relationship among computa- tional power, temperature, leakage, and cooling power needs to be analyzed. By means of an innovative setup that enables monitoring and controlling the computing and cooling power consumption separately on a commercial enterprise server, this paper studies temperature-leakage-energy tradeoffs, obtaining an empirical model for the leakage component. Using this model, we design a controller that continuously seeks and settles at the optimal fan speed to minimize the energy consumption for a given workload. We run a customized dynamic load-synthesis tool to stress the system. Our proposed cooling controller achieves up to 9% energy savings and 30W reduction in peak power in comparison to the default cooling control scheme.

Evaluation of the utilization of electric vehicles for building energy management in hotels

Governments are working in new policies to slow down total energy consumption and greenhouse gases (GHG) emissions, promoting the deployment of electric vehicles (EVs) in all countries. In order to facilitate this deployment and help to reduce the final costs of their batteries, additional utilization of EVs when those are parked has been proposed. EVs can be used to minimize the total electricity cost of buildings (named vehicle to building applications, V2B). In this paper an economic evaluation of EVs in the Building Energy Management System is shown. The optimal storage capacity and its equivalent number of EVs are determined. This value is then used for determining the optimal charging schedule to be applied to the batteries. From this schedule, the total expected profit is derived for the case of a real hotel in Spain.

Lessons learned on home energy monitoring and management: Smartcity Málaga

The Smartcity Málaga project is one of Europe?s largest ecoefficient city initiatives. The project has implemented a field trial in 50 households to study the effects of energy monitoring and management technologies on the residential electricity consumption. This poster presents some lessons learned on energy consumption trends, smart clamps reliability and the suitability of power contracted by users, obtained after six months of data analysis.

Passive design strategies and performance of Net Energy Plus Houses

The first step in order to comply with the European Union goals of Near to Zero Energy Buildings is to reduce the energy consumption in buildings. Most of the building consumption is related to the use of active systems to maintain the interior comfort. Passive design strategies contribute to improve the interior comfort conditions, increasing the energy efficiency in buildings and reducing their energy consumption. In this work, an analysis of the passive strategies used in Net Energy Plus Houses has been made. The participating houses of the Solar Decathlon Europe 2012 competition were used as case studies. The passive design strategies of these houses were compared with the annual simulations, and the competition monitored data, especially during the Passive Monitored Period. The analysis included the thermal properties of the building envelope, geometric parameters, ratios and others passive solutions such as Thermal Energy Storage systems, evaporative cooling, night ventilation, solar gains and night sky radiation cooling. The results reflect the impact of passive design strategies on the houses' comfort and efficiency, as well as their influence in helping to achieve the Zero Energy Buildings category.

Improving photovoltaics grid integration through short time forecasting and self-consumption

The uncertainty associated to the forecast of photovoltaic generation is a major drawback for the widespread introduction of this technology into electricity grids. This uncertainty is a challenge in the design and operation of electrical systems that include photovoltaic generation. Demand-Side Management (DSM) techniques are widely used to modify energy consumption. If local photovoltaic generation is available, DSM techniques can use generation forecast to schedule the local consumption. On the other hand, local storage systems can be used to separate electricity availability from instantaneous generation; therefore, the effects of forecast error in the electrical system are reduced. The effects of uncertainty associated to the forecast of photovoltaic generation in a residential electrical system equipped with DSM techniques and a local storage system are analyzed in this paper. The study has been performed in a solar house that is able to displace a residential user?s load pattern, manage local storage and estimate forecasts of electricity generation. A series of real experiments and simulations have carried out on the house. The results of this experiments show that the use of Demand Side Management (DSM) and local storage reduces to 2% the uncertainty on the energy exchanged with the grid. In the case that the photovoltaic system would operate as a pure electricity generator feeding all generated electricity into grid, the uncertainty would raise to around 40%.