Lightweight middleware for SDR inter-components communication

The ability to use Software Defined Radio (SDR) in the civilian mobile applications will make it possible for the next generation of mobile devices to handle multi-standard personal wireless devices and ubiquitous wireless devices. The original military standard created many beneficial characteristics for SDR, but resulted in a number of disadvantages as well. Many challenges in commercializing SDR are still the subject of interest in the software radio research community. Four main issues that have been already addressed are performance, size, weight, and power. ^ This investigation presents an in-depth study of SDR inter-components communications in terms of total link delay related to the number of components and packet sizes in systems based on Software Communication Architecture (SCA). The study is based on the investigation of the controlled environment platform. Results suggest that the total link delay does not linearly increase with the number of components and the packet sizes. The closed form expression of the delay was modeled using a logistic function in terms of the number of components and packet sizes. The model performed well when the number of components was large. ^ Based upon the mobility applications, energy consumption has become one of the most crucial limitations. SDR will not only provide flexibility of multi-protocol support, but this desirable feature will also bring a choice of mobile protocols. Having such a variety of choices available creates a problem in the selection of the most appropriate protocol to transmit. An investigation in a real-time algorithm to optimize energy efficiency was also performed. Communication energy models were used including switching estimation to develop a waveform selection algorithm. Simulations were performed to validate the concept.^

Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

Performance comparativa entre R437A e R134A paradrop-in em um condicionador de ar automotivo

The reduction in energy consumption is the main requirement to be satisfied in refrigeration and air conditioning by mechanical vapor compression system. In automotive system isn´t different. Thermal analyses in these systems are crucial for a better performance in automotive air conditioner. This work aims to evaluate the conditions of use of R134A refrigerant (used in vehicles) and compare with R437A (alternative refrigerant), varying the speed of the electric fan in the evaporator. All tests were performed in automotive air conditioning unit ATR600, simulating the thermal conditions of the system. The equipment is instrumented for data acquisition temperature, condensation and evaporation pressures and electrical power consumed to determine the coefficient of performance of the cycle. The system was tested under rotations of 800, 1600 and 2400 rpm with constant load of R- 134a. It occurred with the same conditions with R437A. Both recommended by the manufacturer. The results show that the best system performance occurs in the rotation of 800 RPM for both refrigerants.

Investigation of Performance Enhancements for a Liquid-Desiccant Solar Air-Conditioner

Thermally driven liquid-desiccant air-conditioners (LDAC) are a proven but still developing technology. LDACs can use a solar thermal system to reduce the operational cost and environmental impact of the system by reducing the amount of fuel (e.g. natural gas, propane, etc.) used to drive the system. LDACs also have a key benefit of being able to store energy in the form of concentrated desiccant storage. TRNSYS simulations were used to evaluate several different methods of improving the thermal and electrical coefficients of performance (COPt and COPe) and the solar fraction (SF) of a LDAC. The study analyzed a typical June to August cooling season in Toronto, Ontario. Utilizing properly sized, high-efficiency pumps increased the COPe to 3.67, an improvement of 55%. A new design, featuring a heat recovery ventilator on the scavenging-airstream and an energy recovery ventilator on the process-airstream, increased the COPt to 0.58, an improvement of 32%. This also improved the SF slightly to 54%, an increase of 8%. A new TRNSYS TYPE was created to model a stratified desiccant storage tank. Different volumes of desiccant were tested with a range of solar array system sizes. The largest storage tank coupled with the largest solar thermal array showed improvements of 64% in SF, increasing the value to 82%. The COPe was also improved by 17% and the COPt by 9%. When combining the heat recovery systems and the desiccant storage systems, the simulation results showed a 78% increase in COPe and 30% increase in COPt. A 77% improvement in SF and a 17% increase in total cooling rate were also predicted by the simulation. The total thermal energy consumed was 10% lower and the electrical consumption was 34% lower. The amount of non-renewable energy needed from the natural gas boiler was 77% lower. Comparisons were also made between LDACs and vapour-compression (VC) systems. Dependent on set-up, LDACs provided higher latent cooling rates and reduced electrical power consumption. Negatively, a thermal input was required for the LDAC systems but not for the VC systems.

Communication-efficient decentralized sequential detection

The problem of decentralized sequential detection is studied in this thesis, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and error probability, we introduce a new constraint: the number of communications between local sensors and the fusion center. This metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. A new formulation for communication-efficient decentralized sequential detection is proposed where the overall detection delay is minimized with constraints on both error probabilities and the communication cost. Two types of problems are investigated based on the communication-efficient formulation: decentralized hypothesis testing and decentralized change detection. In the former case, an asymptotically person-by-person optimum detection framework is developed, where the fusion center performs a sequential probability ratio test based on dependent observations. The proposed algorithm utilizes not only reported statistics from local sensors, but also the reporting times. The asymptotically relative efficiency of proposed algorithm with respect to the centralized strategy is expressed in closed form. When the probabilities of false alarm and missed detection are close to one another, a reduced-complexity algorithm is proposed based on a Poisson arrival approximation. In addition, decentralized change detection with a communication cost constraint is also investigated. A person-by-person optimum change detection algorithm is proposed, where transmissions of sensing reports are modeled as a Poisson process. The optimum threshold value is obtained through dynamic programming. An alternative method with a simpler fusion rule is also proposed, where the threshold values in the algorithm are determined by a combination of sequential detection analysis and constrained optimization. In both decentralized hypothesis testing and change detection problems, tradeoffs in parameter choices are investigated through Monte Carlo simulations.

A green perspective on Structured parallel programming

Structured parallel programming, and in particular programming models using the algorithmic skeleton or parallel design pattern concepts, are increasingly considered to be the only viable means of supporting effective development of scalable and efficient parallel programs. Structured parallel programming models have been assessed in a number of works in the context of performance. In this paper we consider how the use of structured parallel programming models allows knowledge of the parallel patterns present to be harnessed to address both performance and energy consumption. We consider different features of structured parallel programming that may be leveraged to impact the performance/energy trade-off and we discuss a preliminary set of experiments validating our claims.

ClimateWell TDC with District Heat

The PolySMART demonstration system SP1b has been modeled in TRNSYS and calibrated against monitored data. The system is an example of distributed cooling with centralized CHP, where the driving heat is delivered via the district heating network. The system pre-cools the cooling water for the head office of Borlänge municipality, for which the main cooling is supplied by a 200 kW compression chiller. The SP1b system thus provides pre-cooling. It consists of ClimateWell TDC with nominal capacity of 10 kW together with a dry cooler for recooling and heat exchangers in the cooling and driving circuits. The cooling system is only operated from 06:00 to 17:00 during working days, and the cooling season is generally from mid May to mid September. The nominal operating conditions of the main chiller are 12/15°C. The main aims of this simulation study were to: reduce the electricity consumption, and if possible to improve the thermal COP and capacity at the same time; and to study how the system would perform with different boundary conditions such as climate and load. The calibration of the system model was made in three stages: estimation of parameters based on manufacturer data and dimensions of the system; calibration of each circuit (pipes and heat exchangers) separately using steady state point; and finally calibration of the complete model in terms of thermal and electrical energy as well as running times, for a five day time series of data with one minute average data values. All the performance figures were with 3% of the measured values apart from the running time for the driving circuit that was 4% different. However, the performance figures for this base case system for the complete cooling season of mid-May to midSeptember were significantly better than those for the monitoring data. This was attributed to long periods when the monitored system was not in operation and due to a control parameter that hindered cold delivery at certain times. 

Optimized operations of Distributed Renewable Energy Sources in Smart Grid

The renewable energy sources (RES) will play a vital role in the future power needs in view of the increasing demand of electrical energy and depletion of fossil fuel with its environmental impact. The main constraints of renewable energy (RE) generation are high capital investment, fluctuation in generation and requirement of vast land area. Distributed RE generation on roof top of buildings will overcome these issues to some extent. Any system will be feasible only if it is economically viable and reliable. Economic viability depends on the availability of RE and requirement of energy in specific locations. This work is directed to examine the economic viability of the system at desired location and demand.

Utilizing “Big Data” to Improve the Hotel Sector’s Energy Efficiency: Lessons from Recent Economics Research

Hotel chains have access to a treasure trove of “big data” on individual hotels’ monthly electricity and water consumption. Benchmarked comparisons of hotels within a specific chain create the opportunity to cost-effectively improve the environmental performance of specific hotels. This paper describes a simple approach for using such data to achieve the joint goals of reducing operating expenditure and achieving broad sustainability goals. In recent years, energy economists have used such “big data” to generate insights about the energy consumption of the residential, commercial, and industrial sectors. Lessons from these studies are directly applicable for the hotel sector. A hotel’s administrative data provide a “laboratory” for conducting random control trials to establish what works in enhancing hotel energy efficiency.

Hotel Sustainability Benchmarking Index 2016: Energy, Water, and Carbon

Several studies have been undertaken or attempted by industry and academe to address the need for lodging industry carbon benchmarking. However, these studies have focused on normalizing resource use with the goal of rating or comparing all properties based on multivariate regression according to an industry-wide set of variables, with the result that data sets for analysis were limited. This approach is backward, because practical hotel industry benchmarking must first be undertaken within a specific location and segment.1 Therefore, the CHSB study’s goal is to build a representative database providing raw benchmarks as a base for industry comparisons.2 These results are presented in the CHSB2016 Index, through which a user can obtain the range of benchmarks for energy consumption, water consumption, and greenhouse gas emissions for hotels within specific segments and geographic locations.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Survery and simulation of energy use in the European building stock

the work towards increased energy efficiency. In order to plan and perform effective energy renovation of the buildings, it is necessary to have adequate information on the current status of the buildings in terms of architectural features and energy needs. Unfortunately, the official statistics do not include all of the needed information for the whole building stock.   This paper aims to fill the gaps in the statistics by gathering data from studies, projects and national energy agencies, and by calibrating TRNSYS models against the existing data to complete missing energy demand data, for countries with similar climate, through simulation. The survey was limited to residential and office buildings in the EU member states (before July 2013). This work was carried out as part of the EU FP7 project iNSPiRe.   The building stock survey revealed over 70% of the residential and office floor area is concentrated in the six most populated countries. The total energy consumption in the residential sector is 14 times that of the office sector. In the residential sector, single family houses represent 60% of the heated floor area, albeit with different share in the different countries, indicating that retrofit solutions cannot be focused only on multi-family houses.   The simulation results indicate that residential buildings in central and southern European countries are not always heated to 20 °C, but are kept at a lower temperature during at least part of the day. Improving the energy performance of these houses through renovation could allow the occupants to increase the room temperature and improve their thermal comfort, even though the potential for energy savings would then be reduced.

Measuring energy footprint of software features

Abstract—With the proliferation of Software systems and the rise of paradigms such the Internet of Things, Cyber- Physical Systems and Smart Cities to name a few, the energy consumed by software applications is emerging as a major concern. Hence, it has become vital that software engineers have a better understanding of the energy consumed by the code they write. At software level, work so far has focused on measuring the energy consumption at function and application level. In this paper, we propose a novel approach to measure energy consumption at a feature level, cross-cutting multiple functions, classes and systems. We argue the importance of such measurement and the new insight it provides to non-traditional stakeholders such as service providers. We then demonstrate, using an experiment, how the measurement can be done with a combination of tools, namely our program slicing tool (PORBS) and energy measurement tool (Jolinar).

Energy efficiency and climate policy in the management of public spaces: public lighting

Public Lightning is an important part of municipality’s nighttime landscape. Lighting can be used to enhance public safety and security while improving the aesthetic appeal of the surrounding properties but with the current global financial crisis, such lighting systems must also be sustainable. Most climate policy efforts focus on the state and international level, however national governments won’t be able to meet their international commitments without local action. In Portugal, the Public Lighting is responsible for 3% of energy consumption. The problem is that the trend is to increase (about 4-5% per year) which represents very high costs for the municipal authorities. In terms of numbers are analyzed in this thesis 45 of 278 existent in Continental Portugal what represents only 16,2 % of the counties. This where the local authorities in Portugal that had a Sustainable Energy Action Plan (SEAP) that had been accepted and made available in the Covenant of Mayors website until the end of year 2013. It is important that the Covenant of Mayors will increase the local authorities awareness for energy efficiency and especially to public lighting because there is still a long way to go in terms of energy consumption reduction. In future works it would be interesting to see the payback of the EolGreen post in a real scenario due to lack of energy consumption from the grid it would allow to have a pretty high initial investment even with the maintenance that those technologies need.