Energy Request Research Articles

Multi-Dimensional Resource Allocation for Uplink Throughput Maximisation in Integrated Data and Energy Communication Networks

The interdisciplinary research of the radio-frequency (RF) signal-based wireless power and information transfer is expected to address the energy shortage issue in the massively deployed low-power Internet of Things devices. Different from conventional wireless powered communication networks (WPCNs), the hybrid base station (H-BS) adopts the simultaneous wireless information and power transfer (SWIPT) for the sake of satisfying the downlink data and energy requests of the multiple user equipments (UEs). The energy harvested from the downlink transmissions can be depleted for supporting the UEs’ uplink transmissions. Integrating SWIPT in the downlink transmission of the WPCN yields a generic integrated data and energy communication network, where the H-BS is equipped with multiple antennas and both the downlink and uplink transmissions are slotted in the time-domain. Furthermore, both the sum-throughput and the fair-throughput of the uplink transmissions are maximized by jointly optimizing the transmit beamformer of the H-BS in the spatial-domain, the time-slot allocation in the time-domain and the signal splitting strategies of the UEs in the power domain, while satisfying the UEs’ minimum downlink transmission requirements. Due to the non-convexity of the problem, a low-complexity successive convex approximation-based algorithm is relied upon for obtaining the optimal resource allocation scheme in the time-domain, power-domain, and spatial-domain. The numerical results validate the efficiency of our proposed resource allocation algorithm and they also demonstrate that supporting low-rate data services during the downlink transmissions does not degrade the wireless power transfer and hence does not reduce the uplink throughput.

Lymphoblastoid cell lines as a model to understand amyotrophic lateral sclerosis disease mechanisms.

ABSTRACTIn the past, amyotrophic lateral sclerosis (ALS) has been considered a ‘neurocentric’ disease; however, new evidence suggests that it should instead be looked at from a ‘multisystemic’ or ‘non-neurocentric’ point of view. From 2006, we focused on the study of non-neural cells: ALS patients’ peripheral blood mononuclear cells (PMBCs) and lymphoblastoid cell lines (LCLs). Here, we characterize LCLs of sporadic ALS (sALS) and patients carrying SOD1, TARDBP and FUS mutations to identify an ALS biologically relevant molecular signature, and determine whether and how mutations differentially affect ALS-linked pathways. Although LCLs are different from motor neurons (MNs), in LCLs we found some features typical of degenerating MNs in ALS, i.e. protein aggregation and mitochondrial dysfunction. Moreover, different gene mutations have different effects on ALS cellular mechanisms. TARDBP and FUS mutations imbalance mitochondrial dynamism toward increased fusion, whereas sALS and SOD1 mutations mainly affect fission. With regards to protein aggregation and/or mislocalization, TARDBP and SOD1 mutations show the presence of aggregates, whereas FUS mutation does not induce protein aggregation and/or mislocalization. Finally, all LCLs, independently from mutation, are not able to work in a condition of excessive energy request, suggesting that mitochondria from ALS patients are characterized by a significant metabolic defect. Taken together, these data indicate that LCLs could be a valid cellular model in ALS research in the identification and study of specific pathological pathways.

MINLP Probabilistic Scheduling Model for Demand Response Programs Integrated Energy Hubs

In this paper, an optimal probabilistic scheduling model of energy hubs operations is presented. The scheduling of energy hub determines the energy carriers to be purchased as input and converted or stored, in order to meet the energy requests, while minimizing the total hub's cost. However, as many other engineering endeavors, future operating criteria of energy hubs could not be forecasted with certainty. Load and price uncertainties are the most unclear parameters that hub operators deal with. In this regard, this paper proposes a 2 $m$ + 1 point estimation probabilistic scheduling scheme for energy hubs with multiple energy inputs and outputs. One of the applicable tools of energy hubs to have an efficient participation in the liberalized power market with volatile prices is demand response programs (DRPs). While there is plenty of experience in investigating the effect of DRP, it is electricity DRP that receives increasing attention by research and industry. Therefore, the proposed DRP investigates the effect of both responsive thermal and electric loads in reducing the total cost and participation of different facilities in supplying multiple loads. The proposed model envisages the most technical constraints of converters and storages. Several test systems have been investigated in order to confirm the effectiveness of the proposed model. The results verify the capability of the proposed model in covering the energy hub time-varying output demands as well as the economic advantages of implementing the suggested strategy. In addition, the results are compared with 2 $m$ point estimate method and Monte Carlo simulation.

Etiopathogenesis and Pharmacological Prevention of a Type-2 Diabetes Model in Male Mice.

We describe a stress-derived type-2 diabetes model in male mice, and formulate new hypotheses on how the model was induced, how diabetes-like alterations were prevented through specific pharmacological treatments, and how its possible neuroendocrine pathogenesis could be hypothesized. Pregnant females arrived in our laboratory on their 14th day of conceptional age. After birth, control mice never showed any apparent behavioral-metabolic-endocrine alterations. However, application of postnatal stress (brief mother deprivation, plus sham injection, daily from birth to weaning), was followed in adult male mice by two series of diabetes-like alterations. Some alterations (e.g., body overweight, immune, neurophysiologic, neurobehavioral alterations) were selectively prevented by opioid antagonist naloxone daily administered during nursing period. The aforementioned alterations plus several others (e.g., hyperglycemia, neuroendocrine alterations) were prevented by administration of specific antisense oligodeoxinucleotide, which modulated synthesis-hyperfunction of proopiomelanocortin-derived corticotropin (ACTH)-corticosterone and endorphins in the pituitary. Surprisingly, together with metabolic alterations, enduring increment of neurophysiologic/neurobehavioral brain performances were observed, accompanied by energy compensative reactions, and brain mitochondria hyperfunction. Thus, increased glycemia/lipidemia appeared to furnish fuel necessary to cope with increased request of energy. Diabetes-like alterations were accompanied by enduring hyperfunction of opioid- and ACTH-corticosterone-endogenous structures in the brain, which were apparently due to failure of negative feedback hormone mechanisms in the pituitary, for the control of the hypothalamus-pituitary-adrenal axis. In conclusion, for the first time we can hypothesize that a diabetes-like syndrome is produced by enduring hyperfunction of two proopiomelanocortin-dependent endogenous systems (brain opioid- and ACTH-corticosterone systems), following failure of pituitary feedback hormonal control, after complex stress procedures.

Enhanced electrocatalytic activity and durability of Pt nanoparticles decorated on GO-PVP hybride material for methanol oxidation reaction

The alternative energy request is force to find effective electro catalysts used in fuel cell implementations and to enhance the efficiency of existing materials. In this study, graphene oxide (GO) and polyvinylpyrrolidone (PVP) supported shape-controlled platinum nanoparticles (Pt NPs) were newly synthesized with one-pot approach and used as anode materials in the direct methanol fuel cells (DMFCs). The examination for the performance of Pt @GO-PVP NPs was carried out in methanol oxidation reactions (MOR). Pt @GO-PVP catalysts exhibit high stability and activity against the MOR. The methanol oxidation reactions current can reach to 43mA and can maintain 82.9% of the initial value even after 1000 cycles. The GO-PVP support material provides higher surface area and absorbs more methanol molecules for more efficient oxidation.

A climate driven decision-support model for the distribution of perishable products

The cold chains prevent perishable products from decay, but are highly energy-intensive. As much as 15% of total worldwide energy already fuels cold chains infrastructures and since 40% of food deliveries would need refrigeration, the growth of global food demand and of the widening of the global supply chains will enormously increase the energy request and the associated carbon emissions. The environmental temperature has indeed a clear effect on the performance of the cold chain, and the interaction between climate and the distribution of perishable products cannot be ignored. In this paper a mixed-integer linear programming model for the planning of the production, storage and distribution operations of perishable products which incorporates the interactions with the weather conditions is formulated. This addresses an open field of research, which is still uncovered. The proposed model has been applied to an illustrative case study of a cold chain for cherries, that demonstrates the influence of the weather conditions on the energy costs for the products refrigeration on vehicles during transportation and at the warehouse during storage. Successful control of the distribution operations according to the weather conditions can result in significant reduction of energy consumption and costs, which increase indeed with the raise of environmental temperatures and stresses. Based on the results obtained in this study, these costs are not handled by the extant operations planning models, and their minimization can lead to significant economic and environmental savings for the cold chain.

Solid polymer electrolytes based on phosphorus containing polymers for lithium polymer batteries

This paper is designated to the development of flame retardant solid polymer electrolytes based on phosphorus containing polymers. The new green technique synthesis, respectively polycondensation under microwave irradiation of hexylphosphonic dichloride (HPD) with 4,4′-(1,3-phenylenediisopropylidene) bisphenol (bisphenol M) was described. 86% yield and 0.95dlg−1 inherent viscosity were obtained. The polyphosphonate was characterized by FT-IR, 1H and 31P NMR spectroscopy, gel permeation chromatography, and thermal analysis. The polymer presents thermal stability, begins to lose weight above 280°C. The influence of the reaction temperature and reaction time on yield and inherent viscosity for MW polycondensation was studied and the results were compared with the results of polycondensation reaction under conventional heating in similar conditions. Best results were obtained under microwave irradiation. Solid polymer electrolytes were obtained from the polyphosphonate complexed with different lithium salts using casting technique and the electrochemical properties were determined. The low activation energy of conduction determined for solid polymer electrolyte membrane with bis(oxalato)borate anions overcomes the activation energy request for relaxation process and this membrane presents the best conductivity. Also, the flammability of polyphosphonate and membranes was investigated by measuring limiting oxygen index values.

Assessing the feasibility of cogeneration retrofit and district heating/cooling networks in small Italian islands

Sustainability of energy supply in small islands has been emerging as a severe issue, due to the large margins for improvement of the most frequently adopted solutions. In many European islands large amounts of heat are wasted by the operation of engines-based power plants; conversely, heat is produced by boilers or by electric equipment for different uses, like domestic hot water or space heating. In this paper a techno-economic analysis is proposed to assess the feasibility of CHP-retrofit of existing power plants and the possible utilization of the recovered heat to supply, via a district heating and/or cooling network, the energy requests of civil users in the tertiary and residential sectors. The analysis is performed for six islands in Italy characterized by different demographic and climatic conditions, so as to get a comprehensive understanding of the factors that favour/obstruct the viability of the examined technical solution. As expected, due to the low “linear heat density” observed in small islands, the investments resulted “far from being attractive”; only in the case where public support mechanisms are adopted, the integration of the existing power plants with heat recovery devices and a district heating network resulted moderately attractive, especially in the largest islands.

District Microgrid Management Integrated with Renewable Energy Sources, Energy Storage Systems and Electric Vehicles

This paper addresses the problem of the energy management of cooperative district microgrids: the goal is minimizing the additional energy to be purchased and maximizing the utilization of energy bought at the day-ahead energy market. To this purpose the District Energy Management System (DEMS) predicts the energy consumption of the district and minimizes additional real-time energy requests by optimally integrating renewable energy sources, storage systems and district electric vehicles. To solve this problem two approaches are considered. In the first approach, we assume that the energy consumption, the cumulative production of the renewable energies and the energy costs are known. In this case, a linear programming problem is formulated and solved by the DEMS. In order to deal with the parameters uncertainty, we propose a second approach formulated as a stochastic linear programming problem.

Urban design in favor of human thermal comfort for hot arid climate using advanced simulation methods

Improving outdoor human thermal comfort could be considered as one of the most important targets for achieving successful open space designs. In hot arid climate, residential neighborhoods are responsible for the high request of energy to provide cooling needs for the occupants’ comfort. The main problem is the non-responsive contemporary urban design to human thermal comfort and energy. In this context, this paper aims at testing specific landscape parameters that could enhance outdoor human thermal comfort. The study is limited to the microclimate at urban open space and will be conducted in New Borg El-Arab (hot arid city according to Middleton and others [1], Alexandria, Egypt). The adopted methodology is based on the use of ENVI-met 4.0 software to measure four thermal indices (air temperature, relative humidity, MRT and PMV) and assess outdoor human thermal comfort in an existing neighborhood. In addition, different design scenarios that emphasize different landscape elements were also assessed. The results of this analysis depict changing street networks, landscape design and materials could enhance the level of thermal comfort in the urban open spaces.

Heuristic approaches for a domestic energy management system

In the context of smart buildings, house energy consumption plays a significant role in the energy system. Since there are different billing rates, the aim of the smart grid system is to minimize the overall energy cost by appropriately selecting the best starting times for each household appliance. Further, the scheduler should guarantee that the instant energy request does not overcome the maximum threshold which depends on the customers contract.Although the maximum threshold is a constant, the instant energy consumption may possibly exceed this value, whenever is available some renewable source such as, for instance, solar energy. In this work, we consider the problem of scheduling smart home appliances within a given time horizon respecting the threshold on the energy peak consumption with the objective of minimizing the overall cost related to the average energy consumption of each appliance at each time instant. A hybrid heuristic based on a mixed integer programming formulation of the problem and a particle swarm optimization approach are proposed. Computational results, applying these approaches to real life data are provided and discussed.

Blood lipids in athletes depending on the orientation of the training process

Sports form the metabolic response caused by the body’s adaptation to increased physical stress, which leads to the restructuring of metabolism for energy and plastic maintenance of sport activities. The restructuring of carbohydrate and lipid metabolism is caused primarily by the increasing energy request body, depending on type and intensity of sports activity. In this research blood serum lipids were studied depending on the orientation of the training process. A total of 108 athletes (men and women) aged 15 to 20 years of different sports qualification (I sports category, Candidate Master of Sports and Master of Sports) were examined, and a control group of 28 persons of the same age and gender. Depending of the direction of the training process there were isolated 3 groups: cyclical sport that develops mainly endurance (academic rowing); sports of complex nature (football, volleyball, handball and Nordic combined); and complex coordinated sports (artistic gymnastics). Were studied: total cholesterol, high density lipoproteins, low-density lipoproteins, atherogenic coefficient and triglycerides. The study was conducted in the preparatory period of the training cycle. The research had shown that the level of blood lipids depends on the orientation of training process and sports training. The most marked reduction of total cholesterol and high-density lipoproteins has been observed both in men and women in cyclic kinds of sports, developing mainly stamina that indicates that intense exercise in athletes who train primarily for endurance, cause the connection of lipids to the processes of energy supply of muscle activity.

REACH: An Efficient MAC Protocol for RF Energy Harvesting in Wireless Sensor Network

This paper proposes a MAC protocol for Radio Frequency (RF) energy harvesting in Wireless Sensor Networks (WSN). In the conventional RF energy harvesting methods, an Energy Transmitter (ET) operates in a passive manner. An ET transmits RF energy signals only when a sensor with depleted energy sends a Request-for-Energy (RFE) message. Unlike the conventional methods, an ET in the proposed scheme can actively send RF energy signals without RFE messages. An ET determines the active energy signal transmission according to the consequence of the passive energy harvesting procedures. To transmit RF energy signals without request from sensors, the ET participates in a contention-based channel access procedure. Once the ET successfully acquires the channel, it sends RF energy signals on the acquired channel during Short Charging Time (SCT). The proposed scheme determines the length of SCT to minimize the interruption of data communication. We compare the performance of the proposed protocol with RF-MAC protocol by simulation. The simulation results show that the proposed protocol can increase the energy harvesting rate by 150% with 8% loss of network throughput compared to RF-MAC. In addition, the proposed protocol can increase the lifetime of WSN because of the active energy signal transmission method.

Gas fired boilers: Perspective for near future fuel composition and impact on burner design process

The advancements on gas boiler technology run in parallel with the growth of renewable energy production. The renewable production will impact on the fuel gas quality, since the gas grid will face an increasing injection of alternative fuels (biogas, biomethane, hydrogen). Biogas allows producing energy with a lower CO 2 impact; hydrogen production by electrolysis can mitigate the issues related to the mismatch between energy production by renewable and energy request. These technologies will contribute to achieve the renewable production targets, but the impact on whole fuel gas production-to-consumption chain must be evaluated. In the first part of this study, the Authors present the future scenario of the grid gas composition and the implications on gas fed appliances. Given that the widely used premixed burners are currently designed mainly by trial and error, a broader fuel gas quality range means an additional hitch on this design process. A better understanding and structuring of this process is helpful for future appliance-oriented developments. The Authors present an experimental activity on a premixed condensing boiler setup. A test protocol highlighting the burners' flexibility in terms of mixture composition is adopted and the system fuel flexibility is characterized around multiple reference conditions.

Light and Heavy Energy Refurbishments of Mediterranean Offices. Part II: Cost-optimal Energy Renovation of an Institutional Building

A previous study has evidenced the poor energy performances of a building owned by the University of Naples Federico II. In detail, a reliable energy audit, by means of calibrated input, has been performed, and it revealed energy requests, polluting emissions and energy costs very high. By taking into consideration the exemplary role of the public hand, according to the EU Directives 2010/31/EE and 2012/27/EU, here a cost-optimal energy refurbishment is proposed, by analysing several energy efficiency measures, firstly singularly analysed and then combined in order to evaluate the super-positon effect.

µGRIMOIRE: A Tool for Smart Micro Grids Modelling and Energy Profiling

The construction of a usable, formal, and extensible modeller and simulator for Smart Energy Grids is of a paramount importance in the industrial settings. Final users are interested in deploying effective smart-home configurations able to satisfy energy requests in the most economical way. Hence, a tool able to forecast both energy consumption and related costs of a smart-home configuration is needed. In this paper, the μGRIMOIRE (micro GRId MOdelling envIRonmEnt) toolset is presented. This tool is based on the well-known model-driven paradigm and its successful applications in the generation of formal/quantitative models for complex systems. By using a Domain Specific Modelling Language, a final user can define a smart-home system configuration and energy saving logics. Then, the tool offers the possibility of evaluating the desired user metrics by translating the model into a Fluid Stochastic Petri Net model representing both discrete and continuous variables.

Experimental and numerical study of thin ring and annular fin effects on improving the ice formation in ice-on-coil thermal storage systems

Cooling load demand during the warmest hours of summer days leads to an increase in electrical energy request, intensifying the peak load. Thus, to reduce electrical energy consumption in peak hours, cold energy storage systems are used. One of the most common methods in this area is ice on coil energy storage that deals with the problem of heat transfer rate decreasing during charging. In this paper, performance of two heat transfer enhancement methods including usage of thin rings and annular fins around coils are compared. First, the thermal behavior of the system is simulated and the sensitivity analysis is performed. Then, design parameters for experimental set up are selected based on the results obtained from the sensitivity analysis. For the case of annular fins, results show that the optimum operating point is deduced when the distance between two adjacent fins becomes 50mm. According to the numerical results, the experimental tests are designed. It is shown that ice formation in the cases of using annular fins and rings will be correspondingly 21% and 34% higher with respect to the bare tube. Besides, freezing will be sped up by 15% in the case of using finned and ringed tubes. Accordingly, diagonal thin rings have better performance with respect to annular fins. The reason is that the ice formation rate in the central region between the tubes is enhanced due to the presence of thin rings in this region.

Energetic Sustainability Using Renewable Energies in the Mediterranean Sea

The paper is focused on the analysis of the electrical energy sector in the Maltese islands, focusing on the employment of Renewable Energies in order to increase its energy independence. The main renewable source here proposed is wave energy: thanks to its strategic position, Malta will be able to generate electrical energy through the use of an innovative type of Wave Energy Converter (WEC) based on the prototype of linear generator designed and developed by the University of Palermo. This new technology will be able to cut down the electrical energy production from traditional power plants and, consequently, the greenhouse gas emissions (GHG). Wave energy source and off-shore photovoltaic (PV) technology are proposed here. Particularly, the installation of 18 wave farms, for a total installed capacity of 130 MW, will generate about 5.7% of Malta’s energy requests in 2025, while the installation of 60 MW of off-shore PV will generate about 4.4%.

Geothermal source heat pump performance for a greenhouse heating system: an experimental study

Greenhouses play a significant function in the modern agriculture economy even if require great amount of energy for heating systems. An interesting solution to alleviate the energy costs and environmental problems may be represented by the use of geothermal energy. The aim of this paper, based on measured experimental data, such as the inside greenhouse temperature and the heat pump performance (input and output temperatures of the working fluid, electric consumption), was the evaluation of the suitability of low enthalpy geothermal heat sources for agricultural needs such as greenhouses heating. The study was carried out at the experimental farm of the University of Bari, where a greenhouse was arranged with a heating system connected to a ground-source heat pump (GSHP), which had to cover the thermal energy request. The experimental results of this survey highlight the capability of the geothermal heat source to ensue thermal conditions suitable for cultivation in greenhouses even if the compressor inside the heat pump have operated continuously in a fluctuating state without ever reaching the steady condition. Probably, to increase the performance of the heat pump and then its coefficient of performance within GSHP systems for heating greenhouses, it is important to analyse and maximise the power conductivity of the greenhouse heating system, before to design an expensive borehole ground exchanger. Nevertheless, according to the experimental data obtained, the GSHP systems are effective, efficient and environmental friendly and may be useful to supply the heating energy demand of greenhouses.

Two-Stage Mechanism for Massive Electric Vehicle Charging Involving Renewable Energy

Integrating massive electric vehicles (EVs) into the power grid requires charging to be coordinated to reduce energy costs and the peak-to-average ratio (PAR) of the system. The coordination becomes more challenging when the highly fluctuant renewable energies constitute a significant portion of the power resources. To tackle this problem, a novel two-stage EV charging mechanism is designed in this paper, which mainly includes three parts. At the first stage, based on the prediction of future energy requests and considering the elastic charging property of EVs, an offline optimal energy generation scheduling problem is formulated and solved in a day-ahead manner to determine the energy generation in each time slot the next day. Then, at the second stage, based on the planned energy generation day-ahead, an adaptive real-time charging strategy is developed to determine the charging rate of each vehicle in a dynamic manner. Finally, we develop a charging rate compression (CRC) algorithm, which tremendously reduces the complexity of the problem solving. The fast algorithm supports real-time operations and enables the large-scale small-step scheduling more efficiently. Simulation results indicate that the proposed scheme can help effectively save energy costs and reduce the system PAR. Detailed evaluations on the impact of renewable energy uncertainties show that our proposed approach performs well in enhancing the system fault tolerance against uncertainties and the noises of real-time data. We further extend the mechanism to track a given load profile and handle the scenario where EVs only have several discrete charging rates. As a universal methodology, the proposed scheme is not restricted to any specific data traces and can be easily applied to many other cases as well.