Wireless Networks with Energy Harvesting and Power Transfer: Joint Power and Time Allocation

In this letter, we consider wireless powered communication networks which could operate perpetually, as the base station (BS) broadcasts energy to the multiple energy harvesting (EH) information transmitters. These employ “harvest then transmit” mechanism, as they spend all of their energy harvested during the previous BS energy broadcast to transmit the information towards the BS. Assuming time division multiple access (TDMA), we propose a novel transmission scheme for jointly optimal allocation of the BS broadcasting power and time sharing among the wireless nodes, which maximizes the overall network throughput, under the constraint of average transmit power and maximum transmit power at the BS. The proposed scheme significantly outperforms “state of the art” schemes that employ only the optimal time allocation. If a single EH transmitter is considered, we generalize the optimal solutions for the case of fixed circuit power consumption, which refers to a much more practical scenario.

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

A novel methodology for analysis of large scale interconnected power and gas systems

The European Union continues to exert a large influence on the direction of member states energy policy. The 2020 targets for renewable energy integration have had significant impact on the operation of current power systems, forcing a rapid change from fossil fuel dominated systems to those with high levels of renewable power. Additionally, the overarching aim of an internal energy market throughout Europe has and will continue to place importance on multi-jurisdictional co-operation regarding energy supply. Combining these renewable energy and multi-jurisdictional supply goals results in a complicated multi-vector energy system, where the understanding of interactions between fossil fuels, renewable energy, interconnection and economic power system operation is increasingly important. This paper provides a novel and systematic methodology to fully understand the changing dynamics of interconnected energy systems from a gas and power perspective. A fully realistic unit commitment and economic dispatch model of the 2030 power systems in Great Britain and Ireland, combined with a representative gas transmission energy flow model is developed. The importance of multi-jurisdictional integrated energy system operation in one of the most strategically important renewable energy regions is demonstrated.

Integrated Optimal Power Flow for Distribution Networks in Local and Urban Scales

This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Moral Emotions in Palliative Care: Empirical Insights from Austria and Canada

Research aims: Moral emotions as one specific group of emotions play a vital role in delivering palliative care as e.g. ethical issues and moral distress belong to daily routine.
Moral emotions are oriented to the welfare of other persons or the society as a whole. To better understand moral emotions in Palliative Care the aims of the presented study are to ana- lyze care situations from Austria and Canada in different care settings and identify families of moral emotions on one hand and describe influencing contextual factors on the other hand. Methods: Within a qualitative study design a reanalysis of Austrian narratives on ethical issues and Canadian narra- tives on moral distress were conducted. Data in Austria encompass 36 narratives that were generated through qual- itative questionnaires in nursing homes. Canadian data are based on qualitative interviews with home care palliative specialists and encompass 47 critical incidents. The reanal- ysis of data was conducted with narrative analysis. Results: Preliminary results show that moral emotions in palliative care can be found in families around “empathy and relatedness”, “sadness, isolation and bereavement”, “anger, frustration and powerlessness”, “guilt and shame” and “being touched and feel close”. Contextual factors influencing moral emotions can be summarized as “suffer- ing and decline of client”, “expectations and dynamics of family”, “structural conflicts and power issues” and “lack of resources and information”.
Conclusion: The diversity of moral emotions reflects the everyday experiences in palliative care. It became obvious that most of the moral emotions that have been expressed appear to be interconnected within a bundle of other emo- tions. Contextual factors influencing moral emotions in pal- liative care are relatively independent of care settings. In Palliative Care moral emotions and their contextual factors constitute an important source of insight for reflection in organizational ethics.

Effect of weather and the hybrid energy storage on the availability of standalone microgrid

This paper presents a model for availability analysis of standalone hybrid microgrid. The microgrid used in the study consists of wind, solar storage and diesel generator. Boolean driven Markov process is used to develop the availability of the system in the proposed method. By modifying the developed model, the relationship between the availability of the system with the fine (normal) weather and disturbed (stormy) weather durations are analyzed. Effects of different converter technologies on the availability of standalone microgrid were investigated and the results have shown that the availability of microgrid increased by 5.80 % when a storage system is added. On the other hand, the availability of standalone microgrid could be overestimated by 3.56 % when weather factor is neglected. In the same way 200, 500 and 1000 hours of disturbed weather durations reduced the availability of the system by 5.36%, 9.73% and 13.05 %, respectively. In addition, the hybrid energy storage cascade topology with a capacitor in the middle maximized the system availability.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

Damping Torque Analysis of Power Systems with DFIGs for Wind Power Generation

A grid-connected DFIG for wind power generation can affect power system small-signal angular stability in two ways: by changing the system load flow condition and dynamically interacting with synchronous generators (SGs). This paper presents the application of conventional method of damping torque analysis (DTA) to examine the effect of DFIG’s dynamic interactions with SGs on the small-signal angular stability. It shows that the effect is due to the dynamic variation of power exchange between the DFIG and power system and can be estimated approximately by the DTA. Consequently, if the DFIG is modelled as a constant power source when the effect of zero dynamic interactions is assumed, the impact of change of load flow brought about by the DFIG can be determined. Thus the total effect of DFIG can be estimated from the result of DTA added on that of constant power source model. Applications of the DTA method proposed in the paper are discussed. An example of multi-machine power systems with grid-connected DFIGs are presented to demonstrate and validate the DTA method proposed and conclusions obtained in the paper.

Balancing Rights in Religious Education through Collaboration and Dialogue

While the right of parents to educate their children in their religious or philosophical conviction is recognised in Human Rights instruments (e.g. CoE 1952, protocol 1), educators must also attend to the right of a child to autonomy (UN 1989, Article 12.1) and the right of liberal democratic states to reproduce values of equity and freedom. This paper argues that certain forms of inter-religious dialogue and/or inter-religious collaborative learning can assist educators in balancing these rights where religion has significant influence and power over the management of schools and/or the curriculum. It is argued that in addition to the learning benefits which may result, the use of collaboration and dialogue goes some way in addressing three philosophical criticisms of religious education: first that religiously separate and religiously based education pays insufficient attention to the rights of children and, secondly, is likely to contribute to social fragmentation; and third, pupils will lack the skills to overcome prejudice or intolerance where they have no experience of others as a result of separate schooling or from a religiously narrow curriculum, and the latter may in fact support intolerant views. A rationale is developed that asserts the value of collaboration or dialogue as a pedagogical strategy that can, to some degree, mitigate potential negative outcomes from religious education. This argument is further supported with reference to a range of empirical studies.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

The use of binary mixtures of 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide and aliphatic nitrile solvents as electrolyte for supercapacitors

Abstract The development of high voltage electrolytes is one of the key aspects for increasing both energy and power density of electrochemical double layer capacitors (EDLCs). The usage of blends of ionic liquids and organic solvents has been considered as a feasible strategy since these electrolytes combine high usable voltages and good transport properties at the same time. In this work, the ionic liquid 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide ([Pyrr14][TFSI]) was mixed with two nitrile-based organic solvents, namely butyronitrile and adiponitrile, and the resulting blends were investigated regarding their usage in electrochemical double layer capacitors. Both blends have a high electrochemical stability, which was confirmed by prolonged float tests at 3.2 V, as well as, good transport properties. In fact, the butyronitrile blend reaches a conductivity of 17.14 mS·cm−1 and a viscosity of 2.46 mPa·s at 20 °C, which is better than the state-of-the-art electrolyte (1 mol·dm−3 of tetraethylammonium tetrafluoroborate in propylene carbonate).