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.

Energy systems analysis of transboundary river basins in a nexus approach: the Sava river basin study case

Resource management policies are frequently designed and planned to target specific needs of particular sectors, without taking into account the interests of other sectors who share the same resources. In a climate of resource depletion, population growth, increase in energy demand and climate change awareness, it is of great importance to promote the assessment of intersectoral linkages and, by doing so, understand their effects and implications. This need is further augmented when common use of resources might not be solely relevant at national level, but also when the distribution of resources ranges over different nations. This dissertation focuses on the study of the energy systems of five south eastern European countries, which share the Sava River Basin, using a water-food(agriculture)-energy nexus approach. In the case of the electricity generation sector, the use of water is essential for the integrity of the energy systems, as the electricity production in the riparian countries relies on two major technologies dependent on water resources: hydro and thermal power plants. For example, in 2012, an average of 37% of the electricity production in the SRB countries was generated by hydropower and 61% in thermal power plants. Focusing on the SRB, in terms of existing installed capacities, the basin accommodates close to a tenth of all hydropower capacity while providing water for cooling to 42% of the net capacity of thermal power currently in operation in the basin. This energy-oriented nexus study explores the dependency on the basin’s water resources of the energy systems in the region for the period between 2015 and 2030. To do so, a multi-country electricity model was developed to provide a quantification ground to the analysis, using the open-source software modelling tool OSeMOSYS. Three main areas are subject to analysis: first, the impact of energy efficiency and renewable energy strategies in the electricity generation mix; secondly, the potential impacts of climate change under a moderate climate change projection scenario; and finally, deriving from the latter point, the cumulative impact of an increase in water demand in the agriculture sector, for irrigation. Additionally, electricity trade dynamics are compared across the different scenarios under scrutiny, as an effort to investigate the implications of the aforementioned factors in the electricity markets in the region.

Design of advanced reverse osmosis and nanofiltration membranes for water purification

Most commercially available reverse osmosis (RO) and nanofiltration (NF) membranes are based on the thin film composite (TFC) aromatic polyamide membranes. However, they have several disadvantages including low resistance to fouling, low chemical and thermal stabilities and limited chlorine tolerance. To address these problems, advanced RO/NF membranes are being developed from polyimides for water and wastewater treatments. The following three projects have resulted from my research. (1) Positively charged and solvent resistant NF membranes. The use of solvent resistant membranes to facilitate small molecule separations has been a long standing industry goal of the chemical and pharmaceutical industries. We developed a solvent resistant membrane by chemically cross-linking of polyimide membrane using polyethylenimine. This membrane showed excellent stability in almost all organic solvents. In addition, this membrane was positively charged due to the amine groups remaining on the surface. As a result, high efficiency (> 95%) and selectivity for multivalent heavy metal removal was achieved. (2) Fouling resistant NF membranes. Antifouling membranes are highly desired for “all” applications because fouling will lead to higher energy demand, increase of cleaning and corresponding down time and reduced life-time of the membrane elements. For fouling prevention, we designed a new membrane system using a coating technique to modify membrane surface properties to avoid adsorption of foulants like humic acid. A layer of water-soluble polymer such as polyvinyl alcohol (PVA), polyacrylic acid (PAA), polyvinyl sulfate (PVS) or sulfonated poly(ether ether ketone) (SPEEK), was adsorbed onto the surface of a positively charged membrane. The resultant membranes have a smooth and almost neutrally charged surface which showed better fouling resistance than both the positively charged NF membranes and commercially available negatively charged NTR-7450 membrane. In addition, these membranes showed high efficiency for removal of multivalent ions (> 95% for both cations and anions). Therefore, these antifouling surfaces can be potentially used for water softening, water desalination and wastewater treatment in a membrane bioreactor (MBR) process. (3) Thermally stable RO membranes. Commercial RO membranes cannot be used at temperature higher than 45°C due to the use of polysulfone substrate, which often limits their applications in industries. We successfully developed polyimides as the membrane substrate for thermally stable RO membranes due to their high thermal resistance. The polyimide-based composite polyamide membranes showed desalination performance comparable to the commercial TFC membrane. However, the key advantage of the polyimide-based membrane is its high thermal stability. As the feed temperature increased from 25oC to 95oC, the water flux increased 5 - 6 times while the salt rejection almost kept constant. This membrane appears to provide a unique solution for hot water desalination and also a feasible way to improve the water productivity by increasing the operating temperature without any drop in salt rejection.

Renewable energy scenarios for South Karelia – non-industrial energy demands

Tässä diplomityössä tarkastellaan täysin uusiutuvaa energiajärjestelmää Etelä-Karjalan maakunnan alueella, mikä onkin jo tällä hetkellä Suomen uusiutuvin maakunta. Diplomityössä tarkastellaan julkisen sektorin, liikenteen ja rakennusten energian kulutusta mutta teollisuuden energiankäyttö jätetään tarkastelun ulkopuolelle. Työssä tutustutaan tämän hetken Etelä-Karjalan energiajärjestelmään ja sen perusteella tehdään referenssi-skenaario. Tulevaisuuden skenaariot tehdään vuosille 2030 ja 2050. Tulevaisuuden skenaarioissa muutos keskittyy järjestelmän sähköistymiseen ja uusiutuvien tuotantomuotojen integroimiseen järjestelmään. Sähköistyminen kasvattaa sähkönkulutusta, joka pyritään kattamaan uusiutuvilla tuotantomuodoilla, lähinnä tuuli- ja aurinkovoimalla. Liikennesektori rajataan kumipyöräliikenteeseen ja sen muutos tulee olemaan haastavin ja aikaa vievin. Muutokseen pyritään liikennepolttoaineiden tuotannolla maakunnassa sekä sähköautoilulla. Uusiutuva energiajärjestelmä tarvitsee tuotannon ja kysynnän joustoa sekä älyä järjestelmältä. Työssä tarkastellaan myös järjestelmän kustannuksia sekä työllisyysvaikutuksia.

Análisis de las simulaciones del proceso de deshidratación del gas natural con Aspen Hysys y Aspen Plus

El gas natural ha tomado un rol estratégico importante en el suministro de energía a nivel mundial como consecuencia de la creciente demanda global de energía. El agua es probablemente el componente indeseable más común en el gas natural no tratado ya que su presencia puede ocasionar la formación de hidratos y problemas de corrosión. Debido a las potenciales consecuencias costosas, el gas debe ser sometido a procesos de acondicionamiento a fin de alcanzar las especificaciones requeridas para su venta, transporte hacia los centros de distribución y consumo final. En los últimos años, la simulación de procesos está jugando un papel muy importante en la industria del gas y petróleo como una herramienta adecuada y oportuna para el diseño, caracterización, optimización y monitoreo del funcionamiento de procesos industriales. En el presente trabajo se describe el desarrollo de dos simulaciones estacionarias del proceso de deshidratación de gas natural por absorción con trietilenglicol (TEG), empleando los simuladores comerciales de procesos Aspen HYSYS V8.3 y Aspen PLUS V8.2. La composición del gas natural, la configuración del proceso y las condiciones de operación empleadas en los cálculos y la simulación son típicas de los yacimientos y plantas de acondicionamiento de la provincia de Salta (Argentina).

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.

The reality of cross-disciplinary energy research in the United Kingdom:a social science perspective

Cross-disciplinary research is essential in understanding and reducing energy usage, however the reality of this collaboration comes with many challenges. This paper provides an insight into the integration of social science in energy research, drawing on the expertise and first hand experiences of a range of social science researchers (predominantly Early Career Researchers (ECRs)) working on UK cross-disciplinary projects in energy demand. These researchers, participants in a workshop dedicated to understanding the integration of social science in energy research, identified four groups of challenges to successful integration: Differing expectations of the role of social scientists; Working within academia; Feeling like a valued member of the team; and Communicating and comprehension between disciplines. Suggestions of how to negotiate those challenges included: Management and planning; Increasing contact; Sharing experience; and Understanding team roles. The paper offers a definition of ‘success’ in cross-disciplinary energy research from the perspective of social science ECRs, comprising external, internal and personal components. Using the logics of interdisciplinarity, this paper suggests that integration of the social sciences in the projects discussed may be partial at best and highlights a need to recognise the challenges ECRs face, in order to achieve full integration and equality of disciplines.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia

Measurement of standby power for selected electrical appliances in Australia

High growth in the uptake of electrical appliances is accounting for a significant increase in electricity consumption globally. In some developed countries, standby energy alone may account for about 10% of residential electricity use. The standby power for many appliances used in Australia is still well above the national goal of 1 W or less. In this paper, field measurements taken of standby power and operating power for a range of electrical appliances are presented. It was found that the difference between minimum value and maximum value of standby power could be quite large, up to 22.13 W for home theatre systems, for example. With the exception of home audio systems, however, the annual operating energy used by most electrical appliances was generally greater than the annual standby energy. Consumer behaviour and product choice can have a significant impact on standby power and operating power, which influences both energy demand and greenhouse gas emissions.

Protection of distributed generation interfaced networks

With the rapid increase in electrical energy demand, power generation in the form of distributed generation is becoming more important. However, the connections of distributed generators (DGs) to a distribution network or a microgrid can create several protection issues. The protection of these networks using protective devices based only on current is a challenging task due to the change in fault current levels and fault current direction. The isolation of a faulted segment from such networks will be difficult if converter interfaced DGs are connected as these DGs limit their output currents during the fault. Furthermore, if DG sources are intermittent, the current sensing protective relays are difficult to set since fault current changes with time depending on the availability of DG sources. The system restoration after a fault occurs is also a challenging protection issue in a converter interfaced DG connected distribution network or a microgrid. Usually, all the DGs will be disconnected immediately after a fault in the network. The safety of personnel and equipment of the distribution network, reclosing with DGs and arc extinction are the major reasons for these DG disconnections. In this thesis, an inverse time admittance (ITA) relay is proposed to protect a distribution network or a microgrid which has several converter interfaced DG connections. The ITA relay is capable of detecting faults and isolating a faulted segment from the network, allowing unfaulted segments to operate either in grid connected or islanded mode operations. The relay does not make the tripping decision based on only the fault current. It also uses the voltage at the relay location. Therefore, the ITA relay can be used effectively in a DG connected network in which fault current level is low or fault current level changes with time. Different case studies are considered to evaluate the performance of the ITA relays in comparison to some of the existing protection schemes. The relay performance is evaluated in different types of distribution networks: radial, the IEEE 34 node test feeder and a mesh network. The results are validated through PSCAD simulations and MATLAB calculations. Several experimental tests are carried out to validate the numerical results in a laboratory test feeder by implementing the ITA relay in LabVIEW. Furthermore, a novel control strategy based on fold back current control is proposed for a converter interfaced DG to overcome the problems associated with the system restoration. The control strategy enables the self extinction of arc if the fault is a temporary arc fault. This also helps in self system restoration if DG capacity is sufficient to supply the load. The coordination with reclosers without disconnecting the DGs from the network is discussed. This results in increased reliability in the network by reduction of customer outages.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.

Utilization of bio-oil for cooking and lighting

Considerable attention has been given to development of renewable energy due to imminent depletion of fossil fuels and environmental concerns over global warming. Therefore, it is necessary to find out all the available alternative sources of energy immediately to meet the increasing energy demand of Bangladesh. Among the available alternative sources of energy in Bangladesh bio-oil is recognized to be a promising alternative energy source. In these days bio-oil is merely used in vehicles and power plants after some up gradation .However, it is not used for domestic purposes like cooking and lighting due to it’s high density and viscosity. A gravity stove is designed to use this high dense and viscous bio-oil for cooking purpose. Efficiency of gravity stove with high dense and viscous bio-oil (karanj) is 11.81% which of kerosene stove is 17.80% also the discharge of karanj oil through gravity stove is sufficient for continuous burning.

A basis for inquiry into policy considerations for increasing the application of biophilic urbanism

Urban design that harnesses natural features (such as green roofs and green walls) to improve design outcomes is gaining significant interest, particularly as there is growing evidence of links between human health and wellbeing, and contact with nature. The use of such natural features can provide many significant benefits, such as reduced urban heat island effects, reduced peak energy demand for building cooling, enhanced stormwater attenuation and management, and reduced air pollution and greenhouse gas emissions. The principle of harnessing natural features as functional design elements, particularly in buildings, is becoming known as ‘biophilic urbanism’. Given the potential for global application and benefits for cities from biophilic urbanism, and the growing number of successful examples of this, it is timely to develop enabling policies that help overcome current barriers to implementation. This paper describes a basis for inquiry into policy considerations related to increasing the application of biophilic urbanism. The paper draws on research undertaken as part of the Sustainable Built Environment National Research Centre (SBEnrc) In Australia in partnership with the Western Australian Department of Finance, Parsons Brinckerhoff, Green Roofs Australasia, and Townsville City Council (CitySolar Program). The paper discusses the emergence of a qualitative, mixed-method approach that combines an extensive literature review, stakeholder workshops and interviews, and a detailed study of leading case studies. It highlights the importance of experiential and contextual learnings to inform biophilic urbanism and provides a structure to distil such learnings to benefit other applications.

A simulation framework for smart meter security evaluation

The evolution of classic power grids to smart grids creates chances for most participants in the energy sector. Customers can save money by reducing energy consumption, energy providers can better predict energy demand and environment benefits since lower energy consumption implies lower energy production including a decrease of emissions from plants. But information and communication systems supporting smart grids can also be subject to classical or new network attacks. Attacks can result in serious damage such as harming privacy of customers, creating economical loss and even disturb the power supply/demand balance of large regions and countries. In this paper, we give an overview about the German smart measuring architecture, protocols and security. Afterwards, we present a simulation framework which enables researchers to analyze security aspects of smart measuring scenarios.