För att pådriva utvecklingen mot ett mer hållbart Gävle kommer Gävle Energi AB implementera en ny säsongsbaserad kapacitetsmodell ifrån årsskiftet 2019. Som ska skapa ekonomiska incitament för energieffektivisering i fastigheter inom Gävles fjärrvärmenät. Denna studie kartlägger värmeenergianvändningen i en fastighet som riskerar en förhöjd totalkostnad för fjärrvärmen till följd av den nya prismodellen. Målet med studien är att reducera värmeenergianvändningen utan att investera i fastigheten, vilket möjliggörs genom att värmeenergitillförseln till fastigheten regleras. Genom att programmera ett års historisk data av temperaturer, solinstrålning, el- och värmeeffekter så prognostiseras värmetillförseln på samma sätt som fastighetens styrsystem Kabona Eco-pilot. Styrsystemet tillämpar en flytande inomhustemperatur vilket bidrar till att fastighetens värmetröghet inkluderas i värmeregleringen. Studien inkluderar två prognoser som jämförs med den verkliga värmeenergianvändningen och den nya kapacitetsprismodellen. Prognos 1 är baserad på en årscykel och prognos 2 baseras på intervallet november 2017 till mars 2018. Syftet med prognos 2 är att tillämpa en strategisk värmelaststyrning för att sänka värmekapacitetsbehovet vid -10˚C. Prognos 1 indikerar att en värmeenergibesparing på 26% kan uppnås. Prognosen tar hänsyn till solinstrålning och vissa delar utav den interna värmegenereringen. Utan att Diös fastigheter AB investerat i några energibesparingsåtgärder prognostiseras en besparing på 44 700SEK under ett års drift. Fastigheten har idag energiprestanda energiklass D och kommer efter besparingen att kunna uppnå energiklass C. Prognos 2 indikerar att en kapacitetsreducering kan uppnås motsvarande 46,1% samtidigt som den rörliga värmeenergianvändningen minskar. Totalt sett finns en besparingspotential på 47,8% och 216 700 SEK under perioden 2017-11-01 till 2018-03-31, dock med följd att inomhustemperaturen sjunker. / In order to continue the development towards a more sustainable city of Gävle, Gävle Energi AB will implement a new season-based capacity model by the year 2019. It creates economic incentives for energy efficiency in real estate’s within Gävle's district heating network. This report investigates how the heat energy is used for a building that risks an increased heat energy cost, due to the new pricing model. The aim of the study is to reduce the heat energy usage without investing in the building, which is made possible by regulating the thermal energy supply to the building. By programming one year of historical data of temperatures, solar radiation, power- and heat effects the heat supply is forecasted the same way as the building's control system Kabona Eco-pilot is working. The control system applies a floating indoor temperature, which contribute that the thermal inertia of the building is included in the heat load control. The study includes two forecasts that are compared to the actual heat energy use and the new capacity price model. Forecast 1 is based on an annual cycle and forecast 2 is based on the range of November 2017 to Mars 2018. The aim of forecast 2 is to apply a strategic heat load control to reduce the heat capacity needed at -10˚C. Forecast 1 indicates a potential heat energy saving of 26% even though Diös Fastigheter AB does not invest in any energy saving technology. A saving of approximately 44 700 SEK is forecasted for the annual cycle. The building has an energy class D and has the potential to achieve energy class C after the change of control system parameters. Forecast 2 indicates a potential capacity reduction corresponding to 46,1% while the variable heat energy consumption decreases. Overall, there is an approximated heat energy saving potential of 47,8%, which corresponds to 216 700 SEK, during the range of 2017-11-01 to 2018-03-31. Due to the consequence of a lower indoor temperature.

Human body temperature is an important indicator of physical performance and condition in terms of comfort, heat or cold stress. The aim of this research was to develop Temperature Sensing Fabric (TSF) for continuous temperature measurement in healthcare applications. The study covers the development and manufacture of TSF by embedding fine metallic wire into the structure of textile material using a commercial computerised knitting machine. The operational principle of TSF is based on the inherent propensity of a metal wire to respond to changes in temperature with variation in its electrical resistance. Over 60 TSF samples were developed with combinations of different sensing elements, two inlay densities and highly textured polyester yarn as the base material. TSF samples were created using either bare or insulated wires with a range of diameters from 50 to 150 μm and metal wires of nickel, copper, tungsten, and nickel coated copper. In order to investigate the Temperature-Resistance (T-R) relationship of TSF samples for calibration purposes, a customised test rig was developed and monitoring software was created in the LabVIEW environment, to record the temperature and resistance signals simultaneously. TSF samples were tested in various thermal environments, under laboratory conditions and in practical wear trials, to analyse the relationship between the temperature and resistance of the sensing fabric and to develop base line specifications such as sensitivity, resistance ratio, precision, nominal resistance, and response time; the influence of external parameters such as humidity and strain were also monitored. The regression uncertainty was found to be less than in ±0.1°C; the repeatability uncertainty was found to be less than ±0.5°C; the manufacturing uncertainty in terms of nominal resistance was found to be ± 2% from its mean. The experimental T-R relationship of TSF was validated by modelling in the thermo-electrical domain in both steady and transient states. A maximum error of 0.2°C was found between the experimental and modelled T-R relationships. TSF samples made with bare wire sensing elements showed slight variations in their resistance during strain tests, however, samples made with insulated sensing elements did not demonstrate any detectable strain-dependent-resistance error. The overall thermal response of TSF was found to be affected by basal fabric thickness and mass; the effect of RH was not found to be significant. TSF samples with higher-resistance sensing elements performed better than lower-resistance types. Furthermore, TSF samples made using insulated wire were more straightforward to manufacture because of their increased tensile strength and exhibited better sensing performance than samples made with bare wire. In all the human body wear trials, under steady-state and dynamic conditions both sensors followed the same trends and exhibited similar movement artifacts. When layers of clothing were worn over the sensors, the difference between the response of the TSF and a high-precision reference temperature were reduced by the improved isothermal conditions near the measurement site.

Hydropower is the most important power balancing resource in the Swedish electrical power system, regulating the power supply to match the load. Consequently, several hydropower plants have periods of stand-by operation where the power production is absent but where several devices within a plant are still active. Such a device is the step-up power transformer, which during stand-by operation still generates no-load energy losses. These losses can accumulate to a considerable amount of energy and costs during the long technical lifetime of the apparatus. One option to minimize these no-load energy losses is by turning the transformer off when its generating unit is in stand-by operation. However, when this transformer operational change has been explained to experts in the field, the most common response has been that a more frequent reenergizing of a transformer leads to higher risks for errors or transformer breakdowns. This study aimed to analytically investigate three effects from this operational change. First, the potential of fatigue failure for the windings due to the increased sequences of inrush current. Secondly, the thermal cycling as a consequence of change in present losses. Lastly, the energy and economic saving potentials for hydropower plants where this operational adjustment is applied. The study used both established as well as analytical tools explicitly created for this study. These were then applied on currently active transformers in different plant categories in Fortum’s hydropower fleet. The study primarily showed three things. Firstly, risk of fatigue failure due to the increased presence of inrush currents did not affect the transformer’s technical lifetime. Secondly, the thermal cycling changes were slightly larger with absent no-load losses during stand-by operation. The average temperature for the transformer decreased, which in general is seen as a positive indicator for a longer insulation lifetime and thus the transformer’s technical lifetime. Finally, the created frameworks showed the potential of saving energy and money for all plant categories, where the potential grew with the installed production capacity and the stand-by operation timeshare. Despite the simplifications made to describe the complex reality of a transformer operating in a hydropower plant, this thesis contributes to lay a foundation for future investigation of an easy adjustment to avoid unnecessary energy losses and costs for transformers in hydropower plants