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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Energy and cost analysis of household electricity efficiency improvements in a rental apartment building

Panigrahi, Manaswita January 2012 (has links)
In this thesis potential for (final and primary) energy and CO2 emission reductions and cost effectiveness of replacing existing household electric appliances and light bulbs with most popular or most energy efficient appliances in a multifamily apartment building in Växjö city is studied. The results showed that there is significant potential to reduce electricity demand and thereby to reduce primary energy use and CO2 emissions. The greatest potential lies with replacing existing incandescent bulbs with LED bulbs, while the lowest savings seem to be with replacement of microwave ovens. Assuming that reduced electricity demand reduces electricity generation in coal-based steam turbine (CST) technology, annually about 63 MWh of primary energy and 25 ton CO2 emissions could be reduced from the investigated building if the existing refrigerator/freezer, stove/oven, microwave oven, televisions and light bulbs are replaced with the most energy efficient alternatives available in the market today. Also, the results from ‚discounted payback period‛ and ‚cost of conserved energy‛ analyses also showed that it is cost-effective to install the most energy efficient appliances. This study for a single building is based on limited number of interviews, selected appliance types, and number of assumptions about marginal electricity production systems. To generalize the results more such studies in different conditions with measurement of actual energy use of all the household appliances should be conducted, which would help to fully understand the potential of primary energy savings and CO2 emission reductions in Swedish apartment buildings.
2

Empirical modeling of the thermal systems in an apartment : A study of the relationship between household electricity consumption and indoor temperature

Wallentinsson, Måns, Jacob, Rutfors January 2020 (has links)
In this study, linear and non-linear models were trained on real data to mimic the relationship between household electricity consumption and indoor temperature, in the rooms of an apartment in downtown Stockholm. The aim was to better understand this relationship and to distinguish any divergence between the different rooms. With data from two weeks of measurements, the models proved to perform well when tested on validation data for almost all rooms, only showing performance dips for the middle room. A noticeable correlation between the electricity consumption and the indoor temperature was observed for all rooms except the bedroom. However, the benefits of using this information to predict the indoor temperature are limited and differ between the rooms. The household electricity consumption primarily brought beneficial information to the kitchen models, where most of the heat generating appliances were located. It was found that linear models were sufficient to represent the thermal systems of the rooms, performing equally well and often better than non-linear models.
3

Distributed Photovoltaics, Household Electricity Use and Electric Vehicle Charging : Mathematical Modeling and Case Studies

Munkhammar, Joakim January 2015 (has links)
Technological improvements along with falling prices on photovoltaic (PV) panels and electric vehicles (EVs) suggest that they might become more common in the future. The introduction of distributed PV power production and EV charging has a considerable impact on the power system, in particular at the end-user in the electricity grid. In this PhD thesis PV power production, household electricity use and EV charging are investigated on different system levels. The methodologies used in this thesis are interdisciplinary but the main contributions are mathematical modeling, simulations and data analysis of these three components and their interactions. Models for estimating PV power production, household electricity use, EV charging and their combination are developed using data and stochastic modeling with Markov chains and probability distributions. Additionally, data on PV power production and EV charging from eight solar charging stations is analyzed. Results show that the clear-sky index for PV power production applications can be modeled via a bimodal Normal probability distribution, that household electricity use can be modeled via either Weibull or Log-normal probability distributions and that EV charging can be modeled by Bernoulli probability distributions. Complete models of PV power production, household electricity use and EV home-charging are developed with both Markov chain and probability distribution modeling. It is also shown that EV home-charging can be modeled as an extension to the Widén Markov chain model for generating synthetic household electricity use patterns. Analysis of measurements from solar charging stations show a wide variety of EV charging patterns. Additionally an alternative approach to modeling the clear-sky index is introduced and shown to give a generalized Ångström equation relating solar irradiation to the duration of bright sunshine. Analysis of the total power consumption/production patterns of PV power production, household electricity use and EV home-charging at the end-user in the grid highlights the dependency between the components, which quantifies the mismatch issue of distributed intermittent power production and consumption. At an aggregate level of households the level of mismatch is shown to be lower.

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