aalto phd thesis

Student Guide

Aalto Doctoral Programme in Business, Economics and Finance

Programme main page.

The topic of your doctoral thesis is approved by the Doctoral Programme Committee of the School when you are accepted to the doctoral programme. Your research plan is the basis for your thesis work.

Doctoral thesis at Aalto University Doctoral thesis: preparation for pre-examination and publication (Finalising your doctoral studies, aalto.fi) Publishing your doctoral thesis(Finalising your doctoral studies, aalto.fi) Incentive scholarships for the first two articles and completetion of doctoral thesis (see the conditions)

Published doctoral theses (aaltodoc.aalto.fi)  

Next public defences at Aalto University

Public defence in Processing of materials, M.Sc. Aydin Bordbar Khiabani

Public defence in mathematics, m.sc. (tech) kim myyryläinen, public defence in electronics integration and reliability, m.sc.(tech.) samuel rantataro.

Public defence in Automation, Systems and Control Engineering, M.Sc. Arthur Vieira

Feedback about the page.

• Published: 24.5.2022
• Updated: 18.4.2024

Design Guide: Theses and dissertations

• Articles and databases
• Journal and article assessment
• Theses and dissertations
• Dictionaries and reference works
• Research methods
• Visual resources This link opens in a new window
• Can´t find it?
• Suomeksi This link opens in a new window

How to publish a BA/MA thesis?

The master's and bachelor's theses are collected in the Aaltodoc publication archive via the eAge electronic service delivery system. Instructions for submitting your thesis to the Aaltodoc database: •    Convert your thesis to PDF/A form. The work is archived as one document, please attach the abstract and the possible attachments as one document. •    If you wish, you can save the cover page as a separate file (png image file format). •    Login to eAge with Aalto username. •    Fill in the form in the Thesis information sheet and click Save. •    Add the PDF/A file of your thesis to the Thesis sheet. •    You can add the image file of the cover page on the sheet Thesis cover. The cover picture will be shown in the Aaltodoc publication archive together with the metadata of your thesis. •    In case the documentation of artistic component is not included in the appendices of the written component, please add the image and media appendices on the Image and Media Appendices sheet (acceptable file formats are listed in the eAge form) •    Submit your thesis by clicking Submit in the Case details sheet. •    Details can be found on the instructions tab of the eAge form for submitting the thesis.

eAge guidance: [email protected]

Aaltodoc guidance: [email protected]

Theses by ARTS

The Aaltodoc publication archive serves as an e-repository of theses accepted at the Aalto University (more comprehensive from 2014). This database contains reference information, as well as abstracts and full text files published on the permission of the author.

The reference information of the older printed ARTS/ TaiK theses (prior 2019) can also be checked on Aalto-Primo website. The reference information for all theses of architecture (made either in ARTS or in TKK) can only be retrieved in Aaltodoc.

Older theses are kept in a closed archive of the Learning Centre. All printed master’s theses by Aalto University School of Art, Design and Architecture are in the closed archive of the Learning Centre. You can request any theses by sending a message to [email protected]. Mention the title of the thesis, author’s name and publication year in the request. The material is available at the Learning Centre on the next working day after 12 noon, unless otherwise agreed. Theses cannot be borrowed. Since 2020, all theses made at Aalto University have been published only in electronic form.

Theses from other universities

The reference information on Other Finnish universities’ theses and dissertations can be found in Finna database.

Proquest´s Dissertations & Theses database, OATD and Ebsco Open Dissertations contain open access theses and dissertations from around the world.

How to publish a dissertation?

ARTS Theses assists ARTS doctoral candidates in their dissertation production.

Contact ARTS Theses to arrange the publishing costs, print run and delivery for the books: Annu Ahonen.

Read more:  ARTS Theses' instructions for doctoral candidates | Aalto University

At Aalto University, it is recommended that all doctoral dissertations are included in Aalto University's dissertation series:

Aalto University publication series DOCTORAL DISSERTATIONS

All doctoral dissertations are also recommended to be stored in the Aaltodoc publication archive maintained by the Aalto University Learning Centre. The Learning Centre is responsible for storing the electronic version of dissertations in Aaltodoc  publication archive, with the permission of the doctoral candidate. 

Research projects and dissertations:  Research Information Portal

Open access

Aalto University provides a university-maintained  Aaltodoc publication archive  as a platform for open access publication and requires its researchers to deposit their scientific publications in it.

Read more: Open access and the Aalto University Library

• << Previous: Journal and article assessment
• Next: Dictionaries and reference works >>
• Last Updated: May 2, 2024 9:34 AM
• URL: https://libguides.aalto.fi/design

• ACRIS instructions

Modelling District Heating and Combined Heat and Power

• Department of Mechanical Engineering

Research output : Thesis › Doctoral Thesis › Collection of Articles

• district heating
• combined heat and power
• optimization
• production planning
• heat demand forecast
• state estimation

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

• http://urn.fi/URN:ISBN:978-952-60-6844-2 Licence: Unspecified

Fingerprint

• Model Earth and Planetary Sciences 100%
• Combined Heat and Power Earth and Planetary Sciences 100%
• District Heating Earth and Planetary Sciences 100%
• Models Engineering 100%
• Cogeneration Combined Cooling Heating Power Engineering 100%
• Heating Physics 100%
• Heat Physics 100%
• Network Earth and Planetary Sciences 29%

T1 - Modelling District Heating and Combined Heat and Power

AU - Fang, Tingting

N2 - Combined heat and power (CHP) and district heating (DH) systems are becoming the main-stream technology due to its outstanding energy efficiency and environmental friendliness. In order to better use CHP and DH, we develop a set of models to manage CHP-DH systems. The models can be used sequentially or independently to serve different purposes. We first design a model for the DH systems to forecast heat demand based on the historical customer consumption and weather information. The model was built based on linear regression where outdoor temperature and wind speed predict heat demand. Accuracy of the model was significantly improved by adding different weekly rhythms of heat consumption to the model. The results indicate that the proposed linear regression model (T168h) using 168-hour demand pattern with midweek holidays classified as Saturdays or Sundays gives the highest accuracy among all the tested models. The forecasting model can be the premise of the production planning for DH or CHP systems. In parallel, another model is designed to estimate the water flows, temperatures, and heat losses in different parts of the DH network using automated hourly meter readings from customers. The model can be applied to arbitrary DH networks. According to the uncertainty analysis, the estimation model is robust with respect to the measurement uncertainty. Reliable and automatic DH network state estimation is a prerequisite for various operational network management and optimization tasks. On top of the abovementioned 2 models, optimization is developed in two directions: one direction is to optimize the heat production simultaneously at multiple heat plants at different locations of a DH network in order to minimize the production and distribution costs. The model is based on the static DH system model; it can determine the optimal supply temperatures at different heat plants and optimal load allocation between the plants. Because the objective function is a non-convex and non-smooth function of the decision variables, the genetic algorithm (GA) is applied to solve the problem. Optimization can result in savings in fuel and pumping costs. The other direction is to optimize the heat production between a CHP system and heat storage in order to minimize the net operating cost based on a sliding time window method which considers the uncertainty of the forecasts instead of assuming perfect information of heat demand and power sales price for the planning horizon. The model can be applied for both optimally operating heat storage and supporting investment planning for a new storage. The CHP optimization model based on sliding time window method can achieve 90% of the theoretically possible savings. Overall the key value of this thesis is to enhance the design and operation of CHP and DH systems.

AB - Combined heat and power (CHP) and district heating (DH) systems are becoming the main-stream technology due to its outstanding energy efficiency and environmental friendliness. In order to better use CHP and DH, we develop a set of models to manage CHP-DH systems. The models can be used sequentially or independently to serve different purposes. We first design a model for the DH systems to forecast heat demand based on the historical customer consumption and weather information. The model was built based on linear regression where outdoor temperature and wind speed predict heat demand. Accuracy of the model was significantly improved by adding different weekly rhythms of heat consumption to the model. The results indicate that the proposed linear regression model (T168h) using 168-hour demand pattern with midweek holidays classified as Saturdays or Sundays gives the highest accuracy among all the tested models. The forecasting model can be the premise of the production planning for DH or CHP systems. In parallel, another model is designed to estimate the water flows, temperatures, and heat losses in different parts of the DH network using automated hourly meter readings from customers. The model can be applied to arbitrary DH networks. According to the uncertainty analysis, the estimation model is robust with respect to the measurement uncertainty. Reliable and automatic DH network state estimation is a prerequisite for various operational network management and optimization tasks. On top of the abovementioned 2 models, optimization is developed in two directions: one direction is to optimize the heat production simultaneously at multiple heat plants at different locations of a DH network in order to minimize the production and distribution costs. The model is based on the static DH system model; it can determine the optimal supply temperatures at different heat plants and optimal load allocation between the plants. Because the objective function is a non-convex and non-smooth function of the decision variables, the genetic algorithm (GA) is applied to solve the problem. Optimization can result in savings in fuel and pumping costs. The other direction is to optimize the heat production between a CHP system and heat storage in order to minimize the net operating cost based on a sliding time window method which considers the uncertainty of the forecasts instead of assuming perfect information of heat demand and power sales price for the planning horizon. The model can be applied for both optimally operating heat storage and supporting investment planning for a new storage. The CHP optimization model based on sliding time window method can achieve 90% of the theoretically possible savings. Overall the key value of this thesis is to enhance the design and operation of CHP and DH systems.

KW - district heating

KW - combined heat and power

KW - optimization

KW - production planning

KW - heat demand forecast

KW - state estimation

KW - kaukolämpö

KW - yhdistetty sähkön ja lämmöntuotanto

KW - optimointi

KW - tuotannonsuunnittelu

KW - lämmön kulutusennuste

KW - tilan estimointi

M3 - Doctoral Thesis

SN - 978-952-60-6843-5

T3 - Aalto University publication series DOCTORAL DISSERTATIONS

PB - Aalto University

Customer Reviews

Finished Papers

Still not convinced? Check out the best features of our service:

Who is an essay writer 3 types of essay writers.