7,659 research outputs found
Research Assessment Exercise : Report 2023 : International evaluation of research at the University of Vaasa
The University of Vaasa is a business-oriented and multidisciplinary science university established in 1968. The universityâs strategy focuses on three areas of research: management and change, finance and economic decision-making, and energy and sustainable development. It highlights multidisciplinary research with strong disciplinary knowledge integrated through research platforms to support solving important global challenges. The core mission is to advance new knowledge and to âEnergise Business and Society.â The University of Vaasa has a core faculty of 584 and 5,203 students with 190 international students and 296 PhD students. International accreditations, unique research infrastructure, and partnerships with global businesses and organisations make the University of Vaasa a trusted and valued partner within both regional and international innovation ecosystems.
The Universities Act (Section 87. Evaluation (Amendment 1302/2013)) stipulates that universities must
evaluate their research activities. In line with the strategy of the University of Vaasa, the university evaluates its research activities every five years in order to strengthen the quality of the research internationally, to advance academic and societal impacts of the research, and to further develop the research activities and environment. The previous research evaluations were carried out in 2010 and in 2015. This third research evaluation covered research activities from 2015 to 2020. Diversity, meaningfulness, and focus on future were important features of the research assessment exercise (RAE). The RAE was carried out as a multilevel and multidimensional evaluation targeting research environment, research cooperation and funding, publications, and scientific activities including societal impact. In addition to research groups and the university as a whole, it focused on schools and platforms. The evaluation material and the expert panelsâ interviews thus covered three different levels of the university organisation.
A Steering Committee consisting of members of the Research Council of the University of Vaasa (2021â2023) was nominated to support and guide the research evaluation. The RAE Univaasa 2022 followed practices of responsible evaluation. Engagement of the research units and researchers was an important aspect of the evaluation process. The evaluation team designed, organised, and implemented the different phases of the RAE in collaboration with the heads of the schools, platforms, and research group leaders. All evaluated units got basic summaries of their research output and bibliometric reports before preparing their self-evaluation reports. The material and the bibliometric reports aimed to provide the units tools for self-reflection and further development of their research. In addition to the CWTS analysis prepared by Leiden University, SciVal analyses on Scopus publications were performed for each unit by the Tritonia Academic Library. Bibliometric analyses also included results from AI-analysis of the themes of open access publications (OSUVA, 2018-2021).
The external evaluation was performed by five panels of independent scientific experts. Four of the panels were discipline-specific (based on the schoolâs disciplines). These school-based panels were asked to provide written comments by comparing each research groupâs research to the international and national level of research in the respective field. Based on the research group level evaluations, each school-based panel was asked to offer an overall assessment of the schoolâs research activities and quality of research. A separate team of the panellists were responsible for the assessment of the three research platforms. The University Panel, consisting of the panel chair and the chairs of the school-based panels, was asked to provide an integrating evaluation of the quality of research activities and environment at the University of Vaasa and to offer recommendations for how the university should develop its research. The results of the assessment and the expert panelsâ reports and recommendations will have an effect on the strategic development of research within the university from 2023 onwards.
Evaluation indicated that several research groups are currently at a high international level. The areas represented at the University of Vaasa are ones where excellent researchers have many possibilities. The societal impact of research and the industrial cooperation with regional businesses and also the wider interaction with the society work very well at the University of Vaasa. The flexibility of the cooperation seems to be far greater than in many other universities. Many of the projects contribute clearly to the research and the education of the university and provide useful information for the companies the research groups partner with. However, building international research capacity will remain challenging. This is partly a product of the size of the University and the research groups, most of which are relatively small and rely on a small number of high performing professors.
The international experts gave several recommendations on how to improve the quality of research at the University of Vaasa. Externally funded projects that support the universityâs aim to become an international research university should be encouraged. The experts suggested that the strategy is augmented with more concrete goals on the research focus, quality, and volume. The implementation plan should specify at some level what would be the areas, or modes of operation, in which the university wants to excel, and how this excellence is going to be measured. Recruitment should be prioritised based on the strategy of the university and the availability of excellent people. The university also should consider using international Professors of Practice and inviting more international Visiting Professorships. Moreover, increased possibilities for faculty and PhD students to engage in international activities could boost production of top-level research.
The panels also assessed the role of the evaluated units and the internal cooperation within the university. The research groups vary a lot in their size, but also in their cohesion. The panellists saw that in terms of organisation, some groups were tight clusters, while other groups did not seem to have a clear structure. They considered that it would be very useful if each researcher would have an intellectual home base at the university. The panellists perceived the relationship between research groups and platforms to be unclear. The model was considered complicated relative to the size of the schools and the university. The panellists suggested reviewing the role and form of the platforms. In particular, the panellists suggested that in relation to the service of schools and their research groups, the platforms should have a supporting role, instead of trying to form research identities of their own. However, the panellists also considered that there is no definite need to have all the platforms operate in the same way
Renewable Energy and Energy Storage Systems
The use of fossil fuels has contributed to climate change and global warming, which has led to a growing need for renewable and ecologically friendly alternatives to these. It is accepted that renewable energy sources are the ideal option to substitute fossil fuels in the near future. Significant progress has been made to produce renewable energy sources with acceptable prices at a commercial scale, such as solar, wind, and biomass energies. This success has been due to technological advances that can use renewable energy sources effectively at lower prices. More work is needed to maximize the capacity of renewable energy sources with a focus on their dispatchability, where the function of storage is considered crucial. Furthermore, hybrid renewable energy systems are needed with good energy management to balance the various renewable energy sourcesâ production/consumption/storage. This work covers the progress done in the main renewable energy sources at a commercial scale, including solar, wind, biomass, and hybrid renewable energy sources. Moreover, energy management between the various renewable energy sources and storage systems is discussed. Finally, this work discusses the recent progress in green hydrogen production and fuel cells that could pave the way for commercial usage of renewable energy in a wide range of applications
Optimising heating and cooling of smart buildings
This thesis is concerned with optimization techniques to improve the efficiency of heating and
cooling of both existing and new buildings. We focus on the thermal demand-side and we make
novel contributions to the optimality of both design and operational questions. We demonstrate
that our four novel contributions can reduce operations cost and consumption, optimize retrofit
and estimate relevant parameters of the built environment. The ultimate objective of this work is
to provide affordable and cost-effective solutions that take advantage of local existing resources.
This work addresses four gaps in the state-of-the-art. First, we contribute to current building
practice that is mostly based on human experience and simulations, which often leads to oversized
heating systems and low efficiency. The results in this thesis show the advantages of using
optimization approaches for thermal aspects in buildings. We propose models that seek optimal
decisions for one specific design day, as well as an approach that optimizes multiple day-scenarios
to more accurately represent a whole year.
Second, we study the full potential of buildingsâ thermal mass and design. This has not been
fully explored due to two factors: the complexity of the mathematics involved, and the fast developing
and variety of emerging technologies and approaches. We tackle the mathematical challenge by
solving non-linear non-convex models with integer decisions and by estimating buildingâs thermal
mass. We support rapid architectural development by studying flexible models able to adapt to
the latest building technologies such as passive house design, smart façades, and dynamic shadings.
Third, we consider flexibility provision to significantly reduce total energy costs. Flexibility
studies often only focus on flexible building loads but do not consider heating, which is often the
largest load of a building and is less flexible. Because of that, we study and model a buildingâs
heating demand and we propose optimization techniques to support greater flexibility of heating
loads, allowing buildings to participate more efficiently in providing demand response.
Fourth, we consider a building as an integrated system, unlike many other modelling approaches that focus on single aspects. We model a building as a complex system comprising the buildingâs structure, weather conditions and usersâ requirements. Furthermore, we account for design decisions and for new and emerging technologies, such as heat pumps and thermal storage. Optimal decisions come from the joint analysis of all these interconnected factors.
The thesis is structured in three parts: the introduction, the main body and the conclusions. The main body is made by five chapters, each of which focuses on one research project and has the
following structure: overview, introduction, literature review, mathematical framework description,
application and results section, conclusion and future works. The first two chapters discuss the
optimization of operational aspects. The first focuses on a single thermal zone and the second in
two connected ones. The third chapter is a continuation of the first two, and presents an approach
to optimize both operations and design of buildings in a heat community. This approach integrates
the use of an energy software already in the market. The fourth chapter discusses an approach to
find the optimal refurbishment of an existing building at minimum cost. The fifth chapter shows
an inferring model to represent a house of a building stock. We study the common case where the
houseâs data is lacking or inaccurate, and we present a model that is able to estimate the required
thermal parameters for modelling the house using only heating demand
Natural and Technological Hazards in Urban Areas
Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events
The implementation of SDG12 in and from higher education institutions: universities as laboratories for generating sustainable cities
IntroductionIt is known that the world is facing and will face significant sustainability challenges. Sustainable Development Goal 12 (SDG12), responsible consumption and production, is one of the most relevant SDGs for building Sustainable Cities. This study is based on the analysis of the implementation of SDG12 in cities, starting from universities as laboratories or first examples of sustainability.MethodsThe study was carried out through a multilevel scale approach. A systematic review of the literature (global scale) of the last 5 years (2018â2022) was conducted. An analysis of the program and the initiatives of a Higher Education Institution (Tecnologico de Monterrey) is presented (local scale). Finally, a survey was applied to Faculty at this University (micro-scale).ResultsThe systematic review indicated that the main themes or aspects addressed in SDG12 by higher education institutions were sustainable food, supply chains, community, infrastructure, technology, policies, energy consumption, the collaborative economy, smart cities, and curricula. The local scale analysis highlighted the Distrito Tec project, 37 institutional initiatives, and 26 courses directly related to SDG12. The survey showed that 8% of Faculty considered SDG12 the most important of the SDGs and stated that this goal is necessary to reduce environmental impacts. As the most significant impact that Universities can have on SDG12, 52% of the Faculty consider that Universities should become living labs in the transition toward sustainable cities, followed by 36% who think it would be better to implement operational facilities.DiscussionThe diverse contributions of the HEIs at the three scales were classified into six categories: culture, mitigation, adaptation, education, research, and outreach. The study indicates that SDG 12 has been achieved by universities in different ways, which overlaps widely with the performance of other SDGs. Results demonstrate that following a multistakeholder approach, international collaborations between HEIs can foster technology-driven multi-disciplinary research projects to consolidate sustainable cities. Building capacity to accelerate the transition of universities into urban living labs will promote climate action among the students who enroll every year
Federated learning framework and energy disaggregation techniques for residential energy management
Residential energy use is a significant part of total power usage in developed countries. To reduce overall
energy use and save funds, these countries need solutions that help them keep track of how different
appliances are used at residences. Non-Intrusive Load Monitoring (NILM) or energy disaggregation
is a method for calculating individual appliance power consumption from a single meter tracking the
aggregated power of several appliances. To implement any NILM approach in the real world, it is
necessary to collect massive amounts of data from individual residences and transfer them to centralized
servers, where they will undergo extensive analysis. The centralized fashion of this procedure makes it
time-consuming and costly since transferring the data from thousands of residences to the central server
takes a lot of time and storage. This thesis proposes utilizing Federated Learning (FL) framework for
NILM in order to make the entire system cost-effective and efficient. Rather than collecting data from
all clients (residences) and sending it back to the central server, local models are generated on each
clientâs end and trained on local data in FL. This allows FL to respond more quickly to changes in the
environment and handle data locally in a single household, increasing the systemâs speed. On top of
that, without any data transfer, FL prevents data leakage and preserves the clientsâ privacy, leading
to a safe and trustworthy system. For the first time, in this work, the performance of deploying FL
in NILM was investigated with two different energy disaggregation models: Short Sequence-to-Point
(Seq2Point) and Variational Auto-Encoder (VAE). Short Seq2Point with fewer samples as input window
for each appliance, tries to simulate the real-time energy disaggregation for the different appliances.
Despite having a light-weighted model, Short Seq2Point lacks generalizability and might confront some
challenges while disaggregating multi-state appliances
Multiobjective Optimized Smart Charge Controller for Electric Vehicle Applications
The continuous deployment of distributed energy sources and the increase in the adoption of electric vehicles (EVs) require smart charging algorithms. The existing EV chargers offer limited flexibility and controllability and do not fully consider factors (such as EV user waiting time and the length of next trip) as well as the potential opportunities and financial benefits from using EVs to support the grid, charge from renewable energy, and deal with the negative impacts of intermittent renewable generation. The lack of adequate smart EV charging may result in high battery degradation, violation of grid control statutory limits, high greenhouse emissions, and high charging cost. In this article, a neuro-fuzzy particle swarm optimization (PSO)-based novel and advanced smart charge controller is proposed, which considers user requirements, energy tariff, grid condition (e.g., voltage or frequency), renewable (photovoltaic) output, and battery state of health. A rule-based fuzzy controller becomes complex as the number of inputs to the controller increases. In addition, it becomes difficult to achieve an optimum operation due to the conflicting nature of control requirements. To optimize the controller response, the PSO technique is proposed to provide a global optimum solution based on a predefined cost function, and to address the implementation complexity, PSO is combined with a neural network. The proposed neuro-fuzzy PSO control algorithm meets EV user requirements, works within technical constraints, and is simple to implement in real time (and requires less processing time). Simulation using MATLAB and experimental results using a dSPACE digital real-time emulator are presented to demonstrate the effectiveness of the proposed controller
Days of autonomy for optimal Battery Sizing in Stand-alone Photovoltaic Systems
The main purpose of our article is to optimize the battery sizing by identifying the most appropriate number of autonomy days. A case study has been established and simulated to define the optimal number. In the others current researches, only a small importance has been attributed to the battery autonomy. The objective is generally to ensure a continuous presence of energy especially for isolated systems while this is not always optimal nor economical and does not necessarily guarantee a safe supply. Nevertheless, an over dimensioning of the battery will lead to a consequent cost and a loss of energy. The results show that the number of days of autonomy must correspond to the minimum ratio linking the lack of energy to the surplus during a specific period
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