This thesis is divided in two sections. The first part consists of an interview study with 10 participants to investigate how the industry views the demand for energy storage and how it may develop in the future. Although some views differed, the study showed that a great responsibility lies on the existing hydropower. Batteries are believed to have the greatest potential as short-term storage. The participants agree that hydrogen could have great potential as a flexibility service. The future for Underground Pumped Hydro Energy Storage (UPHES) in Sweden have the participants divided but they seem to agree on the fact that the potential will depend on how price variations develop on the electricity market. Lastly, the industry agreed that a variety of energy storage technologies will be needed for the future energy system. The second part of the study is a deeper investigation into what energy deficit and demand for long-term energy storage (longer than 8 hours) might occur in the future and how UPHES may help shorten the longest deficits. To determine the need for energy storage, the scenario Electrification Renewable from a Svenska Kraftnät (Svk) report was chosen to represent the future energy system for year 2045. The result showed that depending on how the need for energy storage is defined, the amount of energy demand and therefore UPHES facilities, varied. If the need for energy storage was dimensioned regarding the average year it would result in 0,21 TWh of long-term energy deficits and 28 facilities would be enough to cover all of them. If the number of facilities was increased, the result showed a lower usage of all the facilities. However, if the need for energy storage was dimensioned regarding the ''worst case scenario'', the longest deficit out of 35 years, the energy demand in the long deficits was 14 TWh. If 28 facilities were used only 11 % of the energy demand in the long deficits would be covered. If the number of facilities increased, 172 facilities would cover 32 % of the energy demand in the long deficits and 1834 facilities would cover 60 %.

In order to achieve Net Zero emissions in the UK by 2050 and decarbonize the energy sector the integration of increased volumes of additional renewable wind energy is critical. Distribution network operators face challenges in increasing the capacity of this variable source of energy onto the electricity networks. Distribution network operators in Scotland have integrated more wind energy onto their networks to date and have learnings through experience that are worth investigating. The research conducted in this thesis is a comparative analysis of the Network Development Plans of three UK distribution Network Operators, Scottish Power Energy Networks in southern Scotland, Scottish and Southern Energy Networks in northern Scotland, and UK Power Networks in the southeast of England area.  The method used is a comparative analysis of the Network Development Plan documents using a set of pre-selected variables while also allowing for other new emergent variables to be included in the analysis and results. The pre-defined variables are grid capacity, flexibility, grid integration technologies, market structures, planning and regulatory framework, operational experience, efficiency, and location / wind availability. Variable codewords were used to perform the document search and related keywords were used where returns were insufficient. Two further variables emerged frequently in the texts as a result of keyword searches which were transmission links and energy storage and were also included in discussions. Results of the research reveal that Scottish Hydro Electricity Power Distribution, who operate in the north of Scotland, and Scottish Power Energy Networks who operate in the south of Scotland, appear to have a more innovative and proactive approach to grid integration technologies, stakeholder engagement, and innovation projects for increased wind energy integration. UK Power Networks have a larger investment plan approved by the UK electricity and gas markets regulator, Ofgem, but lack of experience in integration of large volumes of wind energy leaves it lagging behind its counterparts when it comes to integration and management of wind energy. Findings from analysis of the Network Development Plans is backed up in literature which claim that energy storage, smart grid technologies, and infrastructure upgrades are critical for integration of wind energy to transform it into a reliable and predictable energy source and manage its integration on to the electricity networks.

In this study, several wave parameters are downloaded or calculated from spectral wave data, and their interdependence is investigated. A literature review is carried out to summarize these dependencies. The literature study is followed by a statistical analysis of the relations between the calculated wave parameters. This statistical analysis is done both for all wave data, resulting in a global expression for the relations, and for the different seas and oceans, resulting in a deeper analysis about local differences and how these differences should be taken into consideration when using wave parameter relations in specific water bodies.

This study performs an overview of the current electricity production for the Island of Lesvos, Greece. With the current trends and transitions towards Renewable Energy Sources, there has been an increase in interest in this topic in the region. This study creates four different scenarios for the generation of electricity with each scenario having an increased amount of RES. The aim of this study is to determine which scenario would be most viable to best implement on the interests of different stakeholders. With the current potential in wind farms due to the wind resource availability, there are large amounts of electricity generated from wind farms in the scenarios.The first scenario is the current scenario of the island. The second scenario has half the total capacity from fossil fuel powerplants with more RES. The third scenario has only RES supplying the island, with the fourth scenario being primarily wind energy with an interconnection with neighboring islands and the mainland. The fourth scenario is the most expensive and hardest scenario to implement. The study applies an MCDA method with the PROMETHEE II tool to rank the different scenarios based on the interests of the stakeholders. This resulted in the fourth scenario being the highest rank for three out of the four stakeholders.

The growing penetration of variable renewable energy has brought all-round challenges to the current power system, no matter for the grid infrastructure, market design or the power producers. The positive and negative externalities caused by the market participators are to be finer priced and a significant amount of flexibility is to be added to the system, in order to counter these problems and facilitate energy transition. The flexibility providers range from dispatchable sources such as thermal generators and gas turbines, interruptible data centers and electric vehicle clusters, to direct and indirect storage such as battery and hydrogen. The intermittency of variable renewable energies can be effectively managed combining with these flexibility providers, and the more expectable output can lead to the more expectable income.  This study investigated a wind-biogas-hydrogen hybrid system, and biogas plays the role of ramping the system up and down according to different situations. When there is a wind deficit, the biogas-to-power unit is activated to compensate for the gap; when there is a wind surplus, the extra power is fed to the biogas pyrolysis equipment and produces hydrogen. To figure out its performance in the power market, a Supply Function Equilibrium approach for the day-ahead market is adopted and extended to the active participation in the balancing market under a two-price settlement scheme. Selling the hydrogen, meanwhile, earns the system additional revenue from the hydrogen market. Given these settings, twelve scenarios of operation mode are proposed and their marginal costs are derived. Results show that the supply function of the system follows the price signal in the balancing market and as well is determined by the cost of activating the flexibility components. By aggregating the Karush-Kuhn-Tucker (KKT) conditions from all the scenarios, the bidding price that maximizes the system profit can thus be obtained.

Sweden’s municipalities are leading the green energy transition, in this study, a techno-economic evaluation was done for a number of carbon neutral scenarios for Växjö municipality’s future energy system, situated within Sweden’s projected energy demand development in 2030 and 2050. The municipality’s partially decentralized energy system relies heavily on interconnected electricity supply from the national grid, and fuels imports from other parts of Sweden. It was a matter of question: in which ways will future demand changes induce supply changes, and whether a future carbon neutral energy system will be less costly in a sustained-electricity supply condition? To answer this, a balanced energy reference system for the municipality was created from an actual energy balance, using an hour-by-hour dynamic energy analysis tool EnergyPlan. Afterward, a future energy demand projection for Växjö was stemmed from the Swedish Energy Agency (SEA) sustainable future scenarios for Sweden, based on an average inhabitant energy demand. Modelling results for Växjö carbon neutral scenarios showed that Växjö energy system will be sufficient to supply future heat demand but not electricity demand, nor transport and industrial fuels. While in the short-term being carbon neutral is more economically attainable without changes in electricity supply technologies, a projected electricity price and consumption increase, change the outcomes for a carbon neutral scenario based on Intermittent Renewable Energy (IRE) to be less costly in the long term.

Buildings and the built environment account for a significant portion of the global energy use and greenhouse gas emissions, and reducing the energy demand in this sector is crucial for a sustainable energy transition. This highlights the need for accurate and large-scale estimations and predictions of the future energy demand in buildings. Urban building energy modeling (UBEM) is an analytical tool for precise and high-quality energy modelling of city-scale building stocks, which is growing in interest as a useful tool for researchers and decision-makers worldwide. This thesis contributes to the understanding and future development in the field of UBEM and multi-variate cluster analysis. Based on a review of contemporary literature, possible improvements and knowledge gaps regarding UBEM are identified. The majority of UBEM studies are developed for similar applications, and some challenges are close to universal. Difficulties in data acquisition and the identification and characterisation of building archetypes are frequently addressed. Drawing on conclusions from the review, a clustering methodology for identifying building archetypes for hybrid UBEM was developed. The methodology utilised the k-means cluster analysis algorithm for multiple diverse parameters, including socio-economic indicators, and is based on open data sets which eliminates data acquisition issues and allows for easy adaptation. Building archetypes were successfully identified for two large data sets, and proved to be representative of the sample building stock. The results of the analysis also show that the error metric values diverge after a certain number of clusters, for multiple runs of the algorithm. This property of the algorithm in combination with the use of both existing and novel error metrics provide a reliable method for determining the optimal number of clusters. The methodology developed in this thesis enables for an improved modelling process, as a part of a complete UBEM.

The share of electricity generation in the power system being based on power electronics is increasing, which will impact the system in different ways, such as an increased risk for undesired interactions. An example is doubly fed induction generator (DFIG) based windfarms which have been shown to present negative resistance in (parts of) the sub-synchronous range (i.e., below the system frequency of 50 or 60 Hz). If such a wind farm is radially connected (deliberately or not) to a series compensated line, undamped or poorly damped sub-synchronous oscillations could occur due to sub-synchronous resonance. One possible cause of such interactions is related to the wind farm control system, and in such cases, the interaction between the wind farm and system leading to sub-synchronous oscillations is referred to as sub-synchronous control interaction (SSCI). This thesis aims to describe different types of so-called sub-synchronous oscillations, with a focus on SSCI. An investigation is performed to find out under what circumstances there is a risk of SSCI, and how one can evaluate this risk. Different methods of obtaining the impedance of non-linear systems (e.g., a wind farm) are discussed, with the method used in this thesis being a dynamic impedance scan. The dynamic impedance scan is implemented in PSCAD and uses a voltage (or current) perturbation of one frequency at a time and measures the current (or voltage) response at that frequency, subsequently giving the impedance as the voltage/current ratio. Combined with the impedance of the grid, screening studies were performed to identify the risk of SSCI under different conditions. A 200 MW photovoltaic (PV) farm is designed and implemented in PSCAD. The PV farm is connected to the same bus as a 200 MW DFIG wind farm, resulting in a hybrid wind and PV farm. The hybrid wind and PV farm is in turn connected to a series compensated transmission system made to resemble a typical Swedish system. Functionality is added to the PV farm that enables it to act as a static synchronous compensator (STATCOM) to damp sub-synchronous oscillations if needed. Simulations are performed in PSCAD showing that the PV farm is able to damp the sub-synchronous oscillations occurring when the wind farm is radially connected with the series compensated line due to a fault, thereby avoiding disconnection or damage to equipment. One of the main conclusions is that assessing the risk of SSCI (screening) is not an exact science, but a highly complex matter. This conclusion is drawn due to contradictory implications given when analysing the measured grid and wind farm impedances. For example, a series resonance point in the combined reactance (grid + wind farm) would suggest that there would be oscillations at this frequency during a fault, but this may not always be the case. The opposite also occurred, i.e., oscillations of a certain frequency occurred even though no series-resonance point was seen in the combined impedance. Nonetheless, the screening method did manage to identify risk cases based on a set of criteria listed in the thesis, although electromagnetic transient analysis (EMT) time-domain simulations should always be performed for verification. The other main conclusion is that a PV farm installed at the point of common coupling (PCC) of a wind farm, i.e., a hybrid wind and PV farm, is able to damp sub-synchronous oscillations by acting as a PV-STATCOM. The use of combined assets, such as utilizing a PV farm to counteract SSCI in a wind farm, means that additional investments, for example in the form of a STATCOM, for this purpose could be avoided.

Both the solar photovoltaic (PV) installation and electric vehicles (EVs) deployment are increasing significantly in Sweden. With the large-scale integration of PV and EVs, problems such as the voltage deviations and overloading of components can arise, since the existing distribution grids are not designed to host the large shares of new EV loads and the intermittent PV power feed-in. This thesis investigates a C2V2C (i.e., Community to EV to Community) energy flow concept and evaluates how it can improve the power balance performances in communities with both PV and EV integrated in Sweden. Community refers to a group of buildings (i.e., two or more) connected within the same microgrid. It aims to develop a C2V2C model, which utilizes smart charging of electric vehicles to deliver electricity between different communities, for improving the performances at multiple-community-level. A coordinated control of EV smart charging is developed using the genetic algorithm, and its performance is compared with an existing individual control. Two control strategies are considered: (i) minimizing the peak energy exchanges with the grid and (ii) minimizing the electricity costs. Case studies are conducted considering a residential community and workplace community, as well as one EV commuting between them. The study results show that the advanced control achieves a cost reduction of up to 280 % in a summer week compared to the individual control. In a winter week, a performance improvement of up to 13 % can be achieved using advanced control. The advanced control can also reduce the energy exchange peaks with the power grid of the multiple communities. This study has proven the effectiveness of the C2V2C model in enhancing the local power balance at multiple-community-level. It will enhance the resilience and grid-friendliness of building communities, thus paving way for the large PV and EV penetration in the future.

In this paper it is investigated the role that geothermal energy could play in theenergy mix, to meet new system requirements. As any other source, geothermal energy harnessing implies a number of risksmainly related to induced seismicity and landslides, together with the releaseof as greenhouse gases and metal salts. Moreover, important barriers to itsimplementation still exist, mainly concerning financial aspects and drillingoperations. As well, administrative status is uncertain and related investmentin R&D negligible. However, geothermal energy presents important advantages in relation toother energy sources, as its reliability and large capacity factor, comparable tonuclear and natural gas plants. It could help to reduce both the globalwarming, whose potential is up to 5 times lower than in the case of fossilfuels, and the landuse, the lowest of any power plant. Additionally, in spite ofthe high and risky initial investment, energy produced by geothermal means is amongst the cheapest. The geothermal potential is large enough to substantially contribute to theenergy mix, through locally available resources. Economic potential in Europeby 2050 is estimated in 100 – 4 000 TWheand 880–1 050 TWhth. Nevertheless, currently available technology strongly limits the access togeothermal resources. In addition, predictions about geothermal utilizationare modest and have hardly been achieved to date. The key for the future isthe development of the Engineered Geothermal Systems.