In the current grid infrastructure, the power flow reaching the limits of the grid capacity induces several problems. A way to circumvent this issue is the introduction of flexibility in order to alleviate the impact on the energy network. However, the estimation of the required flexibility remains a problem in the current state of the art. In this thesis, an approach is proposed to estimate the flexibility of distribution systems by identifying assets based on aggregated transformer measurements. Flexibility can be seen as the ability of the system to adapt to changes coming from demand and generation. Different assets can be available such as solar panels, and heat pumps and have their specificities. The problem thus translates into the identification process in aggregated data. Several steps are important in the process, such as the consumption baseline, the study of the different characteristics of the profiles, and the number of iterations. To allow the accuracy to reach high levels and to match the standards of distribution system operators (DSO), the process requires the minimization of squared error between the data and the chosen profiles. Different cases are investigated and validated prior to the study of the results. For the identification of heat pumps and solar panels, individual approaches have been investigated in the literature. However, the combined identification of assets has not yet been studied. A mixed identification process is proposed in this work, and the method has been tested, reaching a high level of accuracy. Within this new framework aiming at separating the assets, options are proposed to enhance the accuracy of the process.

As global efforts accelerate the transition towards renewable energy sources and decentralized en- ergy systems, the challenge of managing surplus energy during off-peak hours becomes increasingly critical. Without effective and innovative storage solutions, excess capacity from renewable energy resources is being unexploited, reducing the efficiency and sustainability of these technologies. This thesis addresses this issue by proposing the integration of Shared Hydrogen Storage Systems (SHSS) within Energy Communities (ECs), providing a viable method for storing surplus energy as green hydrogen.

By converting and storing renewable energy into hydrogen, ECs can ensure a stable green energy supply, mitigating fluctuations and enhancing energy security. This research presents a modular energy-sharing architecture that integrates blockchain-based smart contracts, with algorithms for equitable distribution and trading of hydrogen capacity between community households. Simula- tions and case studies test the algorithms for hydrogen storage sizing and fair capacity allocation, while also exploring the potential of hydrogen-based heating systems.

The results showcase the critical role of hydrogen storage in increasing the efficiency of renewable energy systems, even during periods of low demand. Two models developed from the simula- tions demonstrate the practical dynamics of using hydrogen for long-term energy storage in urban environments. This work provides a framework for the practical implementation of shared hydro- gen storage for electrification and heating, contributing to the transition towards decentralized, carbon-neutral urban energy infrastructures.

In response to the urgent need for sustainable energy solutions and climate change mitigation, international agreements such as the Paris Agreement have been instrumental in advocating reduced greenhouse gas emissions. As the world shifts towards renewable energy sources and electrification, there arises a heightened challenge of increased congestion and a greater demand for flexibility within electrical networks. Batteries emerge as a crucial source of added flexibility and congestion relief. However, these commercially owned batteries are not obliged to assist with grid congestion, possibly focusing solely on energy arbitrage pursuits for example. This thesis undertakes an exploration of optimizing the efficiency of energy arbitrage batteries by repositioning them to alleviate congestion. Additionally, it delves into the divergence between preferred battery locations for grid operators and battery owners. A comparative analysis is performed among energy arbitrage batteries, congestion relief batteries, and traditional reinforcements. These aspects are evaluated in terms of their contribution to grid flexibility, congestion relief, and load curtailment requirements. The study is conducted using a medium voltage network of a region in the North Rotterdam as a case study. The investigation involves the creation of a linear programming day-ahead market model and a linear programming energy arbitrage battery model. The day-ahead market model generates a price signal that guides the energy arbitrage battery’s charging and discharging decisions for profit maximization. Load and generation forecasts are provided by Stedin for the case study. A Powerfactory model simulates the effect of a congestion relief battery capacity on congestion. Through a heuristic algorithm, the optimal location and size of the energy arbitrage battery capacity are determined. By analyzing these scenarios, the study unveils the positive impact of strategically positioned energy arbitrage batteries that align discharge timing with congestion patterns. The study also highlights the significance of positioning batteries at the deepest points of radial lines to maximize benefits, even though these locations may diverge from battery owner preferences, such as solar farm sites. Interestingly, the addition of energy arbitrage batteries to these solar farm sites can exacerbate congestion due to their relatively low congestion levels. A comparative evaluation reveals that batteries surpass traditional grid reinforcement in enhancing flexibility, with congestion relief batteries outperforming energy arbitrage batteries in alleviating congestion. With the energy arbitrage battery being able to reduce congestion by 27% and the congestion relief batteries being able to reduce it by 94% with the same amount of installed capacity. Energy arbitrage scenarios may necessitate load curtailment to address congestion challenges, they may not independently resolve all congestion. In conclusion, while energy arbitrage batteries show promise in addressing congestion, their effectiveness depends on synergistic technologies and further refinement. Future research avenues may explore enhanced market models, extended predictive analyses, and intricate hybrid strategies to tackle congestion relief, considering the intricate complexities introduced by diverse network topologies.

As the transition towards a sustainable energy system gains momentum, the concept of energy hubs has emerged as a promising solution to make the existing energy system more efficient. This thesis aims to investigate the contribution of energy hubs to network management in the Dutch energy system. The research questions focus on identifying the key components and objectives of energy hubs, understanding the roles and interests of stakeholders involved, assessing the effectiveness of energy hubs in achieving policy goals, and exploring the opportunities and threats they present to the Distribution System Operator (DSO).

The study employs a mixed-methods approach, combining theoretical analysis, stakeholder interviews, SWOT analysis, and case studies. Through a comprehensive literature review, a holistic understanding of energy hubs is established, providing a foundation for further analysis. Stakeholder interviews offer insights into the perspectives and interests of various actors in the energy sector, shedding light on the roles they play and the potential benefits of energy hubs.

The thesis analyses the theoretical and practical value of energy hubs, considering their potential to optimise network capacity, enhance renewable energy integration, and improve system flexibility. SWOT analysis allows for a thorough examination of the strengths, weaknesses, opportunities, and threats associated with energy hubs. The analysis of case study projects further enriches the findings by providing real-world examples and highlighting their applicability in practice.

The results demonstrate that energy hubs have the potential to contribute significantly to network management, offering benefits such as reduced grid congestion, increased renewable energy utilisation, and enhanced collaboration among stakeholders. However, limitations exist, including the need for a clear definition, standardised legal procedures, and a comprehensive understanding of the specific conditions under which energy hubs are most suitable.

This thesis contributes to the existing knowledge on energy hubs and their impact on network management. It offers a comprehensive analysis of their key components, stakeholder dynamics, policy implications, and practical considerations. The research findings provide valuable insights for both academia and industry, informing future research directions and aiding DSOs in harnessing the full potential of energy hubs to facilitate the transition towards a sustainable and resilient energy system.

The purpose of this thesis research was to perform a photovoltaic (PV) performance assessment and comparison between a small-scale land-based PV system and an off-shore off-grid floating PV system. Also from this research design guidelines for off-grid off-shore floating PV systems were developed. The research experiment was carried out in The Netherlands, with one system floating in the North Sea and one system standing on-land. To be able to have a fair comparison two identical 4.32 𝑘𝑊 PV arrays were built simultaneously, consisting of two parallel strings, each with six 360 𝑊𝑝 bifacial PV modules connected in series. Each of the two systems was equipped with a monitoring set up consisting of temperature sensors, pyranometers, reference cells, power meters and an inclinometer for the off-shore system. Additional measurements concerning wind, wave and water temperatures off-shore were taken from the Royal Netherlands Meteorological Institute (KNMI) weather station Hollandse Kust Zuid Alpha (HKZA), which was situated in the same region of the North Sea. The two PV experimental set-ups were compared between 15th November 2022 and 1st January 2023. On the DC side being measured, the on-land PV system recorded 96.3 𝑘𝑊ℎ while the off-shore PV system recorded 93.4 𝑘𝑊ℎ, which was subject to lower irradiance levels. The performance ratio (PR) found off-shore during the period of research was 0.92 while on-land this value was 0.934 between the two PV strings, however these values should be re-validated due to a potential malfunction of the Hall effect sensors. The PR off-shore was higher than expected from literature for a similar system being simulated. With respect to module temperatures recorded off-shore, a low thermal variation was found when compared to on-land, with the average module temperature off-shore being 11.3 𝑜𝐶 higher than on-land during this period of research. Ambient temperatures as well as irradiance on the Plane of Array (POA) were found to have a larger influence on the module temperatures for the on-land system than for the off-shore system. Module temperatures throughout the PV array off-shore were found to be the equal. Additionally, four OFPV linear regression models derived from the empirical measurements were presented and compared with existing empirical FPV models found in literature, which were found to be subject to be site and design specific. Additional environmental effects on the module temperature concerning wind, wave and water temperatures were presented, highlighting the dominant effect of the water with respect to module temperatures. The off-shore floating PV system withstood waves of up to 3.4 meters while the system maximum tilts were found to be to be 13.33 𝑜 and 17.36 𝑜 for the X and Y axis of the PV floater respectively. No permanent soiling due to bio-fouling or salt deposition was detected after one month of measurements but dynamic soiling, in the form of bio-fouling, snow and water splashing were identified, with the latter being the most predominant. The work done through this thesis lays the foundation for further research and comparisons of off-shore floating PV systems. It is recommended to perform this comparison for a period of a complete year to yield annual conclusions.

Currently, the entire aviation sector accounts for 2.5% of global emissions. To commit to the Paris Agreement by 2050, new emerging technology is necessary. Electric aircraft emerged as one of the promising solutions to decarbonize the aviation sector. However, the introduction of electric aviation (EA) causes a shift from kerosene to electricity. With the minimized turnaround times of aircraft, high charging powers are encountered with the adoption of electric aircraft. This can in turn lead to grid instability and costly grid infrastructure upgrades for the grid operator. A battery energy storage system (BESS) can potentially be a promising solution capable of addressing the high power rates associated with electric aircraft charging. Moreover, it provides opportunities for the battery owner to reduce costs and increase the utilization of renewable energy. This thesis aims to gain insight into the contribution of the deployment of a BESS compared to the business-as-usual situation to enable electric aviation while facilitating the interests of both the grid operator and the airport. In particular, this is done for the case study of Bonaire International Airport (BIA) and the grid operator Water- en Energiebedrijf Bonaire (WEB). For the grid operator, the impact on the grid is analyzed focusing on the voltage fluctuations, the load on the distribution cables, and the airport’s transformer (over)loading. From the airport’s perspective, the airport system’s LCOE, and the CO2 emissions from grid electricity are investigated.
Lastly, as electric aviation is currently not commercially used, and faces a lot of uncertainty, the sensitivity of the control strategies to various future scenarios for 2030 is analyzed. This is investigated by a mathematical optimization model for the three battery control strategies, Self-Consumption, Peak-Shaving, and Cost-Optimal. The results showed that in the absence of a BESS, the business-as-usual situation, independent of the adoption level of electric aviation at BIA, the transformer required a capacity upgrade. With the deployment of a BESS, it was found that a Self-consumption-controlled BESS could not effectively reduce the peak loads and defer a transformer capacity upgrade. While voltage fluctuations remained within the acceptable operational range for each control strategy and adoption level of EA. On the other hand, future scenarios with high demand growth could lead voltage fluctuations to reach the allowable threshold. The Self-Consumption strategy is susceptible to an increased electricity demand and adoption level of EA, which substantially influences the load on the distribution cables. Conversely, the Peak-Shaving and Cost-Optimal battery significantly reduces the peak loads in both electricity demand and injection even in scenarios with increased electricity demand and higher adoption levels of EA. Economically, it was shown that a BESS substantially reduced the LCOE depending on the control strategy. Furthermore, it is feasible to reduce CO2 emissions originating from grid electricity production, albeit the reduction is strongly affected by increased electricity demand over time. The research concluded that a BESS is able to defer grid infrastructure upgrades and reduce costs for the airport, although, the extent of these results is highly dependent on the control strategy. Regardless of the control strategies, a battery is able to achieve a reduction in CO2 emissions from the grid given the on-site PV system.

To tackle the effect of climate change while meeting the ever-growing demand of energy, a high scale of integration of renewable energy resources has been performed in the past decade. Solar Photovoltaics have played a monumental role in this process, thus contributing in the fulfillment of the energy demand. The scalability and the flexibility of use has led to a significant development in the technologies implemented for assimilation of Solar PV. In addition, the development in power electronics has made the process of integration seamless. Due to Solar PV's dependency on irradiation there is an ever growing need for establishment of an improved control on power converters.
The aim of this thesis is to implement Maximum Power Point Tracking and Droop control algorithms on PV powered DC-DC Converters while considering the dynamics of Solar PV. Mathematical modelling is used to model the PV generator to consider its dynamics along with the dynamics of the converters to establish control. The output of these converters is connected to a DC Microgrid. After completion of the modelling process, the internal control design was performed followed by the implementation of both the algorithms. The project was performed at the lab of the company DC-Opportunities.
The findings of this research are presented in the current document. Its goal is to outline the procedure taken from the start of the project and the literature review all the way through the design and testing of the power electronic converters. Finally, suggestions for the future are offered, which might serve as a roadmap for more advancements.

The DC Optimal Power Flow (DC-OPF) problem is a widely-studied topic in the field of power systems. A solution to the problem consists of minimizing the running costs of the power system, through defining the optimal operating state for each entity in the system, while adhering to a set of physical constraints. A lot of research has been conducted on decentralized and distributed solutions to this problem, which, when compared to centralized solutions, offer benefits such as adaptability, reliability and scalability. Nevertheless, most of these solutions have only been evaluated through simulations, while physical applications of these algorithms introduce new challenges, such as noise, delays, and the regulation of physical variables like voltage and current. In this thesis, we focus on a decentralized DC-OPF algorithm based on the Consensus and Innovation method, where system entities utilize their physical measurements and communicate with their neighbouring entities in order to reach consensus on a solution. While previous implementations of the algorithm were tested on simulated environments, this thesis explores and proves the effectiveness of the algorithm implemented for a real DC unipolar microgrid, consisting of power supplies, loads and a Power Circuit Board attached to each, where each device's behavior is governed by its own, exclusive entity. The newly-introduced challenges of a physical environment are accounted for, and any negative effects of them are mitigated as much as possible. Furthermore, the algorithm is successfully modified and extended to handle region DC-OPF, something that has not been attempted before, where a single entity of the algorithm could be responsible for many devices in the network. Finally, it is known that the original algorithm has not been experimented on before on scenarios of islanding and de-islanding, which are of importance in OPF, because a power fault may occur and one area may wish to isolate itself from the faulty area, or perhaps a distributed energy resource should only be connected to the network during certain periods, e.g., during sunlight for solar panels. Hence, this thesis also proves the effectivess of the algorithm on scenarios of islanding and de-islanding, in an innovation site called the Green Village, where technologies in the field of sustainable energy provision are tested and applied in a real-life environment.

A large portion of the global population, mostly in the Sub-Saharan African region, still has no access to electricity. Due to the remoteness and limited accessibility of some communities, off-grid solutions such as mini-grids are required to electrify these regions. An essential part of such an isolated mini-grid is the energy storage system. DC Opportunities aims to establish these mini-grids as a third step in the electrification process. As a means of energy storage, the small-scale employment of the mature technology of pumped hydro storage (PHS) should be explored, making use of height differences in terrain often present in these areas. While PHS is the most common energy storage technology, it has thus far only be employed on a large scale and only recently research on its small scale applicability has been gaining ground.
In order to conduct a feasibility study on the use of PHS as a means of energy storage for isolated mini-grids in low-resource settings, such as those in Sub-Saharan Africa, local challenges are identified. These include a suitable operating range, quality of supply and power issues, limited component and material availability, potential arrival of the main grid, funding, low tariffs and revenue, a low-trust society, limited technical skills, theft and vandalism, political vertical networks and corruption, regulatory issues, secondary water use and environmental impact. Based on these challenges, a program of requirements is presented, which consider the technical, economic and socio-cultural requirements.
Subsequently, the available design options are discussed, and based on the program of requirements a technical design synthesis leads to a provisional technical design. This exploration has led to the conclusion that earth dam reservoirs should be used for the water storage system, Glass Reinforced Plastic or Mild Steel pipes for the water conveyance system and a binary unit utilizing a Pump-as-Turbine or a ternary unit employing a Pelton turbine for the powerhouse configuration; this configuration can be either designed for an one-time installation or scalable installation. Based on the provisional technical design and the local challenges, an organizational structure, using the existing local power structure, ensures the PHS plant embeds itself in the community through community involvement and participation, as well as local capacity building by the project facilitator. The capacity requirements of the reservoir, as well as the diameter and material of the penstock, and the powerhouse configuration appear to be highly dependent on site-specific conditions. Therefore an energy flow model was developed, which in combination with a penstock selection tool and a generated demand profile is able to determine the requirements of a Hybrid Energy Storage System (HESS) utilising PHS as its main component for an isolated mini-grid. This model has been deployed for a case study in Adi Araha, Ethiopia, yielding positive results. Further exploration into the economic implications of the modeled system, and socio-cultural factors to be considered for the case study, led to the conclusion that for the case study a PHS plant could prove to be a technically, economically and socially feasible solution. Further research is however warranted, specifically on site.
The developed model was further employed to attain a conclusion on the general economic feasibility. While the socio-cultural factors are very site specific and can not easily be generalized, the results exhibit that for a situation where the gross head is at least 250 meter, and preferably around 300 meter, and the maximum power output requirements of the PHS plant is at least 150 kilowatt, technical and economic feasibility is attainable. Isolated mini-grids requiring a storage solutions, adhering to these conditions, should thus be further investigated to more accurately determine the feasibility of a small pumped hydro storage plant.

Despite of the technological advancements on renewable energies and integration of those into the grid, there are still around 800 million people who lack access to the electricity. In order to tackle this problem, solar home systems are being deployed especially in rural areas to create units for decentralized energy generation, based on DC microgrid premises. Integration of solar home systems, especially in developing countries, has great positive effects on communities' economic and social conditions.
In line with transition to cleaner energy resources and utilization of these, this thesis has been carried at DC Opportunities RD to facilitate the rural electrification project. Within this project, the thesis focuses on implementation of a general adaptable firmware based on USB Type-C power delivery protocol on several components of modular solar home system.
Firstly, the report analyses the existing solar home systems with their characteristics on power delivery and energy management. The limitations on the existing projects are studied and the main motivation on deploying the firmware is pointed out. The main objective of the thesis is hence is formulated as achieving and implementing the USB Type-C power delivery protocol with data acquisition layer on prototypes of charging station, power banks and charging hub, that is tailored to rural applications. The firmware design topology is followed to take into account the modularity, scalability and applicable to energy management.
The USB Type-C power delivery firmware is developed by studying and adapting two open source packages. Several adaptation layers are developed and the firmware is implemented using micro controllers, from STM32, that are capable of running operating system with no faults, deploying several layers of tasks and state machines. Power delivery library functions are tackled with layers of software architectures and data monitoring and transmission layer is deployed, in order to validate the system as well as the hardware.
Implemented firmware is developed on the prototypes and tests are run with the current editions of the prototype. The energy management layer and formulated test case will be run and tested on March 2020, in the field test in Ethiopia. This field test will provide results and data, thanks to the developed firmware and acquisition system, in order to achieve a step closer to the ultimate goal of the project, which is implementing low voltage DC microgrid in rural areas.

Future energy systems will present high penetrations of variable renewable energy (VRES). Due to the uncertainty that is related to the intermittency of wind and solar energy, and loads such as electric vehicles, the need for flexibility will be higher. This research identifies the possible sources of flexibility in a power system. Firstly, using statistical errors and probability theory, the required reserves of flexibility that a system needs to ensure a proper operation are quantified. Secondly, with the increase of VRES, the amount of synchronous generators is expected to decrease. This will mean that the inertial response used to keep a stable frequency will be reduced. On this paper, a method to quantify inertia and the concept of minimum required reaction time of flexibility are explained. Finally, an optimization problem is proposed to allocate the different types of flexibility taking into consideration their technical capabilities. This problem minimizes the cost of reserving different flexibility sources in a distribution grid.

Technical developments in generation and demand of energy will motivate significant change in the electric power grid, both on the transmission and the distribution level. A major innovation would be the successful transformation of the current passive power grid towards an active and ICT-based smart grid. Among the technical efforts that will help to pursue this goal, the renewed interest in DC (direct current) distribution and transmission applications is playing an important role. In particular, the interest in the DC universal distribution networks is renewed since most of the renewable energy generation technologies (e.g. PV modules, fuel cells) and loads (e.g. LED lighting, electric vehicles) are DC-native. Their direct connection would allow to skip conversion steps, thus providing higher efficiency.

The focus of this thesis lies on the steady-state power flow analysis, a numerical study used in electrical engineering to assess the flows of power in the network. The aim of the thesis is to review the state of the art in computational methods for AC and DC power flow analysis and to determine a suitable method to develop a power flow tool for the DC framework.

The literature study revealed that most algorithms aim to solve the non-linear power flow problem without taking into account characteristics typical of future DC networks, such as highly meshed topologies and constant power converters. An innovative power flow method has there- fore been developed in order to include different node behaviours, such as constant voltage, constant current, constant impedance, constant power and I-V droop control. A case study based on the IEEE European Low-Voltage Test Feeder is analysed to provide an example of the application of the power flow tool.

The thesis shows that it is possible to linearize the system equations considering the constant power node either as a current source or as a parallel of current source and impedance. Both methods allow very fast convergence for complex meshed networks, and can therefore be adopted for diverse studies such as market analysis and N-1 redundancy analysis, among others.

Photovoltaic (PV) systems have provided the world with a renewable and environment friendly energy solution. However, PV systems face various loss mechanisms at the module level as well as power electronics level which need to be addressed for further growth of the technology. Power generation from PV modules suffer from heat losses that are a function of the temperature coefficient of maximum power (γ) of the PV module. Another loss mechanism is the shading of PV module where the power output of a module and ultimately the system can be severely compromised. Although various approaches such as bypass diodes and module level power electronics have been employed to minimize the effects of shading on a PV module, so far, the performance of a PV module under shading had only been addressed vaguely and was generally described qualitatively. Therefore, a parameter called Shading Tolerability (ST) was recently developed to quantify the behavior of PV modules under all kinds of shade. However, the observations pertaining to Shading Tolerability were only carried out under Standard Test Conditions (STC). Hence, this thesis aims to investigate whether ST is an innate property of a PV module by formulating a correlation, if there’s any, between ST and ambient temperature, classify various PV technologies based on ST and γ and develop a selection map so that an optimal selection of PV modules can be made for the design of PV systems simply by knowing the specifications of the module along with the meteorological conditions of the installation location. Furthermore, different interpolation techniques were evaluated to achieve a comprehensive picture of the meteorological conditions of The Netherlands to determine the most optimal PV technology for The Netherlands using the PV selection map. Finally, Performance Ratios of various existing PV systems were calculated using suitable irradiation decomposition and transposition models as a proof for the validity of the selection map. The obtained results showed that PV systems using CIGS technologies exhibited higher performance ratios on average as was suggested by the selection map.

Electric Vehicles (EVs) provide a promising sustainable clean mode of transportation with much fewer emissions compared to the traditional Internal Combustion Engine (ICE) vehicles. However, this can only be considered true if the energy sources used for charging EVs are also from clean energy form. Various Renewable Energy Sources (RES) are available to provide the EVs charging demand. Nevertheless, due to intermittency power generation characteristic of RES, there is a high risk of supply and demand power mismatch. A grid-connected topology system is commonly used as a backup for lack or over power supply from RES generation. Even though, this configuration may lead to new problems of under/over voltage issues and maximum transformer/lines loading capacity due to RES fluctuation power production. The storage system is considered necessary to be installed in the system as a buffer of the power mismatch and also reducing the grid stress. Excellent approximation of storage sizing and placement is mandatory to provide satisfactory influence to the overall system technically and economically.

This study proposes optimization strategy for optimal battery sizing and placement with optimal power management system in the EVs charging station using photovoltaics (PV) power in a low voltage distribution network using Mixed Integer Linear Programming (MINLP) algorithm. The lithium-ion battery is considered in this project because of its relatively high power and energy density characteristic along with low self-discharging. The radial low voltage CIGRE benchmark is adopted as a model topology to evaluate the performance of the proposed optimization strategy. Dynamic daily electricity price, residential load, and PV power profile of the Netherlands are taken into account in this project. Furthermore, the research project implements several case studies using DICOPT (Discrete and Continuous OPTimizer) solver in GAMS (General Algebraic Modelling System) software with MATLAB interfacing. As the main result, proper EVs charging strategy with optimal battery sizing and placement with the appropriate power management system is successfully maintaining the system away from the grid violation while at the same time reducing the total cost of the system.

Keywords: EV-PV charging, optimal battery sizing and placement, MINLP

The current architecture of the power grid is outdated and will not provide the means to deal with the decentralization of energy sources. The smart grid is a newly envisioned architecture for the power grid that should solve the weaknesses in the current grid. One application that is part of the smart grid vision is the microgrid: a coalition of prosumers that is able to operate either in parallel to the power grid or isolated from it.

In this work we investigate how these microgrids should be formed in order to maximize their usability while at the same time preserving the freedom of choice for participants. We apply a game theoretic perspective to simulate the choices of individual users. This results in a problem that combines the notion of core stability and maximization of social welfare. For this problem we provide a complexity proof, followed by a relaxation of core stability, $k$-stability, by limiting the available knowledge for participants. Finally we produce our own distributed algorithm which can act as a heuristic.

Wind power as a green and low-carbon renewable energy could effectively mitigate the energy crisis and reduce environmental pollution, including the rapid developing offshore wind power with its rich reserves, wind stability, high wind speed, less interference, noise and other advantages. The trend for development of offshore wind farms is towards a growing size of installed power. This together with higher distances from the shore leads in many cases to HVDC connection as a preferred choice for power export. Thus, the wind turbines are connected through a collection grid to an offshore platform. As the offshore wind farm contains a large number of power electronic devices and submarine cables, it will inevitably lead to the occurrence of harmonic resonance. Offshore wind farm harmonic and resonance will affect the power quality, while poses a huge challenge to the power grid and wind power.
In this thesis work, a comprehensive harmonic analysis in offshore wind farm was studied. Firstly, a detail configuration of the wind energy conversion system and harmonic analysis basics are described and interpreted. Next, a suitable model of one offshore wind farm is built and validated in Matlab/Simulink. The equivalent circuit is calculated for the components in the aggregated wind farm based on their harmonic model. And potential resonance problems are analyzed by frequency scan method to calculate the resonance impedance and frequency. Afterwards, based on the self-built system model, potential harmonic issues that arise in the system are investigated in time domain to interpret the THD at PCC between the collection grid and the onshore grid. As well, a few effective strategy for suppressing harmonics are simulated to evaluate the various influence on the harmonic issue. Both the designed C-type filter and active power filter performed a satisfying results on harmonics suppression.