This master thesis is carried out at KTH Royal Institute of Technology in Stockholmthe spring 2017. The project analyses the impact of wind power in a power system.A fictitious power system, created from the Nordic32 test system, is used for theanalysis. The power sources in the test system are hydro power, nuclear power, CHPand wind power, resembling Swedish conditions. The power production planning inthe system is solved as a mixed integer linear programming problem in GAMS withhourly resolution. From the result of the planning problem calculations of CO2emissions are carried out with Monte Carlo simulations. Different cases with differentamounts of wind power installed in the test system are studied via a stochasticMarkov model. The load model in the test system consists of hourly time seriesdata for a specific day. Furthermore, challenges with wind power as a continuouslyvarying power source are studied. These challenges are balance between productionand consumption in the power system, excess of power etc.The results show that increasing the wind power production results in a decreasein CO2 emissions. This can be seen from the different simulations in the project.However, the results show that increasing the wind power production means that thesystem becomes more sensitive to keep the power balance. Moreover, the dischargecapacity and the efficiency of the hydro power plants are important factors in thetest system.

The European Council has recently set objectives in the matter of energy and climate

policies and thus the interest in renewable energies is more than ever at stake. However,

the introduction of renewable energies in an energy mix is also accelerated and altered

by political targets. The two most widespread renewable technologies, photovoltaic

and wind farms, have specific characteristics - decentralized, intermittency, uncertain

production forecast up until a few hours ahead - that oblige to adapt the network and

the current conventional generator control.

By using optimization techniques, it is possible to characterize the optimal energy mix

(i.e. the optimal share of every power technology in all the countries considered). In

this paper, the optimization function is defined as the sum of the yearly fixed cost of

deploying a certain amount of installed capacity with the cost of electricity generation

over the while year. Then the aim of the model is to evaluate the energy mix of least

cost.

One can imagine multiple applications for this model, depending on which issue is to

solve. Two case studies are developed in this report as examples. Renewable technologies

are modifying the organization of the electricity market because of their specific

characteristics. The first case study aims at quantifying the additional cost due to the

integration of renewable energies. The second is targeted to characterize the impact of

the integration of green energy sources on the deployment of Demand Response.

Electricity is an essential good, which can hardly be replaced. It can be produced thanks to a wide rangeof sources, from coal to nuclear, not to mention renewables such as wind and solar. In order to meetdemand at the lowest cost, an optimisation is made on electricity markets between the differentproduction plants. This optimisation mainly relies on the electricity production cost of each technology.In order to include long-term constraints in the short-term optimisation, a so-called use value (oropportunity cost) can be computed and added to the production cost. One long-term constraint thatEDF, the main French electricity producer, is facing is that its gas plants cannot exceed a given numberof operation hours and starts between two maintenances. A specific software, DiMOI, computes usevalues for this double constraint but its parameters needs to be tested in order to improve thecomputation, as it is not thought to work properly.DiMOI relies on dynamic programming and more particularly on an algorithm called Bellman algorithm.The software has been tested with EDF R&D department in order to propose some modellingimprovements. Electricity and gas market prices, together with real plant parameters such as startingcosts, operating costs and yields, were used as inputs for this work, and the results were checkedagainst reality.This study gave some results but they appeared to be invalid. Indeed, an optimisation problem wasdiscovered in DiMOI computing core: on a deterministic context, a study with little degrees of freedomwas giving better profits than a study with more degrees of freedom. This problem origin was notfound precisely with a first investigation, and the R&D team expected the fixing time to be very long.The adaptation of a simpler tool (MaStock) was proposed and made in order to replace DiMOI. Thisproject has thus led to DiMOI giving up and its replacement by MaStock. Time was missing to testcorrectly this tool, and the first study which was made was not completely positive. Further studiesshould be carried out, for instance deterministic ones (using real past data) whose results could becompared to reality.Some complementary studies were made from a fictitious system, in order to study the impact of someparameters when computing use values and operations schedules. The conclusions of these studiesare the little impacts that changes in gas prices and start-up costs parameters have on the global resultsand the importance of an accurate choice in the time periods durations used for the computations.Unfortunately these conclusions might be too specific as they were made on short study periods.Further case studies should be done in order to reach more general conclusions.

Recent concerns about the environment have resultedinto large investments in renewable energies for electricityproduction, especially wind power. The integration of renewablesources of energy raises however several problemswhich have not yet been completely understood nor studied.Oscillatory events around 13 Hz have been recorded inthe US by Oklahoma Gas & Electric (OG&E). Such a highfrequency is very different from the traditional and wellstudied Inter-area oscillations, it is also beyond the measurementcapabilities of most of the existing measurementequipments and monitoring tools.

This Thesis focuses on the development and implementationof algorithms for oscillation detection which can supportreal-time monitoring tools. It proposes a real-timemonitoring tool that exploits synchronized phasor measurementsfrom PMUs, which allow real-time analysis of higherfrequency events, filling the lack of such monitoring applicationin the power systems area. This tool was built as aprototype for real-time applications which utilize real-timePMU data for enhanced monitoring and control of powergrids.

The short-term (1 to 48 hours) predictability of wind power production from wind power plants in a power system is critical to the value of wind power. Advanced wind power prediction tools, based on numerical weather prediction models and designed for power system operators, are being developed and continuously improved. One objective of the EU-supported WILMAR (Wind power Integration in Liberalised electricity MARkets) project is to simulate the stochastic optimization of the operation of the Nordic and German power systems, in order to estimate the value of potential improvements of wind power prediction tools. For power system simulations including wind power, a model must be developed to simulate realistic wind speed predictions with adjustable accuracy, in which the correlations between wind speed prediction error at the spatially distributed wind power plants is accurate. The simulated wind speed predictions are then converted to aggregate wind power predictions for regions within the Nordic and German power systems. A Wind Speed Forecast Error Simulation Model, based on a multi-variate ARMA(1,1) time-series model, has been developed in Matlab. The accuracy of the model in representing real wind speed predictions in Denmark has been assessed, and various errors resulting from practical limitations of input data have been quantified.

The installation of wind power plant has significantly increased since several years due to the recent necessity of creating renewable and clean energy sources. Before the accomplishment of a wind power project many pre-studies are required in order to verify the possibility of integrating a wind power plant in the electrical network. The creation of models in different software and their simulation can bring the insurance of a secure operation that meets the numerous requirements imposed by the electrical system. Hence, this Master thesis work consists in the creation of a wind turbine model. This model represents the turbines installed at Lillgrund wind farm, the biggest wind power plant in Sweden. The objectives of this project are to first develop an accurate model of the wind turbines installed at Lillgrund wind farm and further to use it in different kinds of simulations. Those simulations test the wind turbine operating according to different control modes. Also, a power quality analysis is carried out studying in particular two power quality phenomena, namely, the response to voltage sags and the harmonic distortion. The model is created in the software PSCAD that enables the dynamic and static simulations of electromagnetic and electromechanical systems. The model of the wind turbine contains the electrical machine, the power electronics (converters), and the controls of the wind turbine. Especially, three different control modes, e.g., voltage control, reactive power control and power factor control, are implemented, tested and compared. The model is tested according to different cases of voltage sag and the study verifies the fault-ride through capability of the turbine. Moreover, a harmonics analysis is done. Eventually the work concludes about two power quality parameters.

Wave power is an energy source which could make a decisive difference in thetransition towards a more sustainable energy sector. The growth of wave powerproduction has however not been as rapid as the growth in other renewableenergy fields, such as wind power and solar power. Some technical obstaclesremain before a major breakthrough for wave power can be expected. Oneobstacle so far has been the low voltages and the resulting high power lossesin many wave power plants. A new type of wave power generator, which hasbeen invented by Anders Hagnestål at KTH in Stockholm, aims to solve theseproblems. This master’s thesis deals with the power electronic converter systemfor Anders Hagnestål’s generator. It describes the planning and constructionprocess for a single-phase AC/DC converter, which will eventually be a partof the larger converter system for the generator. A control system based onhysteresis current control is planned and assembled. The finished single-phaseconverter shows agreeable results working as an inverter, generating a distinctlysinusoidal AC voltage. However, some additional construction and calibrationin the digital control system remain, before the converter can be used in thepower conversion for a wave power plant.

Virtual Power Plant (VPP) is a concept that aggregate Distributed Energy Resources (DER) together, aims to overcome the capacity limits of single DER and the intermit-ted natural characteristics of renewable energy sources like wind and solar. The whole system can be viewed as a single large-capacity power plant from the system‘s point of view.

In this project, the literature review of VPP concept, architecture, existed project and the survey of VPP in Sweden are being conducted first. Secondly, the simplified VPP model is built on MATLAB/Simulink software. The simplified system contains a wind farm, a hydro power plant, a dynamic system load and an infinite bus representing the large transmission grid. During the simulation process, the generation and consump-tion unites are running according to the real history data located in external database. In the third place, optimized control schemes for the hydro unit in VPP model to decrease its effects on transmission grid are implemented in Simulink model. At the same time, hydro turbine should be controlled in an optimized way that without large turbulence. Basically, the hydro power plant is responsible for balancing the active power between the wind farm and dynamic load. Since there is a limit for the hydro turbine output, the rest of either power shortage or surplus power need to be com-pensated by the grid. This is the fundamental control scheme, so called run time con-trol scheme. The advanced control schemes here are based on the moving average control method and forecast compensation control method. The forecast compensa-tion control method use the 24 hours ahead load forecasting data generated by Artifi-cial Neural Network. Later on, analysis of those three control schemes will be pre-sented. The last part of the project is the conclusion of the different control schemes according to comparison of their control results.

Providing reliable electricity to everyone is a very important matter nowadays. Both thetransmission system operator and the distribution system operator are acting on the grid inorder to insure it. The latter sometimes has to deal with problems regarding the voltage,especially in rural areas. Those issues are crucial because they might lead to a bad functioning ordamage some appliances, so they lower greatly the quality of supply. Moreover, the installationof new small producers such as wind power plants and solar panels to this network hasworsened the situation by complicating and multiplying the constraints. New methods are thusneeded to bring more flexibility to the distribution grid and consequently solve the voltageproblems and possibly others.The aim of this project was to test possible solutions to voltage problems in the lowvoltage network which is the part of the distribution grid directly connected to the finalconsumers. The main ones were the use of an on-load-tap-changer, capacitors and the controlof the producers connected at this level. At first, statistical models for the loads and theproducers were developed. The simulation itself was then designed and programmed. It isbased on Monte Carlo using a load flow procedure and takes into account a 30 years evolutionof the network. Finally, many cases were run to observe various behaviors and the mostinteresting ones were selected for the conclusions.The results showed that the on-load tap-changer is the possibility that adds the mostflexibility to the system and seems thus the best option due to the high randomness of theevolution of such networks. The other options tested are efficient in specific cases and cheaperso they might be interesting when it is possible to forecast the new customers and producers ofthe area, which is unfortunately not often the case. Finally, the negative effect of unbalance onsuch networks has been highlighted and it would be very good idea to develop procedures ableto give the best repartition of consumers among the phases at every bus in order to optimizeparameters such as voltage and losses.

The supergrid denotes a transmission grid development option at European scalebased on large power corridors enabling to transport electricity from large productioncenters (such as large oshore wind farms) to large consumption centers.Technico-economic studies show that the development of supergrids could provideoverall benefits in terms of : economic welfare, security of supply and integrationof renewables at European scale. However, some regulatory issues, such asnon-harmonized financial regulatory models for grid investments and rules of coordinatedoperations among transmission system operators, are obstacles to realprojects implementation. In consequence it is of interest for the designer of gridtechnologies to integrate regulation early in the design process. The overall objectiveof the thesis it to propose a methodological approach enabling to integrateregulatory issues into design process. First, relevant regulatory issues are identifiedand classified. Second, a design method (method of technico-economic evaluationof grid technologies) which addresses selected regulatory issues is proposed. Last,the proposed design method is applied on a study case : the design of a power transmissioncorridor.First regulatory issue identified thanks to literature is that current planning methods(methods of assessment of expansion projects) do not measure properly theoverall benefits of supergrids. As a result, they do not make possible the harmonizationof financial regulatory models and eventually the actual development ofsupergrids. Second regulatory issue identified is the high uncertainty about futureoperating rules for two reasons : some current rules are not applicable to supegridsoperations and current security management methods are cost-inecient ina context with several transmission system operators. A general alternative designmethod consistent with future standard planning methods is chosen to address firstregulatory issue. That method is a risk-based cost minimization problem where anoptimal trade-o between technical costs and reliability costs is pursued by simulationof the power system. It relies on a probabilistic description of operatingconditions. The recommendation formulated regarding the second regulatory issueis that the application of the general design method to particular cases requires acase-per-case assessment of operating rules uncertainty. The case study illustratesvthe application of the proposed design method. First, relevant operating mechanismsare identified (system reduction). Then, system cost functions are expressedbased on the reduced power system representation. Additionally, simulation modelsare developed, implemented (on Python) and used to compare several power transmissioncorridor architectures.In conclusion, a risk-based method consistent with standard planning methodscurrent development seems the most appropriate design method to be used and uncertaintyabout future operating rules should be taken into account while applyingthe general design method. The reports shows that such a risk-based method enablesto discriminate between technologies. As a result, it seems a suitable decisiontool for the supergrid designer.

The traditional power systems are statically rated and sometimes renewable energy sources (RES) are curtailed in order not to exceed this static rating. The RES are curtailed because of their intermittent character and therefore, it is difficult to predict their output at specific time periods throughout the day. Dynamic Line Rating (DLR) technology can overcome this constraint by leveraging the available weather data and technical parameters of the transmission line.

The main goal of the thesis is to present prediction models of Dynamic Line Rating (DLR) capacity on two days ahead and on one day ahead. The models are evaluated based on their error rate profiles. DLR provides the capability to up-rate the line(s) according to the environmental conditions and has always a much higher profile than the static rating. By implementing DLR a power utility can increase the efficiency of the power system, decrease RES curtailment and optimize their integration within the grid.

DLR is mainly dependent on the weather parameters and specifically, in large wind speeds and low ambient temperature, the DLR can register the highest profile. Additionally, this is especially profitable for the wind energy producers that can both, produce more (until pitch control) and transmit more in high wind speeds periods with the same given line(s), thus increasing the energy efficiency. 

The DLR was calculated by employing modern Data Science and Machine Learning tools and techniques and leveraged historical weather and transmission line data provided by SMHI and Vattenfall respectively. An initial phase of Exploratory Data Analysis (EDA) was developed to understand data patterns and relationships between different variables, as well as to determine the most predictive variables for DLR. All the predictive models and data processing routines were built in open source R and are available on GitHub.

There were three types of models built: for historical data, for one day-ahead and for two days-ahead time-horizons. The models built for both time-horizons registered a low error rate profile of 9% (for day-ahead) and 11% (for two days-ahead). As expected, the predictive models built on historical data were more accurate with an error as low as 2%-3%. 

In conclusion, the implemented models met the requirements set by Vattenfall of maximum error of 20% and they can be applied in the control room for that specific line. Moreover, predictive models can also be built for other lines if the required data is available. Therefore, this Master Thesis project’s findings and outcomes can be reproduced in other power lines and geographic locations in order to achieve a more efficient power system and an increased share of RES in the energy mix

Li-ion batteries have demonstrated to be a very flexible source with energystorage capability. Due to their scalability and wide range of power and energydensities, they are suitable for several applications. Li-ion storage cantherefore provide different services, the remuneration of which depends onthe electricity market of the country. In this work, two different case studiesof combination of Li-ion batteries with large-scale renewable power plantshave been investigated: batteries with solar PV in India and with wind powerin Sweden. Simulation models have been developed to assess the operationand profitability potential of different services in these two case studies. Themodels have been built using control algorithms, linear optimization (LP) andstochastic programming techniques. The results show that the use of batteriesfor solar power output smoothing under a power purchase agreement canbe a profitable business case in India. Moreover, batteries providing primaryfrequency regulation (FCR-N) in Sweden show to have a positive economicvalue. System breakeven costs to make the stacking of wind power productionimbalance compensation and FCR-N services profitable have been found,which based on conservative price expectations should be achieved by 2022.

Renewable energy sources help reaching the environmental, social and economic goals of producing electrical energy in a clean and sustainable matter. Among the various renewable resources, wind power is assumed to have the most favorable technical and economic prospects and offers signicant potential for reducing greenhouse gas (GHG) emissions. As wind power installations are more and more common in power systems, additional research is needed in order to guarantee the quality and the stability of the power system operation.

Maintaining the frequency as close as possible to its rated level is one of the most important tasks for grid operators in order to maintain a stable electricity grid. However, the signicant penetration of wind generation in power grids has raised new challenges in the operational and planning decisions of power systems. Wind turbine units almost always include power converters decoupling the frequency dynamics of the wind power generators from those of the grid. This decoupling causes a reduction in the total system inertia, affecting the system's ability to overcome frequency disturbances.

To study the impact of wind power on the system inertia, first the Nordic 32-A System, representing a scaled version of the Swedish grid, is implemented in PSS/E. A system identication of model parameters with actual data follows. This ad-hoc identification method determines the dynamic parameters of the governors and prime movers in the model. The two metrics of primary frequency control; the instantaneous minimum frequency and the rate of change of frequency (ROCOF) are simulated using the identified power system, and via an extrapolation, the maximum wind power penetration in Sweden is found, considering that the system has to comply with the instantaneous minimum frequency requirements and also that the tripping of the generators' ROCOF relays is prevented.

The second part of the work focuses on an economic study of the cost to guarantee an adequate frequency response, particulary the Primary Reserve (PR). The Primary Reserves is the capacity of the generators that is reserved for the governors to use for Primary Frequency Control (PFC). Primary Reserves also include the ramping capability requirement of power plants for regulating power imbalances caused by contingencies. Recent studies have shown that having more renewable resources, such as wind with no PFC capability as well as an electricity market design with no incentive for PFC, are important drivers for a decline in the frequency response in the system. One solution is the careful design of a PFC ancillary service market by introducing suitable constraints to ensure the adequacy of Primary Frequency Control. However, applying these constraints will increase the generation cost especially when more and more windpower is integrated. This work proposes the use of an adequacy constraint to evaluate the economic impact of wind integration with respect to its influence on guaranteeing an adequate PFC. To analyze the cost increment for maintaining an adequate frequency response in the presence of wind power, an optimal power ow (OPF) problem is designed with an objective function of the generation cost minimization and considering a PFC adequacy constraint. The results show that the inclusion of the new constraints in the optimal dispatch OPF leads to a higher dispatch cost.

The total energy demand in the world is expected to increase in the future years due to thehigh development rate of developing countries. Access to energy enables development, butthe current global energy mix has to be modified if a sustainable growth is desired. Renewableenergy sources (RES) benefit from both a political and economic support from manygovernments and international entities. The growing installation of RES takes place both inlarge scale, as wind farms with sizes 10 – 1000 MW, and in small scale in homes or smallenterprises with sizes 100 W – 100 kW. Small scale wind power connected to the grid is rarenowadays except in the case of remote mini-grids. By contrast, small scale solar photovoltaic(PV) power is being more and more commonly installed, especially in the form of investorownedroof-installed units. Taking increasing small scale solar and wind power into accountin network planning is a challenge faced by the distribution system operator (DSO).The aim of this thesis is to present a guideline that assists DSOs when planning lowvoltage (LV) distribution networks (DN) with a large amount of small scale distributedgeneration (DG) on a short-term perspective. A review on integration issues of DG isperformed and over-voltage constraints are identified as the most relevant issue. Simple ruleshave already been designed for individual DG units, as the one presented in the AMKhandbookpublished by Svensk Energi; but these are not valid any more when consideringmore than one DG unit. The new proposed guideline employs the AMK-handbook as astarting point and develops it further by including the interaction between DG units. Theguideline is then applicable to scenarios with more than one DG unit. The maximum capacityof a new DG unit applying for a connection to a grid is calculated based on the location andcapacity of the already installed DG units, and without any reinforcement. The proposedguideline can be applied under no load and minimum load condition.Since this thesis is a collaboration project between KTH-Royal Institute of Technologyand Vattenfall R&D, two specific Swedish LV distribution networks owned by VattenfallEldistribution AB are studied. Scenarios with different penetration levels of DG, with valuesbetween 12% and 71%, and capacity of individual DG units below 43.5 kW are analyzed.Evaluation of the results shows that the proposed guideline leads to acceptable results. Thedevelopment of future simple guidelines is suggested to be based on the following twoaspects: absolute and relative location of the DG units; and a correct identification of the weakbus. Relative location reveals the interaction with other DG units within the DN. Moreover, itis stated that the use of the penetration level as a planning measure, based on the total DGcapacity, has a limited application.

Some communities in remote locations with high wind velocities and an unreliable utility supply, will typically install small diesel powered generators and wind generators to form a microgrid. Over the past few years, microgrid projects have been developed in many parts of the world, and commercial solutions have started to appear. Such systems face specific design issues, especially when the wind penetration is high enough to affect the operation of the diesel plant.

The dynamic behavior of a medium penetration hybrid microgrid is investigated. It consists of a diesel generator set, a wind-generator and several loads. The diesel engine drives a 62.5 kVA synchronous generator with excitation control. The fixed-speed wind turbine drives a 60 kW cage rotor induction generator. The microgrid can be connected to the utility grid but can also run as an isolated system. The total load of the microgrid is about 100 kVA which varies during the day, and consists of static and dynamic loads, including an induction motor.

The excitation controller and speed controller for the diesel’s synchronous generator are designed, as well as the power control of the wind turbine, and the controller for capacitor banks and dump load. The system is modeled and simulated using PSCAD.

The study evaluates how the power generation is shared between the diesel generator set and the wind generator, the voltage regulation during load connections, and discusses the need of battery energy storage, the system ride- through-fault capability and frequency control, particularly at times when the utility is disconnected and the microgrid is run as an independent isolated power system. The results of several case studies are presented.

In liberalized electricity markets, the outputs of controllable units (both generatorsand demands) must be defined at regular time intervals ("dispatch intervals"). Nowadays,balancing services are procured and dispatched not in the most efficient waypartly due to long dispatch intervals. The dispatch interval in most European countriesis one hour. The shortest dispatch interval is five minutes and is used in theAustralian National Electricity Market (NEM). During the dispatch interval, demandand wind power capacity uctuates a lot. To keep the supply-demand balance in thesystem, some generators participate in frequency control. This action increases thesystem operation cost.By reducing the dispatch interval to short periods of time over which physical limitsof the power system are fully respected, balance services could be dispatched in amore efficient way. This improves the overall economic efficiency of the system.This work derives the mathematical model for short-run economic dispatch. For thismodeling, three stages are considered: (1) initial steady state in which the systemmight be exposed to a change, (2) the transition period which models the transitioncost after the change happened and before the system goes to another steady stateequilibrium, and finally (3) the final steady state equilibrium which models the systemcost when the change in the system has been handled by the exible generating units.These three stages are modeled in a single optimization problem. The developedoptimization problem is a linear programming problem. The developed formulationfor the short-run economic dispatch is modeled in GAMS platform. Two applicationsof the proposed model are discussed: (1) power system security, and (2) real-timebalancing market. In the first application, analysis of the optimal dispatch of nodaloperating reserves to provide sufficient exibility to survive a set of credible contingenciesis performed. In the second application, an algorithm for the dispatch ofbalancing services in the real-time balancing market is proposed . These two applicationsof the proposed short-run economic dispatch are tested on a simple six-busexample system and IEEE twenty-four-bus example system. The optimal dispatch isfound and conclusions are drawn. The numerical results of the proposed model showpromising results.

This master thesis examines short term wind power forecasting time series models focusing on regimes conditioned to meteorological conditions and the incorporation of spatio-temporal aspects. Novel regime switching autoregressive and vector autoregressive models are proposed, implemented in a .NET framework, and evaluated. The vector autoregressive framework takes advantage of cross-correlation between sites incorporating upstream online production information from all wind farms within a given region. The regimes are formed using K-means clustering based on forecast meteorological conditions. Each of the proposed models are fit to hourly historical data from all of 2015 for 24 wind farms located in Sweden and Finland. Forecasts are generated for all of 2016 and are evaluated against historical data from that year for each of the 24 wind farms. The proposed models are successfully implemented into the .NET framework of Vitec Software’s Aiolos Forecast Studio, which is widely used in the Northern and Western Europe. Vitec’s Aiolos wind power forecast model is based on an ensemble of numerical weather prediction models and adaptive statistical machine learning algorithms. The proposed models are found to have significantly lower mean absolute error and root mean squared error compared to the Aiolos model and autoregressive model benchmarks. The improved short term wind power forecast will inform operation and trading decisions and translate to significant reductions in balancing costs for Vitecs customers. The improvement is valued at as much as between 9.4 million Euros to 42.3 million Euros in reduced balancing costs. Spatio-temporal aspects for wind power forecasting is shown to continue to be promising for improving current state-of-the-art wind power forecasting.

Congestion management methods are useful regulatory mechanisms to prevent transmission capacity problems. This thesis intends to assess whether congestion management can be cost effciently used to postpone or even avoid network capacity reinforcements while increasing the hosting capacity of wind power on Gotland. Two methods, re-dispatch and market splitting, are studied in details and applied to the Gotland case. A simplified electricity market model using historical data from Gotland was designed to perform the simulations. While these methods pass the cost of lack of transmission capacity on diffrent actors in the electricity market (mainly grid owner for re-dispatch and consumers and producers for market splitting), simulations indicate that both method could be employed to raise the installed production capacity of wind power on Gotland by at least 25MW above the stated limit of 195MW without negatively impacting the income of any actors. Moreover, market splitting eÿciently reflects the transmission problems on the energy price of Gotland, thus giving economic incentive for flexible power consumption to alleviate the problems.

In recent years there has been a rapid expansion in wind power production within the Nordic countries which creates a demand for accurate wind power models. This thesis looks into how to create accurate time series of wind power production that can be used in energy market simulations. The thesis has two main part swhere one is to create time series of wind power production based on the currently installed wind parks in the Nordic system and the second is to create future timeseries corresponding to year 2040.

The suggested model uses gridded wind speed time series from 1979 and onward coming from the meteorological model ERA-Interim. The locations of currently installed wind power capacity are matched with their corresponding ERA-Interimwind speed. A power curve is optimized to give the best fit with historical windpower production. The wind speeds time series are transformed into wind power production series by applying the power curve and finally aggregated into onewind energy production series per price region. These wind power production time series are then compared to historical wind power production data and later used for electricity market simulations in a program called EMPS.

For the year 2040 a new set of wind power production series are produced. The differenceis that technological development and increased geographical distribution are taken into account. The resulting series are then used in long term market simulations together with the wind power production series that represents the current system by shifting the weight factor each year from the current series tothe 2040 series.

The final series for the current system provides high hourly correlation and low errors compared with historical wind power production. The effect of the 2040 series gave higher wind value factors, higher power output in relation to installed capacity and a reduced variability in hourly wind power production.

International agreements have set high demands on the share of renewable energy in the total energy mix. From the different renewable sources, significant investments are made in wind power. More and more wind turbines are being built and their number is due to rise dramatically. There are many different generator technologies, but this paper focuses on the doubly-fed induction generator (DFIG).

DFIGs are generators which are connected to the grid on both stator and rotor sides. The machine is controlled via converters connected between the rotor and the grid. The size of these converters determines the speed range of the DFIG.

Wind farm connections to the grid must satisfy grid requirements set by transmission system operators. This means that the study of their dynamic responses to disturbances has become a critical issue, and is becoming increasingly important for induction generators, due to their growing size and number.

Several computer programs exist to carry out dynamical simulations and this work will focus on one of them, namely Power Factory from DigSilent. It offers a large choice of builtin components. These components can be controlled through input signals. It is therefore possible for the user to design control strategies.

Power Factory has two models of DFIG. A new model has also been developed, based upon a controllable voltage source. These three models are compared, in terms of dynamical behavior and simulation time. One is then used to study the effect of introducing a certain signal to the control strategy.

The interest for renewable energies is increasing in Sweden and wind power is a major factor for the increase. Therefore, it is expected that with increasing installed capacity from renewable resources the variations in the power system will increase drastically due to the unexpected energy production from these types of power sources. Thus, a flexible power production is required to balance these variations which can cause serious problems in the power system such as voltage flicker and harmonics. In Sweden, the hydropower is ideal for balancing due to the high installed capacity and the flexible generation of hydropower. Therefore it is import to study the capability of the hydropower systems at balancing these variations and this is done by studying the ability of the hydropower systems at producing with extreme variations on their power production. A short-term mixed-integer linear programming model is utilised to study the capability of a hydropower system while facing extreme variations in its power production. The extreme variations are modelled as square waves where the production of the hydropower system is forced to follow these square waves. The hydropower system model considers both the water delay time and the head-dependency of the power plants. Another interesting factor that is considered in the study is how the arrangement of the power plants in a hydropower system affects the power variation capabilities. The special aspect in this study is that the hydropower systems simulated are completely fictitious systems. This means that the crucial aspects that influence the variation in the power production of a hydropower system can be manipulated to study the effects. The results obtained showed that the capability of a hydropower system at following extreme variation in power production is highly dependent on the reservoir water contents of the different power plants during the simulation period. Another obvious factor that impacted the capability of a hydropower system was the arrangement of the power plants included in the system. Lastly it was shown that if a hydropower system is dominated by small reservoirs, then this will mean more variation in the efficiency of the power production

The aim of the project is to revise the load flow and dynamic PSS/E models of the Gotland network and validate them against a set of measurements collected during a major disturbance, a three phase short circuit in the 70 kV system.

The main task in revising the model is to convert the induction machine models of the wind turbines into user and manufacturer wind turbine models. The validation of the model is divided into two phases. The first is to use the measurements as well as some assumptions on the wind power generation and load distribution from the time of the fault to validate the dynamic behaviour of the system. The second is to use new measurements during a normal operation day. The latter would not be very helpful to illustrate the dynamic behaviour of the system, because of the lack of a major fault that would drastically affect the system, but it would nevertheless be useful to validate the load flow with greater accuracy.

The large integration of photovoltaic (PV) systems as well as wind turbines in the distribution grid poses new challenges on various levels. One of them is the increased steady-state voltage in the low voltage (LV) as well as the medium voltage (MV) grid, caused by the distributed generation. This can lead to voltage violations above the maximum allowed value of 110% of nominal voltage. There exist various approaches to mitigate this problem. These range from expensive grid reinforcements, like strengthened lines or the installation of on-load tap changers (OLTCs) in distribution transformers, to voltage controls by the distributed generators themselves. One of these voltage controls is the consumption of reactive power by PV inverters. This control can lower the voltage locally but also has an impact on other nodes of the network. A range of possibilities exist, most commonly using an active power dependent reactive power characteristic (cos φ (P) control) or using a voltage dependent reactive power characteristic (Q(U) control). These can either depend on local inputs or involve some kind of coordinated control, for which usually a communication infrastructure needs to be built up. In this thesis, two MV feeders located close to Worms, Germany, have been modelled and validated with measurement data provided by the local distribution system operator. Along the two feeders, a total of three low voltage grids has been modelled in detail. The effectiveness of a local Q(U) voltage control with a deadband has been compared with the worst case, where no reactive power control is applied, and with the best case, where all PV plants maximally participate in the reactive power control. These settings were then tested for different scenarios of increased PV shares. Furthermore, the impact of the Q(U) voltage control on other LV grids, located at the same feeder, has been analysed. The results, in conclusion, demonstrate: i) In general, the examined LV grids have already large PV penetrations and large resulting backflows during times of high PV output. However, the share can still be substantially increased, in particular on LV lines that currently have only low or moderate PV penetration; ii) The Q(U) with deadband regulation can increase the hosting capacity of PV plants typically between 20% and 33% for the investigated networks. The performance can however vary highly between different network configurations and PV distributions; iii) due to the Q(U) control, the reactive power support varies widely between different PV plants in the investigated grids. This decreases the fairness of this method and compensation measures might be needed. However, no quantification of this has been made; iv) The best case shows that good reactive power controls would have a very high potential, so e.g. coordinated voltage controls could significantly increase hosting capacities.

Physical systems are becoming more heterogeneous. Different engineering domainsare interacting more and more. Therefore, it is desirable to have modeling tools that allow multi-domain modeling. In thermal power plants, three engineering domains are of particular relevance: a) thermodynamics, b) mechanics and c) electrical engineering. The interaction of these three domains, among a few others, allows the generation of power, power control and power conversion. The goals of this project are: a) to derive a model of a thermal power station and its responses to frequency deviations (primary control), and, b) to document how frequency control is carried out in Denmark and Germany. A model of a thermal power plant has been derived in Dymola, a multi-domain modeling and simulation software tool. Fundamental components of thermal power plants, such as generator, steam turbine and turbine governor, are united in one overall model. Hence, the derived model integrates aspects of three engineering domains and captures respective phenomena relevant for frequency control. Recorded data from Block 1 of Amagerværket in Copenhagen, Denmark, is used to verify the model. Simulation results show that the model responds appropriately to frequency deviations and changes in power set point. Model simplifications are presented and motivated, and, for further model enhancements, possible future work is given. Environmental concerns enhance the integration of renewable energy sources, such as wind and solar power, into electricity production. Wind and solar power can cause fluctuations in power generation which must be compensated by controllable generating units. Due to the large and steadily increasing share of renewable electricity generation in Denmark and Germany, frequency control is documented in these two countries. Frequency control follows different strategies in the ENTSO-ERG Continental Europe (former UCTE) and Nordic (former NORDEL) systems 1 . Load-frequency control is used in the ENTSO-E RG Continental Europe system as a centrally controlled frequency restoring action. In the future, the market for balancing reserves can be expected to be intensified.

Despite all environmental and economic advantages of wind power, noise emission remains an issue for population acceptance. In France, the current noise emission regulation defines noise emergence level thresholds, leading to wind turbine curtailment. Great energy generation losses and thus lost revenues are at stake. This master thesis presents current acoustic campaigns conducted for the development of a wind power project in France and proposes acoustic model improvements to predict curtailment losses before the construction of the wind farm. It first gives insights about the French wind power context and a literature review of available technologies to reduce noise emission from the blades. It then presents the particularities of French regulation of emergence levels and the use of the norm NFS 31-114 during the commissioning acoustic control. It explains the current acoustic model used at the development stage to predict noise emission and curtailment and finally proposes improvements such as considering the topography, the environmental characteristics and the use of uncertainties.

Under the determined impulse of the European Union to limit the environmental impact of energy-related services, the electricity sector will face several challenges in coming years. Integrating renewable energy sources in the distribution networks is certainly one of the most urging issues to be tackled with. The current grid and production structure cannot absorb the high penetration shares anticipated for 2020 without putting at risk the entire system. The innovative concept of smart grid offers promising solutions and interesting implementation possibilities.

The objective of the thesis is to specifically study the technical and economic benefits that the creation of an aggregator on the Swedish island of Gotland would imply.

Comparing Gotland's power system characteristics to the broad variety of solutions offered by demand side management, wind power integration enhancement by demand response appeared particularly suited. A business case, specifically oriented towards the minimisation of transmission losses by adapting the electric heat load of private households to the local wind production was designed. Numerical simulations have been conducted, evaluating the technical and economic outcomes, along with the environmental benets, under the current conditions on Gotland. Sensitivity analyses were also performed to determine the key parameters for a successful implementation. A prospective scenario for 2020, with the addition of electric vehicles, has finally been simulated to estimate the long term profitability of an aggregator on the island.

The simulation results indicate that despite patent technical benefits for the distribution network, the studied service would not be profitable in the current situation on Gotland. This, because the transmission losses through the HVDC-cable concern limited amounts of power that are purchased on a market characterized by relatively cheap prices and low volatility. Besides, the high fixed costs the aggregator has to face to install technical equipment in every household constitutes another barrier to its setting up.

To ensure the reliable operation of the power system, stability analysis considering the interaction between wind power and power system must be understood. In this thesis, the impact of wind power on the stability of Nordic32A power system is of interest.

Many wind farms nowadays employ doubly fed induction generator (DFIG) variable speed wind turbines. In this thesis, a third order DFIG model and its control circuits are employed. The particle swarm optimization algorithm is developed to tune the power system stabilizer, which can greatly increase the computational efficiency and improve the damping of the power system.

Modal analysis is conducted to investigate the behavior of a wind power plant in a conventional power system. The interaction between generators is investigated when we add wind power plants in different locations. In some cases, some unstable oscillation modes may be observed due to the inter-area and local oscillations among different synchronous generator groups in the system.

This master thesis studies the flexibility of Swedish power system. Because of the increase of

fuel price and the environmental issues, renewable energy plays an increasingly important

role. Sweden parliament has a planning frame of 30 TWh wind power energy per year in

2020. Wind power generation is largely dependent of wind speed. Since wind speed varies

all the time and is hard to be predicted, the introduction of wind power will cause variation

of power generation which needs to be balanced. Therefore, it is very important to study the

regulation capacity of the power system in order to balance wind power. In Sweden, it is

hydropower and thermal power that plays the role as balancing power. In earlier studies at

Department of Electric Power Systems KTH, a model has been built to examine the flexibility

of Swedish hydropower system. The aim of this thesis is to further develop this original

model. In the improved model, the flexibility of thermal power in Sweden is included.

Moreover, the improved model further considers the future value of stored water and the

impact of delayed running water released from the upstream power plants at the end of

simulated week.

The whole model is a large short-time planning problem and the objective of this model is to

maximize the profits. In this thesis, the profit is expressed as the future value of hydropower

minus the generation cost of thermal unit. Besides, the profit also includes the income and

the cost for the trading energy. The improved model is built as an optimization problem in

GAMS. The time step is one hour and the time span of each simulation is one week. The load

consumption and wind power production in each area are given as time series. The

constraints considered in this model include the generation limitations, operational

constraints of thermal power plants, hydrological coupling of hydropower plants, load

balance in each bidding area and transmission capacity. Several case studies are performed

in this thesis. Two models, both original model and improved model, will be tested. To find

out how large the regulation capacity the Swedish power system has, four different

expansion levels of wind power: 0 MW, 4000 MW, 8000 MW and 12000 MW are introduced.

The information regarding hydropower is obtained from statistic data in 2009 and the wind

power data for each week is coming from scaling the data in earlier studies. The operational

constraints of thermal power plants are based on the statistics data from 2008 to 2012. The

main finding from these case studies is that spillage will not increase when more wind power

is introduced to the system but only increase when the export capacity is reached and the

surplus power cannot be exported to other countries. Therefore, it can be concluded that

the Swedish power system has good possibilities to balance large amounts of wind power.

However, some simplifications and assumptions are made when the model is built, which

will give rise to some inaccuracy to the result. Therefore, in the end of this thesis, some

future studies are suggested to further improve this model.

Different types of permanent magnet generators for wind power application have been subject of research during last two decades. In this thesis different topologies of electrical generators have been investigated for small scale vertical axis wind turbine application. A two stage induction generator is proposed as a alternative solution with respect to the cost of such a system. However, a biggest emphasis in the report has been put on the design of Permanent Magnet Synchronous Generator (PMSG) suitable for a small scale Vertical Axis Wind Turbine (VAWT)T˙ he characteristics of PMSG makes it highly compatible for variable speed Wind Energy Conversion System (WECS) without any pitch mechanism. Chapters 2 and 3 summarize a thorough literature survey on wind energy systems and corresponding electrical machines. The principles of wind aerodynamics is preceded by a review on wind turbine characteristics and challenges with emphasis on VAWT s. Further different topologies of electrical machines with focus on PMSG s including Permanent Magnet (PM) configurations, different windings and thermal behavior is presented. In chapter 4 a brief review on an alternative solution which includes an Induction Generator (IG) for fixed speed WECS is given. Next, In chapters 5, 6 and 7, a PMSG is designed and the design is verified by means of Finite Element Method (FEM) analysis and thermal modeling. Chapter 5 describes an analytical optimisation of a longitudinal, inner rotor, radial flux, surface mounted PMSG with concentrated winding and natural air cooling system. Cost of active material is chosen as the optimisation criterion. Concepts like "constraints", "requirements", "parameters" (including material, geometry and winding) and procedure of the design are described here. In chapter 6, a FEM model of the optimised machine is developed and the results are illustrated. The iron losses, calculated in this chapter are utilised in thermal analysis in chapter 7 . Thermal model developed is based on a lumped parameter circuit . It ensures the safe thermal behavior of the machine in nominal operation mode.

Distributed generation is transforming the power system grid to decentralized system where separate units like wind power generators or solar panel shall coexist and operate in tandem in order to supplement each other and make one extensive system as a whole so called smart grid. It is utmost important to have a control ability over such units not only on a field level but on a system level as well. To be able to communicate with numerous devices and maintain interoperability universal standard is a must. Therefore, one of the core standards relevant to smart grids is IEC 61850 – Power Utility Automation which comes into assistance and tackles aforementioned challenges. This project uses IEC61850 architecture to implement client/server windows applications for on-load tap changer remote control. The proposed solution and designed applications are tested together with a real time simulator where simple power system is modelled to emulate the system response to control signals in a real time. In this way, the implemented applications can be tried and assessed as if performing in real environment. Consequently, a user of the client application is able to remotely control voltage on the power transformer's secondary side and manipulate the switching equipment simulated in the model.

Wind power, as one of the fastest growing means of generation, can oer environmentalbenets. However, due to its stochastic nature it is dicult to designaccurate prediction tools, thus the forecast errors are inherently present. Goodunderstanding of the errors that may occur is imperative for greater penetrationof wind power into the system as it can facilitate power system planning andoperation.In this paper, wind power forecasts for dierent price areas in Sweden areanalysed and compared. For this purpose, data starting November 2015 weredownloaded every hour from the Nord Pool spot database and Python code forparsing and analysis was written. Common indicators, such as the root-meansquare(RMSE) and bias error were used to characterise the accuracy of theforecasts. As expected, it was shown that in general the RMSE decreases as theforecast hour approaches the delivery hour. In addition, systematic bias erroraround the day-ahead market closure time was identied and discussed.The paper continues to analyse wind power forecast error distribution withrespect to the forecast time and dierent production levels. Four statistical momentsof distribution function were calculated and compared. It was shown thatfor the forecast horizons between 0 and 36 hours the forecast error distributionfunctions are negatively skewed leptokurtic.The temporal wind power forecast error correlations between dierent horizonsas well as the spatial correlations between dierent price areas are calculatedand discussed. As expected, a stronger correlation was identied betweenneighbouring price areas. In addition, correlation coecients between the forecasterrors and the up and down regulation prices were calculated.Finally, a model was developed to quantify the amount of operating reservelevel needed to compensate the uncertainty in the system due to wind powerand load forecasts. Future scenarios with an increasing wind power penetrationlevel are simulated and the amount of operating reserve level for individualprice areas is calculated. It was shown that with rapidly increasing wind powerpenetration, especially price area SE3 will need to plan for higher operatingreserve levels to successfully cope with the uncertainty in the load and windpower forecasts.

During the past years, wind turbine technology has improved and the demand for new installations is increasing. The transmission system operators have looked into different technologies.

Three technologies are discussed in this Masters thesis. The first is the simple induction generator, which is one of the oldest technologies, but is becoming installed less because of increasing requirements of grid codes in Europe. Doubly fed induction generator (DFIG) technology is also examined, and the impact of two features, the crowbar and the chopper. Lastly direct drive synchronous generator (DDSG) technology is discussed.

The disconnection of wind farms due to fault in the western part of France is examined. The volume of shed wind power is highly dependent on the voltage level at which the fault occurs. The higher the voltage, the more wind farms are shed. The topology of the grid is also an important factor with regard to wind power shedding.

A study has been performed on the fault behaviour of a large DFIG wind farm installed near some nuclear power plants. If the fault occurs near these generating units, the wind farms will affect the stability of the power system, and the critical clearing time will decrease. The installation of active power regulation in the wind farms can reduce this effect.

After the deregulation, the electricity markets have been restructured in a way to draw an end to “natural monopoly” of the players. However, by the virtue of the especial nature of electricity market, it gives the players instincts to exercise the market power. As a result of these market power exercise, electricity market becomes inefficient. The presence of market power can change the dispatch order of generators, pressure to over-build transmission networks in order to relieve load pockets in a market. Perhaps most importantly, the exercise of market power results in power price rises and substantial wealth transfers between electricity customers and generators. For these reasons, electricity market regulators around the world tend to be interested in mechanisms for predicting marker power ex ante and detecting and controlling the exercise of market power ex post. At present, there are some indicators, used to predict the market power exercise ability of suppliers. These common ex-ante market power indicators however, mostly disregard power transfer distribution factor, generation and transmission constraints in electric systems and merging effect of the supplier. Moreover, these indicators usually concern static measurement of market power, when electrical power system reflects stochastic nature regarding load and wind generation capacity variation in any system. This master thesis suggests a probabilistic approach of a new market power indicator namely Transmission constrained-Pivotal Supplier Index (TC-PSI) to predict the probability of market power exercise for variation of loads and wind generations with considering generation and transmission constraints in a system.

On the path towards the commercialisation of wave energy, there are still certaindevelopmental challenges to be tackled by industry and academia. One of these challengesis the grid integration of wave farms along with the development of the offshore electricalnetworks for the farms. These networks are distinct from those of offshore wind farms oncertain features – connection layouts, electrical interface equipment (subsea connectors),power ratings and cable lengths amongst many others. These differences apart from somechallenges unique to wave farms make the corresponding research attractive.CorPower Ocean AB has been developing a 250 𝑘𝑊 point-absorber type Wave EnergyConverter (WEC) and the thesis investigates the afore-mentioned challenges with a stagewiseanalysis of wave farms comprising the CorPower WECs. Prior research on electricalnetworks for CorPower WECs is limited and in this regard the objective is to gain apreliminary insight into the electrical architecture of a pre-commercial wave farm.Furthermore, the entire study is based at the wave test site of the European Marine EnergyCentre (EMEC).Analysis of network architecture and operational constraints resulted in 4 networkvariants for the farm ratings of 2 𝑀𝑊 and 10 𝑀𝑊. Three of the variants are applied to a2 𝑀𝑊 farm and are subjected to a varied analysis after which the standout variant is chosenfor subsequent modelling and analysis in the form of a 10 𝑀𝑊 farm. The comparativeanalysis includes an investigation into the capital expenditure (CAPEX), the associatedcost uncertainty, technology readiness level (TRL) of the electrical components andnetwork efficiency.Dynamic modelling and simulation of the networks is then performed on DIgSILENTPowerFactory to provide the network efficiency and voltage quality parameters includingstep voltage change, operational voltage limits and voltage flicker. The voltage quality ofthe modelled networks at the connection point are largely found to be compliant to theUK Distribution Code, applicable at the EMEC site. But, the same could not be said for theresults at some of the internal points of the electrical networks of the wave farms as thevoltage levels at certain terminals were found to be on the higher side.From the results of the thesis, a greater understanding of the compatibility of variants fora 2 𝑀𝑊 farm and 10 𝑀𝑊 farm of 250 𝑘𝑊 point-absorber WECs, has been obtained.Overall, it is believed that the thesis has contributed to the growing reservoir ofinformation on offshore electrical networks of wave farms and the corresponding gridintegration issues.

It is well known that transmission investment yields two major benets: (a) it allows cheaper remote generation to substitute for more expensive local generation, (the efficiency benefit) and (b) by increasing the diversication of uncorrelated generation sources, allows a reduction in the volume of balancing services required (the diversification benefit). Conventional transmission planning processes tend to focus exclusively on the efficiency benefit.

It is well known that increasing wind penetration increases the need for balancing services. Even where the market is able to provide the signals to generators as to when and how much to produce, increasing wind penetration increases the need for higher- exibility plant (such as OCGT or very fast start hydro plant) which typically has a higher long-run cost.

The purpose of this study is to develop a mathematical model for quantifying the diversification benefit for transmission investment.

To do this two-step economic dispatch of the day-ahead energy market and the real-time balancing market are mathematically formulated in a single optimization problem which calculates the results of day-ahead market dispatch and real-time market dispatch in one optimization problem. The new formulation is a linear programming problem which calculates the dispatch cost and the economic deviation from the dispatch cost.

Firstly, this single optimization problem is used for quantifying the diversification benefit of the additional transmission capacity.

Then, a stochastic optimization model for modeling the diversification benefit of additional transmission capacity in the transmission planning process is formulated. Uncertainty of system parameters are modeled using scenarios. ARIMA models anda scenario reduction technique based on Kantorovich distance are used for generating the scenarios.

To explain the diversification benefit, two example systems are studied. Firstly, to evaluate the impact of additional transmission capacity on the dispatch cost of the day-ahead energy market and the real-time balancing market, IEEE thirty-node example system is studied. The diversification benefit is calculated and the conclusions are extracted. Then, a transmission planning approach, which considers the diversification benefit along with the efficiency benefi, is proposed. The proposed and conventional transmission planning approaches are applied to modied IEEE 24-node example system. Conventional transmission planning approach (which models only efficiency benefit in its formulation) is used as a benchmark in this study.

The numerical results show that the proposed approach can effectively quantify the diversification benefit of additional transmission capacity.

It is well known that transmission investment yields two major bene_ts: (a) it allows cheaper remote generation to substitute for more expensive local generation, (the e_ciency bene_t) and (b) by increasing the diversi_cation of uncorrelated generation sources, allows a reduction in the volume of balancing services required (the diversi_cation bene_t). Conventional transmission planning processes tend to focus exclusively on the e_ciency bene_t. It is well known that increasing wind penetration increases the need for balancing services. Even where the market is able to provide the signals to generators as to when and how much to produce, increasing wind penetration increases the need for higher-exibility plant (such as OCGT or very fast start hydro plant) which typically has a higher long-run cost.

The purpose of this study is to develop a mathematical model for quantifying the diversi_cation bene_t for transmission investment. To do this two-step economic dispatch of the day-ahead energy market and the real-time balancing market are mathematically formulated in a single optimization problem which calculates the results of day-ahead market dispatch and real-time market dispatch in one optimization problem. The new formulation is a linear programming problem which calculates the dispatch cost and the economic deviation from the dispatch cost.

Firstly, this single optimization problem is used for quantifying the diversi_cation bene_t of the additional transmission capacity. Then, a stochastic optimization model for modeling the diversi_cation bene_t of additional transmission capacity in the transmission planning process is formulated. Uncertainty of system parameters are modeled using scenarios. ARIMA models and a scenario reduction technique based on Kantorovich distance are used for generating the scenarios.

To explain the diversi_cation bene_t, two example systems are studied. Firstly, to evaluate the impact of additional transmission capacity on the dispatch cost of the day-ahead energy market and the real-time balancing market, IEEE thirty-node example system is studied. The diversi_cation bene_t is calculated and the conclusions are extracted. Then, a transmission planning approach, which considers the diversi_cation bene_t along with the e_ciency bene_t, is proposed. The proposed and conventional transmission planning approaches are applied to modi_ed IEEE 24- node example system. Conventional transmission planning approach (which models only e_ciency bene_t in its formulation) is used as a benchmark in this study. The numerical results show that the proposed approach can e_ectively quantify the diversi_cation bene_t of additional transmission capacity.

The Swedish parliament has passed a planning framework to increase wind power production

and have the annual production of 30 TWh wind power in 2020. The expansion of a

continuously varying generation would result in an increased need for the capability of power

system to keep the balance between generation and consumption. Therefore, it is important to

study the flexibility of Swedish power system.

Two models of Swedish power system are studied in this thesis work. The first model is a

model of Swedish hydro power system which has been developed at KTH. The KTH model is

formulated as a large linear optimization problem simulated in GAMS platform. It has a

detailed representation of large hydro power plants but presents a simple model of electricity

market and trading to other areas. The other model is Apollo which is developed by Sweco

Company. Apollo is also formulated as an optimization problem and is a market model which

uses a simplified model of hydro power system.

The objective of this thesis work is to exchange data between the two models in order to

compare, validate and if possible improve the models. To exchange data, the inputs and some

outputs of Apollo are used as the inputs of KTH model and finally the outputs of KTH model

is compared with the corresponding outputs of Apollo.

There are some differences between the two models that must be removed in order to

exchange data. All of differences except one of them are removed by data adjustment. The

different methods that are used to remove those differences are discussed in the report. Due to

the remaining difference and different efficiencies in the two models, scenarios cannot be

directly transformed from Apollo to the KTH model. Therefore, three methods are introduced

as compensation for the remaining differences. After applying those methods the same results

can be obtained in the two models.

As a result of the work on the data exchange some improvements are implemented in the

KTH model and some improvements are identified and proposed for future work. The

improvements are toward removing all the differences between the two models and make the

models more similar to the real Swedish hydro power system. It is also concluded from the

results that the Apollo hydro power schedules are feasible according to KTH model of hydro

power system. This shows that Apollo does not overestimate the flexibility of Swedish hydro

power system in the tested scenarios.

The North European power system (Sweden, Finland, Norway, Denmark, Estonia, Latvia and Lithuania) is facing changes in its electricity production. The increasing share of intermittent power sources, such as wind power, makes the production less predictable. The decommissioning of large plants, for environmental or market reasons, leads to a decrease of production capacity while the demand can increase, which is detrimental to the power system reliability. Investments in interconnections and new power plants can be made to strengthen the system. Evaluating the reliability becomes essential to determine the investments that have to be made.

For this purpose, a model of the power system is built. The power system is divided into areas, where the demand, interconnections between areas, and intermittent generation are represented by Cumulative Distribution Functions (CDF); while conventional generation plants follow a two-state behaviour. Imports from outside the system are set equal to their installed capacity, with considering that the neighbouring countries can always provide enough power. The model is set up by using only publicly available data.

The model is used for generating numerous possible states of the system in a Monte Carlo simulation, to estimate two reliability indices: the risk (LOLP) and the size (EPNS) of a power deficit. As a power deficit is a rare event, an excessively large number of samples is required to estimate the reliability of the system with a sufficient confidence level. Hence, a pre-simulation, called importance sampling, is run beforehand in order to improve the efficiency of the simulation.

Four simulations are run on the colder months (January, February, March, November, December) to test the reliability of the current system (2015) and of three future scenarios (2020, 2025 and 2030). The tests point out that the current weakest areas (Finland and Southern Sweden) are also the ones that will face nuclear decommissioning in years to come, and highlight that the investments in interconnections and wind power considered in the scenarios are not sufficient to maintain the current reliability levels. If today’s reliability levels are considered necessary, then possible solutions include more flexible demand, higher production and/or more interconnections.

Hybrid Energy Resource System (HERS) is studied and applied aroundworld in recent years. Control and monitor of them are quite important in realapplication. HERS also has the equirement to integral with power grid such asdistribution grid networks. Therefore, to design and implement the informationcommunication system following IEC 61850, which is most promising standard fordesign of substation communication and automation system, is necessary. This paperpresents the design of Information Communication Technology (ICT) architectureand Unified Modeling Language (UML) models and final implementation through LabVIEW programming for Smart Energy Container. Applying design following IEC61850 series standards allow the HERS can communicate and interoperate with other IEC61850 devices and SCADA systems. The implementation is applied to SmartEnergy Container which contains wind power, solar power, battery energy storagesystem, and hydrogen energy storage system. Verification and testing results shows thedesign is qualified to control and monitor Smart Energy Container.

Maintenance is crucial in any industry to keep components in a reasonable functionalcondition, especially in electric power system, where maintenance is done so that thefrequency and the duration of a fault can be shortened, thus increasing the availability of acertain component. And the reliability of the whole electric power system can also beimproved. In the many deregulated electricity markets, reliability and economic drivingforces are the two aspects that system operators mainly consider. It is expected for thesystem operator to provide consumers with the electricity of highest reliability and lowestcost. Therefore, in order to achieve this goal, providing the most economic maintenanceschedule is vital in today’s power systems. One technique is Reliability CentredMaintenance (RCM), which is an effective method to maintain a certain level ofreliability while carrying out maintenance schedules in an economic way.

This thesis proposes an optimization problem for implementing the RCM method for apower system with renewable energy generators such as hydro power, wind power andsolar panel generators. This aim is achieved through the following steps:

1- Literature review on power system reliability.

2- Literature review on maintenance scheduling methods by focus on RCM method.

3- Compare the difference of conventional generators and renewable generators andmodel renewable generators in the power system.

4- Formulating the RCM method as an optimization problem.

5- The formulated model in 4 should be simulated for a test system using MATLAB.

6- The developed model in 5 is solved for different sets of available maintenanceIIstrategies.

7- Summing all possible costs when different maintenance strategies are carried outand compare the costs. Choose the maintenance strategy with the lower cost tocarry out the maintenance.