High penetration of wind energy requires innovations in different areas of power engineering. Methods for improving wind energy and power system interconnection, control, and operation are proposed in this dissertation. A feed-forward transient compensation control scheme is proposed to enhance the low-voltage ride-through capability of wind turbines equipped with doubly fed induction generators. Stator-voltage transient compensation terms are introduced to suppress rotor-current overshoots and torque ripples during grid faults. A dynamic stochastic optimal power flow control scheme is proposed to optimally reroute real-time active and reactive power flow in the presence of high variability and uncertainty. The performance of the proposed power flow control scheme is demonstrated in test power systems with large wind plants. A combined energy-and-reserve wind market scheme is proposed to reduce wind production uncertainty. Variable wind reserve products are created to absorb part of the wind production variation. These fast wind reserve products can then be used to regulate system frequency and improve system security.

The major achievements of this work are based on two categories: (A) introduction of an advanced simulation technique in both time domain and frequency domain, and (B) realistic and reliable models for converters applicable to analysis of alternative transmission systems. The proposed modeling-methodology using a combination of model quadratization and quadratic integration (QMQI) is demonstrated as a more robust, stable, and accurate method than previous modeling methodologies for power system analyses. The quadratic-integration method is free of artificial numerical-oscillations exhibited by trapezoidal integration (which is the most popularly used method in power system analyses). Artificial numerical oscillations can be the direct reason for switching malfunction of switching systems. However, the quadratic-integration method has a natural characteristic to eliminate fictitious oscillations with great simulation accuracy. Also, model quadratization permits nonlinear equations to be solved without simplification or approximation, leading to realistic models of nonlinearities. Therefore, the QMQI method is suitable for simulations of network systems with nonlinear components and switching subsystems. Realistic and reliable converter models by the application of the QMQI method can be used for advanced designs and optimization studies for alternative transmission systems; they can also be used to perform a comprehensive evaluation of the technical performance and economics of alternative transmission systems. For example, the converters can be used for comprehensive methodology for determining the optimal topology, kV-levels, etc. of alternative transmission systems for wind farms, for given distances of wind farms from major power grid substations. In this case, a comprehensive evaluation may help make more-informed decisions for the type of transmission (HVAC, HVDC, and LFAC) for wind farms.

Nowadays, power systems are dealing with some new challenges raisedby the major changes that have been taken place since 80’s, e.g., deregu-lation in electricity markets, significant increase of electricity demands andmore recently large-scale integration of renewable energy resources such aswind power. Therefore, system operators must make some adjustments toaccommodate these changes into the future of power systems.One of the main challenges is maintaining the system stability since theextra stress caused by the above changes reduces the stability margin, andmay lead to rise of many undesirable phenomena. The other important chal-lenge is to cope with uncertainty and variability of renewable energy sourceswhich make power systems to become more stochastic in nature, and lesscontrollable.Flexible AC Transmission Systems (FACTS) have emerged as a solutionto help power systems with these new challenges. This thesis aims to ap-propriately utilize such devices in order to increase the transmission capacityand flexibility, improve the dynamic behavior of power systems and integratemore renewable energy into the system. To this end, the most appropriatelocations and settings of these controllable devices need to be determined.This thesis mainly looks at (i) rotor angle stability, i.e., small signal andtransient stability (ii) system operation under wind uncertainty. In the firstpart of this thesis, trajectory sensitivity analysis is used to determine themost suitable placement of FACTS devices for improving rotor angle sta-bility, while in the second part, optimal settings of such devices are foundto maximize the level of wind power integration. As a general conclusion,it was demonstrated that FACTS devices, installed in proper locations andtuned appropriately, are effective means to enhance the system stability andto handle wind uncertainty.The last objective of this thesis work is to propose an efficient solutionapproach based on Benders’ decomposition to solve a network-constrained acunit commitment problem in a wind-integrated power system. The numericalresults show validity, accuracy and efficiency of the proposed approach. / <p>The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively.QC 20141028</p>

Wind generation is one of the most successful sources of renewable energy for the production of electrical energy. Wind power offers relatively high capacities, with generation costs that are becoming competitive with conventional energy sources. However, a major problem to its effective use as a power source is the fact that it is both intermittent and diffuse as wind speed is highly variable and site-specific. This is translated in large voltage and frequency excursions and dynamically unstable situations when fast wind power changes. Very high wind speeds will result in sudden loss of wind generator production. The requirement to ensure that sufficient spinning reserve capacity exists within the system to compensate for sudden loss of generation becomes crucial. From the utilities operators’point of view, the primary objective is the security of the system, followed by the quality of the supplied power.<p>In order to guard the system security and quality of supply and retain acceptable levels, a maximum allowed wind power penetration (wind margin) is normally assumed by the operators. Very conservative methods are used to assess the impact of wind power and the consequences turn to under-exploitation of the wind power potential in a given region. This thesis presents the study of actual methods of wind power assessment, divided into three parts:<p>1. Part I: Impact on the Security of Power Systems<p>2. Part II: Impact on the Power Quality<p>3. Part III: Impact on the Dynamic Security of Power Systems / Doctorat en sciences appliquées / info:eu-repo/semantics/nonPublished

The following text is devoted to wind power stations. It shows basic distribution of wind engine according to the principle of their function and suitability of their use for power generation. It shows the parameters that must satisfy the suitable sites for building wind power stations and it shows wind maps of the Czech Republic. There are described some of the most frequently installed machines in the Czech Republic. Next chapters describe the economics running part of wind power stations; analyze the basic cost-sharing, mention methods of tax depreciation of tangible assets, the redemption value of electrical energy from renewable sources. There are chosen some of the most used methods for assessment the economic efficiency of wind power stations. There are common methods of static and dynamic in terms of time value of money, the possibilities and limitations of their use. This information is a basis for designing and implementing a program to calculate the economic efficiency of wind power station. The goal is to create a computer program based on your input values and calculation methods to calculate the economic indicators and economic effectiveness of project wind power station in terms of total investment coasts and on equity capital projects. Based on evaluation of data it will be ready to determine whether the investment in to the construction of wind power station can provide the required funding.

The wind power prediction plays a vital role in a wind power project both during the planning and operational phase of a project. A time series based wind power prediction model is introduced and the simulations are run for different case studies. The prediction model works based on the input from 1) nearby representative wind measuring station 2) Global average wind speed value from Meteorological Institute Uppsala University mesoscale model (MIUU) 3) Power curve of the wind turbine. The measured wind data is normalized to minimize the variation in the wind speed and multiplied with the MIUU to get a distributed wind speed. The distributed wind speed is then used to interpolate the wind power with the help of the power curve of the wind turbine. The interpolated wind power is then compared with the Actual Production Data (APD) to validate the prediction model. The simulation results show that the model works fairly predicting the Annual Energy Production (AEP) on monthly averages for all sites but the model could not follow the APD trend on all cases. The sensitivity analysis shows that the variation in production does not depend on ’the variation in roughness class’ nor ’the difference in distance between the measuring station and the wind farm’. The thesis has been concluded from the results that the model works fairly predicting the AEP for all cases within the variation bounds. The accuracy of the model has been validated only for monthly averages since the APD was available only on monthly averages. But the accuracy could be increased based on future work, to assess the Power law exponent (a) parameter for different terrain and validate the model for different time scales provided if the APD is available on different time scales.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis focuses on optimization of wind power tracking control systems in order to capture maximum wind power for the generation system. In this work, a mathematical simulation model is developed for a variable speed wind turbine power generation system. The system consists a wind turbine with necessary transmission system, and a permanent magnet synchronous generator and its vector control system. A new fuzzy based hill climbing method for power tracking control is proposed and implemented to optimize the wind power for the system under various conditions. Two existing power tracking control methods, the tip speed ratio (TSR) control method and the speed sensorless control method are also implemented with the wind power system. The computer simulations with a 5 KW wind power generation system are performed. The results from the proposed control method are compared with those obtained using the two existing methods. It is illustrated that the proposed method generally outperforms the two existing methods, especially when the operating point is far away from the maximum point. The proposed control method also has similar stable characteristic when the operating point is close to the peak point in comparison with the existing methods. The proposed fuzzy control method is computationally efficient and can be easily implemented in real-time.

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The cost of energy and national power utility Eskom, is currently under heated debate after the cost of electricity has more than doubled over the past three years, with another five annual increases of 8% approved by the National Energy Regulator of South Africa. The state owned utility has a monopoly on electricity production in South Africa having sole ownership over the transmission and distribution of electricity. Eskom produces 95% of South Africa’s electricity, predominantly from coal fired power stations, which is one of the leading causes why the country is one of the highest carbon dioxide emitters in the world. The question of independent power production and the use of our abundant renewable resources for electricity generation have been at the forefront with critics arguing against the heavy increases absorbed by industry and consumers. Although the renewable energy space is a well discussed topic, it is not well scientifically documented from an economic standpoint. The primary objective is to determine if renewable energy is price competitive with Eskom, or non-renewable electricity generation, by not only looking at the current scenario but also the future price projection and point where renewable energy is on parity with the grid price. For this purpose the Levelised Cost of Energy calculation method was used. Four different measuring instruments were produced for each technology namely, biogas, biomass, solar and wind and a financial model developed to determine the levelised cost, taking into consideration more complex financial structures, tax incentives, revenues and costs associated with by-products. From the literature it is clear that wind and solar, on a large scale, are competitive with the levelised cost of Eskom’s new build coal power plants and particularly wind, is lower than the grid price in 2017. The empirical study focused on a smaller scale of 1 to 5 megawatt and concluded that the levelised cost of wind energy is lower than Medupi coal fired power plant, currently under construction. The study also determined that biogas and biomass, under certain conditions relating to feedstock costs, are able to compete with Medupi and offer real and sustainable benefits in long-term energy supply. / MBA, North-West University, Potchefstroom Campus, 2015

The cost of energy and national power utility Eskom, is currently under heated debate after the cost of electricity has more than doubled over the past three years, with another five annual increases of 8% approved by the National Energy Regulator of South Africa. The state owned utility has a monopoly on electricity production in South Africa having sole ownership over the transmission and distribution of electricity. Eskom produces 95% of South Africa’s electricity, predominantly from coal fired power stations, which is one of the leading causes why the country is one of the highest carbon dioxide emitters in the world. The question of independent power production and the use of our abundant renewable resources for electricity generation have been at the forefront with critics arguing against the heavy increases absorbed by industry and consumers. Although the renewable energy space is a well discussed topic, it is not well scientifically documented from an economic standpoint. The primary objective is to determine if renewable energy is price competitive with Eskom, or non-renewable electricity generation, by not only looking at the current scenario but also the future price projection and point where renewable energy is on parity with the grid price. For this purpose the Levelised Cost of Energy calculation method was used. Four different measuring instruments were produced for each technology namely, biogas, biomass, solar and wind and a financial model developed to determine the levelised cost, taking into consideration more complex financial structures, tax incentives, revenues and costs associated with by-products. From the literature it is clear that wind and solar, on a large scale, are competitive with the levelised cost of Eskom’s new build coal power plants and particularly wind, is lower than the grid price in 2017. The empirical study focused on a smaller scale of 1 to 5 megawatt and concluded that the levelised cost of wind energy is lower than Medupi coal fired power plant, currently under construction. The study also determined that biogas and biomass, under certain conditions relating to feedstock costs, are able to compete with Medupi and offer real and sustainable benefits in long-term energy supply. / MBA, North-West University, Potchefstroom Campus, 2015