The total amount of frequency deviations have during the last decade increased exponentially in the Nordic synchronous power system. The transmission system operators have therefore decided to implement load frequency control as a new automatic control system to stem these frequency deviations. The aim of this feasibility study is to analyse the effects of an LFC implementation in Swedish hydropower stations by using a more dynamic river governing. The method chosen to analyse the effects of LFC-governing was to create a Matlab Simulink hydropower station library including dynamic modules for rivers and turbine governors. The library is then used to create a river reach that is implemented in an ENTSO-E model for the Nordic frequency reserves. The governing of the river uses economical dispatch theory to optimally distribute a LFC setpoint signal from the ENTSO-E model to the different hydropower stations. Results show that the developed method has a future potential to create more frequency controlled reserves. By creating a central governing unit it was possible to govern frequency controlled reserves over an entire river reach under certain scenarios, but there are still many obstacles to overcome before an actual implementation. The method does however show both the possibilities and drawback of frequency controlled reserves in cascade coupled hydropower systems.

The master thesis project has been executed with the cooperation of Borlänge Energi, with the aim of reducing the high electric energy dependency which Moldova has on Ukraine, Transnistria and Russia. The project examines what reduction that would be possible by wind power installations on the existing electrical grid of Moldova. The installations should not surpass the capacity of the transmission lines or the voltage levels according to regulation. The southern regions of Moldova proved to have the best wind conditions and the locations of Besarabeasca, Zarnesti, Leovo, Ciadyr and Cimislia in the southern region were chosen for wind power installations. For the analysis a model over the Moldovan electrical system is constructed. Each of the five chosen locations is modelled with a generator symbolizing the wind power installation. The power flow software PSS/E is used to construct the model. To examine possible wind power installations different scenarios are created. The scenarios are executed with the southern regions 110 kV system as a focus area. All scenarios are analysed with a contingency analysis, where transmission lines in the focus region are tripped. The contingency analysis and the scenarios are automated using the programming language Python. An economic analysis shows payback periods for wind power investments in Moldova, the analysis also shows the sensitivity of the electricity price and discount rates. The project concludes that wind power installations are possible with the Moldovan electric grid as it looks today. The installations would result in reducing the high dependency of imported electrical energy.

In the pursuit of a cleaner and sustainable environment, solar photovoltaic (PV) power has been established as the fastest growing alternative energy source in the world. This extremely fast growth is brought about, mainly, by government policies and support mechanisms world-wide. Solar PV technology that was once limited to specialized applications and considered very expensive, with low efficiency, is becoming more efficient and affordable. Solar PV promises to be a major contributor of the future global energy mix due to its minimal running costs, zero emissions and steadily declining module and inverter costs. With the expanding practice of managing decentralized power systems around the world, the role of private investors is increasing. Thus, the perspective of all stakeholders in the power system, including private investors, has to be considered in the optimal planning of the grid. An abundance of literature is available to address the central planning authority’s perspective; however, optimal planning from an investor’s perspective is not widely available. Therefore, this thesis focuses on private investors’ perspective. An optimization model and techniques to facilitate a prospective investor to arrive at an optimal investment plan in large-scale solar PV generation projects are proposed and discussed in this thesis. The optimal set of decisions includes the location, sizing and time of investment that yields the highest profit. The mathematical model considers various relevant issues associated with PV projects such as location-specific solar radiation levels, detailed investment costs representation, and an approximate representation of the transmission system. A detailed case study considering the investment in large-scale solar PV projects in Ontario, Canada, is presented and discussed, demonstrating the practical application and usefulness of the proposed methodology and tools.

Wind generation has become one of the most popular choices of technology for adding new generation capacity to power systems worldwide. Several factors have contributed to the increased integration of wind generation, including environmental concerns and the continual increase in fossil fuel prices. As well, recent regulations have moved toward limitations on greenhouse gases, especially in the European Union (EU). Similar laws are currently under consideration in the US and other parts of the world. Other factors have also promoted the use of wind energy, such as advances in manufacturing and control technology and the attractiveness of wind as a “green” source of energy. The large-scale integration of wind power into an electricity system introduces planning and operational challenges because of the intermittent nature of wind speed and the difficulty involved in predicting it. For these reasons, wind energy is often considered an unreliable energy source. Additional problems are associated with the integration of large-scale wind farms into an electrical grid, among which wind power fluctuation is the most challenging. To maximize the penetration level of wind energy in a grid, a reliable technology must be developed in order to eliminate or at least decrease wind power fluctuation. The primary goal of this thesis was to develop methods of maximizing the penetration level of wind energy conversion systems (WECSs) into a grid, which requires mitigating wind power fluctuation. A robust control technique has therefore been developed for mitigating wind power fluctuation. This control technique exploits historical environmental data collected over a number of years in order to evaluate the profile of the output power of a variety of wind energy conversion systems (WECSs). The developed control technique was applied to Types A and C WECSs modifying the pitch angle controller of Type A WECS and the back-to-back converter control of Type C WECS. The Attachment of a storage device to the WECSs after the control technique is applied was investigated from both an economic and a technical point of view. The optimum sizing and siting of the wind energy conversion system equipped with the proposed control technique was also studied. This research is expected to contribute to the advancement of WECS technology by presenting a feasible solution to the problems associated with the integration of large-scale WECSs into electrical grids.

Interest in Distributed Generation (DG) in power system networks has been growing rapidly. This increase can be explained by factors such as environmental concerns, the restructuring of electricity businesses, and the development of technologies for small-scale power generation. DG units are typically connected so as to work in parallel with the utility grid; however, with the increased penetration level of these units and the advancements in unit’s control techniques, there is a great possibility for these units to be operated in an autonomous mode known as a microgrid. Integrating DG units into distribution systems can have an impact on different practices such as voltage profile, power flow, power quality, stability, reliability, and protection. The impact of the DG units on stability problem can be further classified into three issues: voltage stability, angle stability, and frequency stability. As both angle and frequency stability are not often seen in distribution systems, voltage stability is considered to be the most significant in such systems. In fact, the distribution system in its typical design doesn’t suffer from any stability problems, given that all its active and reactive supplies are guaranteed through the substation. However, the following facts alter this situation: • With the development of economy, load demands in distribution networks are sharply increasing. Hence, the distribution networks are operating more close to the voltage instability boundaries. • The integration of distributed generation in distribution system introduces possibility of encountering some active/reactive power mismatches resulting in some stability concerns at the distribution level. Motivated by these facts, the target of this thesis is to investigate, analyze and enhance the voltage stability of distribution systems with high penetration of distributed generation. This study is important for the utilities because it can be applied with Connection Impact Assessment (CIA ). The study can be added as a complement assessment to study the impacts of the installation of DG units on voltage stability. In order to accomplish this target, this study is divided into three perspectives: 1) utilize the DG units to improve the voltage stability margin and propose a method to allocate DG units for this purpose, 2) investigate the impact of the DG units on proximity to voltage stability 3) conduct harmonic resonance analysis to visualize the impacts of both parallel and series resonance on the system’s stability. These perspectives will be tackled in Chapter 3, Chapter 4, and Chapter 5, respectively. Chapter 3 tackles placing and sizing of the DG units to improve the voltage stability margin and consider the probabilistic nature of both the renewable energy resources and the load. In fact, placement and sizing of DG units with an objective of improving the voltage stability margin while considering renewable DG generation and load probability might be a complicated problem, due to the complexity of running continuous load flow and at the same time considering the probabilistic nature of the load and the DG unit’s resources. Therefore, this thesis proposes a modified voltage index method to place and size the DG units to improve the voltage stability margin, with conditions of both not exceeding the buses’ voltage, and staying within the feeder current limits. The probability of the load and DG units are modeled and included in the formulation of the sizing and placing of the DG units. Chapter 4 presents a model and analysis to study the impact of the DG units on proximity to voltage instability. Most of the modern DG units are equipped with power electronic converters at their terminals. The power electronic converter plays a vital role to match the characteristics of the DG units with the requirements of the grid connections, such as frequency, voltage, control of active and reactive power, and harmonic minimization. Due to the power electronics interfacing, these DG units have negligible inertia. Thus, they make the system potentially prone to oscillations resulting from the network disturbances. The main goal of this chapter is to model and analyze the impact of distributed generation DG units on the proximity of voltage instability, with high penetration level of DG units. Chapter 5 studies the harmonic resonance due to the integration of DG units in distribution systems. Normally, the harmonic resonance phenomenon is classified as a power quality problem, however, this phenomenon can affect the stability of the system due to the parallel and series resonance. Thus, the main goal of this chapter is to study and analyze the impact of the integration of distributed generation on harmonic resonance by modeling different types of DG units and applying impedance frequency scan method.

The last two decades have brought about significant changes in the resource planning environment of electric power utilities throughout the world. The conventional generation technologies that have been the backbone of every electric utility i.e., coal, hydro, nuclear, oil and natural gas, are being re-examined to address environmental concerns and resource utilization. The research described in this thesis focuses on the adequacy and economic assessment of non-utility generation (NUG) and demand-side management (DSM) initiatives within a typical power system. The main objective was to examine and extend the ability of the contingency enumeration approach to evaluate the economic reliability benefits of incorporating NUG and DSM options separately or jointly in composite system adequacy assessment. Two test systems were employed in the evaluations. The studies undertaken in this thesis demonstrate the need for accurate load model representations which clearly reflect the mix of customer sectors at each bus.Chronological hourly load curves were developed for each load bus in the test systems recognizing the individual load profiles of the customers. The adequacy and economic implications of demand-side management initiatives in the test systems were examined at each load point in the composite generation and transmission configuration. This thesis illustrates the development of techniques by which system planners and operators can incorporate reliability cost/worth assessment power system applications. Focus is placed in the thesis on the utilization of reliability cost/worth concepts in integrated resource planning in the form of NUG additions and DSM initiatives. Methods for the joint implementation of NUG and DSM options in a composite power system are presented and examples from the studies conducted are used to illustrate the procedures. Studies are presented which illustrate the impacts of NUG additions and DSM initiatives on the test system planning reserve margins (PRM) and on the total societal cost of electrical energy. The total evaluated cost incorporates the explicit cost associated with customer failures but does not include the cost associated with DSM program implementation. The results of the studies conducted show that NUG facilities and DSM programs can have considerable reliability and economic impacts on electric power systems.

There has been significant development in the area of neural network based power system protection in the previous decade. Neural network technology has been applied for various protective relaying functions including distance protection. The reliability and efficiency of ANN based distance relays is improving with the developing digital technologies. There are, however, some inherent deficiencies that still exist in the way these relays are designed. This research addresses some of these issues and proposes an improved protective relaying scheme.<p> The traditional ANN distance relay designs use parameter estimation algorithms to determine the phasors of currents and voltages. These phasors are used as inputs to determine the distance of a fault from relay location. The relays are trained and tested on this criterion; however, no specific relay characteristic has been defined. There is a need for development of a new methodology that will enable designing of an ANN that works as a generic distance relay with clearly defined operating boundary.<p> This research work presents a modified distance relaying algorithm that has been combined with a neural network approach to eliminate the use of phasors. The neural network is trained to recognize faults on basis of a specific relay characteristic. The algorithm is flexible and has been extended for the design of other relays. The neural network has been trained using pure sinusoidal values and has been tested on a 17-bus power system simulated in PSCAD. The training and testing of the neural network on different systems ensures that the relay is generic in nature. The proposed relay can be used on any transmission line without re-training the neural network.<p> The design has been tested for different fault conditions including different fault resistances and fault inception angles. The test results show that the relay is able to detect faults in lesser time as compared to conventional relay algorithms while maintaining the integrity of relay boundaries.

This dissertation attempts to establish an analytical and comprehensive framework to deal with two critical challenges associated with voltage stability analysis: 1. To study the new competitive environment appropriately and give more incentive for reactive power supports, one has to evaluate the impacts of distributed market forces on voltage stability, which complicates the voltage stability analysis. 2. Accurately estimating voltage stability margin online is always the goal of the industry. Industry used to apply static analysis for its computation speed at the cost of losing accuracy. On the other hand, dynamic analysis can result in more accurate estimation, but generally has a huge computation cost. So a challenge is to estimate the voltage stability margin accurately and efficiently at a reasonable cost, especially for large system. Considering the first challenge, this dissertation applied eigenvalue based bifurcation analysis to allocate the contribution of voltage stability. We investigate how parameters of the system influence the bifurcations. Three bifurcations (singularity induced bifurcation, saddle-node and Hopf bifurcation) and their relationship to several commonly used controllers are analyzed. Their parameters’ impact on these bifurcations have been investigated, from which we found a way to allocate the contribution by analyzing the relative positions of the bifurcations. For the second challenge, a new fast numerical scheme is developed to estimate voltage stability margin by intelligently adjusting the load increase ratio. A criterion, named EMD (Equilibrium Manifold Deviation) criterion, is proposed to gauge the accuracy of the estimation. And based on this criterion, a new computation scheme is proposed. The validity of our new approach is proven based on the well-known Runge-Kutta-Fehlberg method, and can be extended to other explicit single-step methods easily. Numerical tests demonstrate that the new approach is very practical and has great potential for industrial applications. This dissertation extends our new numerical scheme to stiff systems. When a system is ill-conditioned, the implicit method would be applied to achieve numerical stability. We further demonstrate the validity to combine the intelligent load adjustment technique with the implicit method to save the computation cost without loss of accuracy. This dissertation also delves into the auto detection of stiffness of the power system, and extends our new numerical scheme to general sytems.

Power industry is undergoing a transition from the traditional regulated environment to the competitive power market. To have a reliable state estimator (SE) in the power market environment, two major challenges are emerging, i.e. to keep SE running reliably even under a contingency and to run SE over a grid with extremely large size. The objective of this dissertation is to use graph theory to address the above two challenges. To keep SE running reliably under a contingency, a novel topological approach is first proposed to identify critical measurements and examine network observability under a contingency. To advance the classical topological observability analysis, a new concept of contingency observability graph (COG) is introduced and it is proven that a power system network maintains its observability under a contingency if and only if its COG satisfies some conditions. As an application of COG, a two-stage heuristic topological approach is further developed based on the new concept of qualified COG (QCOG) to minimize the number of measurements and RTUs under the constraint that the system remains observable under any single contingency. To overcome the disadvantages of existing SE over extremely large networks, a textured distributed state estimator (DSE), which consists of the off-line textured architecture design and the on-line textured computation, is proposed based on COG and a new concept of Bus Credibility Index (BCI). The textured DSE is non-recursive, asynchronous and avoids central controlling node. Numerical tests verify that the performance of the new textured DSE algorithm improves greatly compared with existing DSE algorithms in respect of bad data detection and identification. Furthermore, the software implementation for DSE is formulated as an information integration problem over regional power markets, and is very challenging because of its size and complexity. A new concept of semantic knowledge warehouse (SKW), together with the proposed concepts of semantic reasoning software component (SRSC) and deduction credibility, is developed to implement such an information integration system.

As wind exploitation gains prominence in the power industry, the extensive use of this intermittent source of power may heavily rely on our ability to select the best combination of wind farming sites that yields maximal reliability of power systems at minimal cost. This research proposes a general method to minimize the wind park global power output variance by optimally distributing a predetermined number of wind turbines over a preselected number of potential wind farming sites for which the wind patterns are statistically known. The objective is to demonstrate the benefits of diversification for the reliability of wind-sustained systems through the search for steadier overall power outputs. Three years of wind data from the recent NREL/3TIER study in the western US provides the statistics for evaluating each site for their mean power output, variance and correlation with each other so that the best allocations can be determined. Some traditional reliability indices such as the LOLP are computed by using sequential Monte Carlo simulations to emulate the behavior of a power system uniquely composed of wind turbines and a load modeled from the 1996 IEEE RTS. It is shown that configurations featuring minimal global power output variances generally prove the most reliable for moderate load cases, provided the sites are not significantly correlated with the modeled load. Under these conditions, the choice of uncorrelated/negatively correlated sites is favored. The correlations between the optimized global wind power outputs and the modeled load are studied as well.