SCADA systems have been successfully implemented in industries like oil, gas and electricity for maintenance, monitoring and control. While these systems provide immense advantage in terms of productivity, management and performance, they are also prone to exploitation and problems. These SCADA systems largely consist of network infrastructure which is subject to cyber security issues. Most of the weaknesses, or threats posed to these systems can be eliminated or reduced if the human aspect associated with them can be explored and corrected if needed. Because of human involvement in planning, designing, developing, deployment and operating of such systems, probability of flaws will always be present. This study focuses on such human aspects which effect cyber security in SCADA systems. We identified common mistakes which can be attributed to human error or negligence. A set of causes was then identified by use of interviews and finally, a Bayesian model was developed to simulate the identified cases and mistakes. We analyzed the influence and probability of occurrence of mistakes using this model. Our results prove that causes of the mistakes resulting in security problems for SCADA systems are directly related to human aspects. Furthermore, we identified some of the most prominent of these causes in this study. Based on the identified causes and mistakes, we suggested mitigation strategies to cater the problems faced.

The Modular Multilevel Converter (M2C) is proven to be a key converter technology which is suitable for various high-voltage high-power applications. It offers several advantages over the conventional Voltage Source Converters(VSC) and multilevel converters.This Thesis deals with the measurement system for an M2C. Different methods to measure submodule capacitor voltages are analyzed, implemented on circuit boards and verified experimentally. The aim is to define the best approach to measure submodule capacitor voltages from reliability, speed,accuracy and simplicity point of view. Initially, a detailed study on the operation of a M2C is given in order to define the importance of having a fast and accurate measurement system of the submodule capacitor voltages. Secondly, a study of different methods to measure capacitor voltages is carried out. First the configuration of an ADC (Analog-to-Digital Converter) is presented and afterwards an alternative method based on voltage-to-frequency conversion is presented. Then, a research of the electronic components which are suitable to fulfill the demands of such measurement systems and which are available on the market has been carried out. In particular, two different families of components are examined; VCOs (Voltage Controlled Oscillators) and VFCs(Voltage-to-Frequency Converters). As next step, the description of the digital interface between the submodule and the Field Programmable Gate Array (FPGA) is given. The FPGA receives information about the submodule capacitor voltages. This process is programmed using VHDL (VHSIC-very-high-speed-integrated-circuit Hardware Description Language). Finally, a hardware implementation of the measurement systems is performed, in order to verify the effectiveness of the proposed methods.

From a theoretical perspective, the bi-directional broadcast communication which follows from the network coding idea has been studied extensively in the literature. However, despite the potential gain, not much practical work has been realized. In this thesis, we designed and implemented the traditional bi-directional relaying with 4-phases and the bi-directional communication with XOR network coding with 3-phases schemes using Wireless Open Access Research Platform (WARP) boards. Our experimental results show that when we have low packet error rate, there is an approximately 30% throughput gain in the bi-directional communication with network coding. However, when the link quality degrades, the bene t of the bi-directional communication with network coding scheme becomes less apparent and the traditional bi-directional relaying tends to perform better. It is observed that the performance relates directly to the packet-error rate of the weakest node-relay link.

The conventional transmission planning tends to focus exclusively on efficiency benefit, allowing cheaper remote generation to have priority dispatch over expensivelocal generation (least cost approach). Because of this nowadays deregulatedmarkets face the problem that their systems affect the competitiveness of players,giving room for players to exercise market power.The purpose of this study is to develop a mathematical model that quantitiesthe generation cost and reduces market power, by minimizing the social cost andrestraining producers from withholding generation capacity. To do this, deterministicoptimal transmission switching is proposed, together with a Worst-NashEquilibrium (WNE) optimization, to quantify the social cost.This study considers the transmission switch formulation based on the DCOptimal Power Flow (DCOPF) presented by Schmuel S. Oren as a Mixed-Integerlinear Program (MIP). This formulation employs binary variables to representthe state of the transmission line. The effects of transmission switching withcontingency analysis are also considered in the DCOPF formulation.To include market power cost reduction in our problem, the social cost ofthe system is modeled considering WNE, which maximizes the social cost usinglinearization. The formulation includes strategic generators that might chooseto withhold some of their output and non-strategic generators. This under thecondition that the profit of a portfolio with a strategic generator under NashEquilibrium is always greater than the profit of a portfolio where the offers areconstant.A 14-node example system is studied where the effciency benefits and competitionbenefits of transmission capacity by optimal transmission switching areconsidered. The results demonstrate that the utilization of the proposed methodincrease economic benefit and improves competitiveness in the electricity market.

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.

Heating, Ventilation and Air Conditioning (HVAC) systems consist of all the equipment that control the conditions and distribution of indoor air. Indoor air must be confortable and healthy for the occupants to maximize their productivity. Moreover, HVAC energy consumption is between 20% and 40% of the total energy consumption in developed countries and accounts around 33% of the global CO 2emissions. So the study of HVAC systems plays an important role in building science. The aim of this project is to identify mathematical models that will be employed by intelligent control algorithms which guarantee human comfort indoors, energy saving and less CO 2emissions at the same time. Three models, based on first-principle physical knowledge, are proposed for CO 2concentration, temperature and humidity, respectively, for a room in the Q-building at KTH. Thermodynamic equations and an original estimation of the number of the occupiers of the room are employed. Validation shows that models have really good performances, even with a short training dataset. Discussions on the obtained results are given and some ideas for future work are proposed.

With respect to market liberalization, efficient use of resources is becoming more important for players in the market. In order to achieve that different optimization techniques were developed which enable better operational efficiency. These techniques can be segmented into two different categories, depending on their time horizon: • Yearly time horizon – mid-term hydropower scheduling • Daily time horizon – short-term hydropower scheduling These two time horizons account for two case studies presented in this thesis. In the first case study (mid-term planning), the focus is on determining power plant’s optimal operating strategy, while taking into account the uncertainty in inflows and prices. Stochastic dynamic programming has been chosen as mid-term optimization technique. Since stochastic dynamic programming calls for a discretization of control and state variables, it may fall under the curse of dimensionality and therefore, the modeling of stochastic variables is important. By implementing a randomized search heuristic, a genetic algorithm, into the existing stochastic dynamic programming schema, the optimal way of using the stochasticity tries to be found. Two price models are compared based on the economic quality of the result. The results give support to the idea of using search heuristics to determine the optimal stochasticity setup, however, some deviations from the expected results occur. Second case study deals with short-term hydropower planning, with a focus on satisfying the predefined demand schedule while obtaining maximum profit. With short-term hydropower planning being a nonlinear and nonconvex problem, the main focus is on the linearization of unit performance curves, as well as satisfying technical constraints from the power plant perspective. This optimization techniques also includes the water value in the solution. The problem has been solved by means of mixed integer linear programming. The results from the second case study are fully in line with the expectations and it is shown that mixed integer linear programming approach gives good results with good computational time. Suggested improvements to the model and potential for future work can be found in the final chapter of this thesis.

A resistive magnetohydrodynamic (MHD) code is presented in detail for a cylindrical plasma column surrounded by a perfect conducting wall. The objective is to develop a full eigenvalue problem solver with resistive wall type boundary conditions that can be integrated into the feedback control algorithms of the EXTRAP T2R reversed field pinch (RFP). For the straight tokamak model, linear analysis is carried out around a flowless background equilibrium followed by the normal mode expansion. The numerical method here applied relies on the weak formulation of the Galerkin method. Its implementation gives rise to a general eigenvalue problem which concerns the discretization of non-self adjoint matrix operator. Hence, we are forced to consider all variables to describe the dynamics of the system. Simulations were performed for both ideal and resistive MHD models. In the former case, the results show that the complete ideal spectrum can be extracted accurately, viz. the magnetoacoustic waves, Alfvén and slow modes, provided a shareless background magnetic field and in presence of the (m, n) = (2, 1) interchange instability. Particularly, the behaviour near the marginal point ω —> 0 is in agreement with theoretical predictions. We emphasize the subtleties regarding the optimal choice of space discretizaton, showing that the use of quadratic and cubic finite elements avoids numerical pollution. Concerning the resistive MHD calculations, the effect of resistivity is studied for a tokamak-like equilibrium profiles. Results show that the two most unstable modes, namely the tearing and interchange instabilities, can be extracted from the code simultaneously. Moreover, the scaling relations with resistivity for both growth rates are presented, showing the ∝ η 3/5 and ∝ η1/3 dependence for the tearing and interchange modes, respectively. Nevertheless, the results are found to be valid only for small values of resistivity. In addition, the effect of resistivity on the perturbed profiles is presented. The foreseen extension of the code to study external modes is discussed.

As transmission networks are getting older and as their components are reaching their life span’s end, the number of maintenance outages for equipments reparation or replacement is destined to gradually increase in the coming years. These outages weaken system’s security and lead to highstress situations that often do not comply with N-k operation rules. Thus in-depth risk analysis have to be performed in those cases, to ensure system’s smooth operation and optimal maintenance planning. It requires a comprehensive knowledge of contingencies consequences on system and society, but also refined contingencies occurrence probability estimations. This integration of probabilistic issues in operational problematic is challenging as current doctrines are profoundly deterministic, however the methodology developed here aims to comply with those while preparing the ground for future risk-based doctrines. Finally, integration of curative and preventive risk mitigation means gives more visibility to contingency probability reduction means and measures their economic efficiency, which leads to more optimal decision-making than the only use of classic consequences reduction techniques. This easily implementable method makes accessible new information to operators, allowing them to limit the use of systematic conservative and costly risk mitigation strategies.

Ferro‐resonance is an electrical phenomenon which can cause damage to electrical equipments of power systems by its characteristic steady state over voltages and over currents. Configurations where ferro‐resonance is possible has more than one steady state operation. With time domain simulations, different dangerous steady state operations are hard to find due to the fact of dependancy of initial conditions and parameters of the system. Determination of risk of ferro‐resonance needs special studies involving frequency domain and Fourier series based harmonic balance method. Two different types of harmonic balance method are used; namely analytical and numerical method. In order to draw twoparameter continuous curves, harmonic balance with hyper‐sphere continuation method algorithm is created in MATHCAD environment. Work of two case studies in academic literature are extended by comparing different system parameter curves and calculating stability domain risk zones for fundamental ferro‐resonance, subharmonic‐1/2 and subharmonic ‐1/3 ferro‐resonance. Alstom’s test system is also investigated with approximations. Application of numerical harmonic balance method is more superior than analytical method since it is ease of use with thevenin equivalents rather than deriving system equation by hand and possibility to study subharmonic ferro‐resonance. Hypersphere continuation method worked well enough to turn limit points on parameter curves depending on considered Fourier components. Critical values for system parameters have been found for each type of ferro‐resonance allowing to analyse normal operation and ferroresonance operation regimes. Critical values of static damping resistor in the system can be calculated by harmonic balance method without using empirical formula. Damping resistor calculated by harmonic balance method showed difference than the one calculated by empirical formula. Fundamental and subharmonic ferro‐resonance solutions existence zones are co‐existant and sensitive to parameter changes therefore same attention should be given to subharmonic as in fundamental ferro‐resonance. For future studies, three‐phase models for harmonic balance method should be developed in order to study neutral isolated networks and a more customized method of solving non‐linear harmonic balance equations for faster computation can also be developed in MATLAB environment.