Regulation of Electricity Transmission and Distribution in Russia

The regulation of electricity transmission and distribution business is an essential issue for any electricity market; it is widely introduced in developed electricity markets of Great Britain, Scandinavian countries and United States of America and other. Those markets which were liberalized recently also need well planned regulation model to be chosen and implemented. In open electricity markets the sectors of electricity distribution and transmission remain monopolies, so called "natural monopolies", as introducing the competition into these sectors in most cases appears to be inefficient. Thatis why regulation becomes very important as its main tasks are: to set reasonable tariffs for customers, to ensure non-discriminating process of electricity transmission and distribution, at the same time to provide distribution companies with incentives to operate efficiently and the owners of the companies with reasonable profits as well; the problem of power quality should be solved at the same time. It should be mentioned also, that there is no incentive scheme which will be suitable for any conditions, that is why it is essential to study differentregulation models in order to form the best one for concrete situation. The aim of this Master's Thesis is to give an overview over theregulation of electricity transmission and distribution in Russia. First, the general information about theory of regulation of natural monopolies will be described; the situation in Russian network business and the importance of regulation process for it will be discussed next. Then there is a detailed description ofexisting regulatory system and the process of tariff calculation with an example. And finally, in the work there is a brief analysis of problems of present scheme of regulation, an attempt to predict the following development of regulationin Russia and the perspectives and risks connected to regulation which could face the companies that try to enter Russian electricity market (such as FORTUM OY).

Power line communication in motor cables of variable-speed electric drives − analysis and

Data transmission between an electric motor and a frequency converter is required in variablespeed electric drives because of sensors installed at the motor. Sensor information can be used for various useful applications to improve the system reliability and its properties. Traditionally, the communication medium is implemented by an additional cabling. However, the costs of the traditional method may be an obstacle to the wider application of data transmission between a motor and a frequency converter. In any case, a power cable is always installed between a motor and a frequency converter for power supply, and hence it may be applied as a communication medium for sensor level data. This thesis considers power line communication (PLC) in inverter-fed motor power cables. The motor cable is studied as a communication channel in the frequency band of 100 kHz−30 MHz. The communication channel and noise characteristics are described. All the individual components included in a variable-speed electric drive are presented in detail. A channel model is developed, and it is verified by measurements. A theoretical channel information capacity analysis is carried out to estimate the opportunities of a communication medium. Suitable communication and forward error correction (FEC) methods are suggested. A general method to implement a broadband and Ethernet-based communication medium between a motor and a frequency converter is proposed. A coupling interface is also developed that allows to install the communication device safely to a three-phase inverter-fed motor power cable. Practical tests are carried out, and the results are analyzed. Possible applications for the proposed method are presented. A speed feedback motor control application is verified in detail by simulations and laboratory tests because of restrictions for the delay in the feedback loop caused by PLC. Other possible applications are discussed at a more general level.

Modelling of North-West Russian market behavior considering technical restrictions of transmission grid

Nowadays the Finnish-Russian electric energy interaction is carried out through the back-to-back DC Vyborg substation and several power plants working synchronously with Finnish power system. Constant amount of energy flows in one direction — from Russia to Finland. But the process of electricity market development in Russian energy system makes the new possibilities of electrical cooperation available. The goal of master's thesis is to analyze the current state and possible evolution trends of North-West Russian system in relation with future possible change in power flow between Russia and Finland. The research is done by modelling the market of North-West Russia and examination of technical grid restrictions. The operational market models of North-West region of Russia for the years 2008 and 2015 were created during the research process. The description of prepared market models together with modelling results and their analysis are shown in the work. The description of power flow study process and results are also presented.

Development of power flows around Baltic countries with new grid links

In the Thesis main focus is done on power flow development paths around the Baltic States as well as on market-based requirements for creation of the common Baltic electricity market. Current market regulations between the countries are presented; barriers for creating competitive common Baltic power market and for electricity trading with third countries are clarified; solutions are offered and corresponding road map is developed. Future power development paths around the Baltic States are analysed. For this purpose the 330 kV transmission grid of Estonia, Latvia and Lithuania is modelled in a power flow tool. Power flow calculations are carried out for winter and summer peak and off-peak load periods in 2020 with different combinations of interconnections. While carrying out power balance experiments several power flow patterns in the Baltic States are revealed. Conclusions are made about security of supply, grid congestion and transmission capacity availability for different scenarios.

Chelyabinsk CHP-3 “locked power” problem solving

All over the world power systems become bigger and bigger every day. New equipment is installed, new feeders are constructed, new power units are installed. Some old elements of the network, however, are not changed in time. As a result, “bottlenecks” for capacity transmission can occur. By locked power problem the situation when a power plant has installed capacity exceeding the power it can actually deliver is usually meant. Regime, scheme or even technical restrictions-related issues usually cause this kind of problem. It is really important, since from the regime point of view it is typical decision to have a mobile capacity reserve, in case of malfunctions. And, what can be even more significant, power plant owner (JSC Fortum in our case) losses his money because of selling less electrical energy. The goal of master`s thesis is to analyze the current state of Chelyabinsk power system and the CHP-3 (Combined Heat and Power plant) in particular in relation with it`s ability to deliver the whole capacity of the CHP in it`s existing state and also taking into consideration the prospect of power unit 3 installation by the fourth quarter of 2010. The thesis contains some general information about the UPS of Russia, CPS of Ural, power system of Chelyabinsk and the Chelyabinsk region itself. Then the CHP-3 is described from technical point of view with it`s equipment observation. Regimes for the nowadays power system and for the system after the power unit 3 installation are reviewed. The problems occurring are described and, finally, a solution is offered.

Energy Efficiency Consideration in Electric Vehicle Transmission

This study is a survey of benefits and drawbacks of embedding a variable gearbox instead of a single reduction gear in electric vehicle powertrain from efficiency point of view. Losses due to a pair of spur gears meshing with involute teeth are modeled on the base of Coulomb’s law and fluid mechanics. The model for a variable gearbox is fulfilled and further employed in a complete vehicle simulation. Simulation model run for a single reduction gear then the results are taken as benchmark for other types of commonly used transmissions. Comparing power consumption, which is obtained from simulation model, shows that the extra load imposed by variable transmission components will shade the benefits of efficient operation of electric motor. The other accomplishment of this study is a combination of modified formulas that led to a new methodology for power loss prediction in gear meshing which is compatible with modern design and manufacturing technology.

Vibration analysis of a power take-off line

Gear rattle is a phenomenon that occurs when idling or lightly loaded gears collide due to engine’s torque fluctuations. This behaviour is related to vibration behaviour of the transmission system. Aim of this master’s thesis is to evaluate Adams and Adams/Machinery as a simulation tools for modelling the rattle e ect in a transmission system. A case study of tractor’s power take-o driveline, suspected to be prone to rattle, is performed in this work. Modelling methods used by Adams in this type of study are presented in the theory section while simulation model build with the software during this work is presented in the results. The Machinery toolbox is used to create gears and bearings while other model components are created with standard Adams tool set. Geometries and excitations are exported from other softwares. Results were obtained from multiple variations of a base model. These result sets and literature review suggest that Adams/Machinery may not be the most suitable tool for rattle analysis. While the system behaviour was partially captured, for accurate modelling user-written routines must be used which may be more easily performed with other tools. Further research about this topic is required.

La transmission des normes internationales en droits de la personne et le développement démocratique au Mexique

Quel est le pouvoir des normes internationales de droits humains ? Ces normes ont-elles un pouvoir politique? En s’appuyant sur le cas mexicain (entre 1988 et 2006), la thèse tente de répondre à trois questionnements. Le premier est lié à la trajectoire des normes: les défenseurs mexicains des droits humains cherchent-ils l’appui d’acteurs internationaux pour promouvoir les droits humains vis-à-vis leur gouvernement, tel que le suggère le modèle du boomerang ? Deuxièmement, il s’agit de comprendre l’impact du processus de diffusion des normes sur le respect des droits humains : les acteurs internationaux et nationaux qui défendent les droits humains parviennent-ils à influencer les décisions politiques gouvernementales, en matière de protection des droits humains ? Et finalement: ces groupes contribuent-ils à changer le cours du processus de démocratisation d’un État ? Les résultats de la recherche permettent de tirer quelques conclusions. La thèse confirme dans un premier temps la théorie du boomerang de Keck et Sikkink (1998), puisque les pressions domestiques en matière de droits humains deviennent efficaces au moment où les acteurs domestiques gagnent l’appui des acteurs internationaux. En ce qui concerne l’impact de la diffusion des normes internationales des droits humains sur leur protection gouvernementale, il semble que le gouvernement mexicain entre 1988 et 2006 réagisse aux pressions des acteurs qui diffusent les normes de droits humains par la mise en place d’institutions et de lois et non par une protection effective de ces droits. Un deuxième type d’impact, lié à la diffusion des normes en droits humains, est observé sur le processus de démocratisation. La thèse montre que les acteurs qui diffusent les normes en droits humains jouent un rôle dans la mise en place de réformes électorales, tout en contribuant à une redéfinition plus démocratique des rapports de pouvoir entre la société civile et l’État.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Synthesis of Bio-Compatible SPION–based Aqueous Ferrofluids and Evaluation of RadioFrequency Power Loss for Magnetic Hyperthermia

Bio-compatible magnetic fluids having high saturation magnetization find immense applications in various biomedical fields. Aqueous ferrofluids of superparamagnetic iron oxide nanoparticles with narrow size distribution, high shelf life and good stability is realized by controlled chemical co-precipitation process. The crystal structure is verified by X-ray diffraction technique. Particle sizes are evaluated by employing Transmission electron microscopy. Room temperature and low-temperature magnetic measurements were carried out with Superconducting Quantum Interference Device. The fluid exhibits good magnetic response even at very high dilution (6.28 mg/cc). This is an advantage for biomedical applications, since only a small amount of iron is to be metabolised by body organs. Magnetic field induced transmission measurements carried out at photon energy of diode laser (670 nm) exhibited excellent linear dichroism. Based on the structural and magnetic measurements, the power loss for the magnetic nanoparticles under study is evaluated over a range of radiofrequencies.

Channel Adaptive MAC Protocol with Traffic-Aware Distributed Power Management in Wireless Sensor Networks-Some Performance Issues

In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay

A Numerically efficient power optimization scheme for coded OFDM systems in achieving minimum frame error rate

Coded OFDM is a transmission technique that is used in many practical communication systems. In a coded OFDM system, source data are coded, interleaved and multiplexed for transmission over many frequency sub-channels. In a conventional coded OFDM system, the transmission power of each subcarrier is the same regardless of the channel condition. However, some subcarrier can suffer deep fading with multi-paths and the power allocated to the faded subcarrier is likely to be wasted. In this paper, we compute the FER and BER bounds of a coded OFDM system given as convex functions for a given channel coder, inter-leaver and channel response. The power optimization is shown to be a convex optimization problem that can be solved numerically with great efficiency. With the proposed power optimization scheme, near-optimum power allocation for a given coded OFDM system and channel response to minimize FER or BER under a constant transmission power constraint is obtained

A Reinforcement Learning Algorithm to Economic Dispatch Considering Transmission Losses

Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.

A survey on voltage sag events in power systems

This paper aims to survey the techniques and methods described in literature to analyse and characterise voltage sags and the corresponding objectives of these works. The study has been performed from a data mining point of view

Unusual voltage sag event detection in power systems

Three multivariate statistical tools (principal component analysis, factor analysis, analysis discriminant) have been tested to characterize and model the sags registered in distribution substations. Those models use several features to represent the magnitude, duration and unbalanced grade of sags. They have been obtained from voltage and current waveforms. The techniques are tested and compared using 69 registers of sags. The advantages and drawbacks of each technique are listed