Changes in the electric power industry have brought great challenges and uncertainties in transmission planning area. More effective planning of transmission grids with the appropriate development of advanced planning technologies is badly-needed. The aim of this research is to develop an advanced probabilistic transmission expansion planning (TEP) methodology in a continually changing market environment. The methodology should be able to strengthen and increase the robustness of existing transmission network. By using the proposed probabilistic TEP methodology, it can reduce the risks of major outages and identify weak buses in the system. The significance of this research is shown by its comprehensiveness and powerful practicability. Results from this research are able to improve the planning efficiency and reliability with consideration of financial risks in an electricity market. In order to achieve the target, this research methodologies focused on two main important issues, (1) probability based technical assessment and (2) financial investment evaluation. During the first stage study, probabilistic congestion management, probabilistic reliability evaluation and probabilistic load flow for TEP under uncertainties have been investigated and improved. The developed methodologies and indices, which truly represent the composite impact from both critical state and probability, have linked with financial terms. At financial investment evaluation part, Monte Carlo market simulation is performed to assist economic analysis. The overall planning process has been treated as a constrained multi-objective optimisation task. Comprehensive investigations are conducted on several test systems and testified by real power systems using the available reliability data and economic information from the Australian National Electricity Market (NEM). Overall, this research developed probabilistic transmission planning methodologies that can reflect modern market structures more accurately and it enable a greater utilization of current generation and transmission resources to increase potential operation efficiencies.

Master of Science

The ancillary services are of immanent importance for secure and reliable network operation. As a result of the energy turnaround in Germany, conventional power plant capacities that have so far provided these ancillary services will significantly be reduced. Particularly with regard to frequency control and grid operation, it has already become apparent today that high costs can be expected if current practice and market conditions are maintained. The aim of this thesis is to investigate options for a cost-efficient transformation of the electricity system with a focus on the ancillary services frequency control and grid operation. In a first step, the ancillary services and their development in the recent past is addressed. In a second step, the effects of different cooperation between network operators on network operation are investigated. Here it is shown that in the medium term an intensified cooperation on transmission grid operator level has a positive impact on the operation of the grid. In the long term, it is necessary for distribution system operators to cooperate more closely in order to ensure cost-efficient and secure network operation. In a third step, options for the market design of balancing power markets are examined. The results show that it is necessary to make tendering times more flexible so that renewable energies can participate in the markets and, at the same time, more players can participate in these markets. With these adjustments it is possible to significantly reduce the cost of balancing power to levels below those of 2014. Finally, it is examined which market inefficiencies may occur in more flexible balancing markets due to strategic bidding behavior. Especially in the upward markets it can be seen that increasing market inefficiencies are to be expected, which, however, can be limited by increased international cooperation and the participation of renewable energies.

El crecimiento de los computadores paralelos basados en redes de altas prestaciones ha aumentado el interés y esfuerzo de la comunidad investigadora en desarrollar nuevas técnicas que permitan obtener el mejor rendimiento de estas redes. En particular, el desarrollo de nuevas técnicas que permitan un encaminamiento eficiente y que reduzcan la latencia de los paquetes, aumentando así la productividad de la red. Sin embargo, una alta tasa de utilización de la red podría conllevar el que se conoce como "congestión de red", el cual puede causar una degradación del rendimiento. El control de la congestión en redes multietapa es un problema importante que no está completamente resuelto. Con el fin de evitar la degradación del rendimiento de la red cuando aparece congestión, se han propuesto diferentes mecanismos para el control de la congestión. Muchos de estos mecanismos están basados en notificación explícita de la congestión. Para este propósito, los switches detectan congestión y dependiendo de la estrategia aplicada, los paquetes son marcados con la finalidad de advertir a los nodos origenes. Como respuesta, los nodos origenes aplican acciones correctivas para ajustar su tasa de inyección de paquetes. El propósito de esta tesis es analizar las diferentes estratégias de detección y corrección de la congestión en redes multietapa, y proponer nuevos mecanismos de control de la congestión encaminados a este tipo de redes sin descarte de paquetes. Las nuevas propuestas están basadas en una estrategia más refinada de marcaje de paquetes en combinación con un conjunto de acciones correctivas justas que harán al mecanismo capaz de controlar la congestión de manera efectiva con independencia del grado de congestión y de las condiciones de tráfico. / Ferrer Pérez, JL. (2012). DESIGN OF EFFICIENT PACKET MARKING-BASED CONGESTION MANAGEMENT TECHNIQUES FOR CLUSTER INTERCONNECTS [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/18197

M. Tech. (Information Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology / Traffic congestion is a concern within the main arteries that link Johannesburg to Pretoria. In this study Matlab function Randperm is used to generate random vehicle speeds on a simulated highway. Randperm is used to mimic vehicle speed sensors capturing vehicle traffic on the highway. Java sockets are used to send vehicle speed to the Road Traffic Control Centre (RTCC)-database server through a wireless medium. The RTCC-database server uses MySQL to store vehicle speed data. The domain controller with active directory together with a certificate server is used to manage and provide security access control to network resources. The wireless link used by speed sensors to transmit vehicle speed data is protected using PEAP with EAP-TLS which employs the use of digital certificates during authentication. A java database connectivity driver is used to retrieve data from MySQL and a multilayer perceptron (MLP) model is used to predict future traffic status on the highway being monitored i.e. next 5 minutes from previous 5 minutes captured data. A dataset of 402 instances was divided as follows: 66 percent training data was used to train the MLP model, 15 percent data used during validation and the remaining 19 percent was used to test the trained MLP model. An excel spreadsheet was used to introduce novel (19 percent data not used during training) data to the trained MLP model to predict. Assuming that the spreadsheet data represent captured highway vehicle data for the last 5 minutes, the model showed 100 percent accuracy in predicting the four classes: congested, out congested, into congested and normal traffic flow. Predicted traffic status is displayed for the motorist on the highway to know. Ability of the proposed model to continuously capture the traffic pattern on the highway (monitor) helps in redirecting (controlling) the highway traffic during periods of congestion. Implementation of this project will definitely decrease traffic congestion across main arteries of Johannesburg. Pollution normally experienced when cars idle for a long time during congestion will be reduced by free highway traffic flow. Frequent servicing of motor vehicles will no longer be required by the motorists. Furthermore the economy of Gauteng and South Africa as a whole will benefit due to increase in production. Consumers will also benefit in obtaining competitive prices from organizations that depend on haulage services.

As transportation policies are changing to encourage alternative modes of transportation to reduce congestion problems and air quality impacts, more planning organizations are considering or implementing activity-based travel demand models to forecast future travel patterns. The proclivity towards operating activity-based models is the capability to model disaggregate travel data to better understand the model results that are generated with respect to the latest transportation policy implementations. This thesis first examines the differences between the two major modeling techniques used in the United States and then describes the assessment tool that was developed to recommend whether a region should convert to the advanced modeling procedures. This tool consists of parameters that were decided upon based on their known linkages to the advantages of activity-based models.

With the deregulation of power industry and the market competition, reliable power supply and secured system operation are major concerns of the independent system operator (ISO) or decision-maker (DM). Power dispatch under deregulated environment is complicated with various possibilities of decisions involved. Without the assistance of Energy Management System (EMS), it is not easy for ISO or DM to operate with pure experiences. To enhance the operational efficiency, EMS involves the state-of-the-art control technology, and the fast and effective computer assisted decision support system will help dispatch the power. A conventional EMS has a few major tasks, among them, the ¡§network analysis¡¨ task and the ¡§forecast and scheduling¡¨ task are the most important in assisting the on-line power dispatch. In dealing with the new deregulated environment, an ¡§operational planning¡¨ has to be added to aid the EMS for more security. There are significant changes on EMS after deregulation. This dissertation will focus on the changes and new functions, in the ¡§network analysis¡¨ and the ¡§forecast and scheduling¡¨ tasks of an EMS, which supports the operation in the competitive environment. In the ¡§network analysis¡¨ task, we discuss the real and reactive power dispatch and congestion management with AC optimal power flow (OPF). In this task, the formulation of AC OPF with deregulation issues and the effect of flexible AC transmission systems (FACTS) devices are presented. A predictor-corrector interior-point nonlinear-programming (PCIPNLP) algorithm has been developed to solve the problem. The model involves only slight modification to the present OPF for social welfare maximization to obtain the optimized bid-based dispatch and nodal spot prices. The incorporation of FACTS devices for system operations can ease the difficulties caused by transmission congestion. It is found that PCIPNLP technique is very effective for the modified OPF solution for congestion relief under deregulation. In the ¡§forecast and scheduling¡¨ task, we discuss the resource scheduling for bid-based dynamic economic dispatch and spot dispatch for power and reserve. They can be formulated for social welfare maximizing problem that is solved by using an efficient interior point method. And the optimal resource allocation and nodal spot price can be given from the various test results. We have also proposed a fuzzy based strategic gaming method to determine the GenCo¡¦s bidding strategy. Based on fuzzy set theory, a multi-criteria decision-making method is used to obtain the optimal strategy combination, bids and expected payoffs. Decision maker can find the optimal strategy combination by using weight vector to represent his subjective attitude about the structure of multi-objectives. The advantages have also been demonstrated through the numerical examples. Compared with the classical (¡§nonfuzzy¡¨) game theory, the proposed approach could help the decision maker to obtain higher expected payoffs, and make his choices easily. Possible applications of the proposed fuzzy method can be suggested for other decision-making problems in the power systems

This dissertation focuses on selected aspects of network congestion arising in liberalized electricity markets and their management methods with a special weight placed on the integration of increased renewable generation in Europe and Germany. In a first step, the theoretical concepts of congestion management are introduced complemented by a review of current management regimes in selected countries. In the second step, the European approach of managing congestion on international as well as national transmission links is analyzed and the benefits of an integrated congestion management regime are quantified. It is concluded that benefits can be achieved by a closer cooperation of national transmission system operators (TSOs). Thirdly, the German congestion management regime is investigated and the impact of higher renewable generation up to 2020 on congestion management cost is determined. It is shown that a homogeneous and jointly development of generation and transmission infrastructure is a prerequisite for the application of congestion alleviation methods and once they diverge congestion management cost tend to increase substantially. Lastly, the impact of intermittent and uncertain wind generation on electricity markets is analyzed. A stochastic electricity market model is described, which replicates the daily subsequent clearing of reserve, dayahead, and intraday market typical for European countries, and numerical results are presented.

This dissertation focuses on selected aspects of network congestion arising in liberalized electricity markets and their management methods with a special weight placed on the integration of increased renewable generation in Europe and Germany. In a first step, the theoretical concepts of congestion management are introduced complemented by a review of current management regimes in selected countries. In the second step, the European approach of managing congestion on international as well as national transmission links is analyzed and the benefits of an integrated congestion management regime are quantified. It is concluded that benefits can be achieved by a closer cooperation of national transmission system operators (TSOs). Thirdly, the German congestion management regime is investigated and the impact of higher renewable generation up to 2020 on congestion management cost is determined. It is shown that a homogeneous and jointly development of generation and transmission infrastructure is a prerequisite for the application of congestion alleviation methods and once they diverge congestion management cost tend to increase substantially. Lastly, the impact of intermittent and uncertain wind generation on electricity markets is analyzed. A stochastic electricity market model is described, which replicates the daily subsequent clearing of reserve, dayahead, and intraday market typical for European countries, and numerical results are presented.

Le développement de la production éolienne permet de satisfaire les objectifs de lutte contre le réchauffement climatique. Cependant, dans certaines zones du réseau électrique, l’intégration d’un volume important de production peut créer des congestions qui traduisent l'incapacité du réseau à évacuer cette production. Les méthodes actuelles pour gérer les congestions sont basées sur des calculs prévisionnels de restrictions de production qui peuvent entrainer des pertes de production importantes pour le renouvelable. Cependant, dans le cadre d’un développement important du renouvelable, il est nécessaire de définir une méthodologie de gestion des congestions fiable, optimale du point de vue économique et non discriminatoire pour la production renouvelable.Dans le cadre de cette thèse, la méthodologie de gestion des congestions locales proposée repose sur l’usage d’un contrôle correctif. Le contrôle correctif est basé sur une boucle de régulation et un algorithme utilisant les réseaux de Petri. Une étude de stabilité de la boucle de régulation a montré que les marges de stabilité dépendantes des gains composant la boucle sont suffisantes. L’algorithme permet de définir les groupes de production à choisir pour la gestion des congestions en considérant leur coût d’utilisation et leur impact sur la congestion. Les essais, effectués sous le logiciel EUROSTAG, ont montré la pertinence de la méthodologie proposée et sa capacité à s’adapter à l’insertion des moyens de production. De plus, des conclusions générales sur les différents coûts associés à la gestion des congestions en fonction des différentes règlementations régissant la production renouvelable ont été obtenues / Development of wind generation is a mean towards global warming reduction. However, in some parts of the electrical grid, the massive integration of renewable generation can lead to congestion problems. These congestions are related to the impossibility for the power grid to transport the generation. Nowadays, congestion management methods are based on day(s)-ahead computation of generation restriction which leads to important production losses for renewables. Based on this context, it’s therefore important to develop a methodology which is optimal, reliable and non-discriminatory for renewable.In this work, the proposed congestion management method is based on corrective actions. These actions are computed in real-time using regulation loops and Petri net-based algorithms. A stability study proved that gain margins are sufficient to assure the stability of the corrective actions. The algorithm allows an optimal selection of the generators than will participate in the congestion management. This selection is based on their cost and efficiency for congestion alleviation. Simulation results using the software EUROSTAG have shown the efficiency of the method and its adaptability to different generator types. Furthermore, general conclusions on congestions costs according to different regulations on the renewable generation were obtained