Comparison of Optimum Reactive Power Schedule with Different Objectives Using LP Technique

Three algorithms for reactive power optimization are proposed in this paper with three different objective functions. The objectives in the proposed algorithm are to minimize the sum of the squares of the voltage deviations of the load buses, minimization of sum of squares of voltage stability L-indices of load buses (:3L2) algorithm, and also the objective of system real power loss (Ploss) minimization. The approach adopted is an iterative scheme with successive power flow analysis using decoupled technique and solution of the linear programming problem using upper bound optimization technique. Results obtained with all these objectives are compared. The analysis of these objective functions are presented to illustrate their advantages. It is observed comparing different objective functions it is possible to identify critical On Load Tap Changers (OLTCs) that should be made manual to avoid possible voltage instability due to their operation based on voltage improvement criteria under heavy load conditions. These algorithms have been tested under simulated conditions on few test systems. The results obtained on practical systems of 24-node equivalent EHV Indian power network, and for a 205 bus EHV system are presented for illustration purposes.

Fuzzy Expert Approach with Curtailed Controllers for Improved Reactive Power Dispatch

This paper addresses the problem of curtailing the number of control actions using fuzzy expert approach for voltage/reactive power dispatch. It presents an approach using fuzzy set theory for reactive power control with the purpose of improving the voltage profile of a power system. To minimize the voltage deviations from pre-desired values of all the load buses, using the sensitivities with respect to reactive power control variables form the basis of the proposed Fuzzy Logic Control (FLC). Control variables considered are switchable VAR compensators, On Load Tap Changing (OLTC) transformers and generator excitations. Voltage deviations and controlling variables are translated into fuzzy set notations to formulate the relation between voltage deviations and controlling ability of controlling devices. The developed fuzzy system is tested on a few simulated practical Indian power systems and modified IEEE-30 bus system. The performance of the fuzzy system is compared with conventional optimization technique and results obtained are encouraging. Results obtained for a modified IEEE-30 bus test system and a 205-node equivalent EHV system a part of Indian southern grid are presented for illustration purposes. The proposed fuzzy-expert technique is found suitable for on-line applications in energy control centre as the solution is obtained fast with significant speedups with few number of controllers.

Intelligent Approach for Fault Diagnosis in Power Transmission Systems Using Support Vector Machines

This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.

Evaluation of Suitable Locations for Generation Expansion in Restructured Power Systems: A Novel Concept of T-index Thukaram

In developing countries, a high rate of growth in the demand for electric energy is felt, and so the addition of new generating units becomes inevitable. In deregulated power systems, private generating stations are encouraged to add new generations. Some of the factors considered while placing a new generating unit are: availability of esources, ease of transmitting power, distance from the load centre, etc. Finding the most appropriate locations for generation expansion can be done by running repeated power flows and carrying system studies like analyzing the voltage profile, voltage stability, loss analysis, etc. In this paper a new methodology is proposed which will mainly consider the existing network topology. A concept of T-index is introduced in this paper, which considers the electrical distances between generator and load nodes. This index is used for ranking the most significant new generation expansion locations and also indicates the amount of permissible generations that can be installed at these new locations. This concept facilitates for the medium and long term planning of power generation expansions within the available transmission corridors. Studies carried out on an EHV equivalent 10-bus system and IEEE 30 bus systems are presented for illustration purposes.

State estimation in power systems using linear model infinity norm-based trust region approach

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.

Flexible implementation of power system corrective topology control

This paper proposes a novel decision making framework for optimal transmission switching satisfying the AC feasibility, stability and circuit breaker (CB) reliability requirements needed for practical implementation. The proposed framework can be employed as a corrective tool in day to day operation planning scenarios in response to potential contingencies. The switching options are determined using an efficient heuristic algorithm based on DC optimal power flow, and are presented in a multi-branch tree structure. Then, the AC feasibility and stability checks are conducted and the CB condition monitoring data are employed to perform a CB reliability and line availability assessment. Ultimately, the operator will be offered multiple AC feasible and stable switching options with associated benefits. The operator can use this information, other operating conditions not explicitly considered in the optimization, and his/her own experience to implement the best and most reliable switching action(s). The effectiveness of the proposed approach is validated on the IEEE-118 bus test system. (C) 2015 Elsevier B.V. All rights reserved.

Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

Impacts of Climate Change on European Critical Infrastructures: The Case of the Power Sector

23 p.

Análise de viabilidade técnica e econômica da geração de energia através do biogás de lixo em aterros sanitários.

A geração de energia a partir do biogás do lixo em aterros sanitários é uma maneira de produzir energia elétrica renovável e limpa, reduzindo os impactos globais provocados pela queima dos resíduos sólidos urbanos. A contribuição ambiental mais relevante é a redução de emissões dos gases de efeito estufa (GEE), por meio da conversão do metano em dióxido de carbono, visto que o metano possui um potencial de aquecimento global cerca de 21 vezes maior, quando comparado ao dióxido de carbono (através da combustão do mesmo). De acordo com o Mecanismo de Desenvolvimento Limpo (MDL), os países ricos podem comprar créditos de carbono (CERs) dos países em desenvolvimento (que possuam projetos sustentáveis) para cumprir suas metas ambientais. O objetivo é transformar um passivo ambiental (destinação final dos resíduos sólidos urbanos) em um recurso energético, além do estudo da alternativa de obtenção de recursos financeiros através dos CERs. São analisadas as tecnologias de conversão energética (tecnologia de gás de lixo, incineração, entre outras), com a seleção da melhor alternativa para a geração de energia através do biogás de lixo em aterros sanitários. A metodologia utilizada é a recomendada pela Agência de Proteção Ambiental dos Estados Unidos - USEPA (2005). Serão apresentadas outras duas metodologias de cálculo da geração de metano: a do Banco Mundial e a do IPCC (Painel Intergovernamental sobre Mudanças Climáticas). São apresentados estudos comparativos demonstrando quando as turbinas a gás, motores de combustão interna (ciclos Otto ou Diesel) ou outras tecnologias de conversão energética serão viáveis na área técnica e econômica para implantação de Unidades Termoelétricas a biogás. No caso do Aterro de Gramacho, o projeto é viável com a utilização de motores a combustão interna e a obtenção de receitas com a venda da produção de energia e créditos de carbono. Por fim, será apresentada a alternativa do uso do biogás como substituto do gás natural para fins energéticos ou outros fins industriais.

Compliance verification methodology for renewable generation integration. Application to island power grids

261 p.

Gasificación de biomasa con astillas de madera.

[ES]Este proyecto tiene como objetivo generar energía eléctrica y térmica para un conjunto de viviendas aisladas, sin acceso a la red eléctrica, con una potencia requerida de 12KW. Se pretende plantear una solución que satisfaga las necesidades básicas de auto-abastecimiento de una forma económicamente rentable. Para comenzar, por un lado de cara al objetivo 20/20/20 se realizará un acercamiento a la utilización de las energías renovables como fuente de energía, disminuyendo así el impacto ambiental. Por otro lado, se plantearán diferentes alternativas para la generación de energía eléctrica y térmica, finalmente haciendo hincapié en el estudio de una planta de gasificación de biomasa mediante astillas de madera. De modo que, a lo largo de este documento se analizarán los principios y fundamentos necesarios para el diseño de una planta de generación eléctrica mediante gasificación de biomasa. Para ello se estudiarán los diferentes modelos de gasificadores existentes, el desarrollo del proceso de gasificación con sus respectivas etapas y la limpieza y adaptación del gas obtenido antes de introducirlo en el MACI. Se realizará una descripción de la planta junto al dimensionamiento tanto del almacenamiento de la materia prima como el de los equipos a instalar. Finalmente, para valorar si se trata de un proyecto viable. Se realizará el estudio económico analizando el presupuesto y análisis de rentabilidad. Asimismo, se plantearán los diferentes riesgos a los que puede exponerse una instalación como esta.

Impactos do desenvolvimento do potencial hidroelétrico sobre os ecossistemas aquáticos do Rio Tocantins.

A priorização da implantação de usinas hidrelétricas no Brasil deve-se, primordialmente, ao vasto potencial hidrelétrico existente no país e à competitividade econômica que esta fonte apresenta. PPara atender à crescente demanda, foram implantados ao longo dos anos, diversos empreendimentos hidrelétricos por todo o país. Apesar do inequívoco sucesso quanto ao objetivo central de tais empreendimentos - fornecer energia para o desenvolvimento econômico tais empreendimentos causam impactos com diferentes níveis de severidade aos sistemas físico-biótico, sócio-econômico e cultural das regiões em que as instalações são realizadas. O presente trabalho objetivou identificar problemas e impactos ambientais nos ecossistemas aquáticos do Rio Tocantins relacionados com o desenvolvimento do seu potencial hidroelétrico, de forma a contribuir com a compatibilização de geração de energia e conservação da biodiversidade e manutenção dos fluxos gênicos. O cenário considerado contemplou os empreendimentos em operação e aqueles em instalação, com estudos de viabilidade aprovados e licenças prévias obtidas. A metodologia de Análise de Cadeia Causal (ACC) foi utilizada para que a partir da identificação dos problemas e impactos ambientais prioritários, a relação dos mesmos com diferentes causas imediatas, setoriais e raízes pudesse ser estabelecida. A hierarquização dos impactos foi feita através de matriz de caracterização, tendo as comunidades íctias como principais indicadores. Os impactos considerados como mais relevantes foram: (i) queda na qualidade dos recursos hídricos, (ii) perda e alteração de habitats, (iii) mudanças na estabilidade dos ecossistemas, (iv) redução de recursos pesqueiros, (v) interferência com as comunidades de bentos e de microorganismos, (vi) alteração nas cadeias alimentares e (vii) interferência na dispersão de comunidades íctias e de mamíferos. O conhecimento sobre a biodiversidade existente e a identificação dos principais impactos existentes e em potencial nos ecossistemas aquáticos do Rio Tocantins, representam um passo importante para o desenvolvimento de opções políticas eficazes com vistas à minimização da degradação ambiental decorrente do setor hidroelétrico.

Americium nuclear battery for space power applications

The work presents simplified242mAm fueled nuclear battery concept design featuring direct fission products energy conversion and passive heat rejection. The performed calculations of power conversion efficiency under thermal and nuclear design constraints showed that 14 W/kg power density can be achieved, which corresponds to conversion efficiency of about 6%. Total power of the battery scales linearly with its surface area. 144 kW of electric power can be produced by a nuclear battery with an external radius of about 174 cm and total mass of less than 10300 kg. The mass of242m Am fuel for such a system is 3200 gram.