Posibilidades de operación óptima de la red de baja tensión mediante el uso de transformadores con cambiador de toma automático bajo carga

Universidad de Sevilla. Máster en Sistemas de Energía Eléctric

Distributed observers for LTI systems :an approach based on subspace decomposition

Cuando consideramos plantas de gran escala, como pueden ser fábricas, canales de irrigación de agua o campos solares, la estimación de estado se convierte en un problema más difícil de resolver que en pequeños sistemas. Cabe señalar que la información de estos sistemas con frecuencia es recopilada por muchos agentes individuales que están ubicados en zonas geográficamente remotas, lo que complica el diseño de los estimadores. Además, estos agentes deben comunicarse entre sí para lograr objetivos comunes de todo el sistema, lo que desencadena en problemas derivados de la red de comunicación tales como retrasos, pérdida de paquetes, ancho de banda limitado, etc. El objetivo de esta Tesis es el de proporcionar nuevas soluciones para el problema de la estimación distribuida del estado de una planta Lineal Invariante en el Tiempo (LTI) por parte de una red de agentes. Para lograr este objetivo, se presentan varias novedosas estructuras de observador. Dichas estructuras tienen un principio común: el uso de una descomposición del espacio de estados en los subespacios observables y no observables de cada agente. Primero, se presenta una estructura de observador basada en el principio de la descomposición del espacio de estados mencionado anteriormente. Dicha estructura utiliza las propias medidas del agente para reconstruir la parte observable del estado e incorpora consenso para reconstruir la parte del estado no observable por el agente. Como principales características destacan que es una estructura que puede diseñarse de forma distribuida y tiene la capacidad de fijar de forma arbitraria la velocidad de convergencia del estimador. Por otro lado, cuando se trabaja con modelos perturbados, la tesis presenta un método de diseño distribuido basado en LQ para la estructura de observador introducida anteriormente. Bajo el diseño propuesto, se establecen condiciones de estabilidad y optimidad. Además, se muestra en simulación la respuesta del algoritmo para los escenarios no perturbados y perturbados. Finalmente, el método de diseño presentado permite al usuario, mediante el uso de un parámetro escalar, modificar el diseño del observador de acuerdo con su experiencia con la planta. Finalmente, se presenta una segunda estructura de observador basada en el mismo principio de descomposición en subespacios, pero esta vez, el planteamiento es algo diferente. Cada uno de los agentes involucrados en la red debe realizar un monitoreo en tiempo real del estado de la planta a partir de sus medidas locales del estado y las medidas tomadas por el resto de la red. Esta comunicación inter-agente se lleva a cabo dentro de una red multi-salto. Por lo tanto, la información transmitida sufre un retraso en función de la posición del agente que actúa como fuente de información y el agente receptor de dicha información. Así, para resolver el problema, se presenta una novedosa estructura de observador basada en la fusión de datos. Por último, se abordan dos problemas principales: el diseño del observador para estabilizar el error de estimación cuando no existen perturbaciones y un diseño óptimo de observador para minimizar las incertidumbres en la estimación cuando entran en juego perturbaciones en la planta y ruidos en las medidas. Todas las aportaciones de esta tesis son de carácter teórico. Sin embargo, las soluciones adoptadas podrían aplicarse a una amplia variedad de sistemas distribuidos como pueden ser el control de redes de distribución de agua, la formación de vehículos autónomos, transporte y logística, sistemas eléctricos de potencia o edificios inteligentes, por mencionar algunas aplicaciones

Accurate Assessment of Decoupled OLTC Transformers to Optimize the Operation of Low-Voltage Networks

Voltage control in active distribution networks must adapt to the unbalanced nature of most of these systems, and this requirement becomes even more apparent at low voltage levels. The use of transformers with on-load tap changers is gaining popularity, and those that allow different tap positions for each of the three phases of the transformer are the most promising. This work tackles the exact approach to the voltage optimization problem of active low-voltage networks when transformers with on-load tap changers are available. A very rigorous approach to the electrical model of all the involved components is used, and common approaches proposed in the literature are avoided. The main aim of the paper is twofold: to demonstrate the importance of being very rigorous in the electrical modeling of all the components to operate in a secure and effective way and to show the greater effectiveness of the decoupled on-load tap changer over the usual on-load tap changer in the voltage regulation problem. A low-voltage benchmark network under different load and distributed generation scenarios is tested with the proposed exact optimal solution to demonstrate its feasibility.Ministerio de Economía y Competitividad ENE2014-54115-RMinisterio de Economía y Competitividad ENE2017-84813-RUnión Europea (FEDER Interconecta) CDTI PASTORAITC- 2018110

Distributed consensus-based Kalman filtering considering subspace decomposition

The aim of this paper is to provide a new observer structure able to deal with the distributed estimation of a discrete-time linear system from a network of agents. The main result is an innovative consensus-based structure that decompose the state in the observable and unobservable subspace of the agent using the observability staircase form. The paper proposes a design in which Kalman-like gains are synthetized to minimize the variance of the error on both subspaces. Finally some simulations are shown to compare the proposed estimator with centralized Kalman filter and other distributed schemes found in literture

Distributed estimation design for LTI systems: a linear quadratic approach

This paper deals with the problem of distributedly estimate the state of a plant through a network of interconnected agents. Each of these agents must perform a real-time monitoring of the plant state, counting on the measurements of local plant outputs and on the exchange of information with neighbouring agents. The paper introduces a distributed LQ-based design that is applied to a distributed observer structure based on a multi-hop subspace decomposition. Stability and optimality conditions are derived and tested in simulation. Finally, the design method presented allows the user, through the tune of two scalar parameters, to modify the observer gains according to their experience about the plant

An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes

In the last decades, new types of generation technologies have emerged and have been gradually integrated into the existing power systems, moving their classical architectures to distributed systems. Despite the positive features associated to this paradigm, new problems arise such as coordination and uncertainty. In this framework, microgrids constitute an effective solution to deal with the coordination and operation of these distributed energy resources. This paper proposes a Genetic Algorithm (GA) to address the combined problem of Unit Commitment (UC) and Economic Dispatch (ED). With this end, a model of a microgrid is introduced together with all the control variables and physical constraints. To optimally operate the microgrid, three operation modes are introduced. The first two attend to optimize economical and environmental factors, while the last operation mode considers the errors induced by the uncertainties in the demand forecasting. Therefore, it achieves a robust design that guarantees the power supply for different confidence levels. Finally, the algorithm was applied to an example scenario to illustrate its performance. The achieved simulation results demonstrate the validity of the proposed approach.Ministerio de Ciencia, Innovación y Universidades TEC2016-80242-PMinisterio de Economía y Competitividad PCIN-2015-043Universidad de Sevilla Programa propio de I+D+

A MPC Strategy for the Optimal Management of Microgrids Based on Evolutionary Optimization

In this paper, a novel model predictive control strategy, with a 24-h prediction horizon, is proposed to reduce the operational cost of microgrids. To overcome the complexity of the optimization problems arising from the operation of the microgrid at each step, an adaptive evolutionary strategy with a satisfactory trade-off between exploration and exploitation capabilities was added to the model predictive control. The proposed strategy was evaluated using a representative microgrid that includes a wind turbine, a photovoltaic plant, a microturbine, a diesel engine, and an energy storage system. The achieved results demonstrate the validity of the proposed approach, outperforming a global scheduling planner-based on a genetic algorithm by 14.2% in terms of operational cost. In addition, the proposed approach also better manages the use of the energy storage system.Ministerio de Economía y Competitividad DPI2016-75294-C2-2-RUnión Europea (Programa Horizonte 2020) 76409

Application of Genetic Algorithms for Designing Micro-Hydro Power Plants in Rural Isolated Areas—A Case Study in San Miguelito, Honduras

The use of Micro-Hydro Power Plants (MHPP) has established itself as a fundamental tool to address the problem of energy poverty in rural isolated areas, having become the most used renewable energy source not just in this field but also in big scale power generation. Although the technology used has made important advances in the last few decades, it has been generally applied to big scale hydro-power systems. This fact has relegated the use of isolated MHPPs to the background. In this context, there is still a vast area of improvement in the development of optimization strategies for these projects, which in practice remains limited to the use of thumb rules. It results in a sub-optimal use of the available resources. This work proposes the use of a Genetic Algorithm (GA) to assist the design of MHPP, finding the most suitable location of the different elements of a MHPP to achieve the most efficient use of the resources. For this, a detailed model of the plant is first developed, followed by an optimization problem for the optimal design, which is formulated by considering the real terrain topographic data. The problem is presented in both single (to minimize the cost) and multi-objective (to minimize cost while maximizing the generated power) mode, providing a deep analysis of the potentiality of using GAs for designing MHPP in rural isolated areas. To validate the proposed approach, it is applied to a set of topographic data from a real scenario in Honduras. The achieved results are compared with a baseline integer-variable algorithm and other meta-heuristic algorithms, demonstrating a noticeable improvement in the solution in terms of cost.This research has been partially funded by the University of Seville under the contract “Contratos de acceso al Sistema Español de Ciencia, Tecnología e Innovación para el desarrollo del programa propio de I+D+i de la Universidad de Sevilla” of D. G. Reina

Three-dimensional optimization of penstock layouts for micro-hydropower plants using genetic algorithms

A Micro Hydro-Power Plant is a suitable and effective mean to provide electric power to rural remote communities without harming the environment. However, the lack of resources and technical training in these communities frequently leads to designs based of rules of thumb, compromising both the generation capacity and efficiency. This work makes an attempt to address this problem by developing a new tool to design the layout of the plants. The proposed mechanism relies on a discrete topographic survey of the terrain and utilizes a Genetic Algorithm to optimize the installation layout, making it possible to explicitly incorporate requirements and constraints, such as power supply, cost of the installation, available water flow, and layout feasibility in accordance with the real terrain profile. The algorithm can operate in both single-objective mode (cost minimization) and multi-objective mode (cost minimization and power supply maximization), including in the latter Pareto dominance analyses. The algorithm is applied to a real scenario in a remote community in Honduras, obtaining good results in terms of generation capacity and cost reduction

Provision of Primary Frequency Response as Ancillary Service From Active Distribution Networks to the Transmission System

This paper deals with the provision of primary frequency response (PFR) as ancillary service (AS) from active distribution networks (ADNs) to the transmission system (TS). In particular, two methodologies are developed. The first one aims to quantify the PFR capability range of the ADN. This range is defined by determining the range of the aggregated, i.e., equivalent, active power - frequency P(f ) droop curves that can be provided at the point of interconnection (POI) with the TS. The second one targets to optimally control P(f ) droop curves of individual distributed energy resources (DERs), installed in the premises of the ADN, to guarantee specific frequency regulation characteristic at the POI. This frequency regulation characteristic is expressed by means of a P(f ) droop curve. Both methods are tested on two discrete distribution systems. Several test cases are examined to demonstrate their implementation. Additionally, comparisons against conventional approaches and time series simulations are conducted to evaluate the performance of the proposed methods.Unión Europea Subvención 76409