Distributed resource integration analysis and network design of electric power distribution systems

The integration of high percentages of distributed energy resources and controllable loads into the distribution system coupled with the strict power quality and service reliability requirements at the power distribution level are necessitating a significant change in the planning, operation and control of the traditional power distribution system. The future power distribution circuits should be able to accommodate the new technologies while simultaneously providing a desired level of power quality and service reliability to the customers. This thesis aims to address the current and future grid requirements of both existing as well as new distribution systems with regard to power quality and service reliability issues. Several methods are proposed to evaluate and mitigate power quality and service reliability concerns due to the integration of smart grid technologies into both existing and new distribution circuits. Notably, for the existing distribution circuits, integration studies are simulated to analyze and mitigate the impacts of electric vehicle loads and photovoltaic generation on the distribution voltages. Furthermore, the problem of siting, sizing and deployment of distributed energy storage systems in meeting distribution planning requirements with regard to integrating distributed generation and providing contingency requirements is also addressed. A new distribution system both grid-connected and operating in islanded mode, however, could be designed to the new requirements. The new distribution circuit could be designed to meet the power quality and service reliability standards directly, thus more efficiently mitigating the concerns. In the thesis, the new distribution circuit design is approached from the perspective of maximizing the service reliability. For the new distribution circuit, approaches to reliability based distribution circuit design are proposed.Electrical and Computer Engineerin

Computational Intelligence Application in Electrical Engineering

The Special Issue "Computational Intelligence Application in Electrical Engineering" deals with the application of computational intelligence techniques in various areas of electrical engineering. The topics of computational intelligence applications in smart power grid optimization, power distribution system protection, and electrical machine design and control optimization are presented in the Special Issue. The co-simulation approach to metaheuristic optimization methods and simulation tools for a power system analysis are also presented. The main computational intelligence techniques, evolutionary optimization, fuzzy inference system, and an artificial neural network are used in the research presented in the Special Issue. The articles published in this issue present the recent trends in computational intelligence applications in the areas of electrical engineering

Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods

Feeder flow control and operation in large scale photovoltaic power plants and microgrids : Part I Feeder ow control in large scale photovoltaic power plants : Part II Multi-microgrids and optimal feeder ow operation of microgrids

This thesis deals with the integration of photovoltaic energy into the electrical grid. For this purpose, two main approaches can be identified: the interconnection of large scale photovoltaic power plants with the transmission network, and the interconnection of small and medium-scale photovoltaic installations with the distribution network. The first part of the thesis is focussed on the interconnection of large scale photovoltaic power plants. Large scale photovoltaic power plants are required to provide different ancillary services to the electrical networks. For this purpose, it is necessary to control the active and reactive power injected by photovoltaic power plants at the point of interconnection, i.e. to control the power flow through the main feeder. In this direction, it is developed a central controller capable of coordinating the different devices of the photovoltaic power plants as photovoltaic inverters, FACTS, capacitor banks and storage. The second part is focused on the distributed generation, consisting on small and medium-scale generation facilities connected to the distribution system. In this context, distribution grids, traditionally operated as passive systems, become active operated systems. In this part, the microgrid concept is analysed, which is one of the most promising solutions to manage, in a coordinated manner, the different distributed energy resources. Taking into account the possible transformation of the current distribution system to a multi-microgrid based system, the different architectures enabling microgrids interconnections are analysed. For the multi-microgrid operation, it could result interesting that a portion of their networks operate so that the power exchange is maintained constant, i.e. controlling the power flow at the main feeder. In this thesis, an optimal power flow problem formulation for managing the distributed generation of these feeder flow controlled microgrids is proposed

Application of Power Electronics Converters in Smart Grids and Renewable Energy Systems

This book focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller

Microgrids

Microgrids are a growing segment of the energy industry, representing a paradigm shift from centralized structures toward more localized, autonomous, dynamic, and bi-directional energy networks, especially in cities and communities. The ability to isolate from the larger grid makes microgrids resilient, while their capability of forming scalable energy clusters permits the delivery of services that make the grid more sustainable and competitive. Through an optimal design and management process, microgrids could also provide efficient, low-cost, clean energy and help to improve the operation and stability of regional energy systems. This book covers these promising and dynamic areas of research and development and gathers contributions on different aspects of microgrids in an aim to impart higher degrees of sustainability and resilience to energy systems

Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems

The electrical power system is undergoing a revolution enabled by advances in telecommunications, computer hardware and software, measurement, metering systems, IoT, and power electronics. Furthermore, the increasing integration of intermittent renewable energy sources, energy storage devices, and electric vehicles and the drive for energy efficiency have pushed power systems to modernise and adopt new technologies. The resulting smart grid is characterised, in part, by a bi-directional flow of energy and information. The evolution of the power grid, as well as its interconnection with energy storage systems and renewable energy sources, has created new opportunities for optimising not only their techno-economic aspects at the planning stages but also their control and operation. However, new challenges emerge in the optimization of these systems due to their complexity and nonlinear dynamic behaviour as well as the uncertainties involved.This volume is a selection of 20 papers carefully made by the editors from the MDPI topic “Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems”, which was closed in April 2022. The selected papers address the above challenges and exemplify the significant benefits that optimisation and nonlinear control techniques can bring to modern power and energy systems