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 of Renewable Energy Microgrid Systems for Developing Countries

This research proposes a strategy for reducing the running costs of hybrid microgrids which include both renewable and conventional power generation. The developed system uses metaheuristic methods for microgrid optimisation enabling the planning, maintenance, and effective cost management of the system. The target application for the research is a typical Nigerian remote rural community, not connected to any form of centralised power supply with the dwellers of the community practising peasant farming. The location for application of the proposed microgrid is first examined to determine renewable resources available, current power supply source, their behaviour and electricity consumption patterns, future plans for consumption, and willingness to purchase electricity if provided. In the absence of smart metering, energy use data are gathered through questionnaires and the bottom-up approach adopted for hourly time-step load demand profiles development. Using both end-use and econometric indices, a ten year load forecast is done with the fifth year forecast employed in design analysis. These forecast based on real world questionnaire will provide good resource in real world application. The Hybrid Microgrid (HMG) system is designed using HOMER to cope with variability from both weather and unexpected changes in the load, and has photovoltaic panels, wind turbines, battery storage systems, and a diesel generator in its configuration. The research compares the effectiveness of three optimization strategies, the Genetic Algorithms (GA), Particle Swarm Optimisation (PSO), and Simulated Annealing (SA) by tuning algorithm parameters to improve the speed and quality of solutions. This is the first time its being used for developing country microgrids. The HMG optimisation objective is to minimise its operating costs by reducing the generator running hours. The optimisation is constrained by the requirement to meet the variable load demand at all times. The results showed PSO had the lowest diesel generator run hours, a 65.2% reduction in the diesel running hours is, achieved compared to HOMER simulations of the HMG. The adaptability of the system means that the operator can choose the optimisation strategy based on the required output

Optimization Methods Applied to Power Systems Ⅱ

Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems

Energy storage systems and grid code requirements for large-scale renewables integration in insular grids

This thesis addresses the topic of energy storage systems supporting increased penetration of renewables in insular systems. An overview of energy storage management, forecasting tools and demand side solutions is carried out, comparing the strategic utilization of storage and other competing strategies. Particular emphasis is given to energy storage systems on islands, as a new contribution to earlier studies, addressing their particular requirements, the most appropriate technologies and existing operating projects throughout the world. Several real-world case studies are presented and discussed in detail. Lead-acid battery design parameters are assessed for energy storage applications on insular grids, comparing different battery models. The wind curtailment mitigation effect by means of energy storage resources is also explored. Grid code requirements for large-scale integration of renewables are discussed in an island context, as another new contribution to earlier studies. The current trends on grid code formulation, towards an improved integration of distributed renewable resources in island systems, are addressed. Finally, modeling and control strategies with energy storage systems are addressed. An innovative energy management technique to be used in the day-ahead scheduling of insular systems with Vanadium Redox Flow battery is presented.Esta tese aborda a temática dos sistemas de armazenamento de energia visando o aumento da penetração de energias renováveis em sistemas insulares. Uma visão geral é apresentada acerca da gestão do armazenamento de energia, ferramentas de previsão e soluções do lado da procura de energia, comparando a utilização estratégica do armazenamento e outras estratégias concorrentes. É dada ênfase aos sistemas de armazenamento de energia em ilhas, como uma nova contribuição no estado da arte, abordando as suas necessidades específicas, as tecnologias mais adequadas e os projetos existentes e em funcionamento a nível mundial. Vários casos de estudos reais são apresentados e discutidos em detalhe. Parâmetros de projeto de baterias de chumbo-ácido são avaliados para aplicações de armazenamento de energia em redes insulares, comparando diferentes modelos de baterias. O efeito de redução do potencial de desperdício de energia do vento, recorrendo ao armazenamento de energia, também é perscrutado. As especificidades subjacentes aos códigos de rede para a integração em larga escala de energias renováveis são discutidas em contexto insular, sendo outra nova contribuição no estado da arte. As tendências atuais na elaboração de códigos de rede, no sentido de uma melhor integração da geração distribuída renovável em sistemas insulares, são abordadas. Finalmente, é estudada a modelação e as estratégias de controlo com sistemas de armazenamento de energia. Uma metodologia de gestão de energia inovadora é apresentada para a exploração de curto prazo de sistemas insulares com baterias de fluxo Vanádio Redox

Methodology for sizing hybrid power generation systems (solar-diesel), battery backed in non interconnected zones using PSO

ABSTRACT: Nowadays the access to electrical energy has become fundamental for the development of any region. Nonetheless, in developing countries there still many communities without a proper access to this service. There are plenty of reasons that make difficult the electrification of rural areas, however Hybrid Renewable Energy (HRE) systems have become an attractive option to solve these problems and provide with energy rural areas. Among HRE systems, the Solar-Diesel is often employed because the abundance of the solar resource. Battery banks are used due to the low reliability of photovoltaic energy system makes necessary the storage of energy. In this work, only HRE system based on solar-diesel with batteries are considered. Due to the stochastic nature of the variable associated to an HRE system and the lack of information and technical knowledge on off-grid areas, the design process of these systems could be difficult. For this reason, it is developed a methodology that helps the sizing process of these systems to obtain the most reliable and economic solution. In this work, a sizing methodology including a PSO algorithm is developed based minimizing the levelized cost of energy and including, on the objective function, the annual cost of energy not supplied. Also, the sub-model for estimation of the solar resource and the load demand on the location are described and developed. A dispatch strategy that prioritize the use of renewable energy is explained and applied on the simulation of the HRE system. Three study cases are analyzed and discussed. Lastly, comparison with the software HOMER is performed and discussed. It is expected that this work assists the sizing and design process of HRE systems for off-grid locations minimizing the cost of energy and maximizing the reliability of these 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

The impact of electricity system characteristics on the role and value of power generation technology in the system transitions

System decarbonisation has been a focus in the development of energy systems in the 21st century and the decarbonisation of electricity systems is understood to be critical to enabling the whole system decarbonisation. Accordingly, the future electricity system is anticipated to exhibit distinct characteristics compared to the current system. However, preoccupation with images of the 20st century system persists, leading to a disparity between the climate mitigation goals, policy decisions, future system requirements, technology innovations focus, and market mechanisms. This thesis attempted to address this challenge by investigating the role and value of power generation technology, particularly CCS-equipped power plants, in delivering net-zero emissions targets under different policy and market paradigms in systems with different characteristics. Here, we show that policy mechanisms and technology innovations that overlook the systems’ integration cannot decarbonise the systems while potentially inflating the cost. Despite the necessity to minimise the system’s residual emissions, the carbon tax needs to be paired with CO2 removal (CDR) credit to deep decarbonise the system. These mechanisms can accelerate variable renewable energy (VRE) deployment that is benefited the most from further technology cost reduction. Although CCS continues to be seen as a pre-commercial technology, we found that the incumbent technology is already cost-effective to provide substantial value to the systems and that further cost reduction of CCS will not considerably reduce system cost. Thus, public spending should focus on efforts to enable the commercial deployment of CCS, such as CO2 transport and storage infrastructure deployment. Moreover, the implementation of CDR trading to complement existing wholesale electricity, capacity, and emissions markets can considerably reduce electricity prices. While these system-level findings appear to be relevant in all cases, we found that system characteristics strongly affect directions for future technology improvements in the technology level. Interestingly, in systems with rapidly growing demand, accelerating the deployment of low carbon dispatchable technology is more appreciated than technology improvements.Open Acces

Power system stability scanning and security assessment using machine learning

Future grids planning requires a major departure from conventional power system planning, where only a handful of the most critical scenarios is analyzed. To account for a wide range of possible future evolutions, scenario analysis has been proposed in many industries. As opposed to the conventional power system planning, where the aim is to find an optimal transmission and/or generation expansion plan for an existing grid, the aim in future grids scenario analysis is to analyze possible evolution pathways to inform power system planning and policy making. Therefore, future grids’ planning may involve large amount of scenarios and the existing planning tools may no longer suitable. Other than the raised future grids’ planning issues, operation of future grids using conventional tools is also challenged by the new features of future grids such as intermittent generation, demand response and fast responding power electronic plants which lead to much more diverse operation conditions compared to the existing networks. Among all operation issues, monitoring stability as well as security of a power system and action with deliberated preventive or remedial adjustment is of vital important. On- line Dynamic Security Assessment (DSA) can evaluate security of a power system almost instantly when current or imminent operation conditions are supplied. The focus of this dissertation are, for future grid planning, to develop a framework using Machine Learning (ML) to effectively assess the security of future grids by analyzing a large amount of the scenarios; for future grids operation, to propose approaches to address technique issues brought by future grids’ diverse operation conditions using ML techniques. Unsupervised learning, supervised learning and semi-supervised learning techniques are utilized in a set of proposed planning and operation security assessment tools