Asset Management with Power System Applications – with Models for Predictive Maintenance and Lifetime Extension
The energy system is in a global transition, motivated by climate and energy goals and growth in energy needs. The United Nations adopted a resolution for sustainable development with 17 goals up to 2030. In 2020, the EU Framework Program for Research and Innovation presented the European Green Deal Call of €1 billion investment to boost the green and digital transition, with targets for no net emissions of greenhouse gases by 2050. This calls for transmission system operators (TSOs) and distribution system operators (DSOs) to fast-track the integration of clean energy solutions into the electrical grid, and to develop bold and agile strategies with policymakers and stakeholders to fast-track the integration of clean energy solutions. Renewable energy is becoming the major energy source as the world moves closer to being a carbon-neutral society. Further, the increasing use of intermittent renewable energy sources, such as wind and solar, also raises the demand for long-distance energy transfers, which may involve sea crossings. At the core of the power grid is the electrical equipment such as overhead lines, cables, transformers, switching devices, and converters. Existing ones should be made to work harder while holding high reliability, using improved monitoring of loads, temperatures, insulation aging, and improved modeling of the components. New ones should take advantage of improved materials and component design to have a wider operating range and be less obtrusive, as well as sustainably produced.
The electrical equipment constitutes a considerable economic asset value for the DSOs and TSOs. Many network equipment in power grids has long intrinsic lifetimes, most of which exceed 40 years. Some components of equipment age faster, or become obsolete due to the evolutions of the technologies used and induce premature replacement. Environmental or safety requirements may also be imposed and make the compliance of certain equipment incompatible with the new regulations. Energy transition acts as an accelerator to this approach which is further fueled by the development of digital techniques and the use of data to evolve the maintenance and replacement strategies. Further, weighing the aspect of a circular economy with the number of natural resources that would have to be used for manufacturing new equipment, purposeful asset management could act as a catalyst for achieving the SDGs.
This presentation will introduce the concepts of Asset Management (AM) and maintenance as a coordinated activity of an organization to realize values from assets. It will introduce the systematic method for performing maintenance which is reliability-centered maintenance (RCM) and the quantitative method of reliability-centered asset management (RCAM). The presentation will include models for lifetime extension of electrical equipment, and life cycle cost assessment including the perspective of circular economics. The presentation will include examples from research including predictive maintenance models using condition monitoring data and machine learning techniques. The presentation will include results from a CIRED working group on the lifetime extension of electrical equipment and other related work.
Infrastructure Asset Management with Power System Applications
The electric power system is being modernized to enable a sustainable energy system. New developments include possibilities and challenges with the generation, delivery, and usage of electricity as an integrated part of the energy system. This involves new forms of usage of electricity, e.g. for transportation and demand response, and the updating of existing electricity infrastructures.
For electricity generation, the trend is toward a variety of solutions including new large-scale developments, like offshore wind farms, new small-scale nuclear, small modular reactors (SMR), as well as small-scale developments like rooftop solar energy but also in new small modular reactors (SMR). At the same time, the digitalization of society is creating new opportunities for control and automation as well as new business models and energy-related services. The overall trend for technology developments is new possibilities for measurement and control. An example is Phasor Measurements Units (PMUs), generally located in the transmission network, which provide measurements of voltage and current up to 30-120 times per second. Smart Meters placed with the end consumer, which enables integration of private small-scale electricity production from solar cells, energy storage from electric vehicles, and generally distributed control of energy use, are others. Another trend is the development of diagnostic measurement techniques for assessing the insulation condition and prediction of the life of physical assets, and new methods for condition monitoring. These different trends have in common an overall development towards access to large volumes of data for handling and analysis, and another concept growing in interest is referred to as Big Data, which provides new means for infrastructure asset management (AM).
This Tutorial will include two parts. Firstly, a thorough introduction to AM and providing definitions, terminology, and basic theories. This part of the tutorial will include a detailed presentation of the reliability-centered maintenance (RCM) framework and the proposed quantitative method of reliability-centered asset management method (RCAM). Secondly, a comprehensive set of examples from a wide range of applications for the electric power system and its components will be presented. The main focus will be on input data and the use of condition-monitoring techniques for predictive maintenance. The examples will include the use of modern machine learning models.
The tutorial will be based on the book by Bertling Tjernberg, Infrastructure Asset Management with Power System Examples, CRC Press Taylor and Francis, First Edition, April 2018.
Sustainable Power Systems with Fossil-Free Electricity Generation and Storage for Improving Grid Flexibility (GreenGrids-Flex)
The energy system is in a global transition, motivated by climate and energy goals and growth in energy needs. The United Nations adopted a resolution for sustainable development with 17 goals (sustainable development goals – SDG) to be achieved by 2030. In 2020, the EU Framework Program for Research and Innovation presented the European Green Deal Call of €1 billion investment to boost the green and digital transition, with targets for no net emissions of greenhouse gases by 2050 also including ambitious targets for introducing EVs on a large scale. Besides the policy push, there are geostrategic benefits of non-reliance on conventional energy resources. Energy independence allows for stable and predictable energy costs and availability. Legacy energy resources are not evenly distributed in all geographic regions, therefore fossil-free and renewable electricity sources which are easily deployable in most geographic regions can play a pivotal role in developing the required energy independence. Decarbonizing the electrical power grids has the synergetic result of providing energy and electricity independence, thus it becomes a motivation to do so. A larger amount of low-cost and variable renewable energy sources, wind and solar, implies several system challenges which must be considered in a rational way. This need is increasing in parallel with the strong development of higher sustainability requirements, and other technologies which can be used to mitigate the challenges of weather-dependent power production. The challenges then include the development of technology and systems to be used in the future more flexible grid. A challenge is not only how to develop the solution to an economic and sustainable specific system, but also how to arrive there in an efficient way. The climate requires a fast decrease in the use of fossil fuels. In combination with fast technological development, this means a fast change of electricity use in certain areas, production in new locations, and thereby fast-changing needs of power transfer between different parts of the grid. This is in a system where it can take decades for major changes to grid infrastructure. There is thus a strong need for further development of technology for flexible grids and efficient storage and control. There is also a strong need to further develop technology and markets for system services to obtain an efficient and reliable continuous power supply.
Energy management systems (EMS) provide solutions to create this flexibility and have been in focus for much research and development. EMS can enhance economic value for the prosumers (which is a combination of consumers or small-scale producers) and for the network operators in terms of reliable performance and flexibility of the electric power grid. Strategies using EMS could be influenced, e.g., using a battery energy storage system (BESS), plug-in electric vehicles (PEVs), and various alternatives of local electricity generation like solar photovoltaic (PV) or wind power. Using remote sensing the BESS can be intelligently managed by an EMS that uses the BESS resource for multiple ancillary services, thereby generating additional value from the present resource. An EMS that controls the BESS to perform peak shaving (PS) of a local load and provide frequency regulation services (for the grid operator). Of the more unexplored resources of flexibility provision are EVs. In the future, EVs might work as independent providers of significant flexibility and the introduction of Vehicle-to-Grid would make a significant impact on the power flow availability.
This presentation with introduce generic models for flexibility using BESS, EMS, and EVs for creating value for prosumers, grid operators, and many more actors. The lecture will include examples from research with real case studies.
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