Decentralized smart energy systems play a vital part in the transition towards a low … Contact online >>
Decentralized smart energy systems play a vital part in the transition towards a low
Moving towards sustainability and climate security, electric power systems are going through a major paradigm shift to enable wide integration of distributed energy resources such as solar power, wind power, energy storage, demand response assets, and electric vehicles.
This is a formidable challenge due to the volatility and uncertainty of renewable energy. Today''s grid cannot handle the voltage rise and fast voltage fluctuations from high penetration of renewables, which threaten the security of grid operations and damage electrical equipment. It is widely recognised that the lack of adequate control mechanisms to regulate the voltage within a secure region is a key hindrance of wide integration of renewables into the grid.
Nevertheless, the grid has never been better equipped to handle these challenges than now due to the ongoing digital transformation of the grid, with wide integration of sensors, communications, and advanced data analytics. To meet the full promise of this digital transformation, the technological investments must be coupled with sophisticated control algorithms that can handle the grid''s fast nonlinear dynamics and its stochastic and highly distributed nature.
The goal of this project is to leverage the ongoing digitalization of the grid and state-of-the-art AI approaches to achieve data-driven and communication-efficient control and coordination of smart converters. In particular, our goal is to study how the converters can learn by experience how to make optimal decisions.
We will develop our algorithms in a simulation environment that capture important converter dynamics and interactions. The algorithms will be tested in real experimental microgrids. The developed software will add significant value to industry including advanced reinforcement learning solutions, active grid management, and grid data analytics that have been tested on real hardware. We will make all developments easily accessible for use by practitioners and publicly available.
The full title of this project is "Data-driven control and coordination of smart converters for sustainable power system using deep reinforcement learning".
Researchers at KTH have developed an open-source artificial intelligence (AI) solution to counter the challenges posed by integrating renewable energy and electric vehicles (EVs) in power grids. The increasing reliance on variable sources like solar and wind, combined with the demand for charging EVs, creates voltage fluctuations and deviations, potentially leading to power grid failure. According to Qianwen Xu, Assistant Professor at KTH and a member of the Digital Futures Faculty, the inconsistency of wind power and solar radiation, coupled with unpredictable EV charging needs, introduces many uncertainties.
The team has introduced open-source deep reinforced learning (DRL) algorithms for power converters deep within the grid. These algorithms enable the coordination of energy sources on a large scale, optimizing the system’s performance in the face of fast fluctuations without real-time communication. The decentralized management approach of the solution ensures voltage levels are maintained within required limits, preventing detrimental effects on electrical equipment and overall grid stability.
The researchers have demonstrated the effectiveness of their solution in a real-world smart microgrid hardware platform at KTH. The open-source software package is available on GitHub, and the research paper has been published in the IEEE Transactions on Sustainable Energy. The work is part of Digital Futures collaborating with researchers from the University of California, Berkeley, and Stockholm University.
Learn more in this article on AI protects power grid from fluctuations caused by renewable power and EVs, by David Callahan at KTH.
Photo: Assistant Professor Qianwen Xu in her lab at the Department of Electric Power and Energy Systems, KTH Royal Institute of Technology (by David Callahan)
Digital Futures is a cross-disciplinary research center that explores and develops digital technologies. We bring solutions to great societal challenges, in Sweden and globally. We generate knowledge, innovations and future leaders of high industrial relevance and strategic importance.
Digital Futures is jointly established by KTH Royal Institute of Technology, Stockholm University and RISE Research Institutes of Sweden.
The immediate challenges of climate change demand that we utilize all of the sustainable technologies afforded to us.
Nearly everything that relies on energy is interconnected; therefore, a System-of-Systems perspective is needed to cope with the growing complexity of the challenges ahead. Legacy systems rely on a one-way flow of energy from producers to consumers, but the future will be filled with networks of active "prosumers". We need to think beyond the box of technology to realize the full potential of a sustainable society.
Our research can dive deep into a single component or up to a city district, from engineering economics to "irrational" human behavior; all aiming to deliver sustainable, integrated energy systems.
Below is a list of our active and recently completed research projects:
Building heating solutions in China: a multi-criteria system analysis based on spatial data.
Modern clean, accessible and affordable building space heating is a key towards future sustainable development of China. For a large country as China, it is impossible to recommend identical building space heating solution for everywhere. Therefore, this project aims at developing a systematic evaluation method to assist relative stakeholders decide at where and under what conditions to choose a certain building space heating solution.
This project will apply the knowledge accumulated through the research in supermarket energy systems by building a unique demonstration case study is built where today''s most efficient, environmentally friendly and cost-effective supermarket will be designed, installed, monitored, thoroughly evaluated, and well documented.
Many combined heat and power plants in Sweden waste large amounts of heat summer time due to low heat demand and permanent generation of electricity. This project will provide design and decision making tools for including seasonal thermal storages in the ground so that summer time waste heat can be use during the winter.
The overall aim of the project is to demonstrate, using theoretical calculations, modelling, energy measurements, monitoring and business model evaluation, that a collaboration for efficient use of heating, cooling and air conditioning between real estate and supermarkets owners can be achievable for both parties.
A database, which contains operation data from more than 4000 heat pump installations throughout Sweden, can be potentially exploited by end user applications to allow manufacturers, utilities, customers or third parties to perform data monitoring and analysis. However the database suffers from incompleteness, inconsistency, lack of accuracy or sensor calibration issues. To appropriately utilize the database, we will integrate other sources such as models and lab measurements to turn the low quality data into useful information. We will develop a data-driven lab which will act as a virtual platform to improve the control strategies, fault detection and performance degradation.
Fossil fuels still account for around 7% of input energy used for the production of district heating (DH) in Sweden. With this study, we will develop a high-resolution Geographical Information System (GIS) platform, which can map the potentials of the renewable and recycled heat sources surrounding cities, and analyse cost efficient modalities of matching the sources and seasonal storages with building heat loads.
Buildings and cities are becoming increasingly integrated into the energy supply system, creating a need for transparent, trustworthy, and holistic information for potential prosumers. This project is building the foundation for easy-to-access and automate building energy models to support distributed decision making and the energy transition.
Hybrid energy storage systems (HESS) are responding to the evolving nature of energy systems and have the potential of enabling greater flexibility in energy communities (EC). Understanding and leveraging EC members'' energy-related behaviors, preferences, and constraints can enhance this potential. The PARMENIDES Project aims to develop an interoperable and secure ontology-based Energy Management System for HESS (EMS4HESS) suited for ECs with energy storage technologies, with a focus on the electricity and heating domain, so they can offer flexibility services to the grid, while finding a balance between stakeholders'' individual and collective objectives.
Use of green energy generated by solar and wind power technologies would help contribute to a clean and secure energy future for Sweden compared to conventional fossil energy resources. Along with the EU-directive for renewable energy of July 2009, Sweden declared that its primary national target is at least 50% of its total energy use would be from renewable energy resources by year 2020, and out of that, there would be at least 10% in transport sector.
The project aims at investigating the energy system and innovation process for an upcoming EcoCity in China.
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