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Integrated model construction for state of charge estimation in electric vehicle lithium batteries Energy Inform. Pub Date : 2024-03-14 Yuanyuan Liu, Wenxin Dun
This research addresses the issue of State of Charge (SOC) prediction for electric vehicle batteries by employing a dynamic Kalman neural network model. The model is optimized using a Genetic algorithm to adjust the neural network weights. Additionally, a strategy involving support vector machines for model optimization is proposed. This strategy involves preprocessing the data, selecting appropriate
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Reducing the energy consumption of buildings by implementing insulation scenarios and using renewable energies Energy Inform. Pub Date : 2024-03-11 Arash Shahee, Mahmood Abdoos, Alireza Aslani, Rahim Zahedi
The reduction of fossil energy sources, the harmful environmental effects caused by high energy consumption, and the increase in the share of energy consumption in the building sector have increased the need to pay attention to building energy consumption. This study offers an intricate examination of a residential locality in Florida, with a particular emphasis on the architectural design of a building
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An analysis of the correlation between income and the consumption of energy in Bangladesh Energy Inform. Pub Date : 2024-03-11 Md. Abdus Shabur, Md. Farhad Ali
This research takes a methodical look at how rising incomes and climate change affect energy use in six different divisions of Bangladesh. To investigate the indirect mechanism of income influence on the consumption of energy, this study employs indicators of industrial structure upgrading and urbanization in a novel way using the fixed effects model which has not been used so far in this kind of study
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Analysis of a multi-energy coupling model for rural energy under the rural digital economy Energy Inform. Pub Date : 2024-03-04 Hongyan Li, Xin Li
With the growth of the digital economy, the sustainable growth of rural energy has become crucial. However, traditional rural energy models have the drawback of not considering digital technology and renewable energy. Therefore, there is an urgent need for rational planning and development of rural energy. According to this, a multi-energy coupling model for rural energy systems was established by
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SPAGHETTI: a synthetic data generator for post-Covid electric vehicle usage Energy Inform. Pub Date : 2024-03-04 Anaïs Berkes, Srinivasan Keshav
The Covid-19 pandemic has resulted in a permanent shift in individuals’ daily routines and driving behaviours, leading to an increase in remote work. There has also been an independent and parallel rise in the adoption of solar photovoltaic (PV) panels, electrical storage systems, and electric vehicles (EVs). With remote work, EVs are spending longer periods at home. This offers a chance to reduce
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Photovoltaic systems: a review with analysis of the energy transition in Brazilian culture, 2018–2023 Energy Inform. Pub Date : 2024-03-01 Thamyres Machado David, Teófilo Miguel de Souza, Paloma Maria Silva Rocha Rizol
Countries all over the world have been seeking ways and methods so that their electrical matrices can stand out using clean and renewable energy sources. In this context, this article presents a review with analysis of sector legislation on photovoltaic solar energy in Brazil. This study was grounded in four steps: (i) sample definition; (ii) theoretical basis; (iii) network analysis; and (iv) content
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Probabilistic forecast of electric vehicle charging demand: analysis of different aggregation levels and energy procurement Energy Inform. Pub Date : 2024-02-29 Adrian Ostermann, Theodor Haug
Electric vehicles (EVs) are expected to be vital in transitioning to a low-carbon energy system. However, integrating EVs into the power grid poses significant challenges for grid operators and energy suppliers, especially regarding the uncertainty and variability of EV charging demand. Accurate forecasting of EV charging demand is essential for optimal power system integration, yet previous studies
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A scoping review of In-the-loop paradigms in the energy sector focusing on software-in-the-loop Energy Inform. Pub Date : 2024-02-27 Christian Skafte Beck Clausen, Bo Nørregaard Jørgensen, Zheng Grace Ma
Software-in-the-Loop (SIL) testing is an approach used for verification and validation in the energy sector. However, there is no comprehensive overview of the application, potential, and challenges of SIL within this sector. Therefore, this paper conducts a thorough scoping review of the existing literature within the scope of SIL and related in-the-loop approaches in the energy sector. A total of
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A review of building digital twins to improve energy efficiency in the building operational stage Energy Inform. Pub Date : 2024-02-26 Andres Sebastian Cespedes-Cubides, Muhyiddine Jradi
The majority of Europe’s building stock consists of facilities built before 2001, presenting a substantial opportunity for energy efficiency improvements during their operation and maintenance phase. Digitalizing these buildings with digital twin technology can significantly enhance their energy efficiency. Reviewing the applications and trends of digital twins in this context is beneficial to understand
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Enhanced fault detection in polymer electrolyte fuel cells via integral analysis and machine learning Energy Inform. Pub Date : 2024-02-26 Ester Melo, Julio Barzola-Monteses, Holguer H. Noriega, Mayken Espinoza-Andaluz
The growing energy demand and population raising require alternative, clean, and sustainable energy systems. During the last few years, hydrogen energy has proven to be a crucial factor under the current conditions. Although the energy conversion process in polymer electrolyte fuel cells (PEFCs) is clean and noiseless since the only by-products are heat and water, the inside phenomena are not simple
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Improved electrical coupling integrated energy system based on particle swarm optimization Energy Inform. Pub Date : 2024-02-23 Lei Wang
The rational utilization of energy is an important issue for sustainable development. Electrically coupled integrated energy systems can enhance energy utilization efficiency and reduce energy costs. However, traditional integrated energy system optimization has problems with local optima and slow convergence speed, which cannot fully utilize energy resources. Therefore, this study proposes an improved
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Exploring decentralized data management: a case study of changing energy suppliers in Germany Energy Inform. Pub Date : 2024-02-22 Linda Rülicke, Florian Fehrle, Arne Martin, Antonello Monti, Volker Berkhout, Oliver Warweg, Sven Möller
This paper presents an innovative approach to decentralized data management in the German energy market, focusing on the use of decentralized data management with the help of Data Spaces to facilitate the automated change of energy suppliers within 24 h. The central focus of this research is the MakoMaker Space, a demonstrator project that employs the Connector from the Eclipse Data Space Components
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From use cases to business cases: I-GReta use cases portfolio analysis from innovation management and digital entrepreneurship models perspectives Energy Inform. Pub Date : 2024-02-12 Elena Malakhatka, Manuel Pitz, Marwa Maghnie, Mohammadreza Mazidi, Radu Plamanescu, Christof Sumereder, Thomas Prüfer, Holger Wallbaum, Dirk Müller, Antonello Monti
This study provides a detailed exploration of how innovation management and digital entrepreneurship models can help transform technical use cases in smart grid contexts into viable business cases, thereby bridging the gap between technical potential and market application in the field of energy informatics. It focuses on the I-GReta project Use Cases (UCs). The study employs methodologies like Use
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Recently emerging trends in big data analytic methods for modeling and combating climate change effects Energy Inform. Pub Date : 2024-02-07 Anayo Chukwu Ikegwu, Henry Friday Nweke, Emmanuel Mkpojiogu, Chioma Virginia Anikwe, Sylvester Agbo Igwe, Uzoma Rita Alo
Big climate change data have become a pressing issue that organizations face with methods to analyze data generated from various data types. Moreover, storage, processing, and analysis of data generated from climate change activities are becoming very massive, and are challenging for the current algorithms to handle. Therefore, big data analytics methods are designed for significantly large amounts
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Industrial digital twins in offshore wind farms Energy Inform. Pub Date : 2024-02-06 Evi Elisa Ambarita, Anniken Karlsen, Francesco Scibilia, Agus Hasan
Digital twin technology, aligned with Industry 4.0 standard, has witnessed widespread adoption in various industries, notably in manufacturing. Meanwhile, the concept of digital twin itself is yet to be clearly defined in wind farm sector. Our primary contribution lies in investigating the potential for transferring knowledge of industrial digital twins for the wind farm industry. Through a comprehensive
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Peak load estimation of renewable energy generation based on imitator dynamic algorithm Energy Inform. Pub Date : 2024-02-05 Siqi Ye, Ling Yu, Jinman Luo
In the field of renewable energy generation forecasting, it is crucial to accurately estimate the peak load. However, due to the complex nonlinear characteristics of the data, the traditional long short-term memory network performs poorly in processing these data. This study introduces the imitator dynamic algorithm, which is able to generate samples close to the real situation by learning the change
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ESTSS—energy system time series suite: a declustered, application-independent, semi-artificial load profile benchmark set Energy Inform. Pub Date : 2024-01-22 Sebastian Günther, Jonathan Brandt, Astrid Bensmann, Richard Hanke-Rauschenbach
This paper introduces an univariate application-independent set of load profiles or time series derived from real-world energy system data. The generation involved a two-step process: manifolding the initial dataset through signal processors to increase diversity and heterogeneity, followed by a declustering process that removes data redundancy. The study employed common feature engineering and machine
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Short-term forecasting of German generation-based CO2 emission factors using parametric and non-parametric time series models Energy Inform. Pub Date : 2024-01-10 Adrian Ostermann, Arian Bajrami, Alexander Bogensperger
This study focuses on forecasting German generation-based CO2 emission factors to develop accurate prediction models, which help to shift flexible loads in time with low emissions. While most existing research relies on point forecasts to predict CO2 emission factors, the presented methods are utilized to perform interval forecasts. In addition, compared to other studies, recent data that extends over
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A proposed PMU-based voltage stability and critical bus detection method using artificial neural network Energy Inform. Pub Date : 2024-01-08 Lesnanto Multa Putranto, Izzuddin Fathin Azhar
Voltage stability detection is currently still becoming the main issue in the modern integrated renewable energy power systems. To assess the voltage stability, the classical methods based on continuation power flow (CPF) technique were used to show nose curve. However, the classical methods require complete model of power system and long computation time. Data driven analysis and synchronized real
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Technology and economics of electric vehicle power transfer: insights for the automotive industry Energy Inform. Pub Date : 2023-11-17 Girish Ghatikar, Mohammad S. Alam
Battery-based electric vehicles (BEVs) in the United States (U.S.) set a new sales record in 2022, driven by technology, policy, environmental, and economic objectives. However, the rapid deployment of BEVs and charging infrastructure without a careful review of their integration with the electric grid can have negative economic impacts on reliable and resilient electricity supply. Bi-directional power
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Artificial ecosystem optimized neural network controlled unified power quality conditioner for microgrid application Energy Inform. Pub Date : 2023-11-14 Rajeev Ratnakaran, Gomathi Bhavani Rajagopalan, Asma Fathima
Unified power quality conditioner is chiefly employed to offer power quality improvement, especially in grid connected mode of operation in microgrid applications. This article proposes an artificial ecosystem optimized neural network for control of photovoltaic system and battery powered UPQC for microgrid applications. The intelligent routine implemented by the proposed controller helps tune parameters
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Using weather data in energy time series forecasting: the benefit of input data transformations Energy Inform. Pub Date : 2023-11-02 Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig
Renewable energy systems depend on the weather, and weather information, thus, plays a crucial role in forecasting time series within such renewable energy systems. However, while weather data are commonly used to improve forecast accuracy, it still has to be determined in which input shape this weather data benefits the forecasting models the most. In the present paper, we investigate how transformations
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Towards a systematic and knowledge-based requirements and conceptual engineering for modular electrolysis plants Energy Inform. Pub Date : 2023-10-26 Artan Markaj, Julius Lorenz, Lena Scholz, Vincent Henkel, Alexander Fay
The production of green hydrogen and its scale-up require the enginering and installation of new electrolysis plants. Modular electrolysis plants ease the scale-up as they allow to add further modules with growing demand. While many engineering methods focus on the detailed planning of the plants and their automation systems, the early engineering phases are scarcely considered, supported or formalized
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Energy metaverse: the conceptual framework with a review of the state-of-the-art methods and technologies Energy Inform. Pub Date : 2023-10-25 Zheng Ma
The transition to green energy systems is vital for addressing climate change, with a focus on renewable sources like wind and solar. This change requires substantial investment, societal adaptations, and managing a complex energy ecosystem. However, no existing evaluation methods support this purpose. The "energy metaverse" is proposed as a digital platform that mirrors the energy ecosystem, enabling
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Finding individual strategies for storage units in electricity market models using deep reinforcement learning Energy Inform. Pub Date : 2023-10-19 Nick Harder, Anke Weidlich, Philipp Staudt
Modeling energy storage units realistically is challenging as their decision-making is not governed by a marginal cost pricing strategy but relies on expected electricity prices. Existing electricity market models often use centralized rule-based bidding or global optimization approaches, which may not accurately capture the competitive behavior of market participants. To address this issue, we present
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National-scale bi-directional EV fleet control for ancillary service provision Energy Inform. Pub Date : 2023-10-19 Lorenzo Nespoli, Nina Wiedemann, Esra Suel, Yanan Xin, Martin Raubal, Vasco Medici
Deploying real-time control on large-scale fleets of electric vehicles (EVs) is becoming pivotal as the share of EVs over internal combustion engine vehicles increases. In this paper, we present a Vehicle-to-Grid (V2G) algorithm to simultaneously schedule thousands of EVs charging and discharging operations, that can be used to provide ancillary services. To achieve scalability, the monolithic problem
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Modeling control strategies for prosumers in a Python-based modular simulation tool Energy Inform. Pub Date : 2023-10-19 Andrea Schoen, Jan Ringelstein, Denis Mende, Martin Braun
The planned massive increase of producers and consumers such as electric vehicles, heat pumps and photovoltaic systems in distribution grids will lead to new challenges in the electrical power system. These can include grid congestions at the low voltage level but also at higher voltage levels. Control strategies can enable the efficient use of flexibilities and therefore help mitigate upcoming problems
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Quality properties of IEC 62559 use cases and SGAM models Energy Inform. Pub Date : 2023-10-19 René Kuchenbuch, Johann Schütz, Jürgen Sauer
The Smart Grid Architecture Model (SGAM) and the IEC 62559-2 Use Case Template are essential representatives of the Requirements Engineering of energy systems to promote interoperability. In particular, the quality of the use case descriptions and SGAM models is crucial for the system understanding. In order to measure and assess the quality of given use cases of the SGAM models, the aim of this research
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Generating synthetic load profiles of residential heat pumps: a k-means clustering approach Energy Inform. Pub Date : 2023-10-19 Leo Semmelmann, Patrick Jaquart, Christof Weinhardt
The creation of synthetic heat pump load profiles is essential for energy system modeling and simulations. This paper proposes a methodology to create synthetic heat pump load profiles based on the k-means algorithm and a data set from water-to-water heat pumps from Hamelin, Germany. The quality of the generated load profiles is shown according to load factors, load distribution curves and the Pearson
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From computer systems to power systems: using stochastic network calculus for flexibility analysis in power systems Energy Inform. Pub Date : 2023-10-19 Tim Fürmann, Michael Lechl, Hermann de Meer, Anke Weidlich
As power systems transition from controllable fossil fuel plants to variable renewable sources, managing power supply and demand fluctuations becomes increasingly important. Novel approaches are required to balance these fluctuations. The problem of determining the optimal deployment of flexibility options, considering factors such as timing and location, shares similarities with scheduling problems
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Exploring trade-offs in public bus electrification under stochastic conditions Energy Inform. Pub Date : 2023-10-19 Charitha Buddhika Heendeniya, Lorenzo Nespoli, Marco Belliardi, Vasco Medici
In this article, we address the question of electric bus planning and operation under stochastic travel time and energy consumption. Uncertainties in the environment may cause disruptions to the planning and operation of electric buses, and a transportation planner must anticipate such conditions and be able to respond appropriately. One of the preconditions for planning robust strategies is understanding
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Aggregating multi-time-scale flexibility potentials of battery storages based on open data – a potential analysis Energy Inform. Pub Date : 2023-10-19 Michael Lechl, Luis Schoppik, Hermann de Meer
Flexibility potentials are mostly provided by centrally coordinated flexibility resources such as natural-gas-fired power plants. However, the decentralization of power generation combined with the decarbonization of the sector due to the energy transition requires the exploration of new types of flexibility resources. In particular, to reduce dependence on natural-gas-fired power plants, it would
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Assessing the incorporation of battery degradation in vehicle-to-grid optimization models Energy Inform. Pub Date : 2023-10-19 Valentin Preis, Florian Biedenbach
Bidirectional charging allows energy from the electric vehicles (EV) to be fed back into the grid, offering the possibility of price-optimized charging. However, such strategies cause higher charging cycles, which affect the cyclic aging of the battery and reduce its service life, resulting in additional costs for the user. Various approaches are used to account for battery degradation in optimizations
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Welcome message from the organizers Energy Inform. Pub Date : 2023-10-19 Friederich Kupzog, Ronald Bieber, Mark Stefan, Oleg Valgaev
Dear Readers, Applications of informatics in the energy sector are more important than ever. Energy supply chains need to be reorganized, efficiency increased, energy infrastructure must be built and rebuilt, existing systems must be used in the best possible way. This is particularly true for the DACH region, where the energy transition has become a central topic of public interest and societal issues
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Verifiable proofs for the energy supply chain: small proofs brings you a long way Energy Inform. Pub Date : 2023-10-19 Morten Jokumsen, Torben Pryds Pedersen, Martin Schmidt Daugaard, Daniel Tschudi, Mikkel Wienberg Madsen, Thomas Wisbech
We describe a solution for secure and verifiable handling of energy certificates. Such certificates are increasingly used to claim and prove responsible use of green energy, and there is a strong need for transparency and public verifiability. While the proposed solution is designed for handling electricity it applies to different types of energy as well and the concepts may also be applied to other
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A model-based approach for converting CGMES power system models into operational networks Energy Inform. Pub Date : 2023-10-19 Ammar Memari, Adam Aljamous
This paper presents a model-based approach for converting Common Grid Model Exchange Specification (CGMES) power system models into operational networks. The approach utilizes the Model-Driven Architecture (MDA), borrowed from software engineering, to create a Platform-Independent Model (PIM) saved in a graph database, neo4j. The PIM is then transformed into Platform-Specific Model (PSM) using cypher
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Quantum–classical co-simulation for smart grids: a proof-of-concept study on feasibility and obstacles Energy Inform. Pub Date : 2023-10-19 Dominik Vereno, Amin Khodaei, Christian Neureiter, Sebastian Lehnhoff
With the rising complexity of our electricity infrastructure, smart grid simulations increasingly rely on co-simulation, which involves jointly executing independent subsystem simulations. However, in large-scale simulation scenarios, such as those involving costly power-flow analysis, co-simulation may experience computational-performance issues. Quantum computing offers a potential solution through
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Quantifying the resilience of ICT-enabled grid services in cyber-physical energy system Energy Inform. Pub Date : 2023-10-19 Anand Narayan, Michael Brand, Sebastian Lehnhoff
Information and Communication Technology (ICT) is vital for the operation of modern power systems, giving rise to Cyber-Physical Energy Systems (CPESs). ICT enables the grid services (GSs) needed for monitoring and controlling the physical parameters of the power system, especially for remedying the impact of disturbances. But the ICT integration makes the overall system more complex, leading to new
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Schema matching based on energy domain pre-trained language model Energy Inform. Pub Date : 2023-10-19 Zhiyu Pan, Muchen Yang, Antonello Monti
Data integration in the energy sector, which refers to the process of combining and harmonizing data from multiple heterogeneous sources, is becoming increasingly difficult due to the growing volume of heterogeneous data. Schema matching plays a crucial role in this process by giving each representation a unique identity by matching raw energy data to a generic data model. This study uses an energy
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A methodological framework for geospatial modelling of hydrogen demand in cities Energy Inform. Pub Date : 2023-10-19 Stefan Beck, David Fischer
Urban energy system planning is vital for cities shifting towards a more sustainable and integrated energy system. Hydrogen is considered one of the most promising solutions in future energy systems. Previous work on hydrogen energy systems predominantly analysed hydrogen models on a national level or only parts of the mobility sector. This indicates a research gap for geospatial models that include
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Transformer training strategies for forecasting multiple load time series Energy Inform. Pub Date : 2023-10-19 Matthias Hertel, Maximilian Beichter, Benedikt Heidrich, Oliver Neumann, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer
In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to prevent grid outages. While the number of monitored clients will increase with the ongoing smart meter rollout, the amount of data per client will always be limited. We evaluate whether a Transformer load forecasting model benefits from a transfer learning
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Assess: anomaly sensitive state estimation with streaming systems Energy Inform. Pub Date : 2023-10-19 Michael Brand, Dominik Engel, Sebastian Lehnhoff
Information and communication technology (ICT) is an increasing part of modern power systems, which are, therefore, recognised as cyber-physical energy system (CPESs). The increase of ICT affects the situational awareness in CPESs, which is traditionally solely based on information about the power system but not about the ICT system. However, CPESs are facing various challenges regarding the integrity
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AI temporal planning for energy smart buildings Energy Inform. Pub Date : 2023-10-19 Ilche Georgievski, Muhammad Zamik Shahid, Marco Aiello
Buildings are responsible for about one-third of industrialised countries’ overall energy consumption and greenhouse gas emissions. As if this was not enough, recently, energy prices significantly increased and affected all economic areas. Making buildings more efficient and effective is the step needed toward cost reductions. Key enablers of cost-effectiveness are leveraging batteries, awareness of
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Interaction graph learning of line cascading failure in power networks and its statistical properties Energy Inform. Pub Date : 2023-10-19 Abdorasoul Ghasemi, Hermann de Meer, Holger Kantz
We consider line failure cascading in power networks where an initial random failure of a few lines leads to consecutive other line overloads and failures before the system settles in a steady state. Such cascades are rooted in non-obvious, long-range, and higher-order couplings among the lines’ flows induced by physical constraints on the network. Failure interaction graph encodes which and to what
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Estimating time-delayed variables using transformer-based soft sensors Energy Inform. Pub Date : 2023-10-19 Jelke Wibbeke, Darian Alves, Sebastian Rohjans
In the course of digitization, there is an increased interest in sensor data, including data from old systems with a service life of several decades. Since the installation of sensor technology can be quite expensive, soft sensors are often used to enhance the monitoring capabilities. Soft sensors use easy-to-measure variables to predict hard-to-measure variables, employing arbitrary models. This is
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Abstracts of the 12th DACH+ Conference on Energy Informatics 2023 Energy Inform. Pub Date : 2023-10-04
Simon Grafenhorst\(^{*}\), Kevin Förderer and Veit Hagenmeyer Institute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany Correspondence: Simon Grafenhorst (grafenhorst@kit.edu) Energy Informatics 2023, 6(Suppl 2):P1 Summary Various models of the distribution grid are developed to assess the impact
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A new optimal allocation of DGs in distribution networks by using coot bird optimization method Energy Inform. Pub Date : 2023-09-18 Gholamreza Memarzadeh, Mohammadreza Arabzadeh, Farshid Keynia
Energy is one of the most important topics in the world today and is considered as one of the most effective factors for the development of countries. Due to the limitation of non-renewable energy sources and undesirable effects of consuming these resources on the environment, the strategy of countries has changed towards the use of renewable energy. Renewable energy sources do not decrease over time
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Dynamic energy pricing considering agent specific losses in residential energy hubs Energy Inform. Pub Date : 2023-09-11 Braden Kidd
The rise of distributed energy generation and storage is creating new opportunities for energy consumers to actively engage with energy markets. Achieving these potential benefits will require the implementation of new business models to address limitations of existing market structures. One promising area of research involves the use of decentralised energy trading markets. These markets can increase
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Correction: Synergies and scaling of use case combinations in the field of asset logging and labeling Energy Inform. Pub Date : 2023-09-04 Louisa Wasmeier, Patrick Dossow, Michael Hinterstocker
Correction : Energy Informatics (2023) 6:15 https://doi.org/10.1186/s42162-023-00270-7 Following publication of the original article (Wasmeier et al. 2023), the authors identified an error in Fig. 10. The legends mentioned “Separate implementation including 6” and “Combined implementation including 6”. Fig. 10 Absolute qualitative effort value (left) and effort per asset owner (right) for the use cases
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Solar PV-hydropower enhanced Picogrid as sustainable energy model for hilly remote areas: analytics and prospects thereof Energy Inform. Pub Date : 2023-09-01 Alpesh Desai, Indrajit Mukhopadhyay, Abhijit Ray
This paper presents a techno-economic analysis of ‘Picogrid’ in hilly remote areas of North-East India, where availability of conventional grid power is either none or limited. A Picogrid is a small microgrid (typically a few tens of kW) containing renewable energy sources like solar, wind, small hydro etc. with battery based energy storage of limited capacity. A hybrid solar PV-Hydro based Picogrid
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Synergies and scaling of use case combinations in the field of asset logging and labeling Energy Inform. Pub Date : 2023-08-11 Louisa Wasmeier, Patrick Dossow, Michael Hinterstocker
The digitalization of the energy sector enables a broad range of new digital use cases and business models. For instance, blockchain-technology can be used for the verification of tamper-resistant storage of asset data (asset logging) or manipulation-resistant guarantees of origin for electricity (labeling). Yet, it is associated with high implementation and operating effort. But many of these use
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Enough hot air: the role of immersion cooling Energy Inform. Pub Date : 2023-08-09 Kawsar Haghshenas, Brian Setz, Yannis Blosch, Marco Aiello
Air cooling is the traditional solution to chill servers in data centers. However, the continuous increase in global data center energy consumption combined with the increase of the racks’ power dissipation calls for the use of more efficient alternatives. Immersion cooling is one such alternative. In this paper, we quantitatively examine and compare air cooling and immersion cooling solutions. The
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Exploring the energy informatics and energy citizenship domains: a systematic literature review Energy Inform. Pub Date : 2023-08-02 Ajesh Kumar, Bilal Naqvi, Annika Wolff
To effectively address the challenges posed by the increasing share of the energy sector in global greenhouse effects, the domains of energy informatics and energy citizenship play a critical role. Energy informatics aims at using information systems and channels to reduce energy consumption. However, there is a realization that the challenges posed by global greenhouse effects cannot be catered to
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Interface design for residential energy feedback, in the Indian context Energy Inform. Pub Date : 2023-05-11 Madhur Garg, Vishal Garg, Priyanka Srivastava, Rishika Agarwal
Global access to electricity has increased from 78.2% to 2000 to 90.5% in 2020, resulting in an increased electricity demand worldwide. Unlike commercial electricity consumption, which is managed by professionals, residential consumption is managed by the householders, who often lack insight into their energy usage. Quality feedback, including detailed energy consumption and tips, can lead to substantial
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Publisher Correction: Towards reinforcement learning for vulnerability analysis in power-economic systems Energy Inform. Pub Date : 2023-05-09 Thomas Wolgast, Eric M. S. P. Veith, Astrid Nieße
Correction : Energy Informatics 2021, 4(Suppl 3):21 https://doi.org/10.1186/s42162-021-00181-5 In the original (Wolgast et al. 2021) publication of the article, 2 symbols were erroneously omitted during the publication process. The incorrect and correct information is shown in this correction article. Incorrect Table 1 shows that the average attacker profit increases drastically by about 323.2 on average
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The determinants of reliable smart grid from experts’ perspective Energy Inform. Pub Date : 2023-04-11 Ibrahim Mashal, Osama A. Khashan, Mohammad Hijjawi, Mohammad Alshinwan
A smart grid integrates communication networks with the conventional electrical grid. Due to their potential, smart grids are anticipated to achieve widespread deployment. A key component of the success and adoption of smart grids is reliability. Without knowing users’ impressions of the reliability of the smart grid, users will not easily accept and participate in it or its services. However, very
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Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review Energy Inform. Pub Date : 2023-04-05 Simon Elias Bibri, Alahi Alexandre, Ayyoob Sharifi, John Krogstie
There have recently been intensive efforts aimed at addressing the challenges of environmental degradation and climate change through the applied innovative solutions of AI, IoT, and Big Data. Given the synergistic potential of these advanced technologies, their convergence is being embraced and leveraged by smart cities in an attempt to make progress toward reaching the environmental targets of sustainable
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A digital twin of a local energy system based on real smart meter data Energy Inform. Pub Date : 2023-03-28 Daniel Bayer, Marco Pruckner
The steadily increasing usage of smart meters generates a valuable amount of high-resolution data about the individual energy consumption and production of local energy systems. Private households install more and more photovoltaic systems, battery storage and big consumers like heat pumps. Thus, our vision is to augment these collected smart meter time series of a complete system (e.g., a city, town
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Correction: Using EV charging control to provide building load flexibility Energy Inform. Pub Date : 2023-03-27 Harsimrat Singh Bhundar, Lukasz Golab, Srinivasan Keshav
Correction: Energy Informatics (2023) 6:5 https://doi.org/10.1186/s42162-023-00261-8 During the publication process the author name “Lukasz Golab” was incorrectly published as “Lukas Golab”. The original publication (Bhundar et al. 2023) has been updated to correct this error. The publisher apologizes for the error. Bhundar HS, Golab L, Keshav S (2023) Using EV charging control to provide building
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Plugged-in electric vehicle-assisted demand response strategy for residential energy management Energy Inform. Pub Date : 2023-03-16 Khaldoon Alfaverh, Fayiz Alfaverh, Laszlo Szamel
Demand response (DR) management systems are a potentially growing market due to their ability to maximize energy savings by allowing customers to manage their energy consumption at times of peak demand in response to financial incentives from the electricity supplier. Successful execution of a demand response program requires an effective management system where the home energy management system (HEMS)