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Special Issue "Model Coupling and Energy Systems"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electrical Power and Energy System".

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Guest Editor
Dr. Peter Markewitz

Institute of Electrochemical Process Engineering (IEK-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Website | E-Mail
Interests: energy systems modelling, energy scenarios, greenhouse gas reduction strategies, technology assessment
Guest Editor
Dr. Martin Robinius

Institute of Electrochemical Process Engineering (IEK-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Website | E-Mail
Interests: energy systems analysis and assessment, sector coupling, greenhouse gas reduction strategies
Guest Editor
Prof. Dr. Dominik Möst

Affiliation:Chair of energy economics, Technische Universität Dresden, D-01062 Dresden
Website | E-Mail
Interests: energy system, energy market modelling, energy market design, long-range developments of energy markets, renewable energies and system integration

Special Issue Information

Dear Colleagues,

The degree of complexity of energy systems has significantly increased in the context of high shares of renewables, decarbonisation goals, environmental aspects, economic interactions, etc. Therefore, the development of energy scenarios or greenhouse gas reduction strategies requires the use of model approaches to understand the interdependencies of different technologies and policy measures at the different levels (from regional via national to European level) of the energy sector.

However, different methodologies, model types (technical, economic, etc.), and model coupling approaches are used for energy systems assessment, which themselves significantly impact the scenario results. The methodology can range from pure optimisation models that specifically analyse the development from a cost optimal perspective via models that take into account strategic behaviour, e.g., using mixed complementarity formulations for modelling market equilibriums, as well as taking into account other concepts, like agent-based simulation or system dynamics. In general, the research should demonstrate an additional value for a relevant research question in the energy sector.

Therefore, this Special Issue welcomes research focusing on models, model coupling concepts, and methodological approaches.

Your contribution may describe models, model coupling concepts suitable for generating energy scenarios, and greenhouse gas reduction scenarios on different system levels (international, national, sectoral, urban, infrastructures, etc.).

Dr. Peter Markewitz
Dr. Martin Robinius
Prof. Dr. Dominik Möst
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • modeling of energy systems or energy markets 
  • model coupling 
  • energy supply 
  • greenhouse gas reduction strategies 
  • energy infrastructures 
  • energy sector 
  • end use sectors

Published Papers (7 papers)

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Research

Open AccessArticle
Representation of Balancing Options for Variable Renewables in Long-Term Energy System Models: An Application to OSeMOSYS
Energies 2019, 12(12), 2366; https://doi.org/10.3390/en12122366
Received: 14 May 2019 / Revised: 8 June 2019 / Accepted: 13 June 2019 / Published: 19 June 2019
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Abstract
The growing complexity and the many challenges related to fast-changing and highly de-carbonised electricity systems require reliable and robust open source energy modelling frameworks. Their reliability may be tested on a series of well-posed benchmarks that can be used and shared by the [...] Read more.
The growing complexity and the many challenges related to fast-changing and highly de-carbonised electricity systems require reliable and robust open source energy modelling frameworks. Their reliability may be tested on a series of well-posed benchmarks that can be used and shared by the modelling community. This paper describes and integrates stand-alone, independent modules to compute the costs and benefits of flexible generation options in the open source energy investment modelling framework OSeMOSYS. The modules are applied to a case study that may work as a benchmark. The whole documentation of the modules and the test case study are retrievable, reproducible, reusable, interoperable, and auditable. They create a case to help establish a FAIR-compliant, user-friendly, and low-threshold model and data standards in modelling practices. As is well known, one of the options for balancing high shares of variable renewables is flexible power generation by dispatchable units. The associated costs need to be considered for short-term operational analyses and for long-term investment plans. The added modules contribute to extending the modelling capacity by introducing (a) costs of ramping, (b) non-linear decrease of efficiency at partial load operation, and (c) refurbishment of existing units in the cost minimisation objective function of OSeMOSYS. From application to the test case study, two main insights are drawn: costs of ramping and decreased partial load efficiency may influence the competitiveness of generation technologies in the provision of reserve capacity; and refurbishment of existing units may represent attractive investment options for increasing flexibility. Both effects are also seen in the long-term and may impact infrastructure investment decisions to meet decarbonisation targets. These effects would not be captured without the introduction of the modules. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
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Open AccessArticle
Hourly CO2 Emission Factors and Marginal Costs of Energy Carriers in Future Multi-Energy Systems
Energies 2019, 12(12), 2260; https://doi.org/10.3390/en12122260
Received: 9 May 2019 / Revised: 7 June 2019 / Accepted: 10 June 2019 / Published: 13 June 2019
PDF Full-text (9813 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Hourly emission factors and marginal costs of energy carriers are determined to enable a simplified assessment of decarbonization measures in energy systems. Since the sectors and energy carriers are increasingly coupled in the context of the energy transition, the complexity of balancing emissions [...] Read more.
Hourly emission factors and marginal costs of energy carriers are determined to enable a simplified assessment of decarbonization measures in energy systems. Since the sectors and energy carriers are increasingly coupled in the context of the energy transition, the complexity of balancing emissions increases. Methods of calculating emission factors and marginal energy carrier costs in a multi-energy carrier model were presented and applied. The model used and the input data from a trend scenario for Germany up to the year 2050 were described for this purpose. A linear optimization model representing electricity, district heating, hydrogen, and methane was used. All relevant constraints and modeling assumptions were documented. In this context, an emissions accounting method has been proposed, which allows for determining time-resolved emission factors for different energy carriers in multi-energy systems (MES) while considering the linkages between energy carriers. The results showed that the emissions accounting method had a strong influence on the level and the hourly profile of the emission factors. The comparison of marginal costs and emission factors provided insights into decarbonization potentials. This holds true in particular for the electrification of district heating since a strong correlation between low marginal costs and times with renewable excess was observed. The market values of renewables were determined as an illustrative application of the resulting time series of costs. The time series of marginal costs as well as the time series of emission factors are made freely available for further use. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
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Open AccessArticle
A Comparative Study of Methods for Measurement of Energy of Computing
Energies 2019, 12(11), 2204; https://doi.org/10.3390/en12112204
Received: 5 May 2019 / Revised: 27 May 2019 / Accepted: 28 May 2019 / Published: 10 June 2019
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Abstract
Energy of computing is a serious environmental concern and mitigating it is an important technological challenge. Accurate measurement of energy consumption during an application execution is key to application-level energy minimization techniques. There are three popular approaches to providing it: (a) System-level physical [...] Read more.
Energy of computing is a serious environmental concern and mitigating it is an important technological challenge. Accurate measurement of energy consumption during an application execution is key to application-level energy minimization techniques. There are three popular approaches to providing it: (a) System-level physical measurements using external power meters; (b) Measurements using on-chip power sensors and (c) Energy predictive models. In this work, we present a comprehensive study comparing the accuracy of state-of-the-art on-chip power sensors and energy predictive models against system-level physical measurements using external power meters, which we consider to be the ground truth. We show that the average error of the dynamic energy profiles obtained using on-chip power sensors can be as high as 73% and the maximum reaches 300% for two scientific applications, matrix-matrix multiplication and 2D fast Fourier transform for a wide range of problem sizes. The applications are executed on three modern Intel multicore CPUs, two Nvidia GPUs and an Intel Xeon Phi accelerator. The average error of the energy predictive models employing performance monitoring counters (PMCs) as predictor variables can be as high as 32% and the maximum reaches 100% for a diverse set of seventeen benchmarks executed on two Intel multicore CPUs (one Haswell and the other Skylake). We also demonstrate that using inaccurate energy measurements provided by on-chip sensors for dynamic energy optimization can result in significant energy losses up to 84%. We show that, owing to the nature of the deviations of the energy measurements provided by on-chip sensors from the ground truth, calibration can not improve the accuracy of the on-chip sensors to an extent that can allow them to be used in optimization of applications for dynamic energy. Finally, we present the lessons learned, our recommendations for the use of on-chip sensors and energy predictive models and future directions. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
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Open AccessArticle
Does Increasing Natural Gas Demand in the Power Sector Pose a Threat of Congestion to the German Gas Grid? A Model-Coupling Approach
Energies 2019, 12(11), 2159; https://doi.org/10.3390/en12112159
Received: 3 May 2019 / Revised: 28 May 2019 / Accepted: 2 June 2019 / Published: 5 June 2019
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Abstract
This study aims to investigate the possible congestion in the German natural gas system, which may arise due to an increase in the gas consumption in the power sector in extreme weather events. For this purpose, we develop a two-stage approach to couple [...] Read more.
This study aims to investigate the possible congestion in the German natural gas system, which may arise due to an increase in the gas consumption in the power sector in extreme weather events. For this purpose, we develop a two-stage approach to couple an electricity model and a natural gas network model. In this approach, we model the electricity system in the first stage to determine the gas demand in the power sector. We then use the calculated gas demand to model gas networks in the second stage, where we deploy a newly developed gas network model. As a case study, we primarily evaluate our methodological approach by re-simulating the cold weather event in 2012, which is seen as an extreme situation for the gas grids, challenging the security of supply. Accordingly, we use our coupled model to investigate potential congestion in the natural gas networks for the year 2030, using a scenario of a sustainable energy transition, where an increase in the gas consumption in the power industry is likely. Results for 2030 show a 51% increase in yearly gas demand in the power industry compared to 2012. Further, the simulation results show a gas supply interruption in two nodes in 2012. In 2030, the same nodes may face an (partial) interruption of gas supply in cold winter days such as the 6th of February 2012. In this day, the load shedding in the natural gas networks can increase up to 19 GWhth in 2030. We also argue that the interrupted electricity production, due to local gas interruptions, can easily be compensated by other power plants. However, these local gas interruptions may endanger the local heat production. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
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Open AccessArticle
Eco-Efficient Resource Management in HPC Clusters through Computer Intelligence Techniques
Energies 2019, 12(11), 2129; https://doi.org/10.3390/en12112129
Received: 29 April 2019 / Revised: 26 May 2019 / Accepted: 28 May 2019 / Published: 3 June 2019
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Abstract
High Performance Computing Clusters (HPCCs) are common platforms for solving both up-to-date challenges and high-dimensional problems faced by IT service providers. Nonetheless, the use of HPCCs carries a substantial and growing economic and environmental impact, owing to the large amount of energy they [...] Read more.
High Performance Computing Clusters (HPCCs) are common platforms for solving both up-to-date challenges and high-dimensional problems faced by IT service providers. Nonetheless, the use of HPCCs carries a substantial and growing economic and environmental impact, owing to the large amount of energy they need to operate. In this paper, a two-stage holistic optimisation mechanism is proposed to manage HPCCs in an eco-efficiently manner. The first stage logically optimises the resources of the HPCC through reactive and proactive strategies, while the second stage optimises hardware allocation by leveraging a genetic fuzzy system tailored to the underlying equipment. The model finds optimal trade-offs among quality of service, direct/indirect operating costs, and environmental impact, through multiobjective evolutionary algorithms meeting the preferences of the administrator. Experimentation was done using both actual workloads from the Scientific Modelling Cluster of the University of Oviedo and synthetically-generated workloads, showing statistical evidence supporting the adoption of the new mechanism. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
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Open AccessArticle
HyFlow—A Hybrid Load Flow-Modelling Framework to Evaluate the Effects of Energy Storage and Sector Coupling on the Electrical Load Flows
Energies 2019, 12(5), 956; https://doi.org/10.3390/en12050956
Received: 1 February 2019 / Revised: 26 February 2019 / Accepted: 6 March 2019 / Published: 12 March 2019
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Abstract
HyFlow is a grid-based multi-energy system (MES) modelling framework. It aims to model the status quo of current energy systems, future scenarios with a high share of fluctuating energy sources or additional consumers like electric vehicles, and to compare solution strategies if certain [...] Read more.
HyFlow is a grid-based multi-energy system (MES) modelling framework. It aims to model the status quo of current energy systems, future scenarios with a high share of fluctuating energy sources or additional consumers like electric vehicles, and to compare solution strategies if certain parts of the infrastructure are congested. In order to evaluate the congestion limits and the feasibility and suitability of solution strategies (e.g., energy storage, sector coupling technologies, demand response (DR)), load flow calculations of all three main grid-bound energy carriers are implemented in one single modelling framework. In addition to the implemented load flow models, it allows the interaction of these grids with the use of hybrid elements. This measure enables a proper assessment of future scenarios, not only for the infrastructure of one energy carrier, but for the overall energy system. The calculation workflow of HyFlow, including the implemented load flow calculations, as well as the implementation of the flexibility options, is described in detail in the methodology section. To demonstrate the wide range of applicability of HyFlow with different spatial ranges, two case studies referring to current research problems are presented: a city and a region surrounding the mentioned city. The calculations for the mentioned case studies are performed for three levels. A “status quo” level, a “high-stress” level with added fluctuating energy sources and consumers, and an “improvement” level, where flexibility options are introduced to the system. The effect of the flexibility options on future energy grids is, therefore, analyzed and evaluated. A wide variety of evaluation criteria can be selected. For example, the maximum load of certain power lines, the self-sufficiency of the overall system, the total transport losses or the total energy consumption. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
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Open AccessArticle
Policy Implications of Power Exchanges on Operational Scheduling: Evaluating EUPHEMIA’s Market Products in Case of Greece
Energies 2018, 11(10), 2715; https://doi.org/10.3390/en11102715
Received: 14 August 2018 / Revised: 26 September 2018 / Accepted: 9 October 2018 / Published: 11 October 2018
Cited by 2 | PDF Full-text (2735 KB) | HTML Full-text | XML Full-text
Abstract
A vital component for the development of a functioning internal electricity market is the adoption by each European member state of the Pan-European Hybrid Electricity Market Integration (EUPHEMIA) for the day-ahead market solution. The consideration of the national power market’s characteristics enables more [...] Read more.
A vital component for the development of a functioning internal electricity market is the adoption by each European member state of the Pan-European Hybrid Electricity Market Integration (EUPHEMIA) for the day-ahead market solution. The consideration of the national power market’s characteristics enables more realistic market design towards the implementation of the so-called “Target Model”. This work considers a series of factors, including the EUPHEMIA order types, their use by market participants, the relative competitiveness of power generators, the impact of interconnected markets, the existence of market players with dominant positions, and the existence of specific regulations such as the minimum average variable cost restriction on offers by producers, as well as the strategy adopted by market participants. The main goal of this paper is to provide a comprehensive analysis on the adoption of EUPHEMIA’s algorithm in case of the Greek wholesale market, based on a relevant research project funded by the Joint Research Centre of the European Commission to support the Hellenic Regulatory Authority of Energy on its decision-making. The paper contributes to the relevant literature on the quantification of the impacts of the EUPHEMIA algorithm in the case of the Greek wholesale market, providing insights on the crucial aspects affecting realistic, market-based decision-making. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
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