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: closed (30 June 2020).

Special Issue Editors

Dr. Peter Markewitz
Website
Guest Editor
Institute of Techno-Economic Systems Analysis (IEK-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Interests: energy systems modelling; energy scenarios; greenhouse gas reduction strategies; technology assessment
Dr. Martin Robinius
Website
Guest Editor
Institute of Electrochemical Process Engineering (IEK-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Interests: energy systems analysis and assessment; sector coupling; greenhouse gas reduction strategies
Prof. Dr. Dominik Möst
Website
Guest Editor
Chair of energy economics, Technische Universität Dresden, D-01062 Dresden
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 2000 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 (20 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
How Strategic Behavior of Natural Gas Exporters Can Affect the Sectors of Electricity, Heating, and Emission Trading during the European Energy Transition
Energies 2020, 13(19), 5040; https://doi.org/10.3390/en13195040 - 24 Sep 2020
Abstract
The European demand for natural gas imports may change through the energy transition, which may affect natural gas exporters’ strategic behavior and consequently the natural gas prices. Changes in natural gas prices in turn influence the European energy sector in terms of gas [...] Read more.
The European demand for natural gas imports may change through the energy transition, which may affect natural gas exporters’ strategic behavior and consequently the natural gas prices. Changes in natural gas prices in turn influence the European energy sector in terms of gas consumption in the short-term and investments in the long-term. The present paper develops a large-scale partial equilibrium market model formulated as a mixed complementarity model (MCP) with conjectural variations. This model considers the global natural gas market and the European markets of electricity, heating, and emission trading in one equilibrium. We apply this model to investigate the long-term impact of market power by gas exporters on the mentioned energy-related markets on the horizon of 2050. The results of the study show that a decrease in the market power by gas exporters decreases natural gas prices, leading to cheaper electricity and CO2 prices in the mid-term. However, a very tight emission cap in 2050 can result in the reverse phenomenon. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Figure 1

Open AccessArticle
Integrating Methods and Empirical Findings from Social and Behavioural Sciences into Energy System Models—Motivation and Possible Approaches
Energies 2020, 13(18), 4951; https://doi.org/10.3390/en13184951 - 21 Sep 2020
Cited by 1
Abstract
The transformation of the energy system is a highly complex process involving many dimensions. Energy system models help to understand the process and to define either target systems or policy measures. Insights derived from the social sciences are not sufficiently represented in energy [...] Read more.
The transformation of the energy system is a highly complex process involving many dimensions. Energy system models help to understand the process and to define either target systems or policy measures. Insights derived from the social sciences are not sufficiently represented in energy system models, but address crucial aspects of the transformation process. It is, therefore, necessary to develop approaches to integrate results from social science studies into energy system models. Hence, as a result of an interdisciplinary discourse among energy system modellers, social scientists, psychologists, economists and political scientists, this article explains which aspects should be considered in the models, how the respective results can be collected and which aspects of integration into energy system models are conceivable to provide an overview for other modellers. As a result of the discourse, five facets are examined: Investment behaviour (market acceptance), user behaviour, local acceptance, technology innovation and socio-political acceptance. Finally, an approach is presented that introduces a compound of energy system models (with a focus on the macro and micro-perspective) as well as submodels on technology genesis and socio-political acceptance, which serves to gain a more fundamental knowledge of the transformation process. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Graphical abstract

Open AccessArticle
Numerical Studies on the Performance of the PCM Mesh-Finned Heat Sink Base on Thermal-Flow Multiphysics Coupling Simulation
Energies 2020, 13(18), 4658; https://doi.org/10.3390/en13184658 - 08 Sep 2020
Abstract
Operating temperature is an important parameter of thyristors to ensure the stable operation of power electronic devices. Thermal management technology is of great significance for improving the reliability of thyristors. In this study, the performance of a phase change material (PCM) mesh-finned heat [...] Read more.
Operating temperature is an important parameter of thyristors to ensure the stable operation of power electronic devices. Thermal management technology is of great significance for improving the reliability of thyristors. In this study, the performance of a phase change material (PCM) mesh-finned heat sink is investigated for the thermal management of thyristors. A multi-physical coupling model of the PCM mesh-finned heat sink is established to analyze the effects of different power losses, air velocities, heights of fins, and thickness of PCM on the thermal performance of the PCM heat sink. The influence of thermal and flow fields on PCM is considered in this model. Furthermore, the heat sink design is optimized to improve the thermal performance based on the calculation results of thermal network parameters. The results show that the power losses, the air velocity, the height of fins, and the thickness of PCM significantly affect the protection ability of the PCM heat sink. After optimizing the heat sink, the PCM heat sink provides 80 s protection time and 100 s recovery time. The PCM mesh-finned heat sink demonstrated good potential for the thermal management of thyristors. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Figure 1

Open AccessArticle
Adjustment of the Life Cycle Inventory in Life Cycle Assessment for the Flexible Integration into Energy Systems Analysis
Energies 2020, 13(17), 4437; https://doi.org/10.3390/en13174437 - 27 Aug 2020
Abstract
With an increasing share of renewable energy technologies in our energy systems, the integration of not only direct emission (from the use phase), but also the total life cycle emissions (including emissions during resource extraction, production, etc.) becomes more important in order to [...] Read more.
With an increasing share of renewable energy technologies in our energy systems, the integration of not only direct emission (from the use phase), but also the total life cycle emissions (including emissions during resource extraction, production, etc.) becomes more important in order to draw meaningful conclusions from Energy Systems Analysis (ESA). While the benefit of integrating Life Cycle Assessment (LCA) into ESA is acknowledged, methodologically sound integration lacks resonance in practice, partly because the dimension of the implications is not yet fully understood. This study proposes an easy-to-implement procedure for the integration of LCA results in ESA based on existing theoretical approaches. The need for a methodologically sound integration, including the avoidance of double counting of emissions, is demonstrated on the use case of Passivated Emitter and Rear Cell photovoltaic technology. The difference in Global Warming Potential of 19% between direct and LCA based emissions shows the significance for the integration of the total emissions into energy systems analysis and the potential double counting of 75% of the life cycle emissions for the use case supports the need for avoidance of double counting. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Figure 1

Open AccessArticle
Insights on Germany’s Future Congestion Management from a Multi-Model Approach
Energies 2020, 13(16), 4176; https://doi.org/10.3390/en13164176 - 12 Aug 2020
Cited by 1
Abstract
In Germany, the political decision to phase out nuclear and coal-fired power as well as delays in the planned grid extension are expected to intensify the current issue of high grid congestion volumes. In this article, we investigate two instruments which may help [...] Read more.
In Germany, the political decision to phase out nuclear and coal-fired power as well as delays in the planned grid extension are expected to intensify the current issue of high grid congestion volumes. In this article, we investigate two instruments which may help to cope with these challenges: market splitting and the introduction of a capacity mechanism. For this purpose, we carry out a comprehensive system analysis by jointly applying the demand side models FORECAST and eLOAD, the electricity market model PowerACE and the optimal power flow model ELMOD. While a German market splitting has a positive short-term impact on the congestion volumes, we find the optimal zonal delimination determined for 2020 to become outdated by 2035 resulting in new grid bottlenecks. Yet, readjusting the zonal configuration would lower the ability of the market split to provide regional investment incentives. Introducing a capacity mechanism with a congestion indicator allows allocating new power plants in regions with higher electricity demand. Consequently, we find the required congestion management to be substantially reduced in this setting. However, given the large amount of design parameters, any capacity mechanism needs to be carefully planned before its introduction to avoid new inefficiences on the market side. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Figure 1

Open AccessArticle
Dynamic Modeling of a Decarbonized District Heating System with CHP Plants in Electricity-Based Mode of Operation
Energies 2020, 13(16), 4134; https://doi.org/10.3390/en13164134 - 10 Aug 2020
Cited by 2
Abstract
The targets of global CO2 reduction outline the importance of decarbonizing the heating and cooling sector, which consume half of the final energy in the European Union (EU). Consequently, heating network operators must adapt to growing requirements for carbon neutrality. Energy system [...] Read more.
The targets of global CO2 reduction outline the importance of decarbonizing the heating and cooling sector, which consume half of the final energy in the European Union (EU). Consequently, heating network operators must adapt to growing requirements for carbon neutrality. Energy system modeling allows the simulation of individual network compositions and regulations, while considering electricity market signals for a more efficient plant operation. The district heating model, programmed for this work, covers a measured heat demand with peak load boiler, biomass-fired combined heat and power (CHP) plant, and biomass heating plant supply. The CHP plant reacts to electricity prices of the European Power Exchange market and uses a long-term heat storage to decouple heat and electricity production. This paper presents the results of three annual simulation scenarios aimed at carbon neutrality for the analyzed heating network. Two scenarios achieve a climate-neutral system by replacing the peak load boiler generation. The exclusive storage capacity expansion in the first scenario does not lead to the intended decarbonization. The second scenario increases the output of the CHP plant, while the third simulation uses the biomass heating plant supply. This additional heat producer enables a significant reduction in storage capacity and a higher CHP plant participation in the considered electricity market. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Figure 1

Open AccessArticle
Identification of the Efficiency Gap by Coupling a Fundamental Electricity Market Model and an Agent-Based Simulation Model
Energies 2020, 13(15), 3920; https://doi.org/10.3390/en13153920 - 31 Jul 2020
Cited by 1
Abstract
A reliable and cost-effective electricity system transition requires both the identification of optimal target states and the definition of political and regulatory frameworks that enable these target states to be achieved. Fundamental optimization models are frequently used for the determination of cost-optimal system [...] Read more.
A reliable and cost-effective electricity system transition requires both the identification of optimal target states and the definition of political and regulatory frameworks that enable these target states to be achieved. Fundamental optimization models are frequently used for the determination of cost-optimal system configurations. They represent a normative approach and typically assume markets with perfect competition. However, it is well known that real systems do not behave in such an optimal way, as decision-makers do not have perfect information at their disposal and real market actors do not take decisions in a purely rational way. These deficiencies lead to increased costs or missed targets, often referred to as an “efficiency gap”. For making rational political decisions, it might be valuable to know which factors influence this efficiency gap and to what extent. In this paper, we identify and quantify this gap by soft-linking a fundamental electricity market model and an agent-based simulation model, which allows the consideration of these effects. In order to distinguish between model-inherent differences and non-ideal market behavior, a rigorous harmonization of the models was conducted first. The results of the comparative analysis show that the efficiency gap increases with higher renewable energy shares and that information deficits and policy instruments affect operational decisions of power market participants and resulting overall costs significantly. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Graphical abstract

Open AccessArticle
Development of an Integrated Simulation Model for Load and Mobility Profiles of Private Households
Energies 2020, 13(15), 3843; https://doi.org/10.3390/en13153843 - 27 Jul 2020
Cited by 2
Abstract
The electrification of the mobility and heating sectors will significantly change the electrical behavior of households in the future. To investigate this behavior, it is important to include the heating and mobility sectors in load profile models. Existing models do not sufficiently consider [...] Read more.
The electrification of the mobility and heating sectors will significantly change the electrical behavior of households in the future. To investigate this behavior, it is important to include the heating and mobility sectors in load profile models. Existing models do not sufficiently consider these sectors. Therefore, this work aims to develop an integrated, consistent model for the electrical and thermal load of private households and their mobility behavior. The model needs to generate regionally distinct profiles depending on the building, household and resident type and should be valid for Germany. Based on a bottom-up approach, a model consisting of four components is developed. In an activity model based on a modified Markov chain process, persons are assigned to activities. The activities are then allocated to devices in the electrical and thermal models. A mobility model assigns distances to the journey activities. The results of the simulation to validate the model shows an average annual energy consumption per household of 2751 kWh and a shape of the average load profile, both in good agreement with the reference. Furthermore, the temporal distribution of the vehicles to the locations is in accordance with the reference but the annual mileage is slightly underestimated with 10,730 km. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Graphical abstract

Open AccessArticle
Comparing Power-System and User-Oriented Battery Electric Vehicle Charging Representation and Its Implications on Energy System Modeling
Energies 2020, 13(5), 1093; https://doi.org/10.3390/en13051093 - 02 Mar 2020
Cited by 1
Abstract
Battery electric vehicles (BEV) provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection [...] Read more.
Battery electric vehicles (BEV) provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging and connection decisions significantly decreases the load shifting potential of controlled charging. The analysis of marginal values of equations and variables of the optimization problem yields valuable insights on the importance of specific constraints and optimization variables. Assumptions on fleet battery availability and a detailed representation of fast charging are found to have a strong impact on wind curtailment, renewable energy feed-in, and required gas power plant flexibility. A representation of fleet connection to the grid in high temporal detail is less important. Peak load can be reduced by 5% and 3% in both scenarios, respectively. Shifted load is robust across sensitivity analyses while other model results such as curtailment are more sensitive to factors such as underlying data years. Analyzing the importance of increased BEV fleet battery availability for power systems with different weather and electricity demand characteristics should be further scrutinized. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Graphical abstract

Open AccessArticle
Development of Scenarios for a Multi-Model System Analysis Based on the Example of a Cellular Energy System
Energies 2020, 13(4), 773; https://doi.org/10.3390/en13040773 - 11 Feb 2020
Cited by 1
Abstract
Scenario analysis combined with system and market modelling is a well-established method to evaluate technological and societal developments and their impacts on future energy pathways. This paper presents a process-oriented method for developing consistent energy scenarios using multiple energy system models. Its added [...] Read more.
Scenario analysis combined with system and market modelling is a well-established method to evaluate technological and societal developments and their impacts on future energy pathways. This paper presents a process-oriented method for developing consistent energy scenarios using multiple energy system models. Its added value is that the developed energy scenarios are consistent in a multi-model environment and practicable for a broader target group from scientists to practitioners. The scenarios consist of comprehensive storylines and systematically defined quantitative parameters. Following a step-by-step process, a condensed set of overlapping descriptors is generated and used to define the scenarios in a consistent parameter matrix. The set of descriptors allow consistent and comparable outputs independent of model-specific characteristics. The corresponding quantitative parameters can be used by diverse energy system tools. Using multiple models, a team of researchers can explore questions from differing points of view. In an example study, we apply the method to develop scenarios in the context of a cellular energy system. This approach enables the development of scenarios that provide a consistent basis for both stakeholder discourse and multi-model system analysis. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Graphical abstract

Open AccessArticle
On the Way to a Sustainable European Energy System: Setting Up an Integrated Assessment Toolbox with TIMES PanEU as the Key Component
Energies 2020, 13(3), 707; https://doi.org/10.3390/en13030707 - 06 Feb 2020
Cited by 3
Abstract
The required decarbonization of the energy system is a complex task, with ambitious targets under the Paris Agreement, and related policy analysis should consider possible impacts on the economy and society. By coupling the energy system model TIMES PanEU with the impact assessment [...] Read more.
The required decarbonization of the energy system is a complex task, with ambitious targets under the Paris Agreement, and related policy analysis should consider possible impacts on the economy and society. By coupling the energy system model TIMES PanEU with the impact assessment model EcoSense and the computable general equilibrium model NEWAGE, we present an integrated assessment toolbox for the European energy system capable of internalizing health damage costs of air pollution while simultaneously accounting for demand changes in energy services caused by economic feedback loops. The effects of each coupling step are investigated in a scenario analysis. Additionally, CO2 decomposition analysis is applied to identify the main drivers to decarbonize the energy system. Our results show that integrating externalities forces the system to take early action, which provides benefits on the societal level. Including macro-economic variables has a negative effect on energy service demands and generally reduces the need for structural change, which are still the main drivers of decarbonization. The tighter the models are coupled, the fewer the iterations needed and the lower the CO2 prices resulting from the carbon cap and trade system. In this aspect, an integrated view can provide valuable insights to determine efficient and effective decarbonization paths. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Figure 1

Open AccessArticle
LAEND: A Model for Multi-Objective Investment Optimisation of Residential Quarters Considering Costs and Environmental Impacts
Energies 2020, 13(3), 614; https://doi.org/10.3390/en13030614 - 01 Feb 2020
Cited by 1
Abstract
Renewable energy systems are especially challenging both in terms of planning and operation. Energy system models that take into account not only the costs but also a wide range of environmental impacts support holistic planning. In this way, burden-shifting caused by greenhouse gas [...] Read more.
Renewable energy systems are especially challenging both in terms of planning and operation. Energy system models that take into account not only the costs but also a wide range of environmental impacts support holistic planning. In this way, burden-shifting caused by greenhouse gas mitigation can be identified and minimised at an early stage. The Life cycle Assessment based ENergy Decision support tool LAEND combines a multi-criteria optimising tool for energy system modelling and an integrated environmental assessment for the analysis of decentral systems. By a single or multi-objective optimisation, considering costs, environmental impact indicators as well as weighted impact indicator sets, the model enables the determination of optimal investment planning and dispatch of the analysed energy system. The application of LAEND to an exemplary residential quarter shows the benefit of the model regarding the identification of conflicting goals and of a system that compensates for the different objectives. The observed shift of environmental impacts from the use phase to the production phase of the renewable electricity generators points further to the importance of the integration of the entire life cycle. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Graphical abstract

Open AccessArticle
Cost Uncertainties in Energy System Optimization Models: A Quadratic Programming Approach for Avoiding Penny Switching Effects
Energies 2019, 12(20), 4006; https://doi.org/10.3390/en12204006 - 21 Oct 2019
Cited by 2
Abstract
Designing the future energy supply in accordance with ambitious climate change mitigation goals is a challenging issue. Common tools for planning and calculating future investments in renewable and sustainable technologies are often linear energy system models based on cost optimization. However, input data [...] Read more.
Designing the future energy supply in accordance with ambitious climate change mitigation goals is a challenging issue. Common tools for planning and calculating future investments in renewable and sustainable technologies are often linear energy system models based on cost optimization. However, input data and the underlying assumptions of future developments are subject to uncertainties that negatively affect the robustness of results. This paper introduces a quadratic programming approach to modifying linear, bottom-up energy system optimization models to take cost uncertainties into account. This is accomplished by implementing specific investment costs as a function of the installed capacity of each technology. In contrast to established approaches such as stochastic programming or Monte Carlo simulation, the computation time of the quadratic programming approach is only slightly higher than that of linear programming. The model’s outcomes were found to show a wider range as well as a more robust allocation of the considered technologies than the linear model equivalent. Full article
(This article belongs to the Special Issue Model Coupling and Energy Systems)
Show Figures

Figure 1

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 - 19 Jun 2019
Cited by 1
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)
Show Figures

Figure 1

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 - 13 Jun 2019
Cited by 7
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)
Show Figures

Figure 1

Open AccessArticle
A Comparative Study of Methods for Measurement of Energy of Computing
Energies 2019, 12(11), 2204; https://doi.org/10.3390/en12112204 - 10 Jun 2019
Cited by 11
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)
Show Figures

Figure 1

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 - 05 Jun 2019
Cited by 3
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)
Show Figures

Figure 1

Open AccessArticle
Eco-Efficient Resource Management in HPC Clusters through Computer Intelligence Techniques
Energies 2019, 12(11), 2129; https://doi.org/10.3390/en12112129 - 03 Jun 2019
Cited by 1
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)
Show Figures

Figure 1

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 - 12 Mar 2019
Cited by 14
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)
Show Figures

Figure 1

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 - 11 Oct 2018
Cited by 13
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)
Show Figures

Figure 1

Back to TopTop