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This paper provides a comprehensive overview of approaches to the determination of isocontours and isosurfaces from given data sets. Different algorithms are reported in the literature for this purpose, which originate from various application areas, such as computer graphics or medical imaging procedures. In all these applications, the challenge is to extract surfaces with a specific isovalue from a given characteristic, so called isosurfaces. These different application areas have given rise to solution approaches that all solve the problem of isocontouring in their own way. Based on the literature, the following four dominant methods can be identified: the marching cubes algorithms, the tessellation-based algorithms, the surface nets algorithms and the ray tracing algorithms. With regard to their application, it can be seen that the methods are mainly used in the fields of medical imaging, computer graphics and the visualization of simulation results. In our work, we provide a broad and compact overview of the common methods that are currently used in terms of isocontouring with respect to certain criteria and their individual limitations. In this context, we discuss the individual methods and identify possible future research directions in the field of isocontouring.
Lithium-ion batteries exhibit slow voltage dynamics on the minute time scale that are usually associated with transport processes. We present a novel modelling approach toward these dynamics by combining physical and data-driven models into a Grey-box model. We use neural networks, in particular neural ordinary differential equations. The physical structure of the Grey-box model is borrowed from the Fickian diffusion law, where the transport domain is discretized using finite volumes. Within this physical structure, unknown parameters (diffusion coefficient, diffusion length, discretization) and dependencies (state of charge, lithium concentration) are replaced by neural networks and learnable parameters. We perform model-to-model comparisons, using as training data (a) a Fickian diffusion process, (b) a Warburg element, and (c) a resistor-capacitor circuit. Voltage dynamics during constant-current operation and pulse tests as well as electrochemical impedance spectra are simulated. The slow dynamics of all three physical models in the order of ten to 30 min are well captured by the Grey-box model, demonstrating the flexibility of the present approach.
Nowadays decarbonisation of the energy system is one of the main concerns for most governments. Renewable energy technologies, such as rooftop photovoltaic systems and home battery storage systems, are changing the energy system to be more decentralised. As a consequence, new ways of energy business models are emerging, e.g., peer-to-peer energy trading. This new concept provides an online marketplace where direct energy exchange can occur between its participants. The purpose of this study is to conduct a content analysis of the existing literature, ongoing research projects, and companies related to peer-to-peer energy trading. From this review, a summary of the most important aspects and journal papers is assessed, discussed, and classified. It was found that the different energy market types were named in various ways and a proposal for standard language for the several peer-to-peer market types and the different actors involved is suggested. Additionally, by grouping the most important attributes from peer-to-peer energy trading projects, an assessment of the entry barrier and scalability potential is performed by using a characterisation matrix.
The significant market growth of stationary electrical energy storage systems both for private and commercial applications has raised the question of battery lifetime under practical operation conditions. Here, we present a study of two 8 kWh lithium-ion battery (LIB) systems, each equipped with 14 lithium iron phosphate/graphite (LFP) single cells in different cell configurations. One system was based on a standard configuration with cells connected in series, including a cell-balancing system and a 48 V inverter. The other system featured a novel configuration of two stacks with a parallel connection of seven cells each, no cell-balancing system, and a 4 V inverter. The two systems were operated as part of a microgrid both in continuous cycling mode between 30% and 100% state of charge, and in solar-storage mode with day–night cycling. The aging characteristics in terms of capacity loss and internal resistance change in the cells were determined by disassembling the systems for regular checkups and characterizing the individual cells under well-defined laboratory conditions. As a main result, the two systems showed cell-averaged capacity losses of 18.6% and 21.4% for the serial and parallel configurations, respectively, after 2.5 years of operation with 810 (serial operation) and 881 (parallel operation) cumulated equivalent full cycles. This is significantly higher than the aging of a reference single cell cycled under laboratory conditions at 20 °C, which showed a capacity loss of only 10% after 1000 continuous full cycles.
Photovoltaic-heat pump (PV-HP) combinations with battery and energy management systems are becoming increasingly popular due to their ability to increase the autarchy and utilization of self-generated PV electricity. This trend is driven by the ongoing electrification of the heating sector and the growing disparity between growing electricity costs and reducing feed-in tariffs in Germany. Smart control strategies can be employed to control and optimize the heat pump operation to achieve higher self-consumption of PV electricity. This work presents the evaluation results of a smart-grid ready controlled PV-HP-battery system in a single-family household in Germany, using 1-minute-high-resolution field measurement data. Within 12 months evaluation period, a self-consumption of 43% was determined. The solar fraction of the HP amounts to 36%, enabled also due to higher set temperatures for space heating and domestic hot water production. Accordingly, the SPF decreases by 4.0% the space heating and by 5.7% in the domestic hot water mode. The combined seasonal performance factor for the heat pump system increases from 4.2 to 6.7, when only considering the electricity taken from the grid and disregarding the locally generated electricity supplied from photovoltaic and battery units.
There is a strong interaction between the urban atmospheric canopy layer and the building energy balance. The urban atmospheric conditions affect the heat transfer through exterior walls, the long-wave heat transfer between the building surfaces and the surroundings, the short-wave solar heat gains, and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban microclimatic conditions. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat; this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban microclimate with a temporally lagged and damped temperature fluctuation. We developed a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier's equation and implemented this model into the PALM model.
This paper shows the results of an in-depth techno-economic analysis of the public transport sector in a small to midsize city and its surrounding area. Public battery-electric and hydrogen fuel cell buses are comparatively evaluated by means of a total cost of ownership (TCO) model building on historical data and a projection of market prices. Additionally, a structural analysis of the public transport system of a specific city is performed, assessing best fitting bus lines for the use of electric or hydrogen busses, which is supported by a brief acceptance evaluation of the local citizens. The TCO results for electric buses show a strong cost decrease until the year 2030, reaching 23.5% lower TCOs compared to the conventional diesel bus. The optimal electric bus charging system will be the opportunity (pantograph) charging infrastructure. However, the opportunity charging method is applicable under the assumption that several buses share the same station and there is a “hotspot” where as many as possible bus lines converge. In the case of electric buses for the year 2020, the parameter which influenced the most on the TCO was the battery cost, opposite to the year 2030 in where the bus body cost and fuel cost parameters are the ones that dominate the TCO, due to the learning rate of the batteries. For H2 buses, finding a hotspot is not crucial because they have a similar range to the diesel ones as well as a similar refueling time. H2 buses until 2030 still have 15.4% higher TCO than the diesel bus system. Considering the benefits of a hypothetical scaling-up effect of hydrogen infrastructures in the region, the hydrogen cost could drop to 5 €/kg. In this case, the overall TCO of the hydrogen solution would drop to a slightly lower TCO than the diesel solution in 2030. Therefore, hydrogen buses can be competitive in small to midsize cities, even with limited routes. For hydrogen buses, the bus body and fuel cost make up a large part of the TCO. Reducing the fuel cost will be an important aspect to reduce the total TCO of the hydrogen bus.
Simulation based studies for operational energy system analysis play a significant role in evaluation of various new age technologies and concepts in the energy grid. Various modelling approaches already exist and in this original paper, four models representing these approaches are compared in two real-world hybrid energy system scenarios. The models, namely TransiEnt, µGRiDS, and OpSim (including pandaprosumer and mosaic) are classified into component-oriented or system-oriented approaches as deduced from the literature research. The methodology section describes their differences under standard conditions and the necessary parameterization for the purpose of creating a framework facilitating a closest possible comparison. A novel methodology for scenario generation is also explained. The results help to quantify primary differences in these approaches that are also identified in literature and qualify the influence of the accuracy of the models for application in a system-wide analysis. It is shown that a simplified model may be sufficient for the system-oriented approach especially when the objective is an optimization-based control or planning. However, from a field level operational point of view, the differences in the time series signify the importance of the component-oriented approaches.
The lifetime of a battery is affected by various aging processes happening at the electrode scale and causing capacity and power fade over time. Two of the most critical mechanisms are the deposition of metallic lithium (plating) and the loss of lithium inventory to the solid electrolyte interphase (SEI). These side reactions compete with reversible lithium intercalation at the graphite anode. Here we present a comprehensive physicochemical pseudo-3D aging model for a lithium-ion battery cell, which includes electrochemical reactions for SEI formation on graphite anode, lithium plating, and SEI formation on plated lithium. The thermodynamics of the aging reactions are modeled depending on temperature and ion concentration, and the reactions kinetics are described with an Arrhenius-type rate law. The model includes also the positive feedback of plating on SEI growth, with the presence of plated lithium leading to a higher SEI formation rate compared to the values obtained in its absence at the same operating conditions. The model is thus able to describe cell aging over a wide range of temperatures and C-rates. In particular, it allows to quantify capacity loss due to cycling (here in % per year) as function of operating conditions. This allows the visualization of aging colormaps as function of both temperature and C-rate and the identification of critical operation conditions, a fundamental step for a comprehensive understanding of batteries performance and behavior. For example, the model predicts that at the harshest conditions (< –5 °C, > 3 C), aging is reduced compared to most critical conditions (around 0–5 °C) because the cell cannot be fully charged.
The increasing number of prosumers and the accompanying greater use of decentralised energy resources (DERs) bring new opportunities and challenges for the traditional electricity systems and the electricity markets. Microgrids, virtual power plants (VPPs), peer-to-peer (P2P) trading and federated power plants (FPPs) propose different schemes for prosumer coordination and have the potential of becoming the new paradigm of electricity market and power system operation. This paper proposes a P2P trading scheme for energy communities that negotiates power flows between participating prosumers with insufficient renewable power supply and prosumers with surplus supply in such a way that the community welfare is maximized while avoiding critical grid conditions. For this purpose, the proposed scheme is based on an Optimal Power Flow (OPF) problem with a Multi-Bilateral Economic Dispatch (MBED) formulation as an objective function. The solution is realized in a fully decentralized manner on the basis of the Relaxed Consensus + Innovations (RCI) algorithm. Network security is ensured by a tariff-based system organized by a network agent that makes use of product differentiation capabilities of the RCI algorithm. It is found that the proposed mechanism accurately finds and prevents hazardous network operations, such as over-voltage in grid buses, while successfully providing economic value to prosumers’ renewable generation within the scope of a P2P, free market.
It is considered necessary to implement advanced controllers such as model predictive control (MPC) to utilize the technical flexibility of a building polygeneration system to support the rapidly expanding renewable electricity grid. These can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints, amongst other features. One of the main issues identified in the literature regarding deploying these controllers is the lack of experimental demonstrations using standard components and communication protocols. In this original work, the economic-MPC-based optimal scheduling of a real-world heat pump-based building energy plant is demonstrated, and its performance is evaluated against two conventional controllers. The demonstration includes the steps to integrate an optimization-based supervisory controller into a typical building automation and control system with off-the-shelf HVAC components and usage of state-of-art algorithms to solve a mixed integer quadratic problem. Technological benefits in terms of fewer constraint violations and a hardware-friendly operation with MPC were identified. Additionally, a strong dependency of the economic benefits on the type of load profile, system design and controller parameters was also identified. Future work for the quantification of these benefits, the application of machine learning algorithms, and the study of forecast deviations is also proposed.
This article presents the development, parameterization, and experimental validation of a pseudo-three-dimensional (P3D) multiphysics aging model of a 500 mAh high-energy lithium-ion pouch cell with graphite negative electrode and lithium nickel manganese cobalt oxide (NMC) positive electrode. This model includes electrochemical reactions for solid electrolyte interphase (SEI) formation at the graphite negative electrode, lithium plating, and SEI formation on plated lithium. The thermodynamics of the aging reactions are modeled depending on temperature and ion concentration and the reactions kinetics are described with an Arrhenius-type rate law. Good agreement of model predictions with galvanostatic charge/discharge measurements and electrochemical impedance spectroscopy is observed over a wide range of operating conditions. The model allows to quantify capacity loss due to cycling near beginning-of-life as function of operating conditions and the visualization of aging colormaps as function of both temperature and C-rate (0.05 to 2 C charge and discharge, −20 °C to 60 °C). The model predictions are also qualitatively verified through voltage relaxation, cell expansion and cell cycling measurements. Based on this full model, six different aging indicators for determination of the limits of fast charging are derived from post-processing simulations of a reduced, pseudo-two-dimensional isothermal model without aging mechanisms. The most successful aging indicator, compared to results from the full model, is based on combined lithium plating and SEI kinetics calculated from battery states available in the reduced model. This methodology is applicable to standard pseudo-two-dimensional models available today both commercially and as open source.
This article presents a comparative experimental study of the electrical, structural and chemical properties of large‐format, 180 Ah prismatic lithium iron phosphate (LFP)/graphite lithium‐ion battery cells from two different manufacturers. These cells are particularly used in the field of stationary energy storage such as home‐storage systems. The investigations include (1) cell‐to‐cell performance assessment, for which a total of 28 cells was tested from each manufacturer, (2) electrical charge/discharge characteristics at different currents and ambient temperatures, (3) internal cell geometries, components, and weight analysis after cell opening, (4) microstructural analysis of the electrodes via light microscopy and scanning electron microscopy, (5) chemical analysis of the electrode materials using energy‐dispersive X‐ray spectroscopy, and (6) mathematical analysis of the electrode balances. The combined results give a detailed and comparative insight into the cell characteristics, providing essential information needed for system integration. The study also provides complete and self‐consistent parameter sets for the use in cells models needed for performance prediction or state diagnosis.
Electrochemical pressure impedance spectroscopy (EPIS) has recently been developed as a potential diagnosis tool for polymer electrolyte membrane fuel cells (PEMFC). It is based on analyzing the frequency response of the cell voltage with respect to an excitation of the gas-phase pressure. We present here a combined modeling and experimental study of EPIS. A pseudo-twodimensional PEMFC model was parameterized to a 100 cm2 laboratory cell installed in its test bench, and used to reproduce steady-state cell polarization and electrochemical impedance spectra (EIS). Pressure impedance spectra were obtained both in experiment and simulation by applying a harmonic pressure excitation at the cathode outlet. The model shows good agreement with experimental data for current densities ⩽ 0.4 A cm−2. Here it allows a further simulative analysis of observed EPIS features, including the magnitude and shape of spectra. Key findings include a strong influence of the humidifier gas volume on EPIS and a substantial increase in oxygen partial pressure oscillations towards the channel outlet at the resonance frequency. At current densities ⩾ 0.8 A cm−2 the experimental EIS and EPIS data cannot be fully reproduced. This deviation might be associated with the formation and transport of liquid water, which is not included in the model.
Electrochemical pressure impedance spectroscopy (EPIS) is an emerging tool for the diagnosis of polymer electrolyte membrane fuel cells (PEMFC). It is based on analyzing the frequency response of the cell voltage with respect to an excitation of the gas-phase pressure. Several experimental studies in the past decade have shown the complexity of EPIS signals, and so far there is no agreement on the interpretation of EPIS features. The present study contributes to shed light into the physicochemical origin of EPIS features, by using a combination of pseudo-two-dimensional modeling and analytical interpretation. Using static simulations, the contributions of cathode equilibrium potential, cathode overpotential, and membrane resistance on the quasi-static EPIS response are quantified. Using model reduction, the EPIS responses of individual dynamic processes are predicted and compared to the response of the full model. We show that the EPIS signal of the PEMFC studied here is dominated by the humidifier. The signal is further analyzed by using transfer functions between various internal cell states and the outlet pressure excitation. We show that the EPIS response of the humidifier is caused by an oscillating oxygen molar fraction due to an oscillating mass flow rate.
We present an electrochemical model of a lithium iron phosphate/graphite (LFP/C6) cell that includes combined aging mechanisms: (i) Electrochemical formation of the solid electrolyte interphase (SEI) at the anode, leading to loss of lithium inventory, (ii) breaking of the SEI due to volume changes of the graphite particles, causing accelerated SEI growth, and (iii) loss of active material due to of loss percolation of the liquid electrolyte resulting from electrode dry-out. The latter requires the introduction of an activity-saturation relationship. A time-upscaling methodology is developed that allows to simulate large time spans (thousands of operating hours). The combined modeling and simulation framework is able to predict calendaric and cyclic aging up to the end of life of the battery cells. The aging parameters are adjusted to match literature calendaric and cyclic aging experiments, resulting in quantitative agreement of simulated nonlinear capacity loss with experimental data. The model predicts and provides an interpretation for the dependence of capacity loss on temperature, cycling depth, and average SOC. The introduction of a percolation threshold in the activity-saturation relationship allows to capture the strong nonlinearity of aging toward end of life (“sudden death”).
This paper presents a framework for numerical building validation enhancement based on detailed building specifications from in-situ measurements and evidence-based validation assessment undertaken on a detached sustainable lightweight building in a semi-arid climate. The validation process has been undergone in a set of controlled experiments – a free-float period, and steady-state internal temperatures. The validation was conducted for a complete year with a 1-min time step for the hourly indoor temperature and the variable refrigerant flow (VRF) energy consumption. The initial baseline model was improved by three series of validation steps per three different field measurements including thermal transmittance, glazing thermal and optical properties, and airtightness. Then, the accurate and validated model was used for building energy efficiency assessment in 12 regions of Morocco. This study aims to assess the effect of accurate building characteristics values on the numerical model enhancement. The initial CV(RMSE) and NMBE have improved respectively from 14.58 % and −11.23 %–7.85 % and 1.86 % for the indoor temperature. Besides, from 31.17 % to 14.37 %–20.57 % and 9.77 % for energy consumption. The findings demonstrate that the lightweight construction with the use of a variable refrigerant flow system could be energy efficient in the southern regions of Morocco.
This work presents the results of experimental operation of a solar-driven climate system using mixed-integer nonlinear model predictive control (MPC). The system is installed in a university building and consists of two solar thermal collector fields, an adsorption cooling machine with different operation modes, a stratified hot water storage with multiple inlets and outlets as well as a cold water storage. The system and the applied modeling approach is described and a parallelized algorithm for mixed-integer nonlinear MPC and a corresponding implementation for the system are presented. Finally, we show and discuss the results of experimental operation of the system and highlight the advantages of the mixed-integer nonlinear MPC application.
A balcony photovoltaic (PV) system, also known as a micro-PV system, is a small PV system consisting of one or two solar modules with an output of 100–600 Wp and a corresponding inverter that uses standard plugs to feed the renewable energy into the house grid. In the present study we demonstrate the integration of a commercial lithium-ion battery into a commercial micro-PV system. We firstly show simulations over one year with one second time resolution which we use to assess the influence of battery and PV size on self-consumption, self-sufficiency and the annual cost savings. We then develop and operate experimental setups using two different architectures for integrating the battery into the micro-PV system. In the passive hybrid architecture, the battery is in parallel electrical connection to the PV module. In the active hybrid architecture, an additional DC-DC converter is used. Both architectures include measures to avoid maximum power point tracking of the battery by the module inverter. Resulting PV/battery/inverter systems with 300 Wp PV and 555 Wh battery were tested in continuous operation over three days under real solar irradiance conditions. Both architectures were able to maintain stable operation and demonstrate the shift of PV energy from the day into the night. System efficiencies were observed comparable to a reference system without battery. This study therefore demonstrates the feasibility of both active and passive coupling architectures.
To achieve its climate goals, the German industry has to undergo a transformation toward renewable energies. To analyze this transformation in energy system models, the industry’s electricity demands have to be provided in a high temporal and sectoral resolution, which, to date, is not the case due to a lack of open-source data. In this paper, a methodology for the generation of synthetic electricity load profiles is described; it was applied to 11 industry types. The modeling was based on the normalized daily load profiles for eight electrical end-use applications. The profiles were then further refined by using the mechanical processes of different branches. Finally, a fluctuation was applied to the profiles as a stochastic attribute. A quantitative RMSE comparison between real and synthetic load profiles showed that the developed method is especially accurate for the representation of loads from three-shift industrial plants. A procedure of how to apply the synthetic load profiles to a regional distribution of the industry sector completes the methodology.
This article presents the development, parameterization, and experimental validation of a pseudo-three-dimensional (P3D) multiphysics model of a 350 mAh high-power lithium-ion pouch cell with graphite anode and lithium cobalt oxide/lithium nickel cobalt aluminum oxide (LCO/NCA) blend cathode. The model describes transport processes on three different scales: Heat transport on the macroscopic scale (cell), mass and charge transport on the mesoscopic scale (electrode pair), and mass transport on the microscopic scale (active material particles). A generalized description of electrochemistry in blend electrodes is developed, using the open-source software Cantera for calculating species source terms. Very good agreement of model predictions with galvanostatic charge/discharge measurements, electrochemical impedance spectroscopy, and surface temperature measurements is observed over a wide range of operating conditions (0.05C to 10C charge and discharge, 5°C to 35°C). The behavior of internal states (concentrations, potentials, temperatures) is discussed. The blend materials show a complex behavior with both intra-particle and inter-particle non-equilibria during cycling.
Lithium‐ion battery cells are multiscale and multiphysics systems. Design and material parameters influence the macroscopically observable cell performance in a complex and nonlinear way. Herein, the development and application of three methodologies for model‐based interpretation and visualization of these influences are presented: 1) deconvolution of overpotential contributions, including ohmic, concentration, and activation overpotentials of the various cell components; 2) partial electrochemical impedance spectroscopy, allowing a direct visualization of the origin of different impedance features; and 3) sensitivity analyses, allowing a systematic assessment of the influence of cell parameters on capacity, internal resistance, and impedance. The methods are applied to a previously developed and validated pseudo‐3D model of a high‐power lithium‐ion pouch cell. The cell features a blend cathode. The two blend components show strong coupling, which can be observed and interpreted using the results of overpotential deconvolution, partial impedance spectroscopy, and sensitivity analysis. The presented methods are useful tools for model‐supported lithium‐ion cell research and development.
Lithium-ion batteries show a complex thermo-electrochemical performance and aging behavior. This paper presents a modeling and simulation framework that is able to describe both multi-scale heat and mass transport and complex electrochemical reaction mechanisms. The transport model is based on a 1D + 1D + 1D (pseudo-3D or P3D) multi-scale approach for intra-particle lithium diffusion, electrode-pair mass and charge transport, and cell-level heat transport, coupled via boundary conditions and homogenization approaches. The electrochemistry model is based on the use of the open-source chemical kinetics code CANTERA, allowing flexible multi-phase electrochemistry to describe both main and side reactions such as SEI formation. A model of gas-phase pressure buildup inside the cell upon aging is added. We parameterize the model to reflect the performance and aging behavior of a lithium iron phosphate (LiFePO4, LFP)/graphite (LiC6) 26650 battery cell. Performance (0.1–10 C discharge/charge at 25, 40 and 60°C) and calendaric aging experimental data (500 days at 30°C and 45°C and different SOC) from literature can be successfully reproduced. The predicted internal cell states (concentrations, potential, temperature, pressure, internal resistances) are shown and discussed. The model is able to capture the nonlinear feedback between performance, aging, and temperature.
This paper will introduce the open-source model MyPyPSA-Ger, a myopic optimization model developed to represent the German energy system with a detailed mapping of the electricity sector, on a highly disaggregated level, spatially and temporally, with regional differences and investment limitations. Furthermore, this paper will give new outlooks on the German federal government 2050 emissions goals of the electricity sector to become greenhouse gas neutral by proposing new CO2 allowance strategies. Moreover, the regional differences in Germany will be discussed, their role and impact on the energy transition, and which regions and states will drive the renewable energy utilization forward.
Following a scenario-based analysis, the results point out the major keystones of the energy transition path from 2020 to 2050. Solar, onshore wind, and gas-fired power plants will play a fundamental role in the future electricity systems. Biomass, run of river, and offshore wind technologies will be utilized in the system as base-load generation technologies. Solar and onshore wind will be installed almost everywhere in Germany. However, due to the nature of Germany’s weather and geographical features, the southern and northern regions will play a more important role in the energy transition.
Higher CO2 allowance costs will help achieve the 1.5-degree-target of the electricity system and will allow for a rapid transition. Moreover, the more expensive, and the earlier the CO2 tax is applied to the system, the less it will cost for the energy transition, and the more emissions will be saved throughout the transition period. An earlier phase-out of coal power plants is not necessary with high CO2 taxes, due to the change in power plant’s unit commitment, as they prioritize gas before coal power plants. Having moderate to low CO2 allowance cost or no clear transition policy will be more expensive and the CO2 budget will be exceeded. Nonetheless, even with no policy, renewables still dominate the energy mix of the future.
However, maintaining the maximum historical installation rates of both national and regional levels, with the current emissions reduction strategy, will not be enough to reach the level of climate-neutral electricity system. Therefore, national and regional installation requirements to achieve the federal government emission reduction goals are determined. Energy strategies and decision makers will have to resolve great challenges in order to stay in line with the 1.5-degree-target.
Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor–capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.
Photovoltaic thermal (PVT) technology has been drawing attention recently. Electrification of the heating sector with heat pumps run by carbon-free electricity sources like photovoltaics is setting the ground for the interest. This article gives insight into PVT technologies and collector designs according to application and operating temperatures. For most conventional designs, examples like prototypes from Research & Development projects are presented. In addition, commercial products are listed along these categories, and the influence on the gross thermal and electrical yield is depicted based on Solar Keymark certification data. The process of certification is presented in a comprehensive way, showing current limitations, giving an outlook on the most recent approach for enhanced procedures and specifications. Finally, different system layouts are presented, and examples from installations combined with a heat pump are given with their specific performances. Real performance data of several PVT installations are compared to conventional heat pump systems. The identified seasonal performance factors are in a range from 3.4 to 4.2 and in between air source and ground source heat pumps. Continuous monitoring and derived data are enablers to discover the decisive influence of the system layout and dimensioning on performance indicators like, for example, operating temperatures over the year.
Fast charging of lithium-ion batteries remains one of the most delicate challenges for the automotive industry, being seriously affected by the formation of lithium metal in the negative electrode. Here we present a physicochemical pseudo-3D model that explicitly includes the plating reaction as side reaction running in parallel to the main intercalation reaction. The thermodynamics of the plating reaction are modeled depending on temperature and ion concentration, which differs from the often-used assumption of a constant plating condition of 0 V anode potential. The reaction kinetics are described with an Arrhenius-type rate law parameterized from an extensive literature research. Re-intercalation of plated lithium was modeled to take place either via reverse plating (solution-mediated) or via an explicit interfacial reaction (surface-mediated). At low temperatures not only the main processes (intercalation and solid-state diffusion) become slow, but also the plating reaction itself becomes slower. Using this model, we are able to predict typical macroscopic experimental observables that are indicative of plating, that is, a voltage plateau during discharge and a voltage drop upon temperature increase. A spatiotemporal analysis of the internal cell states allows a quantitative insight into the competition between intercalation and plating. Finally, we calculate operation maps over a wide range of C-rates and temperatures that allow to assess plating propensity as function of operating condition.
Predictive control has great potential in the home energy management domain. However, such controls need reliable predictions of the system dynamics as well as energy consumption and generation, and the actual implementation in the real system is associated with many challenges. This paper presents the implementation of predictive controls for a heat pump with thermal storage in a real single-family house with a photovoltaic rooftop system. The predictive controls make use of a novel cloud camera-based short-term solar energy prediction and an intraday prediction system that includes additional data sources. In addition, machine learning methods were used to model the dynamics of the heating system and predict loads using extensive measured data. The results of the real and simulated operation will be presented.
The use of biochar is an important tool to improve soil fertility, reduce the negative environmental impacts of agriculture, and build up terrestrial carbon sinks. However, crop yield increases by biochar amendment were not shown consistently for fertile soils under temperate climate. Recent studies show that biochar is more likely to increase crop yields when applied in combination with nutrients to prepare biochar-based fertilizers. Here, we focused on the root-zone amendment of biochar combined with mineral fertilizers in a greenhouse trial with white cabbage (Brassica oleracea convar. Capitata var. Alba) cultivated in a nutrient-rich silt loam soil originating from the temperate climate zone (Bavaria, Germany). Biochar was applied at a low dosage (1.3 t ha−1). The biochar was placed either as a concentrated hotspot below the seedling or it was mixed into the soil in the root zone representing a mixture of biochar and soil in the planting basin. The nitrogen fertilizer (ammonium nitrate or urea) was either applied on the soil surface or loaded onto the biochar representing a nitrogen-enhanced biochar. On average, a 12% yield increase in dry cabbage heads was achieved with biochar plus fertilizer compared to the fertilized control without biochar. Most consistent positive yield responses were observed with a hotspot root-zone application of nitrogen-enhanced biochar, showing a maximum 21% dry cabbage-head yield increase. Belowground biomass and root-architecture suggested a decrease in the fine root content in these treatments compared to treatments without biochar and with soil-mixed biochar. We conclude that the hotspot amendment of a nitrogen-enhanced biochar in the root zone can optimize the growth of white cabbage by providing a nutrient depot in close proximity to the plant, enabling efficient nutrient supply. The amendment of low doses in the root zone of annual crops could become an economically interesting application option for biochar in the temperate climate zone.
With the function RooTri(), we present a simple and robust calculation method for the approximation of the intersection points of a scalar field given as an unstructured point cloud with a plane oriented arbitrarily in space. The point cloud is approximated to a surface consisting of triangles whose edges are used for computing the intersection points. The function contourc() of Matlab is taken as a reference. Our experiments show that the function contourc() produces outliers that deviate significantly from the defined nominal value, while the quality of the results produced by the function RooTri() increases with finer resolution of the examined grid.
Batteries typically consist of multiple individual cells connected in series. Here we demonstrate single-cell state of charge (SOC) and state of health (SOH) diagnosis in a 24 V class lithium-ion battery. To this goal, we introduce and apply a novel, highly efficient algorithm based on a voltage-controlled model (VCM). The battery, consisting of eight single cells, is cycled over a duration of five months under a simple cycling protocol between 20 % and 100 % SOC. The cell-to-cell standard deviations obtained with the novel algorithm were 1.25 SOC-% and 1.07 SOH-% at beginning of cycling. A cell-averaged capacity loss of 9.9 % after five months cycling was observed. While the accuracy of single-cell SOC estimation was limited (probably owed to the flat voltage characteristics of the lithium iron phosphate, LFP, chemistry investigated here), single-cell SOH estimation showed a high accuracy (2.09 SOH-% mean absolute error compared to laboratory reference tests). Because the algorithm does not require observers, filters, or neural networks, it is computationally very efficient (three seconds analysis time for the complete data set consisting of eight cells with approx. 780.000 measurement points per cell).
Techno-economic comparison of membrane distillation and MVC in a zero liquid discharge application
(2018)
Membrane distillation (MD) is a thermally driven membrane process for the separation of vapour from a liquid stream through a hydrophobic, microporous membrane. However, a commercial breakthrough on a large scale has not been achieved so far. Specific developments on MD technology are required to adapt the technology for applications in which its properties can potentially outshine state of the art technologies such as standard evaporation. In order to drive these developments in a focused manner, firstly it must be shown that MD can be economically attractive in comparison to state of the art systems. Thus, this work presents a technological design and economic analysis for AGMD and v-AGMD for application in a zero liquid discharge (ZLD) process chain and compares it to the costs of mechanical vapour compression (MVC) for the same application. The results show that MD can potentially be ~40% more cost effective than MVC for a system capacity of 100 m3/day feed water, and up to ~75% more cost effective if the MD is driven with free waste heat.
Lithium-ion battery cells exhibit a complex and nonlinear coupling of thermal, electrochemical,and mechanical behavior. In order to increase insight into these processes, we report the development of a pseudo-three-dimensional (P3D) thermo-electro-mechanical model of a commercial lithium-ion pouch cell with graphite negative electrode and lithium nickel cobalt aluminum oxide/lithium cobalt oxide blend positive electrode. Nonlinear molar volumes of the active materials as function of lithium stoichiometry are taken from literature and implemented into the open-source software Cantera for convenient coupling to battery simulation codes. The model is parameterized and validated using electrical, thermal and thickness measurements over a wide range of C-rates from 0.05 C to 10 C. The combined experimental and simulated analyses show that thickness change during cycling is dominated by intercalation-induced swelling of graphite, while swelling of the two blend components partially cancel each other. At C-rates above 2 C, electrochemistry-induced temperature increase significantly contributes to cell swelling due to thermal expansion. The thickness changes are nonlinearly distributed over the thickness of the electrode pair due to gradients in the local lithiation, which may accelerate local degradation. Remaining discrepancies between simulation and experiment at high C-rates might be attributed to lithium plating, which is not considered in the model at present.
A strong heat load in buildings and cities during the summer is not a new phenomenon. However, prolonged heat waves and increasing urbanization are intensifying the heat island effect in our cities; hence, the heat exposure in residential buildings. The thermophysiological load in the interior and exterior environments can be reduced in the medium and long term, through urban planning and building physics measures. In the short term, an increasingly vulnerable population must be effectively informed of an impending heat wave. Building simulation models can be favorably used to evaluate indoor heat stress. This study presents a generic simulation model, developed from monitoring data in urban multi-unit residential buildings during a summer period and using statistical methods. The model determines both the average room temperature and its deviations and, thus, consists of three sub-models: cool, average, and warm building types. The simulation model is based on the same mathematical algorithm, whereas each building type is described by a specific data set, concerning its building physical parameters and user behavior, respectively. The generic building model may be used in urban climate analyses with many individual buildings distributed across the city or in heat–health warning systems, with different building and user types distributed across a region. An urban climate analysis (with weather data from a database) may evaluate local differences in urban and indoor climate, whereas heat–health warning systems (driven by a weather forecast) obtain additional information on indoor heat stress and its expected deviations.
One of the practical bottlenecks associated with commercialization of lithium-air cells is the choice of an appropriate electrolyte that provides the required combination of cell performance, cyclability and safety. With the help of a two-dimensional multiphysics model, we attempt to narrow down the electrolyte choice by providing insights into the effect of the transport properties of electrolyte, electrode saturation (flooded versus gas diffusion), and electrode thickness on a single discharge performance of a lithium-air button cell cathode for five different electrolytes including water, ionic liquid, carbonate, ether, and sulfoxide. The 2D distribution of local current density and concentrations of electrochemically active species (O2 and Li+) in the cathode is also discussed w.r.t electrode saturation. Furthermore, the efficacy of species transport in the cathode is quantified by introducing two parameters, firstly, a transport efficiency that gives local insight into the distribution of mass transfer losses, and secondly, an active electrode volume that gives global insight into the cathode volume utilization at different current densities. A detailed discussion is presented toward understanding the design-induced performance limitations in a Li-air button cell prototype.