Smart Energy最新文献_第4页

Forecasting day-ahead hydropower bids in the colombian electricity market: A two-stage machine learning framework 预测哥伦比亚电力市场的水电报价：一个两阶段的机器学习框架

IF 5

Smart Energy Pub Date : 2026-02-01 Epub Date: 2025-12-13 DOI: 10.1016/j.segy.2025.100221

Laura Herrera-Mejía, Carlos D. Hoyos, David La Rotta, Yissel Mejía, John Castillo

{"title":"Forecasting day-ahead hydropower bids in the colombian electricity market: A two-stage machine learning framework","authors":"Laura Herrera-Mejía, Carlos D. Hoyos, David La Rotta, Yissel Mejía, John Castillo","doi":"10.1016/j.segy.2025.100221","DOIUrl":"10.1016/j.segy.2025.100221","url":null,"abstract":"<div><div>Forecasting day-ahead energy prices in Colombia is challenging, as bids are shaped not only by hydrology and demand but also by strategic bidding under evolving regulatory and economic conditions. We develop a Machine Learning (ML) framework to forecast day-ahead bids of individual hydroelectric plants in the National Interconnected System (SIN), using plant-specific models that capture operational and strategic heterogeneity. To our knowledge, this is the first study to develop plant-specific ML models for Colombian hydro bidding.</div><div>The framework employs a two-stage architecture: (i) a classifier predicts whether a plant will bid at the regulatory minimum, and (ii) a regression model estimates the actual bid otherwise. Using daily data from XM (2016–2025), we benchmark multiple algorithms—including XGBoost, Random Forest, Gradient Boosting, MLP, and stacked ensembles.</div><div>Across plants, the framework achieves average F1-scores above 0.90 for classification, and regression errors in the range MAE = 1.5–3.0 COP/kWh (normalized by regulatory floor). Tercile classification accuracy exceeds 70% for key strategic plants such as Guavio and San Carlos, indicating strong ordinal predictive skill even under volatile conditions. The models perform particularly well for plants with stable bidding patterns, while highly intermittent plants (e.g. Porce II & III) remain harder to anticipate.</div><div>These results demonstrate that ML methods can capture mid-term gradients and relative positioning of competitor bids, providing actionable insights for market operators and traders. Future extensions should integrate contextual data—portfolio composition, regulatory signals, or sentiment indicators—to improve forecast robustness in behaviorally complex markets.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100221"},"PeriodicalIF":5.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantifying energy transport by electric vehicles: A Monte Carlo and optimization framework for flexible energy communities 量化电动汽车的能源运输：灵活能源社区的蒙特卡洛和优化框架

IF 5

Smart Energy Pub Date : 2026-02-01 Epub Date: 2026-02-11 DOI: 10.1016/j.segy.2026.100230

Alvaro Menendez-Agudin , Gregorio Fernández Aznar , Pavol Bauer , Gautham Ram Chandra Mouli

{"title":"Quantifying energy transport by electric vehicles: A Monte Carlo and optimization framework for flexible energy communities","authors":"Alvaro Menendez-Agudin , Gregorio Fernández Aznar , Pavol Bauer , Gautham Ram Chandra Mouli","doi":"10.1016/j.segy.2026.100230","DOIUrl":"10.1016/j.segy.2026.100230","url":null,"abstract":"<div><div>Rising grid congestion raises concerns that conventional grid expansion may not keep pace with projected increases in demand and renewable generation. This research proposes a supplementary solution: leveraging the inherent mobility of Electric Vehicles to enable energy transfer within different locations. Through an analytical modelling approach, a stochastic energy transport model using Monte Carlo sampling is developed. This model generates synthetic weekly charging and driving profiles to quantify the energy transport potential of private EV fleets, accounting for battery capacity, mobility patterns, and energy consumption. Building on this concept, the study introduces Flexible Energy Communities (FlexECs), where members share the same living location but commute to different workplaces or vice versa. By enabling electric vehicles to charge at one location and discharge at another during routine daily travels, Flexible Energy Communities exploit private EV mobility as a mechanism for spatial energy transfer, extending Energy Community operation beyond purely grid energy exchange.</div><div>Results reveal that approximately 35 kWh, equivalent to 60% of the total energy stored in the EV battery at the time of departure, can be discharged upon arrival. Additionally, when charging patterns are optimized, up to 30 kWh, representing 70% of the energy charged prior to the journey, can be effectively transported and discharged at the destination. By quantifying the impact of EV-imported energy on cost, peak demand, and overall energy consumption reduction, this study underscores the potential of EVs as dynamic energy transporters, providing a technical foundation for energy sharing through private EVs daily travelling patterns.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100230"},"PeriodicalIF":5.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Economic perspectives of hydrogen and fuel cell vehicles in the transition to smart energy systems 氢和燃料电池汽车在向智能能源系统过渡中的经济前景

IF 5

Smart Energy Pub Date : 2026-02-01 Epub Date: 2026-02-10 DOI: 10.1016/j.segy.2026.100229

Amela Ajanovic, Reinhard Haas

{"title":"Economic perspectives of hydrogen and fuel cell vehicles in the transition to smart energy systems","authors":"Amela Ajanovic, Reinhard Haas","doi":"10.1016/j.segy.2026.100229","DOIUrl":"10.1016/j.segy.2026.100229","url":null,"abstract":"<div><div>The transition to a smart energy system necessitates the defossilisation of energy use while maintaining security and efficiency. Green hydrogen has been positioned as an energy carrier with potential to contribute to this transition. This study examines the economic viability of hydrogen use with special focus on the transport sector, analyzing cost trends in electrolysis, fuel cell vehicle deployment, and market dynamics. Despite its potential, hydrogen adoption faces significant barriers, including high production costs, infrastructure limitations, and inefficiencies in conversion processes. The study highlights the challenges of integrating hydrogen into energy systems, explores the competitiveness of hydrogen-powered vehicles across different transport modes, and assesses its role in a market-driven energy landscape. While hydrogen may play a role in hard-to-electrify sectors, its widespread adoption remains uncertain. Hydrogen in transport is likely to remain a niche solution, used only where other low-carbon alternatives are not feasible. Whether it can truly become a cornerstone of Europe's sustainable energy future will depend not just on technological progress but on carefully designed policies, realistic economic planning, and transparent long-term strategies.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100229"},"PeriodicalIF":5.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A mixed-integer linear programming model for BESS sizing optimization considering aging effects and emission costs 考虑老化和排放成本的BESS尺寸优化混合整数线性规划模型

IF 5

Smart Energy Pub Date : 2026-02-01 Epub Date: 2025-12-26 DOI: 10.1016/j.segy.2025.100225

Nguyen Quoc Minh, Tran Van Dai, Pham Minh Hoang, Pham Hong Hai, Le Thi Minh Chau

{"title":"A mixed-integer linear programming model for BESS sizing optimization considering aging effects and emission costs","authors":"Nguyen Quoc Minh, Tran Van Dai, Pham Minh Hoang, Pham Hong Hai, Le Thi Minh Chau","doi":"10.1016/j.segy.2025.100225","DOIUrl":"10.1016/j.segy.2025.100225","url":null,"abstract":"<div><div>With the rapid expansion of renewable energy sources (RES), battery energy storage systems (BESS) have become essential for ensuring grid stability, reliability, and operational efficiency. However, optimizing BESS sizing is a complex challenge that requires balancing economic, technical, and environmental factors while considering the long-term impact of battery degradation and replacement costs. This study presents a comprehensive optimization model for determining the optimal capacity of BESS within a microgrid, explicitly incorporating battery aging effects and associated lifecycle costs. The proposed model employs a mixed-integer linear programming (MILP) approach to minimize the total system cost, which includes investment, operation, and replacement expenses, while ensuring that load demand is met, RES integration is maximized, and system reliability is maintained. By considering the degradation of BESS performance over time, the model provides a more accurate estimation of long-term economic and technical feasibility. Simulation results validate the effectiveness of the model in optimizing BESS sizing and installation costs. Additionally, the study evaluates different BESS technologies and examines the impact of various factors, such as RES penetration and emission costs on overall system performance. The findings offer valuable insights into developing cost-effective BESS operation schedules and management strategies, contributing to improved energy efficiency and sustainability in microgrid applications.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100225"},"PeriodicalIF":5.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrating system dynamics modeling and EnergyPLAN for national energy planning: The case of Georgia 在国家能源规划中整合系统动力学建模和EnergyPLAN：以格鲁吉亚为例

IF 5

Smart Energy Pub Date : 2026-02-01 Epub Date: 2026-02-24 DOI: 10.1016/j.segy.2026.100232

Alaize Dall-Orsoletta , Géremi Gilson Dranka , Gaioz Partskhaladze , Paula Ferreira

{"title":"Integrating system dynamics modeling and EnergyPLAN for national energy planning: The case of Georgia","authors":"Alaize Dall-Orsoletta , Géremi Gilson Dranka , Gaioz Partskhaladze , Paula Ferreira","doi":"10.1016/j.segy.2026.100232","DOIUrl":"10.1016/j.segy.2026.100232","url":null,"abstract":"<div><div>Transitioning to sustainable and resilient energy systems is a key challenge for countries with rising demand, climate vulnerabilities, and geopolitical constraints. In Georgia, substantial renewable energy (RE) potential, growing emissions, and seasonal reliance on energy imports highlight the need for diversified, low-carbon planning. This study models Georgia's long-term generation capacity expansion to 2050 under alternative scenarios using a soft-linked hybrid modeling framework that couples system dynamics (SD) with EnergyPLAN. The SD model captures long-term investment dynamics, learning effects, and policy-driven transitions, while EnergyPLAN evaluates the operational feasibility of resulting system configurations under hourly constraints. Results indicate that variable renewable energy (VRE) can satisfy domestic demand and reduce annual net electricity imports if supported by timely transmission and grid investments. The installed capacity of wind and utility-scale solar energy can reach up to 2.5 GW by 2050, while net imports can decrease from 3.3 TWh to below 1.5 TWh, and power sector emissions can be halved relative to 2023 levels. Hydropower remains central, expanding to 5.3 GW in high-renewable scenarios, though seasonal deficits persist. Methodologically, the study contributes by demonstrating the value of integrating long-term SD-based scenario exploration with high-resolution operational analysis to assess the consistency of energy transition pathways. Future research should focus on strengthening the coupling framework through iterative feedbacks, expanding sectoral coverage, and leveraging improved data availability to support more robust and policy-relevant energy system analysis.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100232"},"PeriodicalIF":5.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of bidirectional EV charging infrastructures within industrial DC grids 工业直流电网内电动汽车双向充电基础设施分析

IF 5

Smart Energy Pub Date : 2026-02-01 Epub Date: 2026-01-30 DOI: 10.1016/j.segy.2026.100227

Henning Rahlf , Lukas Knorr , Simon Althoff , Henning Meschede

{"title":"Analysis of bidirectional EV charging infrastructures within industrial DC grids","authors":"Henning Rahlf , Lukas Knorr , Simon Althoff , Henning Meschede","doi":"10.1016/j.segy.2026.100227","DOIUrl":"10.1016/j.segy.2026.100227","url":null,"abstract":"<div><div>Industrial electrification is increasing to reduce fossil fuel dependence, alongside a growing share of volatile renewables. A secure and reliable energy supply is crucial for industry, leading to a shift from centralised to decentralised grid structures. DC microgrids becoming increasingly popular in industry, since they enable energy recuperation from braking, reduce components and cables, and integrate storage and local generation to manage supply interruptions or peak loads. EVs add further synergies by serving as mobile storage units, helping to store and redistribute locally generated renewable energy. This paper analyses how EV integration in droop-controlled DC grids can contribute to a more stable, low-emission and peak-reduced load profile to the supply grid through load shifting and bridge interruptions. A droop-controlled DC grid model has been developed, incorporating an EV charging park based on probability functions. Scalable scenarios allow for diverse condition analysis using an energy management system that utilises fuzzy logic and sequential MILP optimisation. It has been shown that a 7% improvement of coefficient represented grid-serving behaviour is possible by load shifting. It has also been demonstrated that an optimised EMS can reduce the demand-based CO<sub>2</sub> emissions by 41 kg for a representative day compared to a fuzzy logic EMS. At the same time peak load is decreased yielding a more constant residual load. These results highlight the potential of a controlled bidirectional charging infrastructure in DC grids and underscore the need to explicitly consider charging processes to ensure a residual load as constant as possible.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100227"},"PeriodicalIF":5.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sustainable energy transition towards self-sufficiency for densely populated regions: the case of Belgium 人口稠密地区向自给自足的可持续能源转型：比利时的案例

IF 5

Smart Energy Pub Date : 2026-02-01 Epub Date: 2026-02-16 DOI: 10.1016/j.segy.2026.100231

Rasul Satymov, Mahdi Dashti, Tansu Galimova, Christian Breyer

{"title":"Sustainable energy transition towards self-sufficiency for densely populated regions: the case of Belgium","authors":"Rasul Satymov, Mahdi Dashti, Tansu Galimova, Christian Breyer","doi":"10.1016/j.segy.2026.100231","DOIUrl":"10.1016/j.segy.2026.100231","url":null,"abstract":"<div><div>The energy transition is driven by climate change, emission reduction targets, and the declining cost of renewable energy technologies. This study examines Belgium's transition to a 100% renewable energy system, considering the country's high population density, limited land availability, and high energy use. Specifically, the potential of ocean energy, such as offshore wind power, floating offshore solar photovoltaics, and wave power, is investigated to achieve energy self-sufficiency. Using the EnergyPLAN model for hourly simulations across the power, heat, transport, and industry sectors, the research compares the current system against two 2050 scenarios: full self-sufficiency and e-fuel imports. The results suggest that while self-sufficiency is attainable through significant investment in hydrogen storage and chemical synthesis, importing e-fuels remains the more cost-effective strategy. Both scenarios, however, show a significant decrease in annual energy system costs, with 16.9-22.4 b€ in 2050 compared to 40.4 b€ in 2019. Additionally, the integration of agrivoltaics, hybrid photovoltaics-wind plants, and wave power can optimise land use. Achieving self-sufficiency requires larger initial investments but offers long-term economic and environmental advantages. This study offers a path for Belgium's defossilisation, highlighting the significance of local renewable energy sources and international cooperation in trading e-fuels.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"21 ","pages":"Article 100231"},"PeriodicalIF":5.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Requirements analysis for Model Predictive Control in a decentralized district heating network 分布式集中供热网络模型预测控制的需求分析

IF 5

Smart Energy Pub Date : 2025-11-01 Epub Date: 2025-09-20 DOI: 10.1016/j.segy.2025.100188

Theda Zoschke , Christian Wolff , Armin Nurkanović , Gregor Rohbogner , Daniel Weiß , Lilli Frison , Moritz Diehl , Axel Oliva

{"title":"Requirements analysis for Model Predictive Control in a decentralized district heating network","authors":"Theda Zoschke , Christian Wolff , Armin Nurkanović , Gregor Rohbogner , Daniel Weiß , Lilli Frison , Moritz Diehl , Axel Oliva","doi":"10.1016/j.segy.2025.100188","DOIUrl":"10.1016/j.segy.2025.100188","url":null,"abstract":"<div><div>This study introduces a method to derive requirements for non-linear formulations in optimization problems for Model Predictive Control (MPC) of district heating networks. Those formulations become particularly relevant in decentralized networks where thermohydraulic effects stemming from pressure and temperature distribution impact the optimal dispatch schedule of producers. This is illustrated through a case study of the network in Weil am Rhein, Germany. Initially, a linear MPC formulation that neglects thermohydraulic dynamics was evaluated using one year of measurement data, revealing potential cost reductions of 14.3%. These savings primarily result from reduced operation of fossil fuel boilers and increased utilization of Combined Heat and Power plants. Subsequently, hydraulic simulations and monitoring data were analyzed, revealing that at least one of the production sites is unable to supply its installed capacity into the network during high-load scenarios due to hydraulic limitations. Furthermore, the analysis of thermal losses suggested that supply temperature optimization has an additional cost-saving potential of approximately 1.8%. The study concludes that future versions of the optimization framework require the consideration of pressure losses and pumping limitations to enhance operational reliability, while also recognizing additional improvement potential offered by supply temperature optimization.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"20 ","pages":"Article 100188"},"PeriodicalIF":5.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A comprehensive evaluation of prediction techniques and their influence on model predictive control in smart energy storage systems 智能储能系统预测技术及其对模型预测控制的影响

IF 5

Smart Energy Pub Date : 2025-11-01 Epub Date: 2025-09-04 DOI: 10.1016/j.segy.2025.100202

Ulrich Ludolfinger , Thomas Hamacher , Maren Martens

{"title":"A comprehensive evaluation of prediction techniques and their influence on model predictive control in smart energy storage systems","authors":"Ulrich Ludolfinger , Thomas Hamacher , Maren Martens","doi":"10.1016/j.segy.2025.100202","DOIUrl":"10.1016/j.segy.2025.100202","url":null,"abstract":"<div><div>The increasing share of intermittent renewable energy calls for intelligent building energy management systems to maintain grid stability. A widely used method for operating on-site storage is model predictive control (MPC), whose effectiveness heavily depends on forecast accuracy. This paper systematically evaluates the impact of prediction models on MPC performance in smart energy storage systems (SESS). Using a three-year, multi-building dataset with 15 min resolution, we compare five forecasting methods, linear model, XGBoost, RNN, TimeMixer, and TimesNet, for load, PV generation, and electricity price prediction. While XGBoost achieves the lowest mean squared error (MSE) and yields the highest revenue gain of 104% over a no-storage baseline during a four-month winter–spring test period, other models reveal a mismatch between forecast accuracy and control performance. Notably, the linear model, ranking mostly lowest in MSE, delivers the third-highest revenue (73%), nearly on par with the second best (79%). This illustrates that prediction accuracy alone is not a reliable proxy for control quality. Even the best realistic setup remains far from the ideal benchmark using perfect forecasts (235% gain). Daily retraining improves some models substantially (linear model to 105%) but has limited effect on others (XGBoost to 107%). These findings emphasize three key insights: (1) standard metrics like MSE may misrepresent the utility of forecasts for control, (2) errors across multiple inputs compound degradation in MPC, and (3) frequent retraining can mitigate losses. Overall, the results underscore the importance of robust forecasting and carefully chosen loss functions in the smart energy systems concept.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"20 ","pages":"Article 100202"},"PeriodicalIF":5.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coordinated energy systems in decentralized districts: Evaluating the cellular approach for improved grid stability and renewable integration 分散地区的协调能源系统：评估改善电网稳定性和可再生能源整合的蜂窝方法

IF 5

Smart Energy Pub Date : 2025-11-01 DOI: 10.1016/j.segy.2025.100215

Lukas Richter , Volker Lenz , Martin Dotzauer , Joachim Seifert

引用次数: 0