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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.
Für Verkehrsunternehmen stellt die Erprobung neuer Technologien eine große Herausforderung dar.
Sowohl Wasserstoff-Busse als auch Batterie-Busse können ihren Beitrag zur Umstellung des ÖPNV auf emissionsfreie Mobilität leisten. Je nach Anwendungsmuster können sich beide Technologien gut ergänzen und zu einem volkswirtschaftlichen Optimum führen. Es gilt, die Technologien im realen Umfeld zu erproben, um praxisnahe Erfahrung zu sammeln und dabei Mitarbeiter auszubilden, ohne die Qualität des Betriebes zu gefährden. Bei der aktuellen Kostenlage sehen beide Technologien ihre Einführung in den Betrieb mit Mehrkosten im Vergleich zu der aktuellen Diesel-Lösung verbunden.
Bei einer Batterie-basierten Lösung mit Pantograph-Schnellladung sind kürzere Linien gute Kandidaten für eine elektrische Umstellung ohne Auswirkungen auf die Größe der Busflotte. Auch Liniensysteme beliebiger Länge mit Knotenpunkten in regelmäßigen Abständen ermöglichen eine gemeinsame Nutzung der Ladeinfrastruktur und stellen somit reduzierte Aufbaukosten der Ladeinfrastruktur in Aussicht. In diesem Fall sind aber auch Fahrplanmanagement-Aspekte hinsichtlich der Ladezeit am Pantograph mit zu berücksichtigen, die nicht Bestandteil dieser Studie gewesen sind. Allgemein lassen die Kosten-Prognosen für Batterie und Batterie-elektrische Fahrzeuge eine signifikante Kostenreduzierung bis 2030 erkennen, die in manchen Konfigurationen zur Kostenparität und sogar geringeren Kosten als mit der Diesel-Variante führen würde.
Anders als für Batterie-Busse stellt die Linien-Konfiguration keinen wirtschaftlichen Einflussfaktor auf den Betrieb von Wasserstoff-Bussen dar. Die derzeitige Reichweite der H2-Busse reicht aus, um die zu erwartende tägliche Fahrleistung zu decken. Bei der Wasserstoffmobilität sind aber die Versorgungsinfrastruktur und die damit verbundenen Kraftstoffkosten von entscheidender Bedeutung. Ihr Aufbau ist mit hohen Investitionskosten und gesetzlichen Verpflichtungen verbunden (BImSchG, BetrSichV), die für eine erste Erprobung der Technologie im kleinen Maßstab eine Hürde für Verkehrsunternehmen darstellen könnte. Die H2 Mobility Deutschland bietet die Möglichkeit an, 700 bar Tankstellen mit einem 350 bar Modul zu erweitern, das die tägliche Versorgung von ca. 6 Bussen ermöglicht. Mit begrenzten Risiken für die Verkehrsunternehmen bietet es sich daher an, die H2 Mobilität auf eine limitierte Busflotte zu erproben. Da der Aufbau des H2-Mobility Deutschland Tankstellennetzes eine Lücke in Offenburg und Umgebung aufweist, wäre es vorstellbar, an der Errichtung einer solchen Tankstelle zu arbeiten, die die Betankung und Erprobung von Wasserstoff-Bussen ermöglicht. Auf längerer Sicht ist die Sicherstellung einer gut platzierten zuverlässigen und nachhaltigen Wasserstoffquelle von entscheidender Bedeutung. Derzeit liegen vorhandene Wasserstoffquellen in mehr als 100 km Entfernung. Eine Nutzung der Wasserkraft des naheliegenden Rheins erscheint durchaus sinnvoll, sowohl aus wirtschaftlichen als auch aus umwelttechnischen Gründen (erneuerbarer Strom, Stromkostenreduzierung durch Eigenversorgung, kürzere Transportwege, möglicher Nutzen für die Eurometropole Straßburg).
Es lässt sich festhalten, dass für die Region Offenburg zunächst die Erprobung beider Technologien, der Elektromobilität als auch der Wasserstoffmobilität, empfohlen wird. Es sollte zeitnah in den Erfahrungsaufbau in beide Technologien investiert werden. Zudem sollte bei der Elektromobilität das Flottenmanagement untersucht und evaluiert werden und bei der Wasserstoffmobilität die Möglichkeiten der Kooperation für den Aufbau der Wasserstofftankstelle. Im Rahmen der nächsten Ausschreibungsrunde für den öffentlichen Nahverkehr in Offenburg wird empfohlen, diesen emissionsfrei auszuschreiben. Es ist absehbar, dass aus Kostengründen (Kostenparität der Elektromobilität mit der Dieselvariante) als auch aus Gründen der Anforderung bzgl. der Emissionsgrenzwerte der ÖPNV emissionsfrei umgesetzt werden sollte.
During pyrolysis, biomass is carbonised in the absence of oxygen to produce biochar with heat and/or electricity as co-products making pyrolysis one of the promising negative emission technologies to reach climate goals worldwide. This paper presents a simplified representation of pyrolysis and analyses the impact of this technology on the energy system. Results show that the use of pyrolysis can allow getting zero emissions with lower costs by making changes in the unit commitment of the power plants, e.g. conventional power plants are used differently, as the emissions will be compensated by biochar. Additionally, the process of pyrolysis can enhance the flexibility of energy systems, as it shows a correlation between the electricity generated by pyrolysis and the hydrogen installation capacity, being hydrogen used less when pyrolysis appears. The results indicate that pyrolysis, which is available on the market, integrates well into the energy system with a promising potential to sequester carbon.
Short-term load forecasting (STLF) has been playing a key role in the electricity sector for several decades, due to the need for aligning energy generation with the demand and the financial risk connected with forecasting errors. Following the top-down approach, forecasts are calculated for aggregated load profiles, meaning the sum of singular loads from consumers belonging to a balancing group. Due to the emerging flexible loads, there is an increasing relevance for STLF of individual factories. These load profiles are typically more stochastic compared to aggregated ones, which imposes new requirements to forecasting methods and tools with a bottom-up approach. The increasing digitalization in industry with enhanced data availability as well as smart metering are enablers for improved load forecasts. There is a need for STLF tools processing live data with a high temporal resolution in the minute range. Furthermore, behin-the-meter (BTM) data from various sources like submetering and production planning data should be integrated in the models. In this case, STLF is becoming a big data problem so that machine learning (ML) methods are required. The research project “GaIN” investigates the improvement of the STLF quality of an energy utility using BTM data and innovative ML models. This paper describes the project scope, proposes a detailed definition for a benchmark and evaluates the readiness of existing STLF methods to fulfil the described requirements as a reviewing paper.
The review highlights that recent STLF investigations focus on ML methods. Especially hybrid models gain more and more importance. ML can outperform classical methods in terms of automation degree and forecasting accuracy. Nevertheless, the potential for improving forecasting accuracy by the use of ML models depends on the underlying data and the types of input variables. The described methods in the analyzed publications only partially fulfil the tool requirements for STLF on company level. There is still a need to develop suitable ML methods to integrate the expanded data base in order to improve load forecasts on company level.
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.
Die Digitalisierung kann der Türöffner sein, um effizient die mittelständische Industrie und den Energiemarkt zu verbinden. Das Projekt GaIN hat das Ziel, mit hochaufgelösten Produktions- und Messdaten von zehn mittelständischen Industriebetrieben neuartige Tarife und angepasste Marktplattformen zu entwickeln, die Prognosegüte für Energiebedarf, Nachfrage und Flexibilitätsverfügbarkeit zu erhöhen, die Interaktion vieler flexibler Unternehmen im Verteilnetz und in dem Bilanzkreis zu bewerten und die Auswirkung einer Nutzung der Daten auf die Energiewende anhand einer Systemanalyse zu beurteilen.
Ziel des Pilotprojektes EnMa-HAW ist die Erarbeitung und Erprobung technisch und organisatorisch übertragbarer Konzepte für ein automationsgestütztes Energiemanagement an allen Hochschulen für angewandte Wissenschaften im Land Baden-Württemberg. Das Energiemanagement wird technisch mittels Messtechnik, Datenerfassung, Datenspeicherung und Visualisierung umgesetzt und organisatorisch mit einem Energiezirkel in den Hochschulen verankert.
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.
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.
Most recently, the federal government in Germany published new climate goals in order reach climate neutrality by 2045. This paper demonstrates a path to a cost optimal energy supply system for the German power grid until the year 2050. With special regard to regionality, the system is based on yearly myopic optimization with the required energy system transformation measures and the associated system costs. The results point out, that energy storage systems (ESS) are fundamental for renewables integration in order to have a feasible energy transition. Moreover, the investment in storage technologies increased the usage of the solar and wind technologies. Solar energy investments were highly accompanied with the installation of short-term battery storage. Longer-term storage technologies, such as H2, were accompanied with high installations of wind technologies. The results pointed out that hydrogen investments are expected to overrule short-term batteries if their cost continues to decrease sharply. Moreover, with a strong presence of ESS in the energy system, biomass energy is expected to be completely ruled out from the energy mix. With the current emission reduction strategy and without a strong presence of large scale ESS into the system, it is unlikely that the Paris agreement 2° C target by 2050 will be achieved, let alone the 1.5° C.