Energy

Journal: Energy

Abbreviation

Energy

Publisher

Elsevier

ISSN

0360-5442
1873-6785

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Publications1 - 10 of 122

Market integration of local energy systems: Is local energy management compatible with European regulation for retail competition?
Eid, Cherrelle; Bollinger, L. Andrew; Koirala, Binod; et al. (2016)
Energy
The growing penetration of distributed energy resources is opening up opportunities for local energy management (LEM) – the coordination of decentralized energy supply, storage, transport, conversion and consumption within a given geographical area. Because European electricity market liberalization concentrates competition at the wholesale level, local energy management at the distribution level is likely to impose new roles and responsibilities on existing and/or new actors. This paper provides insights into the appropriateness of organizational models for flexibility management to guarantee retail competition and feasibility for upscaling. By means of a new analytical framework three projects in the Netherlands and one in Germany have been analysed. Both the local aggregator and dynamic pricing projects present potentials for retail competition and feasibility of upscaling in Europe.
Low exergy building systems implementation
Meggers, Forrest; Ritter, Volker; Goffin, Philippe; et al. (2012)
Energy
Optimization of charging infrastructure and strategy for an electrified public transportation system
Moradi, Mohammad Hossein; Widmer, Fabio; Turin, Raymond C.; et al. (2024)
Energy
Government policies and incentives aimed at reducing the carbon footprint are increasingly focusing on the electrification of public transportation, particularly transit buses. However, electrification faces significant challenges, including optimizing the charging infrastructure, battery size and type, and charging strategies. Addressing these challenges is crucial for the effective deployment and operation of electric bus fleets. This study presents an innovative method for optimizing these aspects of electric bus systems under diverse route conditions. By leveraging general transit feed specification (GTFS) and GeoTIFF data, the developed approach ensures scalability and is grounded in real-world data. A detailed physical model, especially concerning battery degradation, adds a unique dimension to the study, providing more accurate and reliable results. The optimization method employed in this study is dynamic programming (DP), which allows for a comprehensive evaluation of various factors influencing the performance and efficiency of electric buses. The proposed approach has been validated through three distinct case studies. The findings of this study indicate that the optimized solution can lead to a substantial cost reduction of nearly 35% for operators compared to current state-of-the-art practices in Zurich, which underscores the potential of the proposed approach to contribute to more sustainable and cost-effective public transportation systems.
Comparison of alternative decision-making criteria in a two-stage stochastic program for the design of distributed energy systems under uncertainty
Mavromatidis, Georgios; Orehounig, Kristina; Carmeliet, Jan (2018)
Energy ~ The 30th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems - ECOS 2017
The design of distributed energy systems (DES) is affected by uncertainty, which can render designs suboptimal. DES design is further complicated by the various decision-maker attitudes towards uncertainty, which range between pessimism and optimism. An additional important factor is the risk of extreme outcomes (e.g. high costs) in highly unfavourable scenarios. Incorporating all decision-maker attitudes towards uncertainty in DES design enables more informed design decisions under uncertainty. In this work, a two-stage stochastic program for the design of cost-optimal DES under uncertainty is presented. The model’s key innovation is the use of multiple criteria that form the model’s objective functions and reflect the whole range of attitudes towards uncertainty. As uncertain model parameters, building energy demands, solar radiation, energy carrier prices and feed-in tariffs are considered. In the model’s first stage, DES design decisions are included, which are made before the uncertain parameters become known. In the second stage, DES operating decisions are made for multiple scenarios of the uncertain parameters. The model is used to design a DES for a Swiss neighbourhood and diverse optimal DES configurations are obtained for the different criteria. The systems’ economic performance and characteristics are contrasted and the trade-offs between the criteria are highlighted.
Production of Solar Hydrogen by a Novel, 2-Step, Water-Splitting Thermochemical Cycle
Tamaura, Yutaka; Steinfeld, Aldo; Kuhn, Peter; et al. (1995)
Energy
Estimating the heat transfer in fractured geothermal reservoirs
Heinze, Thomas; Gunatilake, Thanushika Samudinie (2025)
Energy
Geothermal systems in fractured rock are a promising energy resource due to the increased temperatures at depth. To enable wide-spread implementation of such systems, modeling tools that are faster and require less input data than discrete fracture network models, yet cover site-specific characteristics, are needed. Heat flow in fractures poses a challenge for the physical/numerical description due to the small water volumes flowing through the fractures. A novel heat transfer model was developed to assess the feasibility of fractured reservoirs for geothermal heat extraction and seasonal storage. The model is based on an innovative approach to determine the heat transferred between rock and flowing fluid in a fractured reservoir considering fracture spacing, fracture aperture, and production/injection rate as main model parameters. Such parameters are often available through borehole logging of a prospective well or outcrop data. The model is compared to laboratory tests, analytical solutions, field data, and complex numerical models proving its suitability and flexibility. The model was successfully demonstrated on hot dry rock and hydrothermal systems, as well as seasonal aquifer thermal energy storage. This makes it an ideal tool for feasibility studies based on early prospection results, minimizing economic risks, and studying possible operational procedures.
A finite line source model with Cauchy-type top boundary conditions for simulating near surface effects on borehole heat exchangers
Rivera, Jaime A.; Blum, Philipp; Bayer, Peter (2016)
Energy
Does cost optimization approximate the real-world energy transition?
Trutnevyte, Evelina (2016)
Energy
CO2 mitigation costs of catalytic methane decomposition
Zhang, Xiang; Kätelhön, Arne; Sorda, Giovanni; et al. (2018)
Energy
Catalytic methane decomposition (CMD) is promising for producing hydrogen without direct CO2 emissions. We estimate the CO2 mitigation costs associated with CMD for hydrogen production and subsequent power generation in a fuel cell. The overall CO2 emissions and economic viability are evaluated based on four scenarios: whether the by-product carbon can be sold or must be discarded into landfill; whether the catalyst can be recycled or not. CO2 emission savings and the associated costs of CMD concept are compared to the combined-cycle gas turbine (CCGT) power plant with and without carbon capture and storage (CCS). The results illustrate that the profitability of the concept as well as the ensuing CO2 abatement costs strongly depend on the ability to separate the catalysts from the carbon generated during the CMD. The life-cycle CO2 emissions per unit of electricity output of a CCGT plant with CCS are marginally higher than those generated in the CMD with perfect separation and regeneration of the catalysts. The levelized costs of electricity generation (LCOE) of CMD without selling the by-product are also higher than for CCGT with CCS. In contrast, the CMD can be highly profitable assuming selling the by-product carbon at current prices. ©2018 Elsevier Ltd. All rights reserved.
Estimating demand response potentials of domestic appliances: Insights from a Japanese survey
Kachirayil, Febin; Yamaguchi , Yohei; Chen , Chien-fe; et al. (2025)
Energy
Intermittent renewable electricity generation increases flexibility needs in energy systems. Demand response (DR) programs can effectively address these needs. However, their success depends on consumer willingness to participate. This study quantifies load-shifting potentials from air conditioners, water heaters, electric vehicles, and washing machines based on survey data from 1,402 Japanese households. Logistic regression analyses link willingness to engage in DR programs with socio-demographic and dwelling characteristics, yielding specific participation rates by appliance and household type. These participation rates are integrated with appliance-specific ownership data and annual energy consumption calculations to estimate flexibility potentials for Japan's Kanto region. The study employs three distinct quantification approaches: (1) a bottom-up activity-based model, (2) a top-down average-based estimate, and (3) a hybrid method using synthetic population data. The results indicate that water heaters consistently exhibit the highest load-shifting potential across all scenarios and time frames, both per household and regionally. By 2050, electric vehicles emerge as an equally important source of flexibility due to increased adoption rates and improvements in water heater efficiency. While the top-down estimation method effectively captures overall population-level flexibility potentials, the hybrid approach is critical for accurately representing household-level variations. These findings facilitate the development of targeted DR programs and contribute to more realistic flexibility modeling within energy systems analysis. Future research should further explore behavioral uncertainties and address additional barriers to the implementation of residential demand response.

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