512 research outputs found

    A Multi-Agent Energy Trading Competition

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    The energy sector will undergo fundamental changes over the next ten years. Prices for fossil energy resources are continuously increasing, there is an urgent need to reduce CO2 emissions, and the United States and European Union are strongly motivated to become more independent from foreign energy imports. These factors will lead to installation of large numbers of distributed renewable energy generators, which are often intermittent in nature. This trend conflicts with the current power grid control infrastructure and strategies, where a few centralized control centers manage a limited number of large power plants such that their output meets the energy demands in real time. As the proportion of distributed and intermittent generation capacity increases, this task becomes much harder, especially as the local and regional distribution grids where renewable energy generators are usually installed are currently virtually unmanaged, lack real time metering and are not built to cope with power flow inversions (yet). All this is about to change, and so the control strategies must be adapted accordingly. While the hierarchical command-and-control approach served well in a world with a few large scale generation facilities and many small consumers, a more flexible, decentralized, and self-organizing control infrastructure will have to be developed that can be actively managed to balance both the large grid as a whole, as well as the many lower voltage sub-grids. We propose a competitive simulation test bed to stimulate research and development of electronic agents that help manage these tasks. Participants in the competition will develop intelligent agents that are responsible to level energy supply from generators with energy demand from consumers. The competition is designed to closely model reality by bootstrapping the simulation environment with real historic load, generation, and weather data. The simulation environment will provide a low-risk platform that combines simulated markets and real-world data to develop solutions that can be applied to help building the self-organizing intelligent energy grid of the future

    Local electronic structure of the peptide bond probed by resonant inelastic soft X-ray scattering.

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    The local valence orbital structure of solid glycine, diglycine, and triglycine is studied using soft X-ray emission spectroscopy (XES), resonant inelastic soft X-ray scattering (RIXS) maps, and spectra calculations based on density-functional theory. Using a building block approach, the contributions of the different functional groups of the peptides are separated. Cuts through the RIXS maps furthermore allow monitoring selective excitations of the amino and peptide functional units, leading to a modification of the currently established assignment of spectral contributions. The results thus paint a new-and-improved picture of the peptide bond, enhance the understanding of larger molecules with peptide bonds, and simplify the investigation of such molecules in aqueous environment

    Coupling methylammonium and formamidinium cations with halide anions: Hybrid orbitals, hydrogen bonding, and the role of dynamics

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    The electronic structures of four precursors for organic–inorganic hybrid perovskites, namely, methylammonium chloride and iodide, as well as formamidinium bromide and iodide, are investigated by X-ray emission (XE) spectroscopy at the carbon and nitrogen K-edges. The XE spectra are analyzed based on density functional theory calculations. We simulate the XE spectra at the Kohn–Sham level for ground-state geometries and carry out detailed analyses of the molecular orbitals and the electronic density of states to give a thorough understanding of the spectra. Major parts of the spectra can be described by the model of the corresponding isolated organic cation, whereas high-emission energy peaks in the nitrogen K-edge XE spectra arise from electronic transitions involving hybrids of the molecular and atomic orbitals of the cations and halides, respectively. We find that the interaction of the methylammonium cation is stronger with the chlorine than with the iodine anion. Furthermore, our detailed theoretical analysis highlights the strong influence of ultrafast proton dynamics in the core-excited states, which is an intrinsic effect of the XE process. The inclusion of this effect is necessary for an accurate description of the experimental nitrogen K-edge X-ray emission spectra and gives information on the hydrogen-bonding strengths in the different precursor materials

    Direct Policy Search for Multiobjective Optimization of the Sizing and Operation of Citizen Energy Communities

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    Citizen Energy Communities (CECs) are increasingly promoted in the European Union and beyond as a form of locally operated microgrids. While traditional microgrid research is often focused on an optimized operation, individual preferences regarding conflicting objectives are becoming more important in such communities. In this study, we present an evolutionary algorithm that has previously been used for a multiobjective operation of microgrids and include the perspective of heat consumption and initial sizing decisions using direct policy search. This way, the developed tool can be used by CEC planners to integrate conflicting objectives of residents in the installation phase. We introduce the algorithm formulation and demonstrate its functionality on a case study for different ambient conditions. The results show the opportunities to size and operate CECs through the presented algorithm
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