Local Energy
Recently Published Documents





Computation ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 98
Valeri Poltev ◽  
Victor M. Anisimov ◽  
Veronica Dominguez ◽  
Andrea Ruiz ◽  
Alexandra Deriabina ◽  

Deciphering the contribution of DNA subunits to the variability of its 3D structure represents an important step toward the elucidation of DNA functions at the atomic level. In the pursuit of that goal, our previous studies revealed that the essential conformational characteristics of the most populated “canonic” BI and AI conformational families of Watson–Crick duplexes, including the sequence dependence of their 3D structure, preexist in the local energy minima of the elemental single-chain fragments, deoxydinucleoside monophosphates (dDMPs). Those computations have uncovered important sequence-dependent regularity in the superposition of neighbor bases. The present work expands our studies to new minimal fragments of DNA with Watson–Crick nucleoside pairs that differ from canonic families in the torsion angles of the sugar-phosphate backbone (SPB). To address this objective, computations have been performed on dDMPs, cdDMPs (complementary dDMPs), and minimal fragments of SPBs of respective systems by using methods of molecular and quantum mechanics. These computations reveal that the conformations of dDMPs and cdDMPs having torsion angles of SPB corresponding to the local energy minima of separate minimal units of SPB exhibit sequence-dependent characteristics representative of canonic families. In contrast, conformations of dDMP and cdDMP with SPB torsions being far from the local minima of separate SPB units exhibit more complex sequence dependence.

Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5526
Iván González-Veloso ◽  
Nádia M. Figueiredo ◽  
M. Natália D. S. Cordeiro

This work aims at unravelling the interactions in magnetic ionic liquids (MILs) by applying Symmetry-Adapted Perturbation Theory (SAPT) calculations, as well as based on those to set-up a polarisable force field model for these liquids. The targeted MILs comprise two different cations, namely: 1-butyl-3-methylimidazolium ([Bmim]+) and 1-ethyl-3-methylimidazolium ([Emim]+), along with several metal halides anions such as [FeCl4]−, [FeBr4]−, [ZnCl3]− and [SnCl4]2− To begin with, DFT geometry optimisations of such MILs were performed, which in turn revealed that the metallic anions prefer to stay close to the region of the carbon atom between the nitrogen atoms in the imidazolium fragment. Then, a SAPT study was carried out to find the optimal separation of the monomers and the different contributions for their interaction energy. It was found that the main contribution to the interaction energy is the electrostatic interaction component, followed by the dispersion one in most of the cases. The SAPT results were compared with those obtained by employing the local energy decomposition scheme based on the DLPNO-CCSD(T) method, the latter showing slightly lower values for the interaction energy as well as an increase of the distance between the minima centres of mass. Finally, the calculated SAPT interaction energies were found to correlate well with the melting points experimentally measured for these MILs.

Walter Konhäuser

AbstractThe energy turnaround created a high volatility in the energy production based on renewable energy. To integrate renewable energy economically in buildings and smart cities an additional concept of energy storage and energy supply based on energy management concepts must be claimed. The political views have changed during the last years and energy efficiency in buildings is seen important because 35% of greenhouse gas is produced by the final energy consumption. The deployment of local energy production concepts is an important step to energy turnaround. To generate and distribute energy effectively in buildings, digital components such as sensors, actuators, meters, and energy management systems must be installed in the buildings and the digital components must be able to communicate via communication networks. The paper describes systems for local energy generation, necessary communication networks for buildings and smart cities and digitization applications in industrial buildings. As an example of energy management, the Oktett64 system is presented, which is based on Enterprise IT technology and has implemented AI and blockchain technology. Digitalization with platforms such as Oktett64 are based on technologies that are superior to today's often commercially available Programmable Logic Controllers. The article also shows how the future mobile communications standards 5G beyond and 6G can offer special solutions for the digitization of buildings in their edge clouds.

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5622
Justino Rodrigues ◽  
Carlos Moreira ◽  
João Peças Lopes

The Smart Transformer (ST) is being envisioned as the possible backbone of future distribution grids given the enhanced controllability it provides. Moreover, the ST offers DC-link connectivity, making it an attractive solution for the deployment of hybrid AC/DC distribution grids which offer important advantages for the deployment of Renewable Energy Sources, Energy Storage Systems (ESSs) and Electric Vehicles. However, compared to traditional low-frequency magnetic transformers, the ST is inherently more vulnerable to fault disturbances which may force the ST to disconnect in order to protect its power electronic converters, posing important challenges to the hybrid AC/DC grid connected to it. This paper proposes a Fault-Ride-Through (FRT) strategy suited for grid-tied ST with no locally available ESS, which exploits a dump-load and the sensitivity of the hybrid AC/DC distribution grid’s power to voltage and frequency to provide enhanced control to the ST in order to handle AC-side voltage sags. The proposed FRT strategy can exploit all the hybrid AC/DC distribution grid (including the MV DC sub-network) and existing controllable DER resources, providing FRT against balanced and unbalanced faults in the upstream AC grid. The proposed strategy is demonstrated in this paper through computational simulation.

2021 ◽  
Vol 11 (17) ◽  
pp. 8248
Eunsung Oh

This paper focuses on a virtual power plant (VPP) implementation strategy for smart local energy communities (SECs) with energy service providers. It is difficult to balance energy in the implementation stage due to uncertainties in demand and resources. Therefore, VPP implementation was modeled using the risk factor of energy balance. Using this risk factor, it was shown that the temporal correlation between demand and resources was the dominant factor involved in VPP implementation. Based on this, two risk-based VPP implementation strategies are proposed: an optimization-based strategy and a simple strategy that is solved in an iterative way. To minimize VPP implementation costs, the proposed strategies select the resources that have high correlation coefficients with demand and low correlation coefficients with other resources. Experimental results using real data sets show that the proposed strategies based on the risk factor are effective means of VPP implementation for commercial and residential SECs. The results imply that VPPs for commercial SECs are possible when PV is used as the main resource and is supplemented by wind, and it is effective to configure VPPs for residential SECs using wind according to the correlation between demand and resources.

2021 ◽  
Vol 9 ◽  
Yong Fan ◽  
Xianze Cui ◽  
Zhendong Leng ◽  
Junwei Zheng ◽  
Feng Wang ◽  

As a man-made engineering hazard, it is widely accepted that the rockbursts are the result of energy release. Previous studies have examined the unloading of in-situ stress resulting from deep tunnel excavation as a quasi-static process but the transient stress variation during excavation has received less attention. This research discusses rockbursts that happened during the construction of a diversion tunnel at Jinping II hydropower station. The brittle-ductile-plastic (BDP) transition property of Jinping marble was numerically described by the Hoek-Brown strength criterion, and the dynamic energy release process derived from the transient unloading of in-situ stress was studied using an index, local energy release rate. Studies have shown that, due to transient unloading, the strain energy of the surrounding rock mass goes through a dynamic process of decreasing at first, increasing second, then reducing before finally stabilizing. The first decrease of strain energy results from elastic unloading waves and does not cause brittle failure in rock masses, which is consistent with the elastic condition but the secondary reduction of strain energy is because the accumulated strain energy in rock masses exceeds the storage limit, which will inevitably trigger the brittle failure in the rock mass. Thus, the shorter the distance to the tunnel wall the bigger and more intense the energy release. Finally, a relationship between the average value of the local energy release rate and the rockburst intensity was established to assess the risk of rockburst induced by the blasting excavation of a deep tunnel.

2021 ◽  
Vol 7 ◽  
pp. 5269-5288
Claudia Antal ◽  
Tudor Cioara ◽  
Marcel Antal ◽  
Vlad Mihailescu ◽  
Dan Mitrea ◽  

2021 ◽  
Vol 4 (S3) ◽  
Enrico Toniato ◽  
Prakhar Mehta ◽  
Stevan Marinkovic ◽  
Verena Tiefenbeck

AbstractThe transport sector is responsible for 25% of global CO2 emissions. To reduce emissions in the EU, a shift from the currently 745,000 operating public buses to electric buses (EBs) is expected in the coming years. Large-scale deployments of EBs and the electrification of bus depots will have a considerable impact on the local electric grid, potentially creating network congestion problems and spikes in the local energy load. In this work, we implement an exact, offline, modular multi-variable mixed-integer linear optimization algorithm to minimize the daily power load profile peak and optimally plan an electric bus depot. The algorithm accepts a bus depot schedule as input, and depending on the user input on optimization conditions, accounts for varying time granularity, preemption of the charging phase, vehicle-to-grid (V2G) charging capabilities and varying fleet size. The primary objective of this work is the analysis of the impact of each of these input conditions on the resulting minimized peak load. The results show that our optimization algorithm can reduce peak load by 83% on average. Time granularity and V2G have the greatest impact on peak reduction, whereas preemption and fleet splitting have the greatest impact on the computational time but an insignificant impact on peak reduction. The results bear relevance for mobility planners to account for innovative fleet management options. Depot infrastructure costs can be minimized by optimally sizing the infrastructure needs, by relying on split-fleet management or V2G options.

Forecasting ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 596-632
Stephen Haben ◽  
Julien Caudron ◽  
Jake Verma

The energy sector is moving towards a low-carbon, decentralised, and smarter network. The increased uptake of distributed renewable energy and cheaper storage devices provide opportunities for new local energy markets. These local energy markets will require probabilistic price forecasting models to better describe the future price uncertainty. This article considers the application of probabilistic electricity price forecasting models to the wholesale market of Great Britain (GB) and compares them to better understand their capabilities and limits. One of the models that this paper considers is a recent novel X-model that predicts the full supply and demand curves from the bid-stack. The advantage of this model is that it better captures price spikes in the data. In this paper, we provide an adjustment to the model to handle data from GB. In addition to this, we then consider and compare two time-series approaches and a simple benchmark. We compare both point forecasts and probabilistic forecasts on real wholesale price data from GB and consider both point and probabilistic measures.

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5227
Laura Stößel ◽  
Leila Poddie ◽  
Tobias Spratte ◽  
Ralf Schelenz ◽  
Georg Jacobs

The pressure on the energy sector to reduce greenhouse gas emissions is increasing. In the light of current greenhouse gas emissions in the energy sector, further expansion of renewable energy sources (RES) is inevitable to reduce emissions and reach the climate goals. This study aims at investigating structural characteristics of German counties regarding advantages for self-sufficient power systems based on RES. The modelling of the power sector based on RES is coupled with a cluster analysis in order to draw a large-scale conclusion on structural characteristics beneficial or obstructive for municipal energy systems. Ten clusters are identified with the Ward algorithm in a hierarchical-agglomerative method. The results underline a further need for RES expansion projects in order to close the gap between supply and demand. Only then, bioenergy can effectively balance the offset and support a truly self-sufficient local energy system. While the model results indicate that the majority of the counties are suitable for further expansion, this suitability is to be questioned in cluster 10. High population density is a critical characteristic, because with it come both a high demand and limited sites for further RES expansion projects.

Sign in / Sign up

Export Citation Format

Share Document