Demand response through automated air conditioning in commercial buildings - a data-driven approach

Building operation faces great challenges in electricity cost control as prices on electricity markets become increasingly volatile. Simultaneously, building operators could nowadays be empowered with information and communication technology that dynamically integrates relevant information sources, predicts future electricity prices and demand, and uses smart control to enable electricity cost savings. In particular, data-driven decision support systems would allow the utilization of temporal flexibilities in electricity consumption by shifting load to times of lower electricity prices. To contribute to this development, we propose a simple, general, and forward-looking demand response (DR) approach that can be part of future data-driven decision support systems in the domain of building electricity management. For the special use case of building air conditioning systems, our DR approach decides in periodic increments whether to exercise air conditioning in regard to future electricity prices and demand. The decision is made based on an ex-ante estimation by comparing the total expected electricity costs for all possible activation periods. For the prediction of future electricity prices, we draw on existing work and refine a prediction method for our purpose. To determine future electricity demand, we analyze historical data and derive data-driven dependencies. We embed the DR approach into a four-step framework and demonstrate its validity, utility and quality within an evaluation using real-world data from two public buildings in the US. Thereby, we address a real-world business case and find significant cost savings potential when using our DR approach

The token’s secret: the two-faced financial incentive of the token economy

Multi-sided platforms are omnipresent in today’s digital world. However, establishing a platform includes challenges: The platform utility usually increases with the number of participants. At an early stage, potential participants expect the platform utility to be low and lack an incentive to join (i.e., “chicken and egg” problem). Blockchain-enabled utility tokens hold the promise to overcome this problem. They supposedly provide a suitable financial incentive for their owners to join the platform as soon as possible. In the first half of 2018, investors seemed to believe in the presumption and spent more than US$ 17.6 billion in token sales. To date, we know little about this financial incentive in the context of the token economy. For this purpose, we model the token value development and the associated incentives in a multi-sided blockchain-enabled platform. The resulting findings suggest that blockchain-enabled utility tokens can help to overcome the “chicken and egg” problem. However, these tokens lead to contradictory incentives for platform participants, and can even inhibit platform usage. The contribution of our work is twofold: First, we develop one of the first models for token value development. Second, our research contributes to a deeper understanding of the utility token’s financial incentive

How different electricity pricing systems affect the energy trilemma: assessing Indonesia's electricity market transition.

Indonesia's current energy policy, which relies on cheap fossil fuels and focuses on two out of the three horns of the energy trilemma, namely, energy security and energy equity, may impede its efforts to higher shares of renewable energy sources. This paper develops three generic models that allow policymakers to analyze the impact of introducing a wholesale electricity market managed under either a nodal, a zonal, or a uniform pricing system on the three horns of the energy trilemma. It evaluates the models using a simplified network representation of the Indonesian electricity sector. The results indicate that under the model assumptions made, and given the used input parameters as well as the used metrics for the three horns of the energy trilemma, a uniform pricing system might help Indonesia to balance its energy trilemma

Excited States of Proton-bound DNA/RNA Base Homo-dimers: Pyrimidines

We are presenting the electronic photo fragment spectra of the protonated pyrimidine DNA bases homo-dimers. Only the thymine dimer exhibits a well structured vibrational progression, while protonated monomer shows broad vibrational bands. This shows that proton bonding can block some non radiative processes present in the monomer.Comment: We acknowledge the use of the computing facility cluster GMPCS of the LUMAT federation (FR LUMAT 2764

The sustainability imperative in information systems research

This paper reports on a panel discussion at the Pre-ICIS 2015 Workshop on Green Information Sys-tems on the current state and future perspectives of SIGGreen, the special interest group of the Association of Information Systems on green information systems. SIGGreen recognizes the central role of information systems (IS) in creating an ecologically sustainable society. Over the past years, IS scholars have made important contributions advancing our knowledge about how information systems can contribute to solving problems associated with the degradation of the natural envi-ronment. Still, it seems that green IS is, by and large, viewed as just another research branch in IS. We put forward the proposition that, to meet our social responsibility, green IS must not be treated as yet another IS research area. The problem addressed by green IS is simply too big. While, for instance, the awareness of the potential of information systems to increase productivity has been in our disciplines DNA for more than five decades, this is clearly not the case for the potential of information systems to achieve a sustainable world. We suggest that the IS community embraces sustainability as a research imperative and integrates sustainability related aspects in research across methods, theories, and areas

Probing the competition among different coordination motifs in metal-ciprofloxacin complexes through IRMPD spectroscopy and DFT calculations

The vibrational spectra of ciprofloxacin complexes with monovalent (Li+, Na+, K+, Ag+) and polyvalent (Mg2+, Al3+) metal ions are recorded in the range 1000-1900 cm(-1) by means of infrared multiple-photon dissociation (IRMPD) spectroscopy. The IRMPD spectra are analyzed and interpreted in the light of density functional theory (DFT)-based quantum chemical calculations in order to identify the possible structures present under our experimental conditions. For each metal-ciprofloxacin complex, four isomers are predicted, considering different chelation patterns. A good agreement is found between the measured IRMPD spectrum and the calculated absorption spectrum of the most stable isomer for each complex. Metal ion size and charge are found to drive the competition among the different coordination motifs: small size and high charge density metal ions prefer to coordinate the quinolone between the two carbonyl oxygen atoms, whereas large-size metal ions prefer the carboxylate group as a coordination site. In the latter case, an intramolecular hydrogen bond compensates the weaker interaction established by these cations. The role of the metal cation on the stabilization of ionic and nonionic structures of ciprofloxacin is also investigated. It is found that large-size metal ions preferentially stabilize charge separated motifs and that the increase of metal ion charge has a stabilizing effect on the zwitterionic form of ciprofloxacin

Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

Stable Lithium Argon compounds under high pressure

High pressure can fundamentally alter the bonding patterns of chemical elements. Its effects include stimulating elements thought to be “inactive” to form unexpectedly stable compounds with unusual chemical and physical properties. Here, using an unbiased structure search method based on CALYPSO methodology and density functional total energy calculations, the phase stabilities and crystal structures of Li−Ar compounds are systematically investigated at high pressure up to 300 GPa. Two unexpected Li(m)Ar(n) compounds (LiAr and Li(3)Ar) are predicted to be stable above 112 GPa and 119 GPa, respectively. A detailed analysis of the electronic structure of LiAr and Li(3)Ar shows that Ar in these compounds attracts electrons and thus behaves as an oxidizing agent. This is markedly different from the hitherto established chemical reactivity of Ar. Moreover, we predict that the P4/mmm phase of Li(3)Ar has a superconducting transition temperature of 17.6 K at 120 GPa

Design of agile supply chains including analysing the trade-off between number of partners and reliability

The reliability of supply partners is particularly vital in agile supply chains as it is vulnerable to the inability of a supply partner to meet its high responsiveness and flexibility requirements resulting in the disruption of the whole network. Disruption can have expensive and extensive results for the entire agile supply chain. To mitigate the risk of disruption and improve the reliability of the whole agile supply chain, decision-makers need to pay more attention to supply chain design and construction, whilst simultaneously taking into account the sourcing strategy decisions. This paper proposes a series of models for the design of agile supply chains using dynamic programming modelling. These provide decision-makers with a systematic way of analysing one of the key decisions of sourcing strategy, namely the trade-off between the number of supply partners and reliability. The efficacy of the models is demonstrated through their application to a Chinese bus and coach manufacturer by way of an empirical illustration. The results show that this approach is effective for this application and it can be applied in other related decision-making scenarios. The methods offered in this paper provide managers with a practical tool to design their agile supply chains while considering the trade-offs between the number of partners and the reliability of the entire agile supply chain