The multiplex structure of interbank networks

The interbank market has a natural multiplex network representation. We employ a unique database of supervisory reports of Italian banks to the Banca d'Italia that includes all bilateral exposures broken down by maturity and by the secured and unsecured nature of the contract. We find that layers have different topological properties and persistence over time. The presence of a link in a layer is not a good predictor of the presence of the same link in other layers. Maximum entropy models reveal different unexpected substructures, such as network motifs, in different layers. Using the total interbank network or focusing on a specific layer as representative of the other layers provides a poor representation of interlinkages in the interbank market and could lead to biased estimation of systemic risk.Comment: 41 pages, 8 figures, 10 table

Interbank markets and multiplex networks: centrality measures and statistical null models

The interbank market is considered one of the most important channels of contagion. Its network representation, where banks and claims/obligations are represented by nodes and links (respectively), has received a lot of attention in the recent theoretical and empirical literature, for assessing systemic risk and identifying systematically important financial institutions. Different types of links, for example in terms of maturity and collateralization of the claim/obligation, can be established between financial institutions. Therefore a natural representation of the interbank structure which takes into account more features of the market, is a multiplex, where each layer is associated with a type of link. In this paper we review the empirical structure of the multiplex and the theoretical consequences of this representation. We also investigate the betweenness and eigenvector centrality of a bank in the network, comparing its centrality properties across different layers and with Maximum Entropy null models.Comment: To appear in the book "Interconnected Networks", A. Garas e F. Schweitzer (eds.), Springer Complexity Serie

Application of unscented Kalman filter for condition monitoring of an organic Rankine cycle turbogenerator

This work relates to a project focusing on energy optimiza-tion on offshore facilities. On oil and gas platforms it is common practice to employ gas turbines for power produc-tion. So as to increase the system performance and reduce emissions, a bottoming cycle unit can be designed with par-ticular emphasis on compactness and reliability. In such con-text, organic Rankine cycle turbogenerators are a promising technology. The implementation of an organic Rankine cy-cle unit is thus considered for the power system of the Drau-gen offshore platform in the northern sea, which is the case study for this project. Considering the plant dynamics, it is of paramount importance to monitor the peak temperatures within the once-through boiler serving the bottoming unit to prevent the decomposition of the working fluid. This paper accordingly aims at applying the unscented Kalman filter to estimate the temperature distribution inside the primary heat exchanger by engaging a detailed and distributed model of the system and available measurements. Simulation results prove the robustness of the unscented Kalman filter with re-spect to process noise, measurement disturbances and initial conditions. 1

Thermodynamic analysis of an integrated gasification solid oxide fuel cell plant combined with an organic Rankine cycle

A 100 kWe hybrid plant consisting of gasification system, solid oxide fuel cells and organic Rankine cycle is presented. The nominal power is selected based on cultivation area requirement. For the considered output a land of around 0.5 km2 needs to be utilized. Woodchips are introduced into a fixed bed gasification plant to produce syngas which fuels the combined solid oxide fuel cells e organic Rankine cycle system to produce electricity. More than a hundred fluids are considered as possible alternative for the organic cycle using non-ideal equations of state (or state-of-the-art equations of state). A genetic algorithm is employed to select the optimal working fluid and the maximum pressure for the bottoming cycle. Thermodynamic and physical properties, environmental impacts and hazard specifications are also considered in the screening process. The results suggest that efficiencies in the region of 54e56% can be achieved. The highest thermal efficiency (56.4%) is achieved with propylcyclohexane at 15.9 bar. A comparison with the available and future technologies for biomass to electricity conversion is carried out. It is shown that the proposed system presents twice the thermal efficiency achieved by simple and double stage organic Rankine cycle plants and around the same efficiency of a combined gasification, solid oxide fuel cells and micro gas turbine plant