Representation of the German transmission grid for Renewable Energy Sources impact analysis

The increasing impact of fossil energy generation on the Earth ecological balance is pointing to the need of a transition in power generation technology towards the more clean and sustainable Renewable Energy Sources (RES). This transition is leading to new paradigms and technologies useful for the effective energy transmission and distribution, which take into account the RES stochastic power output. In this scenario, the availability of up to date and reliable datasets regarding topological and operative parameters of power systems in presence of RES are needed, for both proposing and testing new solutions. In this spirit, I present here a dataset regarding the German 380 KV grid which contains fully DC Power Flow operative states of the grid in the presence of various amounts of RES share, ranging from realistic up to 60\%, which can be used as reference dataset for both steady state and dynamical analysis.Comment: The dataset to which this paper refers can be found in: Mureddu, M. (2016). Representation of the German transmission grid for Renewable Energy Sources impact analysis.figshare. http://doi.org/10.6084/m9.figshare.4233782.v

A novel complex system approach for the determination of renewable energy sources impact on electricity infrastructures

The increasing environmental awareness, associated with the increasing demand and price of fossil fuels, is leading to the implementation of novel energy models based on renewable energy sources (RES) and sustainable mobility. However, the actual physical and economic models on which power system management rules are based on, are not able to properly manage the high amount of unwanted power fluctuations introduced by RES power generation. For such reason, major issues has been pointed out in term of energy security and access, inspiring changes in methods and paradigms associated to energy supply management. Moreover, the transaction towards an emission free mobility must be based on the interaction between RES generation and Electric Vehicles (EV) mobility, pointing out the need of a new approach able to combine mobility and energy supply infrastructures. In order to describe and model power systems with an high amount of RES generation, is important to indicate that such systems are made by a great number of microscopical interacting elements which behave in a stochastic way. For this reason, these systems can not easily be described in a deterministic way, but must be described by a statistical representation of the system observables. In this thesis, a novel approach based on statistical mechanics methods is presented, able to model the impact of such sources over the system. By using such approach, has been possible to evaluate the possible impact of such sources in terms of power system stability and sustainable mobility

A novel complex system approach for the determination of renewable energy sources impact on electricity infrastructures

The increasing environmental awareness, associated with the increasing demand and price of fossil fuels, is leading to the implementation of novel energy models based on renewable energy sources (RES) and sustainable mobility. However, the actual physical and economic models on which power system management rules are based on, are not able to properly manage the high amount of unwanted power fluctuations introduced by RES power generation. For such reason, major issues has been pointed out in term of energy security and access, inspiring changes in methods and paradigms associated to energy supply management. Moreover, the transaction towards an emission free mobility must be based on the interaction between RES generation and Electric Vehicles (EV) mobility, pointing out the need of a new approach able to combine mobility and energy supply infrastructures. In order to describe and model power systems with an high amount of RES generation, is important to indicate that such systems are made by a great number of microscopical interacting elements which behave in a stochastic way. For this reason, these systems can not easily be described in a deterministic way, but must be described by a statistical representation of the system observables. In this thesis, a novel approach based on statistical mechanics methods is presented, able to model the impact of such sources over the system. By using such approach, has been possible to evaluate the possible impact of such sources in terms of power system stability and sustainable mobility

A Statistical Approach for Modeling the Aging Effects in Li-Ion Energy Storage Systems

This paper presents a novel approach for the technical and economic assessment of Li-ion battery energy storage systems (BESS) in smart grids supported by renewable energy sources. The approach is based on the definition of a statistical battery degradation cost model (SBDCM), able to estimate the expected costs related to BESS aging, according to the statistical properties of its expected cycling patterns. This new approach can improve the assessment of the economical sustainability of BESSs in this kind of applications, helping in this way the planning processes in electricity infrastructures in presence of high penetration of intermittent renewable energy sources. The SBDCM proposed in this paper is a statistical generalization of a battery degradation model presented in the literature. The proposed approach has been validated numerically comparing the results with those of the deterministic model considering for the BESS a stochastic dataset of input signals. In order to test the usefulness of the proposed model in a real world application, the proposed SBDCM has been applied to the evaluation of the economic benefit associated to the development of distributed energy storage system scenarios in the Italian power system, aimed to provide ancillary services for supporting electricity market

Community core detection in transportation networks

This work analyses methods for the identification and the stability under perturbation of a territorial community structure with specific reference to transportation networks. We considered networks of commuters for a city and an insular region. In both cases, we have studied the distribution of commuters' trips (i.e., home-to-work trips and viceversa). The identification and stability of the communities' cores are linked to the land-use distribution within the zone system, and therefore their proper definition may be useful to transport planners.Comment: 8 pages, 13 figure

Blockchain-Based Hardware-in-the-Loop Simulation of a Decentralized Controller for Local Energy Communities

The development of local energy communities observed in the last years requires the reorganization of energy consumption and production. In these newly considered energy systems, the commercial and technical decision processes should be decentralized in order to reduce their maintenance costs. This will be allowed by the progressive spreading of IoT systems capable of interacting with distributed energy resources, giving local sources the ability to be optimally coordinated in terms of network and energy management. In this context, this paper presents a decentralized controlling architecture that performs a wide spectrum of power system optimization procedures oriented to the local market management. The controller framework is based on a decentralized genetic algorithm. The manuscript describes the structure of the tool and its validation, considering an automated distributed resource scheduling for local energy markets. The simulation platform permits implementing the blockchain-based trading process and the automated distributed resource scheduling. The effectiveness of the tool proposed is discussed with a hardware-in-the-loop case study

A genetic algorithm approach for the identification of microgrids partitioning into distribution networks

In this paper a Genetic Algorithm (GA) is used to partition a distribution network with the aim to minimize the energy exchange among the microgrids (i.e. maximize self-consumption) in presence of distributed generation. The proposed GA is tested on the IEEE prototypical network PG & E 69-bus. The microgrid partitioning is tested over a period of one year with hourly sampled data of real household consumption and real distributed generation data. The proposed GA approach is compared with a Tabu Search (TS) method already presented in the scientific literature. Results show that both GA and TS lead to the identification of equivalent microgrids. However, the GA based approach achieves better convergence results allowing for a reliable network partitioning with less CPU effort. Moreover, the histograms of the power unbalances of the microgrids show unimodal and skewed distributions offering an interesting starting point for the appropriate deployment of storage and control systems

Energy Blockchain for Public Energy Communities

This paper suggests an application of blockchain as an energy open data ledger, designed to save and track data regarding the energy footprint of public buildings and public energy communities. The developed platform permits writing energy production and consumption of public buildings using blockchain-enabled smart meters. Once authenticated on the blockchain, this data can be made available to the public domain for techno-economic analyses for either research studies and internal or third parties audits, increasing, in this way, the perceived transparency of the public institutions. A further feature of the platform, starting on the previously disclosed raw data, allows calculating, validating, and sharing sustainability indicators of public buildings and facilities, allowing the tracking of their improvements in sustainability goals. The paper also provides the preliminary results of a field-test experimentation of the proposed platform on a group of public buildings, highlighting the possible benefits of its widespread exploitation

A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility

We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas

2-arilbenzimidazoli come potenziali agenti antivirali e antitumorali

I derivati benzimidazolici trovano impiego in numerose patologie. Tra gli esempi di più estesa applicazione si ricordano i farmaci antielmintici per il loro meccanismo d’inibizione mitotica. Recentemente sono stati oggetto di valutazione anche come farmaci antivirali. Gli esempi riportati rappresentano la struttura di composti che mimano i nucleosidi purinici, nei quali la base è stata sostituita con il nucleo benzimidazolico