Examinando por Autor "Ioakimidis, Christos S."

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    Life cycle assessment of a lithium iron phosphate (LFP) electric vehicle battery in second life application scenarios
    (MDPI, 2019-05-01) Ioakimidis, Christos S.; Murillo Marrodán, Alberto ; Bagheri, Ali; Thomas, Dimitrios; Genikomsakis, Konstantinos N.
    This paper presents a life cycle assessment (LCA) study that examines a number of scenarios that complement the primary use phase of electric vehicle (EV) batteries with a secondary application in smart buildings in Spain, as a means of extending their useful life under less demanding conditions, when they no longer meet the requirements for automotive purposes. Specifically, it considers a lithium iron phosphate (LFP) battery to analyze four second life application scenarios by combining the following cases: (i) either reuse of the EV battery or manufacturing of a new battery as energy storage unit in the building; and (ii) either use of the Spanish electricity mix or energy supply by solar photovoltaic (PV) panels. Based on the Eco-indicator 99 and IPCC 2007 GWP 20a methods, the evaluation of the scenario results shows that there is significant environmental benefit from reusing the existing EV battery in the secondary application instead of manufacturing a new battery to be used for the same purpose and time frame. Moreover, the findings of this work exemplify the dependence of the results on the energy source in the smart building application, and thus highlight the importance of PVs on the reduction of the environmental impact.
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    Simulation of wind-battery microgrid based on short-term wind power forecasting
    (MDPI AG, 2017-11-06) Genikomsakis, Konstantinos N.; López, Sergio; Dallas, Panagiotis I. ; Ioakimidis, Christos S.
    The inherently intermittent and highly variable nature of wind necessitates the use of wind power forecasting tools in order to facilitate the integration of wind turbines in microgrids, among others. In this direction, the present paper describes the development of a short-term wind power forecasting model based on artificial neural network (ANN) clustering, which uses statistical feature parameters in the input vector, as well as an enhanced version of this approach that adjusts the ANN output with the probability of lower misclassification (PLM) method. Moreover, it employs the Monte Carlo simulation to represent the stochastic variation of wind power production and assess the impact of energy management decisions in a residential wind-battery microgrid using the proposed wind power forecasting models. The results indicate that there are significant benefits for the microgrid when compared to the naïve approach that is used for benchmarking purposes, while the PLM adjustment method provides further improvements in terms of forecasting accuracy.
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    A university e-bike sharing system used as a real-time monitoring emissions tool under a smart city concept
    (AVERE, 2016-12-30) Ioakimidis, Christos S. ; Rycerski, Pawel; Koutra, Sesil; Genikomsakis, Konstantinos N.
    This work intents to describe a new approach that would be able to combine the positive effects from the use of an E-Bike sharing system in a medium-large population urban city of Belgium demonstrated initially in case of the local University Campuses along with the use of the E-Bikes as environmental mobile sensing units.