1,720,986 research outputs found
Dynamic analysis of an improved MPPT based on model predictive control applied to a single-ended primary-inductor converter
No full textPhotovoltaic (PV) systems are playing a major role in the energy transition towards renewables, and low power units are certainly key components in the smart city concept. Indeed, in urban environments it is mandatory to apply a suitable Maximum Power Point Tracking (MPPT) in order to maximize the efficiency and reduce the space occupancy. In this paper an improved MPPT-Predictive Control is proposed, to be applied to a PV panel connected by a Single-Ended Primary-Inductor Converter (SEPIC). The goal of this new technique is to reduce the hardware complexity (sensors number) of the classical Predictive Control technique and at the same time to keep its performance when the system works in buck or boost mode. The behavior of such a system is analyzed in all mode operations by means of a simulation model implemented in the Matlab/Simulink software environment, showing very good results
Open Switch Fault Diagnosis and Localization for Voltage Source Inverters in Synchronous Reluctance Motor Drives
No full textFault diagnosis and localization play a crucial role in the domain of motor drive systems to safeguard system integrity and optimize maintenance interventions. This paper proposes a new methodology to promptly diagnose and locate semiconductor open switch faults in power converters driving synchronous reluctance motor drives. In the exploration of innovative diagnostic methodologies, it is evident that the signal-based approach exhibits accuracy in identifying faults. Focusing on a signal-based approach, a novel algorithm is proposed and implemented in Matlab for fault detection and localization. In this paper, 27 types of different open-switch faults have been analyzed through a power-based diagnostic algorithm. The fault is diagnosed in less than 2 ms, corresponding to 2 % of the motor's current fundamental period. The performance of the proposed technique is analyzed through simulations, showing its effectiveness in enhancing the reliability of motor drive systems
The potential of urban PV generation in the Italian context of energy transition: A case study
No full textFifteen years after the connection of the first PV plant to the distribution network of the city of Milan, the role of this technology is more and more crucial, considering the Italian and European energy transition goals. The availability of a zero-emission modular and dispersed electricity generation could allow the cities to meet the growing electricity demand in the coming years in a sustainable way. The PV plants that could be installed on the roofs of city buildings represent a precious resource, which has only been partially exploited. Quantifying this available surface can help to understand the electricity generation potential in relation to the future scenarios of electricity demand. This paper aims to analyze these aspects focusing on the city of Milan (Italy), determining the total power that could be installed on the roofs, its potential contribution to the electricity balance of the network distribution in 2020-2030 and the benefits for the grid in relation to the system losses
Flexible resources dispatching to assist DR management in urban distribution network scenarios including PV generation. An Italian case study
No full textNowadays, Distributed System Operators (DSOs) are facing more and more difficult challenges in meeting the user needs with an increasing overall power demand, at the same time guaranteeing the required level of reliability. A possible solutions is offered by the Demand Response (DR) management, aiming to reduce the total load demand of the distribution system during peak periods in order to maintain the integrity of the network and stability of the whole system. The paper analyses different scenarios based on real data from the distribution grid of Milan (Italy), evaluating benefits and costs of DR implementation in three different plants, to solve problems related to feeders congestion, power losses, and voltage drops, through either the scheduling or remote control of distributed resources. Moreover, load shape considerations suggests the possibility to integrate in the system a higher share of photovoltaic (PV) generation, of which the effects on DR are also evaluated in the paper
Resilience of the Milan distribution network in presence of extreme events: Covid-19
No full textThe pandemic generated by Covid-19 caused social and economic consequences that constituted a global challenge for all countries. Italy was one of the first nations to be affected by the pandemic, especially in the heart of its production system and in the most densely populated area: The Lombardy Region. Starting in February 2020, there was a progressive slowdown until a total lockdown that paralyzed almost all social and economic activities, until a partial resumption of normal activities in May and a further increase in mid-June. The study was motivated by the fact that the electricity demand strongly decreased and changed in its typical characteristics, introducing new critical issues in the system at both the transmission and distribution levels. The goal was to analyze the strong impact of this changes on the distribution network and the transmission grid, focusing on the distribution network of Milan during the whole period. The results provide a useful example of the effects of such a pandemic and can constitute a reference valid also for many other big cities in the world
Open Switch Fault Diagnosis and Current Sensor Fault Tolerant Control of a DC-DC Interleaved Boost Converter using Generalized Proportional Integral Observer
No full textFault diagnosis and fault-tolerant control are important and stringent in the research field of renewable energy systems. Interleaved Boost DC-DC converters are today widely used in different applications such as PV or fuel cell-based systems and usually are operated in closed-loop control.This paper proposes an open-switch fault diagnosis and current sensor fault-tolerant control of a DC-DC interleaved boost converter using a Generalized Proportional Integral Observer (GPIO). First, an observer model is designed in order to estimate the current sensor fault. When the current sensor fault is reconstructed, it is compensated in the closed-loop control. Then, the compensated currents are used to diagnose the open switch fault based on the converter's currents variations. The main advantage of the proposed approach is that it is able to diagnose power semiconductor faults even under faulty current measurements. The performance and robustness of the proposed technique are validated through simulation results
Improvement of energy savings in electric railways using coasting technique
Full text linkThe main goal of this work is the evaluation of the energy saving achievable in railway drive when using the coasting technique extensively, with reference to a practical case of the Italian railway network taken as an example. This technique consists in exploiting the kinetic energy accumulated by the running train whenever possible. To implement a driving style on purpose, the only driver contribution is not enough; indeed, it is necessary to provide an embedded automatic calculation control system. In the paper, an algorithm has been developed to evaluate the energy absorption of railway locomotives during the normal service and validated on a real railway line. The proposed hardware and software system could be implemented aboard the train, allowing motion data processing in real-time. Speed, time intervals and power absorption for a given path are calculated; then, the best coasting parameters are estimated to maximize the energy savings. In particular, the case study presented in the paper showed that the fast-run strategy, always adopted by the railway company to recover an unexpected delay, can lead to a negligible time recovery with respect to the coasting strategy, while determining a significantly larger energy consumption
Design of an Efficient Energy Harvesting System for Smart Grid Connection Based on Piezoelectric Technology
No full textThe production of electrical energy is now a crucial component of the power system due to the rising demand brought on by population expansion and economic development. Experts are looking for new and more sustainable energy sources to meet the rising demand. One of the most promising methods in the sector is the application of piezoelectric material to transform environmental vibrations into electrical energy. The proposed study focuses on the design, optimization, and experimental validation of an effective piezoelectric-based energy-harvesting prototype that serves as the foundation for the development of a modular piezoelectric system to capture the kinetic energy of moving people and traffic for integration and connection with smart grids. In this study, four different configurations of two types of piezoelectric materials were examined and compared in both simulation and experimental tests. The four examined configurations are: series connection, parallel connection, series-parallel connection and parallel-series connection. Two different prototypes are implemented, which include eight piezoelectric elements. The amount of stored energy produced by both prototypes demonstrates how effective the parallel-series configuration is in terms of simulation and experimental results
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