La filiera fotovoltaica e le varie tipologie di pannelli fotovoltaici

2008-09-19Sala anfiteatro, Via Roma 253, CagliariSeminario tecnico sugli impianti fotovoltaici per amministrazioni ed enti pubblic

A Novel Highly Integrated Hybrid Energy Storage System for Electric Propulsion and Smart Grid Applications

This chapter addresses potentialities and advantages of a highly integrated hybrid energy storage system (HESS) for electric propulsion and smart grids. This configuration consists of a highly integrated battery-ultracapacitor system (HIBUC) and aims to benefit from the advantages of both passive and active HESS configurations. Particularly, the integration of the ultracapacitor module (UM) within the DC-link of the DC/AC multilevel converter enables the decoupling between DC-link voltage and energy content without the need for any additional DC/DC converter. As a result, HIBUC benefits from simplicity and energy flow management capabilities very similar to those achieved by passive and active HESS configurations, respectively. This is highlighted properly by a theoretical analysis, which also accounts for a comparison between HIBUC and both passive and active HESS configurations. Some HIBUC application examples are also reported, which highlight the flexibility and potentialities of HIBUC for both electric propulsion systems and smart grids

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

Il laboratorio fotovoltaico del cluster tecnologico energie rinnovabili

2007-11-28Sardegna Ricerche, Edificio 2, Località Piscinamanna 09010 Pula (CA) - ItaliaPresentazione del Progetto Cluster Solare fotovoltaico in Sardegn

Il laboratorio fotovoltaico: attività svolte e agenda dei lavori

2008-04-18Sala conferenze CIS, CagliariPresentazione del Laboratorio fotovoltaico del Cluster Energie rinnovabil

Energy Management and Control System Design of an Integrated Flywheel Energy Storage System for Residential Users

This paper presents the energy management and control system design of an integrated flywheel energy storage system (FESS) for residential users. The proposed FESS is able to draw/deliver 8 kWh at 8 kW, and relies on a large-airgap surface-mounted permanent magnet synchronous machine, the inner rotor of which integrates a carbon-fiber flywheel, leading to a compact and efficient FESS. The proposed energy management system is based on four different operating modes, which are defined and can be selected in accordance with FESS speed and/or user’s preference, while FESS control system is devoted to power/current tracking at both machine- and grid-side converters. The effectiveness of the proposed solutions, as well as the overall energy performance of the proposed FESS, are verified by real-time simulations, which regard different operating conditions and/or realistic scenarios

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

A Forecasting-Based Control Algorithm for Improving Energy Management in High Concentrator Photovoltaic Power Plant Integrated with Energy Storage Systems

The High Concentrator Photovoltaic (HCPV) technology, due to its high efficiency, is considered one of the most promising solutions for the exploitation of sun-irradiation-based Renewable Energy Sources (RES). Nevertheless, the HCPV production is strictly connected to the Direct Normal Irradiation (DNI) making this photovoltaic technology more sensible to cloudiness than traditional ones. In order to mitigate the power intermittence and improve production programmability, the integration between Energy Storage Systems (ESSs) and HCPV, resorting to forecasting algorithms, has been investigated. Specifically, a local weather forecasting algorithm has been used for estimating the daily time evolution of DNI, air Temperature (T), Wind Speed (WS), and Air Mass (AM). These data are subsequently processed by means of an accurate HCPV model for the estimation of one day-ahead daily power production profile. The processing of HCPV forecasted generation by means of a properly tuned filter-based algorithm allows one day-ahead the definition of power profiles of ESS and power plant respectively, considering also the ESS constraints and the characteristic of the implemented real-time control algorithm. The effectiveness of the proposed forecasting model and control algorithm is verified through a simulation study referring to the solar power plant constituted by HCPV and ESS installed in Ottana, Italy. The results highlight that the application of the proposed approach lessens the power fluctuation effect caused by HCPV generation preserving the batteries at the same time. The feasibility and advantages of the proposed approach are finally presented