Robust 24 Hours ahead Forecast in a Microgrid: A Real Case Study

Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and dispatching of the available assets. In this article, a methodology to provide the 24 h ahead Photovoltaic (PV) power forecast based on a Physical Hybrid Artificial Neural Network (PHANN) for microgrids is presented. The goal of this paper is to provide a robust methodology to forecast 24 h in advance the PV power production in a microgrid, addressing the specific criticalities of this environment. The proposed approach has to validate measured data properly, through an effective algorithm and further refine the power forecast when newer data are available. The procedure is fully implemented in a facility of the Multi-Good Microgrid Laboratory (MG(Lab)(2)) of the Politecnico di Milano, Milan, Italy, where new Energy Management Systems (EMSs) are studied. Reported results validate the proposed approach as a robust and accurate procedure for microgrid applications

Analyzing the Improvements of Energy Management Systems for Hybrid Electric Vehicles Using a Systematic Literature Review: How Far Are These Controls from Rule-Based Controls Used in Commercial Vehicles?

Featured Application This work is useful for researchers interested in the study of energy management systems for hybrid electric vehicles. In addition, it is interesting for institutions related to the market of this type of vehicle. The hybridization of vehicles is a viable step toward overcoming the challenge of the reduction of emissions related to road transport all over the world. To take advantage of the emission reduction potential of hybrid electric vehicles (HEVs), the appropriate design of their energy management systems (EMSs) to control the power flow between the engine and the battery is essential. This work presents a systematic literature review (SLR) of the more recent works that developed EMSs for HEVs. The review is carried out subject to the following idea: although the development of novel EMSs that seek the optimum performance of HEVs is booming, in the real world, HEVs continue to rely on well-known rule-based (RB) strategies. The contribution of this work is to present a quantitative comparison of the works selected. Since several studies do not provide results of their models against commercial RB strategies, it is proposed, as another contribution, to complete their results using simulations. From these results, it is concluded that the improvement of the analyzed EMSs ranges roughly between 5% and 10% with regard to commercial RB EMSs; in comparison to the optimum, the analyzed EMSs are nearer to the optimum than commercial RB EMSs

Model predictive control of a microgrid with energy-stored quasi-Z-source cascaded H-bridge multilevel inverter and PV systems

This paper presents a new energy management system (EMS) based on model predictive control (MPC) for a microgrid with solar photovoltaic (PV) power plants and a quasi-Z-source cascaded H-bridge multilevel inverter that integrates an energy storage system (ES-qZS-CHBMLI). The system comprises three modules, each with a PV power plant, quasi-impedance network, battery energy storage system (BESS), and voltage source inverter (VSI). Traditional EMS methods focus on distributing the power among the BESSs to balance their state of charge (SOC), operating in charging or discharging mode. The proposed MPC-EMS carries out a multi-objective control for an ES-qZS-CHBMLI topology, which allows an optimized BESS power distribution while meeting the system operator requirements. It prioritizes the charge of the BESS with the lowest SOC and the discharge of the BESS with the highest SOC. Thus, both modes can coexist simultaneously, while ensuring decoupled power control. The MPC-EMS proposed herein is compared with a proportional sharing algorithm based on SOC (SOC-EMS) that pursues the same objectives. The simulation results show an improvement in the control of the power delivered to the grid. The Integral Time Absolute Error, ITAE, achieved with the MPC-EMS for the active and reactive power is 20 % and 4 %, respectively, lower than that obtained with the SOC-EMS. A 1,3 % higher charge for the BESS with the lowest SOC is also registered. Furthermore, an experimental setup based on an OPAL RT-4510 unit and a dSPACE MicroLabBox prototyping unit is implemented to validate the simulation result

Multi-Objective Optimization of PV and Energy Storage Systems for Ultra-Fast Charging Stations

The installation of ultra-fast charging stations (UFCSs) is essential to push the adoption of electric vehicles (EVs). Given the high amount of power required by this charging technology, the integration of renewable energy sources (RESs) and energy storage systems (ESSs) in the design of the station represents a valuable option to decrease its impact on the grid and the environment. Therefore, this paper proposes a multi-objective optimization problem for the optimal sizing of photovoltaic (PV) system and battery ESS (BESS) in a UFCS of EVs. The proposed multi-objective function aims to minimize, on one side, the annualized cost of the station, and on the other side, the produced pollutant emissions. The decision variables are the number of PV panels and the capacity of the ESS to be installed. The optimization problem is reduced to a single-objective problem by applying the linear scalarization method. Then the equivalent single-objective function is optimized through a genetic algorithm (GA). The proposed optimization framework is applied to a study case and the results prove that PV and ESS could lead to a significant reduction of both the annualized cost and the pollutant emissions. Finally, a sensitivity analysis is also presented to validate the effectiveness of the proposed solution

Improvement of the Coupling of Renewable Sources through Z-Source Converters Based on the Study of Their Dynamic Model

The classical coupling of renewable energy sources greatly limits the coupling power and the output voltage of the coupled sources. Moreover, it does not eliminate the randomness of the sources. In this work a renewable sources coupling with high randomness is obtained by series connection of the output terminals of Z-source converters. To achieve the coupling, the stationary and dynamic models of a Z-source-based converter have been studied. With the results of the stationary model, the converter behavior has been evaluated as a function of its parameters and a method for calculating the Z-network parameters has been implemented. Moreover, with the dynamic model a controller has been designed for all the converters. The main contributions of this work are the coupling of the sources, the stationary and dynamic models obtained and their analysis. The coupling achieves a stable supply avoiding the sources' randomness reaching the load. A system composed of a wind turbine, a set of photovoltaic panels and two groups of batteries has been modeled. To study the system behavior and the supply quality, several aggressive tests have been forced and experimental evidence has also been provide

Clinical features and natural history of clinically non-functioning pituitary incidentalomas

ePoster presentation: pituitary and neuroendocrinologyDisclaimer: this is not the definitive version of record of this article. This manuscript has been accepted for publication in Endocrine Abstracts, but the version presented here has not yet been copy-edited, formatted or proofed. Consequently, Bioscientifica accepts no responsability for any errors or omissions it may contains. The definitive version in now freely avaliable at Endocrine Abstracts web page

Hydrogen based configurations for an overhead crane with quasi-Z-source inverter

Most of the overhead cranes used to date are powered by diesel engine or electrical grid and voltage source inverter. The economic and environmental costs of fossil fuels, and the unsteady price of electricity, encourage exploring new applications for developing electric power technologies. In this scenario, the main objective of this paper is to analyze the technical and economic feasibility of two new configurations based on hydrogen system and quasi-Z-source inverter (qZSI) for an overhead crane. The first configuration uses a fuel cell (FC) connected to a qZSI to supply the crane. The second one integrates an electrolyzer (LZ) as an energy storage system (ESS) into the impedance network of the qZSI (without additional DC/DC converter), which allows to recover energy during the regenerative braking of the crane and use it to produce hydrogen. The modelling and control are described, and short simulations of the working cycle of the crane under different initial hydrogen tank levels, and long simulations with several working cycles, are considered. The results show the technical viability of the two hydrogen-based configurations and the control systems implemented, since they can power the crane under all the situations studied. Nevertheless, the configuration with FC and LZ presents a higher energy efficiency (65% vs 44% with the FC-only configuration). Regarding the economic study, both configurations are compared with a diesel-based and with a full-electric configuration powered by the grid. Analyzing both hydrogen-based configurations, the results show that the configuration with FC and FZ becomes more profitable after 1.56 years, despite the higher initial cost. However, both configurations result more expensive than those based on diesel engine and fully powered by the grid. The two proposed configurations would be more cost-effective than the initial configuration in a plausible future with a 40% decrease in hydrogen cost14 página

Model Predictive Control-Based Optimized Operation of a Hybrid Charging Station for Electric Vehicles

This paper presents an energy management system (EMS) based on a novel approach using model predictive control (MPC) for the optimized operation of power sources in a hybrid charging station for electric vehicles (EVs). The hybrid charging station is composed of a photovoltaic (PV) system, a battery, a complete hydrogen system based on a fuel cell (FC), electrolyzer (EZ), and tank as an energy storage system (ESS), grid connection, and six fast charging units, all of which are connected to a common MVDC bus through Z-source converters (ZSC). The MPC-based EMS is designed to control the power flow among the energy sources of the hybrid charging station and reduce the utilization costs of the ESS and the dependency on the grid. The viability of the EMS was proved under a long-term simulation of 25 years in Simulink, using real data for the sun irradiance and a European load profile for EVs. Furthermore, this EMS is compared with a simpler alternative that is used as a benchmark, which pursues the same objectives, although using a states-based strategy. The results prove the suitability of the EMS, achieving a lower utilization cost (-25.3%), a notable reduction in grid use (-60% approximately) and an improvement in efficiency

Averaged Dynamic Modeling and Control of a Quasi-Z-Source Inverter for Wind Power Applications

Typically, permanent magnet synchronous generator (PMSG)-driven wind turbines (WTs) present a two-stage power converter topology based on a DC/DC boost converter and voltage source inverter. In this study, this configuration is substituted by a quasi-Z-source inverter (qZSI), which is an attractive solution for boosting and converting the voltage from DC to AC in a single stage. A 2 MW PMSG WT with qZSI was studied herein. A switched dynamic model (SDM) of the qZSI (including the modeling of all switches and firing pulses) is not recommended for steady-state stability studies, long-term simulations, or large electric power systems. For such studies, two averaged dynamic models are proposed in this work. Both models present the same control system as the SDM, except for the generation of firing pulses, which is not necessary in the averaged models. The two proposed models were evaluated and compared with the SDM in the large-scale WT under different operating conditions, such as wind speed fluctuations, variable power references, and grid disturbances (voltage sag and 3(rd) and 5(th) order harmonics injection), in order to demonstrate their adequacy to represent the system response with a high reduction in the simulation time and computational efforts.This work was supported in part by the Spain's Ministerio de Ciencia, Innovacion y Universidades (MCIU), Agencia Estatal de Investigacion (AEI), and Fondo Europeo de Desarrollo Regional (FEDER) Union Europea (UE) under Grant RTI2018-095720-B-C32, in part by the National Council of Technological and Scientific Development (CNPq), Brazil, in part by the Federal Center for Technological Education of Minas Gerais, Brazil, under Process 23062-010087/2017-51, and in part by the Regional Ministry of Economic Transformation, Industry, Knowledge and Universities of Junta de Andalucia under Grant PY20_00317