Revistas
Autores:
Samanbakhsh, R. (Autor de correspondencia); Koohi, P.; Martín Ibañez, F.; et al.
Revista:
INTERNATIONAL JOURNAL OF ELECTRICAL POWER AND ENERGY SYSTEMS
ISSN:
0142-0615
Año:
2023
Vol.:
147
Págs.:
108819
Z-source inverters are essential to electrical power systems, renewable energy conversion, and numerous other industrial applications. The efficiency and performance of power systems can be improved by using them. Due to their single-stage buck-boost inversion ability and better immunity to EMI noise, research on Z-source inverters has recently been significantly intensified. As known, the immunity to EMI noise is important since affect circuits and prevent them from working correctly. However, their boost gains are restricted because of higher component-voltage stresses and poor output power quality. A new structure of switched network quasi Z-source inverter (SN-qZSI) is proposed to mitigate these drawbacks. The proposed inverter structure has a very high voltage boost gain at a low shoot through duty ratio and high modulation index to reduce the semiconductor stress. Also provides a better-quality output waveform. Furthermore, the proposed structure applies less voltage across its capacitors. Therefore, the installation cost, and weight can be reduced by using lower rating capacitors. Moreover, this suggested structure can also overcome the problem of starting inrush current. The proposed in-verter's operating principle, steady-state analysis, and impedance parameter selections are presented. In addi-tion, the proposed structure of the Z-source inverter is compared with other impedance-source inverters to highlight its features. Both simulation (Matlab/Simulink) and experimental results in a scaled-down prototype successfully validated the proposed theoretical analysis.
Autores:
Davalos Hernández, F. (Autor de correspondencia); Samanbakhsh, R.; Martin Ibáñez, F.; et al.
Revista:
ENERGIES
ISSN:
1996-1073
Año:
2022
Vol.:
15
N°:
1
Págs.:
338
Energy Storage Systems (ESS) are an attractive solution in environments with a high amount of renewable energy sources, as they can improve the power quality in such places and if required, can extend the integration of more renewable sources of energy. If a large amount of power is needed, then supercapacitors are viable energy storage devices due to their specific power, allowing response times that are in the range of milliseconds to seconds. This paper details the design of an ESS that is based on a modular multilevel converter (MMC) with bidirectional power flow, which reduces the number of cascaded stages and allows the supercapacitors SCs to be connected to the grid to perform high-power transfers. A traditional ESS has four main stages or subsystems: the energy storage device, the balancing system, and the DC/DC and DC/AC converters. The proposed ESS can perform all of those functions in a single circuit by adopting an MMC topology, as each submodule (SM) can self-balance during energy injection or grid absorption. This article analyses the structure in both power flow directions and in the control loops and presents a prototype that is used to validate the design.
Autores:
Samanbakhsh, R.; Ibáñez, F. M.; Koohi, P.; et al.
Revista:
IEEE ACCESS
ISSN:
2169-3536
Año:
2021
Vol.:
9
Págs.:
92276 - 92287
This paper presents a new structure of a multilevel inverter with fewer components, which is suitable for renewable energy sources and industrial loads applications. The structure has three unequal input sources and ten switches that can generate a 15-level output voltage. Furthermore, it can be connected in cascade for increasing, even more, the number of levels and output voltage. The main feature of the proposed inverter is its very low harmonic distortion at the output voltage and current due to the control method, which is based on the nearest level control method for generating a high-quality output voltage. A typical application of this inverter is in solar cells and wind turbines. Both simulations in Matlab/Simulink and experimental results in a scaled-down prototype validate the proposed theoretical analysis.
Revista:
ENERGY
ISSN:
0360-5442
Año:
2021
Vol.:
229
Págs.:
120647
Photovoltaic generation has arisen as a solution for the present energy challenge. However, power obtained through solar technologies has a strong correlation with certain meteorological variables such as solar irradiation, wind speed or ambient temperature. As a consequence, small changes in these variables can produce unexpected deviations in energy production. Although many research articles have been published in the last few years proposing different models for predicting these parameters, the vast majority of them do not consider spatiotemporal parameters. Hence, this paper presents a new solar irradiation forecaster which combines the advantages of machine learning and the optimisation of both spatial and temporal parameters in order to predict solar irradiation 10 min ahead. A validation step demonstrated that the deviation between the actual and forecasted solar irradiation was lower than 4% in 82.95% of the examined days. With regard to the error metrics, the root mean square error was 50.80 W/m(2), an improvement of 11.27% compared with the persistence model, which was used as a benchmark. The results indicate that the developed forecaster can be integrated into photovoltaic generators' to predict their output power, thus promoting their inclusion in the main power network. (C) 2021 Elsevier Ltd. All rights reserved.
Revista:
IEEE TRANSACTIONS ON ENERGY CONVERSION
ISSN:
0885-8969
Año:
2020
Vol.:
35
N°:
2
Págs.:
733 - 745
This article analyzes a stochastic supercapacitor model and uses the model to estimate the losses for different balancing methods. In addition, it proposes guidelines for designing a supercapacitor bank that includes balancing networks. Supercapacitors (SCs) can be used as the main part of an energy storage system (ESS) that transfers high power to a DC or AC grid. This is needed in grids with a high penetration of renewable energies in order to balance generation and consumption. The design method is based on a supercapacitor model which uses stochastic variables: capacitance, series resistance and self-discharge current. As the balancing network affects the overall efficiency of the SC bank, dissipative and non-dissipative balancing networks are studied. Then different strategies are compared taking into account the complexity, cost and efficiency of the balancing network in the bank.
Revista:
ELECTRIC POWER SYSTEMS RESEARCH
ISSN:
0378-7796
Año:
2020
Vol.:
185
Págs.:
106369
This paper proposes a Field Oriented Control (FOC) for a Permanent Magnet Synchronous Machine (PMSM) which is supplied by a Parallel Multi-Inverter System. The parallelization of the Voltage Source Inverters is safely achieved using a V-f Droop Control strategy as a distributed generation system would be considered like in Smart-Grids. This novel technique is the combination of the previous mentioned both strategies, and will be key when answering to the need of modularity, scalability, redundancy and parallelization for electrical machine control systems. Theoretical and experimental analysis are provided in order to validate the new combined control strategy which fulfills the motor control requirements while current balancing is safely achieved between individual parallelized inverters.
Revista:
SENSORS AND ACTUATORS A-PHYSICAL
ISSN:
0924-4247
Energy distribution companies have experienced an increase in catastrophic failures in power systems due to the theft of grounding cable. The objective of this study is to develop an innovative technology which is able to detect the absence of grounding cable in medium and high voltage systems. The wireless technology developed communicates periodically with the system's central control unit to ensure reliable and safe operation of the installation. Because it is not economically profitable to modify power systems' infrastructure, this novel sensor is non-intrusive as well as self-supplying. Based on the validation step's results, we conclude that the sensor is ready to be tested in smart grid equipment to monitor the state of grounding cables. (C) 2020 Elsevier B.V. All rights reserved.
Revista:
ENERGIES
ISSN:
1996-1073
Año:
2020
Vol.:
13
N°:
19
Electrical load forecasting plays a crucial role in the proper scheduling and operation of power systems. To ensure the stability of the electrical network, it is necessary to balance energy generation and demand. Hence, different very short-term load forecast technologies are being designed to improve the efficiency of current control strategies. This paper proposes a new forecaster based on artificial intelligence, specifically on a recurrent neural network topology, trained with a Levenberg-Marquardt learning algorithm. Moreover, a sensitivity analysis was performed for determining the optimal input vector, structure and the optimal database length. In this case, the developed tool provides information about the energy demand for the next 15 min. The accuracy of the forecaster was validated by analysing the typical error metrics of sample days from the training and validation databases. The deviation between actual and predicted demand was lower than 0.5% in 97% of the days analysed during the validation phase. Moreover, while the root mean square error was 0.07 MW, the mean absolute error was 0.05 MW. The results suggest that the forecaster's accuracy is considered sufficient for installation in smart grids or other power systems and for predicting future energy demand at the chosen sites.