Wireless Power Transfer for Distributed Energy Sources Exploitation in DC Microgrids

Baros, Dimitris; Voglitsis, Dionisis; Papanikolaou, Nick; Kyritsis, Anastasios; Rigogiannis, Nick

doi:10.1109/tste.2018.2877902

Cited by 26 publications

(26 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…DC microgrids are composed of renewable energy, energy storage devices, and electronic loads, which are interconnected by means of DC/DC power converters. Their efficiency is improved by the simplicity of their control states and the reduction in energy conversion stages [7].…”

Section: Introductionmentioning

confidence: 99%

Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models

et al. 2019

View full text Add to dashboard Cite

This paper addresses the optimal dispatch problem for battery energy storage systems (BESSs) in direct current (DC) mode for an operational period of 24 h. The problem is represented by a nonlinear programming (NLP) model that was formulated using an exponential voltage-dependent load model, which is the main contribution of this paper. An artificial neural network was employed for the short-term prediction of available renewable energy from wind and photovoltaic sources. The NLP model was solved by using the general algebraic modeling system (GAMS) to implement a 30-node test feeder composed of four renewable generators and three batteries. Simulation results demonstrate that the cost reduction for a daily operation is drastically affected by the operating conditions of the BESS, as well as the type of load model used.

show abstract

Section: Introductionmentioning

confidence: 99%

Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The advantages of DC distribution systems, compared to their AC counterparts have been extensively presented in the scientific literature over the past few years, including higher efficiency and reliability with simpler control schemes. Furthermore, modern power systems, such as the M/A-EA distribution network, feature various electronic loads, energy storage systems and distributed power units, which are in their vast majority DC or (at least) adopt an intermediate DC-link, leading so to DC distribution architectures [12][13][14][15][16].…”

Section: Of 22mentioning

confidence: 99%

“…It is noted that in our application, non-synchronous operation is considered. The amount of the recovered stored charge (Q r ), which is used in the following Equations (15) and (19), can be defined as the integral of the antiparallel diode current over the t r time interval, which corresponds to the duration of the reverse recovery process [23] and it is available in the NVHL160N120SC1 SiC MOSFET datasheet [28]. According to [23] and the qualitative representation of switches transitions in Figure 6, the energy being dissipated during the turn-on transition is calculated as:…”

Section: Power Losses Analysismentioning

confidence: 99%

Voltage Transients Mitigation in the DC Distribution Network of More/All Electric Aircrafts

Rigogiannis

Voglitsis²,

Jappe³

et al. 2020

Energies

Self Cite

View full text Add to dashboard Cite

The objective of this paper is to present a power conversion system, based on a bidirectional DC/DC converter, along with a supercapacitor bank, that mitigates the voltage transients that occur on the DC distribution network of More/All Electric Aircrafts. These transients, such as voltage sags and swells appear on the DC buses of on-board microgrids, mainly due to load variations and are classified according to the aircrafts electric power system standards. First, we shortly describe an aircraft distribution network, that is applicable to the most common actual aircraft architectures, then we present the proposed system, along with the bidirectional DC/DC converter design, the control technique and the supercapacitor bank sizing. Finally, we present simulation and experimental results that support the effectiveness of the proposed system to effectively compensate voltage transients, supporting the DC buses in dynamic conditions. Concluding, the proposed system provides high power quality and compliance with the respective power quality standards for aircraft microgrids.

show abstract

“…To date, a large number of studies have been conducted to determine the PDFs that provide for accurate renewable power generation prediction models. The variety of distributions used to model wind and solar forecast error range from normal distribution [9][10][11], the Weibull distribution [32][33][34][35][36], mixed distribution based on Laplace and normal distributions [37], the Beta distribution [38], the hyperbolic distribution [39], and the Levy α-stable distribution [40].…”

Section: Wind Power Outputmentioning

confidence: 99%

Optimal Allocation of Spinning Reserves in Interconnected Energy Systems with Demand Response Using a Bivariate Wind Prediction Model

2019

View full text Add to dashboard Cite

The proposed study presents a novel probabilistic method for optimal allocation of spinning reserves taking into consideration load, wind and solar forecast errors, inter-zonal spinning reserve trading, and demand response provided by consumers as a single framework. The model considers the system contingencies due to random generator outages as well as the uncertainties caused by load and renewable energy forecast errors. The study utilizes a novel approach to model wind speed and its direction using the bivariate parametric model. The proposed model is applied to the IEEE two-area reliability test system (RTS) to analyze the influence of inter-zonal power generation and demand response (DR) on the adequacy and economic efficiency of energy systems. In addition, the study analyzed the effect of the bivariate wind prediction model on obtained results. The results demonstrate that the presence of inter-zonal capacity in ancillary service markets reduce the total expected energy not supplied (EENS) by 81.66%, while inclusion of a DR program results in an additional 1.76% reduction of EENS. Finally, the proposed bivariate wind prediction model showed a 0.27% reduction in spinning reserve requirements, compared to the univariate model.

show abstract

Wireless Power Transfer for Distributed Energy Sources Exploitation in DC Microgrids

Cited by 26 publications

References 33 publications

Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models

Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models

Voltage Transients Mitigation in the DC Distribution Network of More/All Electric Aircrafts

Optimal Allocation of Spinning Reserves in Interconnected Energy Systems with Demand Response Using a Bivariate Wind Prediction Model

Contact Info

Product

Resources

About