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Conference

International Youth Conference on Energy 

About: International Youth Conference on Energy is an academic conference. The conference publishes majorly in the area(s): Renewable energy & Photovoltaic system. Over the lifetime, 310 publications have been published by the conference receiving 915 citations.

Papers published on a yearly basis

Papers
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Proceedings ArticleDOI
21 Jun 2017
TL;DR: In this paper, a state-of-the-art review of three artificial intelligence techniques for short-term electric load forecasting is comprehensively presented, including artificial neural network, support vector machine, and adaptive neuro-fuzzy inference system.
Abstract: According to privatization and deregulation of power system, accurate electric load forecasting has come into prominence recently. The new energy market and the smart grid paradigm ask for both better demand side management policies and for more reliable forecasts from single end-users, up to system scale. However, it is complex to predict the electric demand owing to the influencing factors such as climate factors, social activities, and seasonal factors. The methods developed for load forecasting are broadly analyzed in two categories, namely analytical techniques and artificial intelligence techniques. In the literature, commonly used analytical methods are linear regression method, Box-Jenkins method, and nonparametric regression method. The analytical methods work well under normal daily circumstances, but they can't give contenting results while dealing with meteorological, sociological or economical changes, hence they are not updated depending on time. Therefore, artificial intelligence techniques have gained importance in reducing estimation errors. Artificial neural network, support vector machine, and adaptive neuro-fuzzy inference system are among these artificial intelligence techniques. In this paper, a state-of-the-art review of three artificial intelligence techniques for short-term electric load forecasting is comprehensively presented.

71 citations

Proceedings ArticleDOI
06 Jun 2013
TL;DR: In this paper, the grey-box modeling of a vapor-compression refrigeration system for residential applications based on maximum likelihood estimation of parameters in stochastic differential equations is presented.
Abstract: This paper presents the grey-box modeling of a vapor-compression refrigeration system for residential applications based on maximum likelihood estimation of parameters in stochastic differential equations. Models obtained are useful in the view of controlling refrigerators as flexible consumption units, which operation can be shifted within temperature and operational constraints. Even if the refrigerators are not intended to be used as smart loads, validated models are useful in predicting units consumption. This information can increase the optimality of the management of other flexible units, such as heat pumps for space heating, in order to smooth the load factor during peak hours, enhance reliability and efficiency in power networks and reduce operational costs.

33 citations

Proceedings ArticleDOI
27 May 2015
TL;DR: In this paper, an intelligent residential demand side management (DSM) system for a rooftop installed residential PV is introduced, which aims to reduce costs of the customer and also power losses on the grid.
Abstract: Lately, over the past decade both the growing environmental awareness and the subsidies provided for renewable energy sources triggered a remarkable residential investment in photovoltaic (PV) systems. Although this is a desirable change, the effects of these widespread distributed energy resources (DER) have to be considered, both financial and technical aspects. The intermittent electricity production of PV systems brings several issues on the grid operator's side. In order to be able to control and take the DER's production into the grid without risking power quality, demand side management (DSM) can make positive effects on this issue at residential level. Also the electricity provider's tariff structure has to be considered at the optimization of the monetary costs. In this paper an intelligent residential DSM system for a rooftop installed residential PV is introduced. The applied DSM technique aims to reduce costs of the customer and also power losses on the grid. In order to avoid reducing the consumer's convenience significantly, a scheduling algorithm is applied, using historical data of the consumer's habits and PV generation forecasts.

20 citations

Proceedings ArticleDOI
06 Jun 2013
TL;DR: In this paper, the authors presented a case study where an existing twin gas station would be converted to a fully electric charging station and investigation on the impact of the additional electricity demand onto the supplying medium voltage (MV) grid is carried through.
Abstract: Electric vehicle batteries have to be recharged either by means of low-charging at home or at parking lots or at fast charging stations. Fast chargers may re-charge the battery in less than 15 minutes, but this technology requires a bigger amount of power capacity from the electrical grid. Thus, it is a plausible assumption that these charging stations will be supplied from the medium voltage (MV) grid and will be constructed alongside motorways in a similar way than the gasoline stations exist today. In the case study going to be presented in the paper, it is supposed that an existing twin gas station would be altered to a fully electric charging station and investigation on the impact of the additional electricity demand onto the supplying MV grid is carried through. The grid model is constructed in DIgSILENT Power Factory software based on measurement data from the local DSO. Simulations to determine the voltage drop along the lines and the loading of the secondary supply cable between the twin stations are conducted.

20 citations

Proceedings ArticleDOI
06 Jun 2013
TL;DR: In this article, the authors present the procedure for the evaluation of the risk connected to lightning strikes according to the Standard IEC EN 62305-2; then it applies the procedure to typical PV installations, analyzing risks and risk components which have to be kept into account.
Abstract: Lightning strikes can affect photovoltaic (PV) generators and their installations, involving also the inverter's electronics. It is therefore necessary to evaluate the risk connected to lightning strikes in order to adopt the correct protective measures for the system. The Standard IEC (EN) 62305-2 reports the procedures for the risk calculation and for the choice of proper lightning protection systems. Usually the technical guidelines suggest protecting with SPDs (surge protective devices) both DC and AC sides of the PV installation. The paper estimates overvoltages due to lightning discharges and evaluates the actual need of lightning protection measures on the basis of the results of the risk analysis and of the protection costs. The paper in the first part presents the procedure for the evaluation of the risk connected to lightning strikes according to the Standard IEC EN 62305-2; then it applies the procedure to typical PV installations, analyzing risks and risk components which have to be kept into account. In the second part the paper studies the surge overcurrents to be expected on LV systems, induced voltages caused by direct flashes and by flashes near the PV installation. Approximated equations for the calculation of induced voltages and currents are given for different types of LPS (lightning protection systems) and lightning flashes. In the last part of the paper the methodology is applied as an example to a practical case and some conclusions are given.

17 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
202230
201943
201761
201596
201380