17 research outputs found

    Analysis of harmonic current interaction in an industial plant

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    An analysis of current transients caused by the operation of a nearby device in an industrial plant is presented in the paper. The source of current transients in the factory lighting system was traced to the operation of the nearby six-pulse AC/DC converter. To determine the nature of the interaction, a measurement was done with a storage oscilloscope. Also, laboratory experiments on one lamp were conducted. It was possible to exclude the presence of a parallel resonance on this site. It was concluded that transients are caused by voltage notches in certain working regimes of the six-pulse converter. Possible solutions to the problem are separating the supplies of the converter and the lighting installation, filtering, or adding additional line reactance

    Support Vector Machine in Prediction of Building Energy Demand Using Pseudo Dynamic Approach

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    Building's energy consumption prediction is a major concern in the recent years and many efforts have been achieved in order to improve the energy management of buildings. In particular, the prediction of energy consumption in building is essential for the energy operator to build an optimal operating strategy, which could be integrated to building's energy management system (BEMS). This paper proposes a prediction model for building energy consumption using support vector machine (SVM). Data-driven model, for instance, SVM is very sensitive to the selection of training data. Thus the relevant days data selection method based on Dynamic Time Warping is used to train SVM model. In addition, to encompass thermal inertia of building, pseudo dynamic model is applied since it takes into account information of transition of energy consumption effects and occupancy profile. Relevant days data selection and whole training data model is applied to the case studies of Ecole des Mines de Nantes, France Office building. The results showed that support vector machine based on relevant data selection method is able to predict the energy consumption of building with a high accuracy in compare to whole data training. In addition, relevant data selection method is computationally cheaper (around 8 minute training time) in contrast to whole data training (around 31 hour for weekend and 116 hour for working days) and reveals realistic control implementation for online system as well.Comment: Proceedings of ECOS 2015-The 28th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems , Jun 2015, Pau, Franc

    CONTROL OF MICRO-INVERTERS AS AN OVERVOLTAGE PREVENTION METHOD UNDER HIGH PV PENETRATION

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    Low voltage (LV) residential grids are generally not designed for high penetration of photovoltaic (PV) distributed generation. Maximization of PV output is not only opposed by solar energy intermittency, but also by grid impacts in form of reverse power flow and overvoltage. More intelligent control of PV inverters is required to balance the voltage requirements of the grid and maximum energy yield wanted by the end user. This paper discusses how micro-inverter topology could be utilized to handle overvoltage problem and avoid power output losses by applying an innovative control method. Control is realized as partial generation shedding at PV module level which is an optimized alternative comparing to conventional, entire PV array tripping in the event of overvoltage

    Analytical Approach to Grid Operation With Phase Shifting Transformers

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    Wind power grid integration: The European experience

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    17th Power Systems Computation Conference (PSCC), Stockholm, Sweden, 2011Europe currently holds the largest installed capacity of wind power plants of all continents. Over decades of development, significant adaptations have been implemented to integrate wind turbines into the electrical power system. Wind power research has been accelerated by the need to maintain grid performance and reliability in the face of the exponential deployment of wind turbines. This paper explains the basic requirements and principles in grid codes, modeling, reserves, forecasting, system planning, and operation, and relates how experience especially in Europe has led to new practices and new research.Science Foundation IrelandDeposited by bulk impor

    Sustainable transition to high PV penetration: curtailment retrofit for the already deployed micro-inverters

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    Increasing photovoltaic (PV) capacity in low voltage networks is limited by occasional congestion, resulting in unacceptable voltage levels. Network managers and policy makers are getting aware of this problem and various technical recommendations are given. Of special interest are ancillary services (reactive power control and active power curtailment) that could be provided by the "smart" inverters. Most PV inverters deployed to date are solely designed to maximize power output. To make the transition towards smart inverters, they either have to be replaced or retrofitted. Retrofit can be a more sustainable option, especially if it can be done only by software intervention ("soft retrofit"). This paper presents a curtailment method suitable for the already deployed micro-inverters without needing to replace them. Sequential module-level tripping is an optimized overvoltage trip scheme that achieves curtailment on a system level, without modifying the functionality of individual micro-inverter unit. The proposed method was simulated for an increased PV penetration scenario for a Dutch LV network. The annual feed-in losses of curtailment were compared against conventional overvoltage protection. Depending on the location of PV in the distribution network, 62-100% less feed-in loss was achieved with the proposed curtailment method

    Distributed routing algorithms to manage power flow in agent-based active distribution network

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    The current transition from passive to active electric distribution networks comes with problems and challenges on bi-directional power flow in the network and the uncertainty in the forecast of power generation from grid-connected renewable and distributed energy sources. The power flow management would need to be distributed, flexible, and intelligent in order to cope with these challenges. Considering the optimal power flow (OPF) problem as a minimum cost flow represented with the graph, this paper applies a cost-scaling push-relabel algorithm in order to solve the OPF in a distributed agent environment. The algorithm's performance is compared with the successive shortest path algorithm developed in our previous work. The simulation is implemented for both meshed and radial networks. The simulation results show the advantages of the cost-scaling push-relabel algorithm over the shortest path algorithm in the radial networks with respect to significantly reduced number of exchanged messages on the agent platform, and thus the reduced time for calculation. This will be of great importance if the method is to be applied to a large system

    Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch

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