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Arnhem, The Netherlands

Van Westering W.,Alliander | Hellendoorn H.,Technical University of Delft
ICNSC 2015 - 2015 IEEE 12th International Conference on Networking, Sensing and Control | Year: 2015

A novel method is proposed to interpret sensor data by applying a gas distribution network model based on the steady-state Weymouth equation. The proposed data interpretation method merges data gathered from sensors and models by comparing variances, so that more information is extracted than by applying the methods available in literature. The data interpretation method is subsequently used to define an objective function for finding the optimal sensor locations to minimize the uncertainty of the flows in a gas network. This method is then applied on the real high-pressure network of the island of Texel, for which gas consumption data is created using a Monte Carlo approach. The resulting optimization problem is solved by using a genetic and a greedy algorithm. The greedy algorithm performs best and yields a realistic set of sensor locations. © 2015 IEEE. Source


Arends M.,Alliander | Hendriks P.H.J.,Radboud University Nijmegen
Utilities Policy | Year: 2014

The introduction of intelligent technology to turn electricity networks into smart grids is an important vehicle to meet the many challenges modern society poses. However, technology alone will not make energy supply more intelligent and may for the medium and long range even involve risks of intelligence reduction in the larger energy system. Crucially important, yet mostly overlooked is the intelligence of the service company that runs the grids. Based on concepts of knowledge management and learning organizations, the paper develops guiding principles for designing intelligent knowledge infrastructures within companies adopting smart grid technologies. The case study of intelligent SASensor technology, which is currently being introduced by the Dutch power network administrator Alliander, provides an illustration of the argument. © 2013 Elsevier Ltd. Source


Bhattacharyya S.,TU Eindhoven | Cobben S.,TU Eindhoven | Cobben S.,Alliander | Myrzik J.,TU Eindhoven | Kling W.,TU Eindhoven
European Transactions on Electrical Power | Year: 2010

Voltage flicker is an irritating problem especially for the low voltage (LV) customers. It is mainly caused by the loads having repetitive cycle of operation. During the past years, the network operators around the world have registered many complaints from the customers about flicker related problems. Presently, there is no common standard value for the flicker planning level available globally. Moreover, in some countries (for example, in the Netherlands), the existing networks are not even based on a specific planning level value for flicker. Therefore, it is necessary to discuss the flicker planning level values in different voltage levels to overcome flicker related problems. In this paper a typical LV network is simulated to analyze the flicker propagation behavior in the network. The effects of switching LV disturbing loads (such as elevator, welding machine, etc.) on flicker generation at different customer's installations are studied by using synchronized measurement technique. Also, the impacts of the background flicker pollution transferred from the upstream to the downstream networks are analyzed. The simulation results give an overview of the flicker pollution levels at the LV customer's installations in the presence of background flicker. This paper estimates the maximum value of flicker emission share at different customer's point of connections (POC), considering the impact of background flicker pollution. Finally, planning level values of flicker in different voltage levels are suggested that can be useful for the network operators in designing their future networks. Copyright © 2010 John Wiley & Sons, Ltd. Source


Louie H.,Seattle University | Dauenhauer P.,University of Strathclyde | Wilson M.,Torchbearer Foundation for Missions Reconciliation and Development | Zomers A.,Alliander | Mutale J.,University of Manchester
IEEE Power and Energy Magazine | Year: 2014

Sustainability has been famous?ly defined as ?the ability to meet the needs of the present without compromising the ability of future generations to meet their own needs.? While elegant in its conceptual simplicity, this definition is often not the most useful one to practitioners, especially those working in the area of energy deployment in developing communities. The sustainability of small-scale, off-grid energy systems?systems that appear to fit this definition neatly?cannot, in fact, be taken for granted. And sustainability is key: it can mean the difference between prolonged poverty and transformational prosperity for the 1.2 billion people around the world who lack electricity, some 85% of them in rural areas. © 2014 IEEE. Source


Nijhuis M.,Alliander | Rawn B.,Technical University of Delft | Gibescu M.,Technical University of Delft
IET Renewable Power Generation | Year: 2014

During partly cloudy conditions, the power delivered by a photovoltaic array can easily fluctuate by three quarters of its rated power in 10 s. Fluctuations from photovoltaics of this size and on this time scale may necessitate adding an additional component to power system secondary and primary reserves to regulate frequency. This study quantifies the benefit of dynamically sizing a reserve component to cover photovoltaic fluctuations so that the additional reserves are different for each hour. The concept of categorising an hour as belonging to one of three possible fluctuation classes is presented. Based on historical array data and weather forecast information, several methods of forecasting these classes are evaluated, including persistence, Markov chains and a neural network. A practical tool based on class forecasting is proposed to aid in estimating a photovoltaic reserve requirement ahead of time for horizons ranging from 1 to 24 h. Results indicate that of a 10% possible reduction in total reserves held, most of this benefit (8%) can be obtained for hour-ahead scheduling with persistence forecasting and that a similar benefit may be possible for four-hour ahead scheduling if neural networks based on weather forecast information are introduced. © The Institution of Engineering and Technology 2014. Source

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