Gas Natural Fenosa (Spain)

In this paper (Part I), a study of the zero-sequence stray losses in wye-wye-connected transformers without a (stabilizing) tertiary winding is presented. The paper shows where and when eddy losses and circulating current losses appear in the transformer structural metallic components. The overheating hazard potential due to the presence of zero-sequence flux is categorized (as severe, serious, and moderate) by the permitted neutral current. The method is successfully applied to (and experimentally verified with) three-phase, three-legged, core type, wye-wye-connected transformers based on factory acceptance tests (FATs) data. It is uncovered that the severity of the overheating is determined by the phase angle difference between the zero-sequence current and the positive-sequence current. This is formulated by the proposed complex current capacity factor (CCF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> ). In the companion paper (Part II), the maximum permitted heating on the transformer structural metallic components due to the zero-sequence current vs. time duration is presented. The idea is to gauge the temperature of the hot spots in structural metallic components by monitoring (magnitude and angle) the neutral current. The ultimate goal of these two papers is to provide engineering practical knowledge to properly design protection procedures for two-winding transformers with wye-connected primary and secondary and one neutral grounded without stabilizing winding. <list list-type="simple" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <list-item> 3D FEM electromagnetic fields, heating hazard, hot-spot, stray losses, tertiary stabilizing windings, zero-sequence. </list-item> </list>

Cool steam is an innovative distillation technology based on low-temperature thermal distillation (LTTD), which allows obtaining fresh water from non-safe water sources with substantially low energy consumption. LTTD consists of distilling at low temperatures by lowering the working pressure and making the most of low-grade heat sources (either natural or artificial) to evaporate water and then condensate it at a cooler heat sink. To perform the process, an external heat source is needed that provides the latent heat of evaporation and a temperature gradient to maintain the distillation cycle. Depending on the available temperature gradient, several stages can be implemented, leading to a multi-stage device. The cool steam device can thus be single or multi-stage, being raw water fed to every stage from the top and evaporated in contact with the warmer surface within the said stage. Acting as a heat carrier, the water vapor travels to the cooler surface and condensates in contact with it. The latent heat of condensation is then conducted through the conductive wall to the next stage. Net heat flux is then established from the heat source until the heat sink, allowing distilling water inside every parallel stage.

Technical losses of smart grids can be computed using the customer's smart meter measurements (active and reactive energy) and the energy measurement registered by the Low Voltage (LV) supervisor deployed at secondary substations. However, in some LV networks, some customers do not provide information regarding the energy consumed and produced in real time. This fact complicates the calculation of technical losses because this information is necessary for estimating the load demand for this subset of customers. In this paper, a stochastic approach is proposed for the estimation of technical losses in smart grids under uncertain load demands (e.g., non-telemetered customers and uncertain smart meters readings). Load demand estimation of non-metered customers was performed by means of a top-down approach. Intra-hour load demand profiles of customers were synthetically generated by applying a Markov process. The data and network used in this process corresponded to the roll-out deployed by the Spanish Research and Development (R&D) demonstration project OSIRIS.

This paper presents the implementation of an adaptive load forecasting methodology in two different power networks from a smart grid demonstration project deployed in the region of Madrid, Spain. The paper contains an exhaustive comparative study of different short-term load forecast methodologies, addressing the methods and variables that are more relevant to be applied for the smart grid deployment. The evaluation followed in this paper suggests that the performance of the different methods depends on the conditions of the site in which the smart grid is implemented. It is shown that some non-linear methods, such as support vector machine with a radial basis function kernel and extremely randomized forest offer good performance using only 24 lagged load hourly values, which could be useful when the amount of data available is limited due to communication problems in the smart grid monitoring system. However, it has to be highlighted that, in general, the behavior of different short-term load forecast methodologies is not stable when they are applied to different power networks and that when there is a considerable variability throughout the whole testing period, some methods offer good performance in some situations, but they fail in others. In this paper, an adaptive load forecasting methodology is proposed to address this issue improving the forecasting performance through iterative optimization: in each specific situation, the best short-term load forecast methodology is chosen, resulting in minimum prediction errors.

ABSTRACTThe design of intake-outlet structures for pumped-storage hydroelectric power plants requires site-specific location and geometry studies in order to ensure their satisfactory hydraulic performance. This article presents the numerical and physical model studies conducted on the lower intake-outlet of Belesar III power station in Northwest Spain. The proposed location of this structure in a narrow reservoir and at a shallow depth is particularly challenging and required the analysis of both the near-field and far-field flow dynamics in the reservoir. First, the hydrodynamics of the reservoir were studied with a 2D shallow water model. The location of the intake was found to be suitable, with adequate flow conditions in the reservoir even for the lower operating water levels. The intake could be fed with the maximum pumping discharge without being limited by the reservoir’s hydraulics. Second, the flow in the near-field was investigated by complementary use of 3-dimensional numerical simulations and reduced-scale physical modeling. The results allowed the verification of the submergence requirements and the comparison of geometry alternatives. In comparison with the initial design, the final proposed design shows a more symmetrical approach flow into the structure during pumping mode, resulting in a more homogenous flow distribution between the openings and reduced head loss. This study can provide guidance in the application of hydraulic modeling procedures to locate and design intake-outlet structures in existing lakes or reservoirs and to evaluate potential limitations on water levels, inflows and outflows. It can be useful during planning stages of power plants to aim for the shortest possible waterways between the reservoirs while ensuring adequate flow conditions.

Data from utility meters (gas, electricity, water) is a rich source of information for distribution companies, beyond billing. In this paper we present a supervised technique, which primarily but not only feeds on meter information, to detect meter anomalies and customer fraudulent behavior (meter tampering). Our system detects anomalous meter readings on the basis of models built using machine learning techniques on past data. Unlike most previous work, it can incrementally incorporate the result of field checks to grow the database of fraud and non-fraud patterns, therefore increasing model precision over time and potentially adapting to emerging fraud patterns. The full system has been developed with a company providing electricity and gas and already used to carry out several field checks, with large improvements in fraud detection over the previous checks which used simpler techniques.

Martinez, M. y Rodríguez, J. (2015): “Arte y salud social. Programas de participación sociocultural para personas con diversidad funcional”, Revista Española de Discapacidad, 3 (2): 125-131.

This article provides an overview of the European Union (EU) electricity and natural gas sectors by focusing on the specific case of mainland Spain. The integration of renewable production has created a strong link between the operations of the electricity and natural gas systems. This calls for a coordinated gas and electricity operation and for the coordinated long-term planning of both electricity and natural gas facilities.