Chronological Monte Carlo-based assessment of distribution system reliability

Regulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties, and in some cases rewards, which introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the Maximum Continuous Interruption Duration per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML -Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed. © Copyright KTH 2006.

GPR applied to mapping utilities along the route of the Line 4 (yellow) subway tunnel construction in Sao Paulo City, Brazil

The rapid industrial development and disorganized population growth in huge cities bring about various urban problems due to intense use of physical space on and below the surface. Subsurface problems in metropolitan areas are caused by subway line construction, which often follows the routes of utility networks, such as electric and telephone cables, water and gas pipes, storm sewers, etc. Usually, the main problems are related to damage or destruction of preexisting utilities, often putting human lives at risk. With the purpose of minimizing risks. GPR-profiling with 200 MHz antennae was done at two sites, both located in downtown Sao Paulo, Brazil. The objectives of this work were to map utilities or existing infrastructure in the subsurface in order to orient the construction of the Line 4 (yellow) subway tunnel in Sao Paulo. GPR profiles can detect water pipes, utility networks in the subsurface, and concrete foundation columns or pilings in subsoil up to 2 m depth. In addition. the GPR profiles also provided details of the target shapes in the subsurface. GPR interpretations combined with lithological information from boreholes and trenches opened in the study areas were extremely important in mapping of the correct spatial distribution of buried utilities at these two sites in Sao Paulo. This information improves and updates maps of utility placement, serves as a basis for planning of the geotechnical excavation of the Line 4 (yellow) subway tunnel in Sao Paulo, helps minimize problems related to destruction of preexisting utilities in the subsoil, and avoids risk of dangerous accidents. (C) 2012 Elsevier B.V. All rights reserved.

New Orleans, Louisiana, Water Distribution System, 1902 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Map of the city of New Orleans : showing proposed water distribution system, [by] Sewerage and Water Board New Orleans, LA.; Geo. G. Earl, genl. sup't. It was published by the Sewerage and Water Board New Orleans in 1902. Scale [ca. 1:50,900]. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Louisiana State Plane Coordinate System, South NAD83 (in Feet) (Fipszone 1702). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, or other information associated with the principal map. This map shows water distribution features such as existing and proposed water mains (with sizes), suction pipes, and water purification station sites. Also shows other features such as roads, canals, levees, drainage, cemeteries, Parish boundaries, and more. Shaded to show built-up and unbuilt areas for construction. This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.