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SAP Business One offers several reporting options – Crystal Reports for SAP Business One, SAP Business One queries, SAP Business One Drag and Relate, pivot tables and Dashboards. In summary – SAP Business One offers standard reports with multiple selection criteria and the opportunity to write your own reports using the SAP Business One Query Generator, Crystal reports for SAP Business One and Pivot tables.
You must have JavaScript enabled in your browser to utilize the functionality of this website. Our Sales Target Selection And Achievement Flat Powerpoint Design are great for evolving businesses. State governments are challenging electric companies to increase the utilization of renewable energy sources. According to the United States Energy Information Administration, Arizona is one of the states with the greatest solar photovoltaic (PV) resource potential in the country; however, finding suitable locations for large-scale solar farms is difficult due to zoning and other restrictions. The pilot study analyzed four square miles surrounding the University of Arizona in Tucson. A digital elevation model (DEM) was derived from the LiDAR data and was saved in ArcGIS as a floating-point raster image. Using the Area Solar Radiation Tool in the ArcGIS Spatial Analyst extension, a solar map was generated from the georeferenced image specifying Tucson's latitude of 32 degrees and a yearly interval. High radiation—The site should receive, on average, at least some minimum amount of solar radiation per year.
In general, the goal is to find rooftops that face south or are flat and have a slope that is not too steep for installing solar panels.
Using ModelBuilder, masks were generated to select locations that had these desirable characteristics and met the project requirements.
A bare-earth file was generated from the LiDAR data and georeferenced to the same coordinates as the input image. To find feasible locations for the solar panels, all the binary rasters were combined into a final raster that takes a value of 1 for locations that meet all conditions and 0 for those that do not. The output generated using the five masks was input for the Raster To Polygon tool that generated polygons for all the suitable areas. Because inverters and other hardware required to connect solar panels to the grid are expensive, the theoretical number of solar panels that can fit in each area can be used by the analyst to select only those locations that can fit at least a predetermined number of solar panels. In this digital elevation model (DEM) derived from LiDAR data, the university's campus is the brightest area in the image and has the highest buildings. To find areas with a slope of 35 degrees or less, all cells with a slope less than or equal to 35 degrees were assigned a value of 1 and shown in blue. All binary rasters were combined into a final raster that assigns a value of 1 to the cells that meet all the requirements and 0 for those that do not to find all feasible locations.


The output generated using the five masks was used as input for the Raster To Polygon tool that generated suitability polygons.
When the Raster To Polygon tool was used, a very large polygon that consisted of the perimeter of the image was created. Andrea Chaves currently works as a business technology analyst at Deloitte Consulting LLP in Denver, Colorado.
According to the Database of State Incentives for Renewables and Efficiency (DSIRE), 29 states have renewable energy standards that establish requirements for increasing renewable energy usage, and nine states have renewable energy goals.
Regulations imposed by state and federal agencies, such as Arizona Game and Fish and the United States Bureau of Land Management, significantly reduce the areas that can be utilized for solar energy production.
Original data for the area of this pilot study was obtained from a light detection and ranging (LiDAR) image provided by the Pima Association of Governments (PAG). Because the DEM was not georeferenced, the raster was georeferenced using the Georeferencing toolbar in ArcGIS. This solar map takes into consideration the changes in the elevation (azimuth) and position of the sun, as well as any shading effect caused by buildings or other objects in the input raster. A binary ground raster was generated that identified nonground cells by assigning a value of 1 for any cell greater than or equal to the bare earth value plus five feet and assigning 0 to all others, which were ground cells.
From this new aspect raster, a binary aspect raster was created by selecting all the cells that had south, southeast, southwest, or flat aspects and assigning them a value of 1. Using the filtered georeferenced image as an input, a binary raster was created by selecting all cells with a slope less than or equal to 35 degrees and assigning those cells a value of 1. The model uses six main inputs: the DEM, the aspect raster, the slope raster, the radiation raster, the bare earth raster, and the analyst mask.
This requirement was based on the size of the solar panels most commonly used at the Tucson Electric Power solar panel test yard with a 15 percent buffer to accommodate the mounting frame and additional spacing. Any cell with an elevation greater than or equal to the bare earth elevation plus five feet was given a value of 1 and shown in green.
Cells with south, southeast, southwest, or flat aspects were assigned a value of 1 and shown in blue.
These polygons were symbolized based on the theoretical number of solar panels that could fit in each polygon. This polygon has no relation to suitable solar panel locations and could not be included in the analysis. However, it should be developed further so the decision- making process can consider factors such as PV panel and inverter costs, return on investment, and engineering concerns.
She earned a bachelor's degree in industrial engineering, a master's degree in management with emphasis in finance, and a master's in industrial engineering, all from the University of Arizona, Tucson.


You can run this report based on a number of different criteria – by customer, items or sales employee. The image depicts the area surrounding the University of Arizona that contains residential development, commercial development, university buildings, open areas, and athletic fields. The resulting dimensions and point locations of the georeferenced image were verified using several points with known locations.
This last constraint eliminates sites located next to taller buildings that block sunlight for a significant portion of the day. A low-pass filter was used on the georeferenced image to generate a smoother aspect raster and facilitate the analysis of the final output of the GIS. In 2008, she was a recipient of the Wayne Wymore Award for excellence in systems and industrial engineering and was named outstanding senior for her graduating class. He received his doctorate in electrical engineering and computer science from the University of California, Berkeley.
The report can be run for different date ranges, with or without grouping, by salesperson and to include or exclude various properties. The Arizona Corporation Commission Renewable Energy Standard (RES) requires that 15 percent of Arizona's retail sales be derived from renewable sources by 2025.
First, a Max field was added that contains the maximum allowable polygon size in square meters.
One standard report with a number of reporting options and criteria available for the user. For these companies, he presented seminars on systems engineering, worked on system development teams, and helped them describe their systems engineering process. In this case, the site had an area of four square miles, so the maximum polygon size was set at nine million square meters. He is a fellow of the Institute of Electrical and Electronics Engineers (IEEE), of Raytheon, and of the International Council on Systems Engineering (INCOSE) and the Founding Chair Emeritus of the INCOSE Fellows Selection Committee. Second, every row that has an Area field value larger than the Max field value is selected and deleted from the table.



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