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# Difference between revisions of "Solar powered internet methods"

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 This page was part of an MTU course MY5970/EE5900: Solar Hacking: Photovoltaic Materials, Cells and Systems Engineering Please leave comments using the discussion tab. The course runs over Spring semester 2012. It is not open edit.

## METHODS

The potential of successful PV mesh networks is based on five variables: system design and sizing, solar energy availability, economic analysis, and integrating geospatial information to optimize deployment locations. An example system was designed and built to assess the economic feasibility and overall system design.

### Design Methodology

The following design methodology was created, employed and demonstrated in an example system. The sizing of the electronic components was determined using PVSyst. The assocaiated converters and controllers were selected to optimize efficiency while minimizing cost and necessary components. Mechanical components including the structural elements, mounting hardware, and fasteners were selected based upon the following criteria: cost, weight, strength, component life, transportability, ease of use, and maintenance. The structural support system was designed to hold the solar array at the optimum angle for the latitude at which the system will be utilized. Using the design methodology, several example systems were built for testing.

### Sizing of system parts

The control of all the converters is controlled by a Microcontroller. The results of sizing from PVSyst obtained are as 13Ah capacity battery, 92Wp capacity solar panel, Generalizing the design, a 10 ultracapacitor bank of 3000F each is being selected as the storage, and a 190Wp solar panel is used. Material properties for each mechanical component were assessed to ensure all components could withstand the loading conditions including wind loads, rain loads, and snow loads (PV Systems Engineering 2006). Each mechanical component was then sized using a factor of safety of 1.5. Equipment: PV panel, ultracapacitor bank, router, converters, batteries, hardware - this will be based on either PVSyst or GRASS/rsun in ArcGIS.

The current options of Routers are the Netgear CG 3000d -18W, Cisco Linksys WRT54-- 6W. Going with an autonomy of 1 day and a maximum Loss of Load of 5% we can arrive at the size of the system as follows:

Ultra cap size = (Total Wattage * number of hours *allowed autonomy)/(Depth of Discharge*Efficiency*Operating voltage)

Taking Cisco router into consideration, taking DOD=0.98,Efficiency=0.95, and an operating voltage of 9V. The size of Ultra cap bank is 16.84 Ah. The size of each Ultra capacitor is 2.25 Ah so making a quick calculation we can get the total Ultra capacitors required is around 8. Taking an optimistic approximation of 10 Ultracapacitors will provide enough room for unprecedented events.

### Hardware Implementation:

The implementation of the hardware is going to be made using DC/DC converters as shown in the schematic shown below

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The firing of the MOSFET’s is done using a Micro controller based circuit, it has been proposed to use the Arduino Uno to implement this circuit. The Perturb and Observe algorithm being considered to be used to implement the MPPT control [1].The advantage of this method is , it is easy to implement and robust in structure which increases the efficiency of the system.

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### Economic viability

The present cost of bringing broadband Internet access to rural areas was compared to the implementation of PV mesh networks. A Comparison of router configuration was also done in order to optimize energy demand, with system configuration and antenna spacing. Finally, a comparison was made between the use of standalone PV systems and connecting areas to electric grid in distance from current availability. In order to perform the economic analysis the cost of stacking standalone systems to a rural area from a WLAN hub , a comparison to the cost of extending electric and broadband infrastructure was made. The total cost of the system was calculated to include solar panels, inverter, batter bank, router, mounting, installation, and travel to rural areas (McLaughlin et al. 2010). Additionally, connection costs and WLAN hub was also included but varies with distance from land lines.

### Geographical potential using GIS

In order to assess various aspects of the PV system implementation, a geographical representation of the variables is necessary. Local level spatial disparities are necessary to assess to find places lacking infrastructure and technology for broadband access (Grubesic and Murray 2001).

Among the geo-processing capabilities of GIS perhaps the most useful is the overlay function. GIS has shown its usefulness in rural and urban planning, sustainable development, and identifying site specific locations (Refs). The different layers, including electric networks, broadband networks, and population density, can be synced to identify rural locations for technology dissemination. The geographical information system (GIS), ArcGIS, was used to organize spatial variables to find cells, of resolution 1 km2, that is appropriate for standalone PV system installation. We computed the locations of remote sites for SAPV installation from creating 6 layers incorporating buffers from the electric grid and broadband access at 500m, 1,000m, and >1,000m (Muselli et al. 1999). Additionally, a layer of population density is used to interpret potential market and impact.

### Testing methodology

The afore mentioned system was built and tested using the following methodology. The system, comprised of three stand alone units, was placed outdoors with each branch unit roughly 500 meters from the main unit. The range and capacity of the mesh system was then measured. Finally, current and voltage readings for each unit was collected. Since the units were placed on rooftops, it was assumed that shading played a limited role and that systems were placed in an optimized location above shaded areas. Therefore, calculations regarding orientation and sizing due to shading parameters were ignored.