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Sizing & Data Capturing For A Vacation Home. Solar Energy Systems ECET-52100. Presented By: Abdulhaleem Al Owaisheer Jen Vacendak Tanima Zaman. Project Objectives.
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Sizing & Data Capturing For A Vacation Home Solar Energy Systems ECET-52100 Presented By: Abdulhaleem Al Owaisheer JenVacendak TanimaZaman
Project Objectives The goal established for this project was to design and simulate an alternative solar power system for a vacation house which enables an owner: • To rely the least on the “Grid Power” • To meet the electricity requirements for • “Reasonable Costs” during the winter season • To earn money by selling the additional power generated in the off-seasons to the “Power Grid” • To “Monitor System Parameters” (e.g. temperature, power etc.) from original residence • Store “Backup Power” for the cloudy day (If financially feasible
Research Considerations The design approaches established and all simulations performed in this project were focused on the following preliminary data: • Location: Key West, Florida, FL 33040 • Latitude: 24 o 33 ‘N,81o 45 ‘W • Power Requirement: 1120kWh/month • Cost of Electricity in Florida: $0.1165/KW • PV System Size: 10.785KWatt • The annual solar irradiation data Software Tools: • SolarBear (www.pvpower.com) • Battery Sizing Calculator • Homer • Onset’s HOBO Data Logger
Methodology 1 • The first approach for the project was to figure out recommendations for PV Systems from SolarBear based on the zip code, price per kWh and solar system size. The obfollowing systems with three different criteria were tained: • Lowest Price System • Lowest Cost per Watt System • Most Powerful System
SolarBear Recommendations • Lowest $/W, Most Powerful and Least Expensive System • Most Powerful • System
Methodology 2 • Secondly, energy storage battery bank s were sized for sufficient backup purpose. The battery sizing calculator was used to determine the watt-hours and amp-hours . The results obtained were 223,252Wh and 9303Ah in order to meet the following criteria: • 2 Days backup power • 37,333Wh of energy usage/day • 400 F minimum temperature • 24V battery bank • Based on the calculations, the system would require 12 6V, 200Ah in 3 strings. The cost for this came out to be $1678/each with a total of $20,136.
Methodology 3 • Thirdly, the simulations were performed in HOMER software based on the two recommendations provided by SolarBear . Two simulations were run with and without considering the battery backup systems. The parameter values collected and entered in HOMER were as below: • General Information: • Solar radiation index • Latitude and longitude for Key West • Energy usage per month 9 (zero 8months of the year) • Cost per kWh • 20-year life time
PV Information • System size in KW • Total cost • Efficiency • Nominal Operating Cell Temperature • Pmax (%/ 0C) • Inverter Information • Size in Watt • Cost • Efficiency
Battery Backup Information • Single battery voltage and Ah rating • Batteries per string • Number of strings • Cost • Lifetime • HOMER provided the simulations results with all scenarios including buyback.
Methodology 4 • Finally, the HOBO Data Logger was introduced in the design for monitoring conditions (e.g. temperature, solar radiation, power consumed by appliances and output power of the PV systems) remotely over the internet when the owner is back to his/her original residence after vacation. Following the image of how HOBO provides information:
Result 1: Cost Comparison without Battery Most Powerful Lowest Cost per kWatt System
Result 2: Cost Comparison with Battery Most Powerful Lowest Cost per kWatt System
Our Recommendations • 1. Lowest Cost per Watt/ Lowest Price ($15,553.96) • 11kW PV System (11 modules, 4 strings) • 10kW Inverter (1) • Grid-tied for Electricity Buyback • 2. No Battery Backup • 3. Data Logging Equipment ($2178.00) • Onset HOBO U30 Ethernet Data • Small Backup Battery (1) • Solar Radiation Sensor (2) • Energy & Power Meter (2) • Temperature Sensor (1) • HOBOlinkRemore Monitoring Software
Significance of the project • We found this project a significant design problem as it very closely related to real-life solar application. This project lead us to some challenge regarding gathering pertinent information, simulate the systems, data analysis and based on the simulations come up with a right choice. It bridged the classroom and field work and that is very valuable