adminWe are seeking an experienced developer or development team to create an API service that estimates solar energy production based on solar radiation data from the Norwegian Meteorological Institute. The API should function similarly to the PVGIS service but should utilize the Norwegian datasets to provide more accurate estimates for solar power systems in Norway.
**Objective of the API Service:**
The API should be able to accept specifications for a solar power system and return expected solar energy production per month and total for the year. The estimates should be based on historical solar radiation data from the Norwegian Meteorological Institute, combined with technical parameters of the solar installation.
**API Features:**
1. **Input Parameters:**
– **Geographical Coordinates:** Latitude and longitude of the solar power system’s location in Norway.
– **System Size:** Installed capacity in kW (kilowatt peak – kWp).
– **Panel Orientation:** Azimuth (direction in degrees, where 180° is south).
– **Panel Tilt:** Inclination angle in degrees from the horizontal plane.
– **System Losses:** Option to input percentage losses (e.g., due to inverters, cables, etc.).
2. **Output:**
– **Expected Monthly Solar Energy Production:** Estimates in kWh per month.
– **Annual Solar Energy Production:** Total kWh for the entire year.
– **Graphical Representation (Optional):** Monthly energy production as a JSON structure or graphic (e.g., a curve).
3. **Database:**
– Implement a database containing pre-calculated TMY (Typical Meteorological Year) data for various regions in Norway to facilitate quick lookups and responses.
4. **API Functionality:**
– The API should be RESTful and adhere to standard API design principles.
– Responses should be in JSON format.
– The API should be well-documented to enable easy integration by developers.
5. **Scalability and Performance:**
– The API should be designed to handle multiple concurrent requests with low latency.
– Cloud services like AWS, Google Cloud, or Azure should be utilized to ensure scalability.
6. **Security:**
– Implement authentication and authorization to control access to the API (e.g., via API keys).
– SSL/TLS encryption to secure data transmission.
**Solar Production Calculation Methodology:**
The API service should calculate the expected solar energy production by combining the input parameters provided by the user with the data from the TMY (Typical Meteorological Year) database. The following outlines the methodology for these calculations:
1. **TMY Data Retrieval:**
– For the specified geographical coordinates (latitude and longitude), the API will retrieve the corresponding TMY data from the database. The TMY data will include hourly or daily solar radiation values (in kWh/m²) for a typical year at the specified location.
2. **Adjustment for Panel Orientation and Tilt:**
– The retrieved solar radiation data should be adjusted based on the panel’s orientation (azimuth) and tilt angle. This adjustment can be done using the solar position and angle of incidence calculations:
– **Direct Normal Irradiance (DNI)** and **Diffuse Horizontal Irradiance (DHI)** components from the TMY data are used to calculate the total irradiance on the tilted plane of the solar panels.
– The **angle of incidence** (the angle between the sun’s rays and the panel surface) will be calculated based on the panel’s azimuth and tilt. Formulas such as the Perez model can be employed to adjust the irradiance values accordingly.
3. **System Losses:**
– Apply system losses to the irradiance data. These losses can include inverter efficiency, shading, soiling, and other factors. The user can specify these as a percentage, or default values can be used if not provided.
4. **Calculation of Energy Output:**
– The adjusted irradiance on the panel surface (in kWh/m²) is multiplied by the panel area (based on the system size in kWp) to calculate the potential energy production.
– The formula used is:
[
text(Energy Output (kWh)) = text(Irradiance (kWh/m²)) times text(Panel Area (m²)) times text(System Efficiency)
]
Where:
– **Panel Area (m²)** is derived from the system size in kWp, considering the typical efficiency and area required for standard solar panels.
– **System Efficiency** accounts for the user-specified or default system losses.
5. **Monthly and Annual Aggregation:**
– The hourly or daily energy output is aggregated to provide monthly totals and a yearly total. These values will be returned in the API response.
6. **Final Output:**
– The API will return the expected energy production for each month and the total annual production, taking into account the specific location, system size, panel orientation, tilt, and system losses.
By following this methodology, the API will provide accurate and location-specific solar energy production estimates, which can be directly used for planning and analysis of solar power installations in Norway.
**Steps to Create a TMY (Typical Meteorological Year):**
Creating a TMY involves several key steps:
1. **Data Collection:**
– Download solar radiation data from the Norwegian Meteorological Institute. You can access the data here: [Meteorologisk institutt – Sunpoint Data](https://thredds.met.no/thredds/catalog/sunpoint/ML-Optimized-Maps/catalog.html).
2. **Data Analysis:**
– Analyze the collected data to determine representative periods that best reflect average conditions. This typically involves statistical methods to select days or hours from different years that represent the typical solar radiation levels.
3. **TMY Construction:**
– Combine these representative periods to create a continuous dataset that represents a typical meteorological year. Python libraries such as `pandas`, `numpy`, and `xarray` are commonly used for this type of analysis.
4. **Reference Material:**
– For further reading on how TMY datasets are created and their applications, you can refer to the following resources:
– [NREL’s TMY3 Data](https://www.nrel.gov/grid/solar-resource/solar-tmy.html) – National Renewable Energy Laboratory (NREL) provides detailed documentation on TMY data and methodologies.
– [Typical Meteorological Year (TMY) – Wikipedia](https://en.wikipedia.org/wiki/Typical_Meteorological_Year) – A general overview of what TMY represents and its significance.
**Deliverables:**
1. A fully functioning API service deployed on a selected cloud platform (e.g., AWS, Google Cloud, or Azure).
2. Source code and full documentation of the system, including API documentation.
3. Test data and results demonstrating that the API works as specified.
4. Optional: A simple web front-end to demonstrate the functionality of the API (not required but nice to have).
**Qualifications:**
– Experience in developing API services, particularly in the energy or meteorological domain.
– Experience handling large datasets, such as NetCDF or equivalent formats.
– Proficiency in Python, Flask/FastAPI, or similar technologies.
– Experience with cloud services for hosting and scaling.
– Experience with databases like PostgreSQL, InfluxDB, or similar is a plus.
**Timeline:**
The project is expected to be completed within [timeline, e.g., 8-12 weeks].
**Application:**
Please submit your application with:
– A brief description of your experience with similar projects.
– Examples of previous work (especially API projects).
– A proposed plan for how you will execute this project, including the technology stack and methodology.
– Estimated cost for the project.
We look forward to working with a skilled developer who can help bring this project to life!
Budget: $3,000
Posted On: August 16, 2024 08:17 UTC
Category: Full Stack Development
Skills:API Development, Python, Flask, PostgreSQL, FastAPI, Cloud Services
Country: Norway
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