Solar4everybody –Your impact on energy production!

This project was carried out as part of the TechLabs “Digital Shaper Program” in Münster (winter term 2021/22).

Abstract

Solar4everybody is an application to calculate easily if an individual investment in a balcony power plant is profitable. It is suitable for every consumer of energy and enables them to exploit their individual influence on energy production. In addition to an assessment of the individual conditions for a balcony power plant, current electricity prices and the amortization of the investment are considered. For a better understanding, the impact of a balcony power plant is visualized in comparison to the power demand of household devices. Considering climate change, unstable energy prices and political entanglement of energy production, it is important to let consumers know their possibilities of individual investment in power production.

Introduction

Energy is needed in all areas of everyday life: Electricity is used to enable housing, the production of goods and public life. Despite the already visible consequences of climate change, electricity is still largely produced with negative consequences for the environment. In addition, a current rapid price increase and political crises pose challenges to consumers: Is there a way to produce electricity reliably, environmentally friendly and independent of global political developments?

General approach

The goal was to develop an application showing the impact of a balcony power plant given the individual conditions. It was important to all group members to emphasize the easiness of individual contribution to energy production with a straightforward application. A first research phase showed us that an individualized calculation of the possible amount of power generation was possible.

Therefore, the following five steps were identified to achieve our goal:

• Webscraping of current prices (electricity and balcony power plant)
• Amortization calculation
• Comparison to household appliances
• Visualization possibilities and access for the public
• Continuous testing of extensions

Due to the pandemic and geographical distance, we relied on various digital collaboration tools to communicate:

• Slack — our central communication tool to define deadlines and to address short queries on specific topics
• Programming environment — each group member chose an environment best suitable for the individual needs (PyCharm, Anaconda, …)
• Github — to exchange ideas and collaborate while coding
• Streamlit — used for the visualization of the results

Webscraping of current prices (electricity and balcony power plant)

Especially nowadays, prices of electricity and consumer goods are subject to volatile changes. To offer results based on current prices and for our application to be low maintenance, we decided to use webscraping. Doing this, we implemented the up-to-date prices of the solar modules recommended and of electricity.

Amortization calculation

Since our goal was to offer people a first glance into the world of producing their own solar power, it was essential to add a visualization to show when the acquisition of a solar panel pays off. We decided to use the manufacturer’s specification on average energy production per year, which is roughly 1000 kWh produced per 1 kWp, meaning a module which generates 370Wp (Watt peak) approximately generates 3700 kWh per year. While the current market price for electricity is varying, customers usually have contractually fixed prices. To personalize the calculation, we implemented the ability for users to enter their own current price of electricity.

Comparison to household appliances

To emphasize the impact every energy consumer can have using a balcony power plant, we chose to compare the amount of power generated with the power demand of household appliances. Based on the personal use of household appliances, we decided to illustrate the power amount with seven specific devices and determined corresponding average values for consumption according to various internet sources.

Visualization possibilities and access for the public

Visualization of the results was a challenge for us, because all group members were beginners in UX and part of the Data Science track. After examining various options, we found Streamlit to be the most efficient way of presenting the results. From our point of view, there is still potential regarding the visualization. However, it should be emphasized that the focus of the project was more on data science and less on layout.

Continuous testing of extensions

During the development of the application, various expansion ideas emerged and were discussed in the group. One possible extension was the integration of geodata for an individualized assessment of location suitability. Because of the complexity of geodata and bare knowledge about the use of corresponding applications, it was not possible to integrate this information into the application. Concerning further development of the project, the integration of geodata would be an interesting approach.

Results of the project

The application Solar4everybody as the result of our project can be viewed on this page. User input is integrated to calculate the annual energy production and the amortisation time of the investment. Afterwards, the amount of generated energy is visualized compared to the average power demand of household devices.

Overall, the goal to provide an easy access estimating the impact of an individual balcony power plant has been achieved. Although the impact of the application is not measurable yet, further integrations and linkages to the purchase of balcony power plants would make the impact of the application measurable.

Our Github Repository

The team

Björn Budde Data Science (LinkedIn)

Jonas Klose Data Science (LinkedIn)

Sarah Ecklebe Data Science (LinkedIn)

Tabea Krause Data Science (LinkedIn)

Niklas Tacke Data Science (LinkedIn)

Roles inside the team

To stick to the above-mentioned structure, the roles in the team can be assigned to each step. However, it should be noted that it was by no means only the person listed who worked on the content. Collaboration took place and results were exchanged within the group.

• Research (Tabea)
• Webscraping of current prices (Björn & Jonas)
• Amortization calculation (Björn)
• Comparison to household appliances (Niklas)
• Visualization possibilities and access for the public (Sarah & Jonas)
• Continuous testing of extensions (all)

Mentor

Maximilian Maiberger