Master Thesis Data-Driven Identification and Forecasting of Thermal Flexibility in Residential Heat Pump Systems

Bosch; Renningen; Hybrid; EUR 8,900 - 13,000; Full time

Job summary

Robert Bosch GmbH in Renningen sucht eine Masterarbeit im Bereich der automatischen Schätzung und Prognose der Flexibilität von Wohn-Wärmepumpensystemen anhand von Monitoring-Daten.

Sie überprüfen Ansätze, analysieren Felddaten und definieren Datenprozesse. Basierend darauf entwickeln Sie Modelle, integrieren sie in einen Forecast-Workflow und evaluieren deren Leistung; Umfang umfasst Datenaufbereitung, thermische Systemcharakterisierung, Speicherungskapazität und Flexibilitätsprognose.

Qualifications

• Masterstudium in Computer Science oder vergleichbar.
• Erfahrung und Kenntnisse in Python; Datenbanken von Vorteil.
• Persönlichkeit: zuverlässig, lernbereit, motiviert.

Responsibilities

• Existierende Ansätze prüfen und Datenmonitoring analysieren.
• Datenprozesse definieren und Modelle entwickeln.
• Modelle in einen Flexibilitäts- forecasting-Workflow integrieren und leisten bewerten.
• End-to-end-Workflow überprüfen: Datenaufbereitung, thermische Systemcharakterisierung, Speicherkapazität, Flexibilitätsprognose.

Skills

Heat pump systems knowledge

Education

Master studies in Computer Science or comparable

Tools

Python

Databases

Job description

Bei Bosch gestalten wir Zukunft mit hochwertigen Technologien und Dienstleistungen, die Begeisterung wecken und das Leben der Menschen verbessern. Unser Versprechen an unsere Mitarbeiterinnen und Mitarbeiter steht dabei felsenfest: Wir wachsen gemeinsam, haben Freude an unserer Arbeit und inspirieren uns gegenseitig. Willkommen bei Bosch.

Die Robert Bosch GmbH freut sich auf eine Bewerbung!

Residential heat pumps can provide electrical flexibility by utilizing the thermal storage available in buildings, domestic hot water (DHW) tanks, and buffer storage systems.
This Master's thesis focuses on the automated estimation and forecasting of the flexibility potential of residential heat pump systems. Building on existing concepts and methods, you will investigate how thermal characteristics and storage capacities can be identified from monitoring data and used to quantify the flexibility that a heat pump system can provide.

• You will review existing approaches, analyze field monitoring data, and define suitable data processing workflows. Based on this data, you will identify key thermal parameters of buildings and storage systems and use them to estimate available flexibility over time.
• Furthermore, you will integrate the developed models into a flexibility forecasting workflow and evaluate their performance using real-world data. The analysis will cover both individual homes and aggregated fleets of heat pumps, including the impact of aggregation on flexibility estimation and forecasting accuracy.
• As part of the thesis, you will extend and validate an automated end-to-end workflow covering: Data preprocessing and quality assessment, Thermal system characterization, Estimation of thermal storage capacity, Flexibility estimation and forecasting, Analysis of individual systems and aggregated fleets.
• Finally, you will evaluate the developed approach.

• Education: Master studies in the field of Computer Science or comparable
• Experience and Knowledge: of Python; experience with databases and knowledge of heat pump systems advantageous
• Personality and Working Practice: you are a reliable, curious individual with a strong internal motivation and a willingness to learn new things
• Work Routine: partially mobile working is possible, with work on premises at 60% (three days a week)
• Languages: business fluent in German and English

Start: according to prior agreement
Duration: 6 months

Requirement for this thesis is the enrollment at university.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

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