Master Thesis: Model Predictive Control–Based Energy Management System (EMS) for an Office Building

HANSA Klimasysteme GmbH; Saterland; Vor Ort; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A company specializing in energy management solutions in Niedersachsen, Germany is seeking a dedicated candidate for a Master Thesis in Model Predictive Control–Based Energy Management System. The role involves developing a neural network-based building model and implementing an EMS, optimizing strategies for heating and cooling while managing dynamic electricity pricing. Candidates should have strong knowledge in energy systems and experience with MATLAB or Python. A supportive environment will be provided by experienced professionals.

Leistungen

Individualized support from qualified professionals

Innovative work environment

Qualifikationen

• Knowledge in energy system analysis, building modeling, and control.
• Experience with MATLAB/Simulink or Python essential for modeling.
• Knowledge in machine learning and predictive control concepts.

Aufgaben

• Develop a neural network-based building model for thermal dynamics.
• Design and implement a Model Predictive Control-based EMS for operations.
• Optimize pre-heating, cooling strategies, and manage dynamic electricity prices.

Kenntnisse

Knowledge in energy system analysis

Experience with MATLAB/Simulink or Python

Knowledge in machine learning

Background in Mechanical, Electrotechnical or Informatics

Jobbeschreibung

Master Thesis: Model Predictive Control–Based Energy Management System (EMS) for an Office Building

With the increasing demand for residential comfort and the rising importance of energy cost optimization, it is a major challenge to balance comfort, economy, and sustainable energy usage in residential buildings. Advanced energy management systems (EMS) provide a practical solution for achieving this goal.

This thesis will develop a Model Predictive Control (MPC)–based EMS for a data‑driven building model, created using neural networks in MATLAB or Python. The building model will represent a modular office building, including thermal zones, a HVAC system, a static heating system, a cold water storage tank, and an electric chiller for cooling. The MPC‑based EMS will optimize pre‑heating in winter and pre‑cooling in summer, taking into account electricity prices, including the contribution of a photovoltaic (PV) system, and the operation of thermal storage and cooling equipment.

Tasks

• Development of a neural network–based building model capable of predicting thermal dynamics for heating and cooling scenarios
• Design and implementation of a Model Predictive Control–based EMS for Winter and Summer operations, considering:
• Pre‑heating and pre‑cooling strategies
• Cold water storage and electric chiller operation
• Static heating system
• HVAC system
• Dynamic electricity prices and PV generation

Qualifications

• Knowledge in energy system analysis, building modeling, and control
• Experience with MATLAB/Simulink or Python (essential for neural network modeling and MPC implementation)
• Knowledge in machine learning (neural networks) and predictive control concepts
• Mechanical, electrotechnical, or informatics background

Apply online via this platform or by email: [e-mail]

We offer individualized support from highly qualified and dedicated professionals within an innovative, medium‑sized company.

We look forward to receiving your application.
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