Ettore Zanetti, Donghun Kim, David H. Blum, R. Scoccia, M. Aprile
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Performance comparison of quadratic, nonlinear, and mixed integer nonlinear MPC formulations and solvers on an air source heat pump hydronic floor heating system
There is a gap in literature on comparisons between different MPC optimal control formulations and solver choices for the same building HVAC system. Mixed Integer Nonlinear (MINL) formulations are rarely considered, despite being the most physically accurate way to represent HVAC systems. This work compares several MPC formulations, including Quadratic, Nonlinear, and MINL, applied to a case study building and investigates benefits and challenges of MINL MPCs from practical perspectives. Ten different MPC formulations were developed and implemented using Pyomo. Then, a detailed emulator model was developed using open-source Modelica libraries and used with BOPTEST to assess the performance of each MPC. Results show that convergence and control switching behaviours of MINL MPCs are sensitive to formulations, initialization approaches, solver selections, and solver parameters. Thus, they require significant effort for tuning. However, a very well-tuned MINL MPC performed similarly to successful Nonlinear MPC formulations.
期刊介绍:
The Journal of Building Performance Simulation (JBPS) aims to make a substantial and lasting contribution to the international building community by supporting our authors and the high-quality, original research they submit. The journal also offers a forum for original review papers and researched case studies
We welcome building performance simulation contributions that explore the following topics related to buildings and communities:
-Theoretical aspects related to modelling and simulating the physical processes (thermal, air flow, moisture, lighting, acoustics).
-Theoretical aspects related to modelling and simulating conventional and innovative energy conversion, storage, distribution, and control systems.
-Theoretical aspects related to occupants, weather data, and other boundary conditions.
-Methods and algorithms for optimizing the performance of buildings and communities and the systems which service them, including interaction with the electrical grid.
-Uncertainty, sensitivity analysis, and calibration.
-Methods and algorithms for validating models and for verifying solution methods and tools.
-Development and validation of controls-oriented models that are appropriate for model predictive control and/or automated fault detection and diagnostics.
-Techniques for educating and training tool users.
-Software development techniques and interoperability issues with direct applicability to building performance simulation.
-Case studies involving the application of building performance simulation for any stage of the design, construction, commissioning, operation, or management of buildings and the systems which service them are welcomed if they include validation or aspects that make a novel contribution to the knowledge base.