Experimental demonstration of grid-supportive scheduling of a polygeneration system using economic-MPC
- Drawing off the technical flexibility of building polygeneration systems to support a rapidly expanding renewable electricity grid requires the application of advanced controllers like model predictive control (MPC) that can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints amongst other features. In this original work, an economic-MPC-based optimalDrawing off the technical flexibility of building polygeneration systems to support a rapidly expanding renewable electricity grid requires the application of advanced controllers like model predictive control (MPC) that can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints amongst other features. In this original work, an economic-MPC-based optimal scheduling of a real-world building energy system is demonstrated and its performance is evaluated against a conventional controller. The demonstration includes the steps to integrate an optimisation-based supervisory controller into a standard building automation and control system with off-the-shelf HVAC components and usage of state-of-art algorithms for solving complex nonlinear mixed integer optimal control problems. With the MPC, quantitative benefits in terms of 6–12% demand-cost savings and qualitative benefits in terms of better controller adaptability and hardware-friendly operation are identified. Further research potential for improving the MPC framework in terms of field-level stability, minimising constraint violations, and inter-system communication for its deployment in a prosumer-network is also identified.…
Document Type: | Article (reviewed) |
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Zitierlink: | https://opus.hs-offenburg.de/5253 | Bibliografische Angaben |
Title (English): | Experimental demonstration of grid-supportive scheduling of a polygeneration system using economic-MPC |
Author: | Parantapa Amarsinh SawantORCiDGND, Adrian Bürger, Clemens Felsmann, Jens PfafferottStaff MemberORCiDGND |
Date of Publication (online): | 2021/12/03 |
Publisher: | Elsevier |
Page Number: | 18 |
Article Number: | 111619 |
Parent Title (English): | Energy & Buildings |
Volume: | 254 |
ISSN: | 0378-7788 (Print) |
ISSN: | 1872-6178 (Online) |
DOI: | https://doi.org/10.1016/j.enbuild.2021.111619 |
Language: | English | Inhaltliche Informationen |
Institutes: | Forschung / INES - Institut für nachhaltige Energiesysteme |
Fakultät Maschinenbau und Verfahrenstechnik (M+V) | |
Institutes: | Bibliografie |
DDC classes: | 600 Technik, Medizin, angewandte Wissenschaften | Formale Angaben |
Relevance: | Wiss. Zeitschriftenartikel reviewed: Listung in Master Journal List |
Open Access: | Closed Access |
Licence (German): | Urheberrechtlich geschützt |
Comment: | Online am 3. Dezember 2021 veröffentlicht. |