Climate Control Using Model Predictive Control to Reduce Energy Consumption in Hjørring Badminton Arena
Translated title
Klima Kontrol ved brug af Model Predictive Control til at Reducere Energiforbrug i Hjørring Badminton Arena
Author
Givskov, Michael Harding
Term
4. term
Education
Publication year
2021
Submitted on
2021-06-03
Pages
81
Abstract
Denne afhandling undersøger, hvordan model predictive control (MPC) kan anvendes til at reducere energiforbruget i opvarmning, ventilation og aircondition (HVAC) i ældre kommercielle bygninger, med Hjørring Badminton Arena som cases. Udgangspunktet er, at bygninger står for en stor del af energiforbruget, og at rumopvarmning udgør en betydelig andel. Der opstilles komfortkrav for brugere og aktivitetsmønstre, så temperaturen kan sænkes i nattetimer og ved tomme perioder, mens den holdes komfortabel under brug. Arenaens HVAC-system modelleres med termiske delmodeller for krydsstrømsrekuperator, vand–luft-varmeveksler (fjernvarme) og hovedhallen; modellerne kombineres til en ikke-lineær samlet model, hvor luftstrøm, varmeafgivelse, returluft- og udetemperaturer er inputs og rumtemperaturen er output. Antal personer i hallen behandles som en forstyrrelse. En gain-scheduled MPC designes og tunes til at optimere opvarmningsstrategien; på grund af en fejl i varmevekslermodellen anvendes blæserne primært ved kølebehov. Simuleringer viser en reduktion i energiforbruget på omkring 4 % sammenlignet med det eksisterende system i samme periode. Resultatet er lavere end forventet, hvilket tilskrives et større varmetab i modellen end i det virkelige anlæg. Arbejdet demonstrerer et proof-of-concept for MPC-baseret klimastyring, men yderligere model- og systemforbedringer er nødvendige for at kvantificere og øge besparelserne.
This thesis investigates the use of model predictive control (MPC) to reduce energy consumption in heating, ventilation, and air conditioning (HVAC) systems in older commercial buildings, using Hjørring Badminton Arena as a case study. Buildings consume a substantial share of energy, with space heating representing a significant fraction. Occupant comfort ranges and activity patterns are defined so that indoor temperature can be lowered during night and vacancy periods while maintaining comfort during occupancy. The arena’s HVAC is modeled with thermal submodels for a cross-flow recuperator, a water–air heat exchanger (district heating), and the main hall; these are combined into a nonlinear overall model where airflow, heater power, return-air, and ambient temperatures are inputs and room temperature is the output. The number of occupants is treated as a disturbance. A gain-scheduled MPC is designed and tuned to optimize the heating strategy; due to a flaw in the heater model, the fans are mainly used when cooling is needed. Simulations show an energy reduction of about 4% compared with the existing system over the same period. This is lower than expected, attributed to higher modeled heat loss than in the real system. The work provides a proof of concept for MPC-based climate control, with further model and system improvements required to quantify and enhance savings.
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