Nadgradnja ogrevalnega sistema z internetom stvari

magistrsko delo

Branko Zebec (Avtor), Andrej Škraba (Mentor)

Povzetek

Magistrsko delo vsebuje analizo in razvoj prototipa za nadgradnjo ogrevalnega sistema, pri katerem smo sledili dvema ciljema: povezati ogrevalni sistem v internetno omrežje s pomočjo tehnologije interneta stvari in optimizirati ogrevalni sistema. Za dosego ciljev smo raziskali vse potrebne tehnologije, programska orodja in strojno opremo. Pri implementaciji smo uporabili programsko platformo Home Assistant, s katero smo razvili glavni krmilnik na strojni opremi Raspberry Pi 4. V okviru platforme Home Assistant smo integrirali dodatna programska orodja: Cloudflare za vzpostavitev varne povezave na oblačni strežnik in s tem ustvarjanje varnega tunela do glavnega krmilnika, Node-RED, s katerim smo razvili programsko kodo za povezavo z napravami Modbus in optimizacijo sistema vključno s PID krmilnikom, InfluxDB za bazo podatkov vseh spremenljivk našega ogrevalnega sistema, Grafano za vizualizacijo podatkov iz baze, Google SDK za integracijo Googlovega pomočnika na Home Assistant. Na krmilnik smo povezali naprave prek protokola Modbus TCP/IP (angl. Transmission Control Protocol/Internet Protocol): Daikin krmilnik za dostop do toplotne črpalke Daikin Altherma HT, Siemens sobni termostat. Za spremljanje porabe električne energije smo razvili merilnik porabe na modulu ESP32, ki smo ga povezali na kontakte S0 analognega števca. Programsko kodo C++ smo povzeli in prilagodili ter povezali prek protokola MQTT na Home Assistant. Razvili smo tudi simulacijski model, s pomočjo katerega smo preverjali nastavitve PID krmilnika. S statistično analizo smo preverili, ali so podatki po optimizaciji sistema resnično potrdili pričakovane rezultate glede zmanjšanja porabe električne energije, manjšega vtoka ogrevalne vode ter sprememb sobne temperature. Prototip smo preverjali v celotnem ogrevalnem obdobju, le-ta je deloval zanesljivo brez izpadov. Za oddaljeni dostop smo uporabljali Home Assistant pomočnika in Googlovega pomočnika. Optimizacija ogrevalnega sistema se je izkazala za zelo uspešno, kar smo potrdili z meritvami spremenljivk, predvsem porabe električne energije. Ugotovili smo, da se v prehodnem obdobju ogrevanja poraba znatno zmanjša. Na podlagi tega smo prepričani, da bomo na dolgi rok podaljšali življenjsko dobo toplotne črpalke ter prispevali k trajnostni naravnanosti našega sistema ogrevanja.

Ključne besede

internet stvari (IoT);pametni dom;ogrevanje;Home Assistant;Node-RED;PID.;

Podatki

Jezik:	Slovenski jezik
Leto izida:	2024
Tipologija:	2.09 - Magistrsko delo
Organizacija:	UM FOV - Fakulteta za organizacijske vede
Založnik:	[B. Zebec]
UDK:	004
COBISS:	216082691
Št. ogledov:	0
Št. prenosov:	1
Ocena:	0 (0 glasov)
Metapodatki:

Ostali podatki

Sekundarni jezik:	Angleški jezik
Sekundarni naslov:	Upgrading the heating system with internet of things
Sekundarni povzetek:	The master's thesis includes the analysis and development of a prototype for upgrading the heating system, where we pursued two objectives: connecting the heating system to the internet using technology Internet of Things (IoT) and optimizing the heating system. To achieve our objectives, we researched all the necessary technologies, software tools, and hardware. In the implementation, we used the Home Assistant software platform to develop the main controller on Raspberry Pi 4 hardware. Within the Home Assistant platform, we integrated additional software tools: Cloudflare to establish a secure connection to the cloud server, thereby creating a secure tunnel to the main controller; Node-RED, which we used to develop the software code for connecting with Modbus devices and optimizing the system, including a PID controller; InfluxDB for the database of all variables in our heating system; Grafana for data visualization from the database; and the Google SDK for integrating Google Assistant with Home Assistant. We connected devices to the controller via the Modbus TCP/IP protocol (Transmission Control Protocol/Internet Protocol): a Daikin controller for accessing the Daikin Altherma HT heat pump, and a Siemens room thermostat. To monitor electricity consumption, we developed a consumption meter using an ESP32 module, which we connected to the S0 contacts of the analog meter. We adapted and customized the C++ code and connected it to Home Assistant via the MQTT protocol. We also developed a simulation model to test the PID controller settings. Using statistical analysis, we verified whether the data after system optimization truly confirmed the expected results regarding the reduction in electricity consumption, lower heating water flow, and changes in room temperature. The prototype was tested throughout the entire heating period and operated reliably without any failures. For remote access, we used the assistant Home Assistant and Google Assistant. The optimization of the heating system proved to be very successful, as confirmed by the measurements of variables, particularly electricity consumption. We found that during the transitional heating period, consumption significantly decreased. Based on this, we are confident that, in the long run, we will extend the lifespan of the heat pump and contribute to the sustainability of our heating system.
Sekundarne ključne besede:	Avtomatizacija doma;Univerzitetna in visokošolska dela;
Vrsta dela (COBISS):	Magistrsko delo/naloga
Komentar na gradivo:	Univ. v Mariboru, Fak. za organizacijske vede
Strani:	f.
ID:	25044141