Environmentally friendly electricity management
Fragment książki (Rozdział w monografii)
MNiSW
20
Poziom I
| Status: | |
| Autorzy: | Buczaj Marcin |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Strony: | 165 - 182 |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Witryna wydawcy |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 21 sierpnia 2023 |
| Abstrakty: | angielski |
| The use of computer tools and applications in the process of achieving electricity economy enables efficient management of the technical infrastructure potential and elements of building equipment. The presented software tools do not eliminate the human factor from the supervision process, but they do facilitate the work and expand its capabilities. Thanks to the tools enabling the management of the electricity distribution process, the information transfer process and the decision-making process can be improved and shortening the time of identifying a potential threat by the BMS system also reduces the negative economic effects (cost reduction) and ecological failures (limiting the emission of hazardous compounds). Thanks to the use of software enabling the acquisition and analysis of measurement data, it is possible to change the strategy of using individual systems and, as a result, reduce the demand for electricity in buildings. The use of analytical programs in one of the facilities of Lublin University of Technology made it possible to reduce the demand for electricity by approx. 20% compared to the reference period in which the building was operated with the manufacturer’s standard settings. This results in a reduction of electricity consumption by over 250,000 kWh per year. The use of software for the acquisition and analysis of measurement data allows simulations related to the selection of electricity tariffs and their adaptation to the nature of the building load. Additionally, it is possible to analyse other technical parameters, such as reactive power consumption. Thanks to the analysis of reactive power data and the use of reactive power compensation systems, its share in electricity bills has been limited to trace amounts. The analysis of time histories and the knowledge of the functioning of the technical infrastructure in the building enables the reduction of daily and monthly power peaks while the demand for electricity remains unchanged. Based on the measurement data, the determination of correspondingly lower expected peak loads reduces the costs of electricity supply. An additional rational distribution of the load variability course also reduces the charges related to the capacity fee. |
