Paghatag ug Pag-analisis sa mga Katangian sa Load sa mga Distribution Transformers

Larangan: Pagsusi sa Transformer

China

Dalam na Analisis ug mga Konsiderasyon sa Pag-evaluha sa Load Characteristic

Ang pag-evaluha sa load characteristic usa ka pundasyon sa pagdisenyo sa distribution transformer, nga direkta nga naghuhumong sa pagpili sa kapasidad, distribusyon sa loss, kontrol sa temperature rise, ug ekonomiya sa operasyon. Ang evaluasyon kini kinahanglan isulod sa tulo ka dimensyon: klase sa load, temporal dynamics, ug environmental coupling, uban ang modelo nga gihatag basehan sa aktwal nga kondisyon sa operasyon.

1. Mas detalyadong Analisis sa Mga Klase sa Load

Klasipikasyon ug Katangian

Residential Loads: Dominado sa ilaw ug mga panimalay nga gamit, uban ang daily load curve nga nagpakita og dual peaks (buntag ug gabii) ug usab ang mababa nga annual load factor (humoltar 30%–40%).
Industrial Loads: Ikatulong sa continuous (e.g., steel mills), intermittent (e.g., machining), ug impact loads (e.g., electric arc furnaces), nga nagkinahanglan og atensyon sa harmonics, voltage fluctuations, ug inrush currents.
Commercial Loads: Taliwala sa shopping malls ug data centers, nga nagpakita og seasonal variations (e.g., summer air conditioning) ug nonlinear characteristics (e.g., UPS, frequency converters).

Load Modeling

Gamiton ang equivalent circuit models o measured data fitting aron makwantihi ang power factor (PF), harmonic content (e.g., THDi), ug load rate fluctuations.

2. Dynamic Analysis Across Temporal Dimensions

Daily Load Curve

Gidugay gikan sa field monitoring o standard curves (e.g., IEEE), nga nagpakita sa peak ug off-peak periods ug ilang durasyon.
Example: An industrial park’s daily curve reveals dual peaks from 10:00–12:00 and 18:00–20:00, with nighttime load rates below 20%.

Annual Load Curve

Nagpakita sa seasonal variations (e.g., summer cooling, winter heating) ug nagpredict sa future load growth pinaagi sa historical data.
Key Metrics: Annual maximum load utilization hours (Tmax), load factor (LF), ug load coefficient (LF%).

3. Environmental Coupling and Correlation Assessment

Temperature Impact

Every 10°C increase in ambient temperature reduces transformer rated capacity by approximately 5% (based on thermal aging models), necessitating overloading capability verification.

Altitude Impact

Every 300m increase in altitude decreases insulation strength by ~1%, requiring insulation design adjustments or capacity derating.

Pollution Severity

Categorized per IEC 60815 (e.g., light, heavy pollution), influencing bushing and insulator selection and creepage distance.

4. Evaluation Methods and Tools

Measurement-Based Approach

Collects real-world load data via smart meters and oscillographs, followed by statistical analysis (e.g., load rate distribution, harmonic spectrum).

Simulation-Based Approach

Utilizes software like ETAP or DIgSILENT to model power systems under various scenarios.

Empirical Formulas

Such as the load factor formula in IEC 60076 for rapid transformer capacity estimation.

5. Application of Evaluation Results

Capacity Selection

Determines transformer capacity based on load rate (e.g., 80% design margin) and overloading capability (e.g., 1.5× rated current for 2 hours).

Loss Distribution

Iron losses (PFe) are load-independent, while copper losses (PCu) scale with load squared, necessitating a balance between no-load and load losses.

Temperature Rise Control

Calculates winding hot-spot temperatures based on load characteristics to ensure compliance with insulation material thermal ratings (e.g., Class A ≤105°C).

Conclusion

Ang pag-evaluha sa load characteristic kinahanglan intehrahan ang klase sa load, temporal dynamics, ug environmental coupling gamit ang measurement, simulation, ug empirical methods aron makabuo og mas detalyadong modelo. Ang resulta direktang nahimong basehan sa pagpili sa kapasidad, distribusyon sa loss, ug operational reliability, nga nagbuhat sa pundasyon sa pagdisenyo sa distribution transformer.