A comparative analysis of the most common deterministic methods for the calculation of electricity losses in industrial networks

: The work is devoted to the analysis of deterministic most common methods for determining electricity losses in low-voltage industrial power supply networks. The method of graphical integration, the method of calculating electricity losses using the maximum loss time, the method of determining losses by time 2t, the method of calculating electricity losses by the average node loads are considered. The features of the application of each method are revealed. It is shown that for the method of graphical integration, initial data on the dependences of load schedules for each network element are required, and the method of calculating losses by average node loads can be used in networks with relatively constant loads. We consider the methods of calculating the losses based on graphical integration, the time of largest losses, 2t and the root-mean-square loads.

At the same time, the errors of the considered methods for calculating electricity losses can be due to such reasons as the neglect of the heating temperature of the conductors, the neglect of the resistances of the contact connections of switching devices, the inaccuracy of determining the values of losses during the highest and lowest power demand, the inaccuracy of determining the time of the largest losses,. disregarding the form of the load schedule of consumers.

Using the example of an industrial radial network site with known load graphs of consumers, the electric power losses in the circuit lines with the specified methods were calculated with the determination of the error of each method and the identification of the causes of errors. In this case, the method of graphical integration was adopted as the reference method of calculation. As a result of the calculations, it was established that the method of calculating 2t has the smallest error. It is shown that when choosing a method for determining electricity losses, it is necessary to observe the condition of compliance with methodological and informational errors.

1. Ponomarenko OI., Holidaynov II. Influence of the asymmetrical modes on losses power in electrical networks of the distributed systems of power supply. Energetik. 2015;12:6-8.

2. Kosouhov FD., Vasilev NV. Filippov AO. Decrease of losses from asymmetry of currents and improvement of electric energy in networks of 0,38 kV with household loadings. Electrical Euipment. 2014;6:8-12.

3. Averbuh MA., Zhilin EV. About losses of the electric power in systems of powersupply of individual housing construction. Energetik. 2016; 6:54-57.

4. Eremina MA. Development of automatic systems for commercial energy accounting of energy resources (AMRMS). Molodojuchenyj. 2015;3:135-138.

5. Sapronov AA., Kuzhekov SL., Tynjanskij VG. Expeditious identification of uncontrollable electricity consumption in electric networks up to 1kV. News of higher education institutions. Electromecanics.2004;1 55-58.

6. Gracheva EI. Processing of statistical information for the purpose of revealing the laws of changing the parameters of the equipment of the workshop networks. News of hidheredicational institutions of the Chernozem region. 2016;2:34-43.

7. Zelenskii EG., Kononov YG., Levchenko II. Identification of parameters of distribution networks by synchronized current and voltage measurements. Russian Electrical Engineering. 2016;87(7):363-368.

8. .Stepanov AS., Stepanov SA., Kostyukova SS. Identification of parameters of models of electric network elements on the basis of tellegens theorem. Russian Electrical Engineering. 2016;87(7):369-372.

9. Gracheva EI. Specification of the magnitude of the equivalent resistance of the guild networks. Reliability and safety of power engineering. 2015;3:34-36.

10. Zhelezko YuS., Artemyev AV., Savchenko OV. Calculation, analysis and rationing of electric power losses in electric networks: A guide for practical calculations. M: Publishing House NTs ENAS, 2004. 280 p.

11. Zhelezko YuS. Statistical characteristics of the errors of measuring systems and their use in calculating the under-accounting of electricity. Electric stations. 2006;2:32-40.

12. Zhelezko YuS. About regulatory documents in the field of electric power quality and reactive power consumption conditions. Electric stations. 2002;6:18-24.

13. Marinopoulos AG. Energy losses in a distribution line with distributed generation based jg stochastic power flow. 2011;5:86-94.

14. Wang F. Reliability Evaluation of Distribution System Based on Modified Failure Mode and Effect Analysis Method. Low Voltagt Apparatus. 2013;1:37-42.

15. Graovac D. Universal power quality system – an extension to the universal power quality conditioner. International conference on power electronics and motion control.2000;4:32-38.