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Load Curve Monitoring Techniques and Data Analytics

M. Sreenivasa Reddy, A. Shubhangi Rao, Ch. Sai Prakash

Abstract


In India we may get the information from the India central energy information, the consumption of energy is nearly 33% from commercial buildings which is increasing day by day. The rise in energy consumption by commercial buildings is increasing at a rate of 8-10% every year in India. Generally, load curve monitoring is a method which is used to determine the electricity consumption of various electrical appliances which are present in the college building. The load consumption of various appliances based on their composite loads is measured at the electric meters in the college building. These electric energy meters can provide the information like the type of load, appliances working condition, appliances energy consumption details to the consumer and the state electric board. This information is used to plan the load strategy in the college for various blocks for optimal utilization the grid which is inter connected with solar power. So, load curve monitoring is generally classified into 2 types. Intrusive and non-Intrusive load monitoring. Intrusive load monitoring is costly because the manufactured equipment’s are to be installed, and it provides accurate data values of each electric appliance energy consumption to the state electric board and to the consumers. Non-Intrusive load monitoring method is a cost-effective method, because in this method only the few equipment’s need to be installed. Load curve monitoring and analysis is an efficient instrument aiming to study, which is necessary to develop Electrical energy distribution network and reduce electrical energy internal consumption. In this paper, the load curve analysis for MLRIT campus which is fed from 440 Volts is presented. The article is concerned with the different load monitoring techniques.

 

Keywords: Load duration curve, rise time, peak time, current unbalancing, base load, load rescheduling, optimal usage

 


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References


Panapakidis, I. P., Papadopoulos, T. A., Christoforidis, G. C., & Papagiannis, G. K. (2014). Pattern recognition algorithms for electricity load curve analysis of buildings. Energy and Buildings, 73, 137-145.

Pellegrino, A., Verso, V. R. L., Blaso, L., Acquaviva, A., Patti, E., & Osello, A. (2016). Lighting control and monitoring for energy efficiency: A case study focused on the interoperability of building management systems. IEEE Transactions on Industry Applications, 52(3), 2627-2637.

Smith, R. A., Shultz, R. D., & Sweet, T. M. (1983). Cumulant method equivalent load curve calculation performance for small generation systems. IEEE Transactions on Power Apparatus and Systems, (5), 1302-1307.

Qian, K., Zhou, C., Allan, M., & Yuan, Y. (2010). Modeling of load demand due to EV battery charging in distribution systems. IEEE transactions on power systems, 26(2), 802-810.

Qian, K., Zhou, C., Allan, M., & Yuan, Y. (2010). Modeling of load demand due to EV battery charging in distribution systems. IEEE transactions on power systems, 26(2), 802-810.

Pellegrino, A., Verso, V. R. L., Blaso, L., Acquaviva, A., Patti, E., & Osello, A. (2016). Lighting control and monitoring for energy efficiency: A case study focused on the interoperability of building management systems. IEEE Transactions on Industry Applications, 52(3), 2627-2637.

McCarthy, R., & Yang, C. (2010). Determining marginal electricity for near-term plug-in and fuel cell vehicle demands in California: Impacts on vehicle greenhouse gas emissions. Journal of Power Sources, 195(7), 2099-2109.

Albicki, A. (2000). Intrusive Identification of Electrical Loads in a Three- Phase Measurement Technology. IMTC2000, 1, 24-29.

Du, Y., Du, L., Lu, B., Harley, R., & Habetler, T. (2010, September). A review of identification and monitoring methods for electric loads in commercial and residential buildings. In 2010 IEEE Energy Conversion Congress and Exposition (pp. 4527-4533). IEEE.

Li, J., & Yang, H. (2012, March). The investigation of residential load identification technologies. In 2012 Asia-Pacific Power and Energy Engineering Conference (pp. 1-4). IEEE.


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