Peak demand happens on electrical grid and it happens when the average power of electricity demand reaches its peak in specified period of time (Gyamfi, Krumdieck & Urmee, 2013). Peak demand has specified unit of power, kW, and generally it is presented as seasonal, daily or annual. It can be observed in moments like when turning all the lights on in a facility or turning on the power in some big electric motor that is responsible for propelling some high intensity work. Company responsible for providing electricity has to be able to deliver needed amount of electricity that allows for that peak to happen, but it comes with higher costs of utility (Rogner, 2012).
How peak demand is measured
There is a concrete period of time that is considered in which there is a need to measure consumed energy by simply adding it up and assigning it directly with kW units of power. The result of this operation is peak demand value (Oldewurtel et al., 2010).
The effect of a billing method on the behaviour
Because of the fact that in some regions utilities act according to "ratchet clause" (billing for the highest one-time peak demand in the entire billing cycle), engineers are more likely to minimize their energy bills to conserve energy. The peak demand can even go up from 30% to 70% of the electricity bill (Sioshansi, 2013).
Factors that affect peak demand:
- Utility provider,
- region of living or working,
- applicable tariffs,
- pricing structures specified by utility providers, regional or national law, or others (Ma et al., 2012).
Avoiding peak demand
Since peak demand is not profitable for financial costs there are a few ways that engineers can avoid it:
- Automating and monitoring used powers load (Tang et al., 2013).
- Another method of dealing with this problem is to distribute power over different parts of the facility. It is advised to observe and control power loads and to turn the power - intensive equipment on in steps, not all at once. Although it's not obvious at first, it is possible to spend less money on electric bill by keeping electronic machinery turned on (Liu, Miller & Ledwich, 2017).
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- Gyamfi, S., Krumdieck, S., & Urmee, T. (2013). Residential peak electricity demand response—Highlights of some behavioural issues, Renewable and Sustainable Energy Reviews, 25, 71-77.
- Harvey, D. (2010). Energy and the new reality 1: Energy efficiency and the demand for energy services, Routledge.
- Liu, L., Miller, W., & Ledwich, G. (2017). Solutions for reducing electricity costs for communal facilities, Australian Ageing Agenda.
- Ma, J., Qin, J., Salsbury, T., & Xu, P. (2012). Demand reduction in building energy systems based on economic model predictive control, Chemical Engineering Science, 67(1), 92-100.
- Oldewurtel, F., Ulbig, A., Parisio, A., Andersson, G., & Morari, M. (2010). Reducing peak electricity demand in building climate control using real-time pricing and model predictive control, In 49th IEEE conference on decision and control (CDC) (pp. 1927-1932). IEEE.
- Rogner, H. H. (2012). Energy resources, In Energy for Development (pp. 149-160). Springer, Dordrecht.
- Sioshansi, F. P. (2013). Energy efficiency: towards the end of demand growth, Academic Press.
- Tang, S., Huang, Q., Li, X. Y., & Wu, D. (2013). Smoothing the energy consumption: Peak demand reduction in smart grid, In 2013 Proceedings IEEE INFOCOM (pp. 1133-1141). IEEE.
- Wang, L. (2008). Energy efficiency and management in food processing facilities. CRC press.
Author: Katarzyna Atłas