[UC09] EV Charging & Use of Reserved Capacity Analysis

Billing
Consumer Rates and Programs
Electric Vehicles (EV)

Utilities must have accurate insight into grid load growth due to the rapid rise in EV chargers. For such analysis, data cleansing and correction are usually required.

The Utility Problem

Electromobility is one of the leading innovative trends of today and one of the main instruments to achieve the goals of the Paris Agreement. Utilities must have accurate insight into grid load growth due to the rapid rise in EV chargers. 

One of the tools utilities use for keeping the load at individual consumption points “under control” is assigning fixed reserved capacity for each consumer – usually by master circuit breaker (MCB). The maximal reserved capacity of the consumption point describes the maximum power consumed at a given moment. Based on the utility billing scheme, the customer might:

  1. Pay a specified fixed monthly amount for this capacity and/or
  2. When this capacity is exceeded, a fee is charged, or the main circuit breaker is tripped. 

These capacity fees and peak load charges might be significant, especially for industrial customers, so it is important to optimize them. Utilities also use MCB (and maximal demand) values for network dimensioning, assessing the grid’s capacity. 

Just synchronizing the data from the meters and EV chargers can be challenging as the data from the different systems will likely be in various formats. To optimize these values, utilities or EV charger administrators usually focus only on the maximum load of EV chargers and the maximum load of other electricity-consuming equipment. However, this does not describe the real world, where the maximum load on all elements occurs in rare cases. Thus, there is a need to look at this issue in more detail using synchronized measured data. This methodology should work based on probabilities and more closely approximates actual behaviour. For such analysis, the data cleaning and possible correction might also need to be solved.

This analysis can identify under-utilized (unused) reserved capacity at a selected location (consumption point), saving consumers significant amounts in capacity fee payments. Consumers can also simulate how many EV chargers can be added before the maximal capacity is exceeded. On the utility side, this can save investment funds, as it will not be necessary to upgrade the grid with, for example, a higher-diameter conductor or a new station with a higher capacity. 

 

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