Mean square deviation Root mean square deviation Variance Standard deviation.
Cost of penalties for deviation of wind power forecasting in india
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Transcript of Cost of penalties for deviation of wind power forecasting in india
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“ACCURATE WIND POWER FORECASTING IS NO MORE EXPENSIVE with del2infinity”
Cost of Penalties for deviation of Wind Power Forecasting in India
With increasing penetration of wind power having unscheduled fluctuations, system
stakeholders face massive difficulties in maintaining grid reliability; hence the forecasting and
scheduling of wind power is essential for system stability. Though the scheduling is mandatory
with effect from January 1, 2012, earlier this year, the Central Electricity Regulatory
Commission (CERC) introduced a robust framework to strengthen forecasting in
the renewable sector in India. The CERC also issued the Indian Electricity Grid Code (Third
Amendment) Regulations, 2015 and Deviation Settlement Mechanism and related matters
(Second Amendment), Regulations 2015.
Based on comments from all stakeholders during a public hearing at New Delhi, the CERC
recently published a Statement of Reasons document detailing the importance of wind/solar
energy forecasting. The regulation laid down the detailed aspects of wind/solar energy
forecasting to be done by generators in India. The mechanism is applicable from November 1,
2015.
The key features of the mechanism are mentioned below:
The mechanism shall be applicable to wind and solar generators.
Scheduling of wind generators have been made mandatory for aggregated capacity of 50
MW and above.
The maximum number of revisions has been increased from 8 to 16.
A new forecast error computation formula has been formulated, which is:
=100*(Scheduled Generation-Actual Generation)/Available Capacity.
The penalties for deviation have been computed as per Power Purchase Agreements
and shall be levied for any deviation beyond +/-15%
It is required to calculate the approximate average cost of penalties for deviation of wind power
forecasting. Without showing the detailed statistical analysis, this article shows some important
statistical relations and approximations to measure the cost of penalty. For simplification let
consider,
C = average cost per available capacity
c(e) = cost of penalty due to error e where error in new regulation is defined as
,
here AvC = available capacity, xa = actual power and xf = forecast power
If h(e) represents the probability distribution of error e, it is easy to show that the cost per
available capacity can be represented as,
∫
For a good forecasting with maximum 16 revision, we can consider that the mean of
distribution h(e) is approximately 0, variance is and h(- e) = h(e). Considering the no
penalty band as [-m,+m], we can consider the deviation charge follows an linear relation as
| | if | |
= 0 , otherwise
Using some algebraic manipulation we can show that
[ ∫
]
The integral part of the right hand side of the previous equation can be approximated and with
some basic approximation we can state that
[
]
Where
∫
Here represents the probability that the absolute error |e| lies in [0, m]. If we
approximate the variance as
( )
The average cost per available capacity can be represented as
( )
According to CERC (recently published Statement of Reasons document),
Abs Error (%of AvC) |e| Deviation Charge
15%-25% 0.15-0.25 0.1 of PPA rate
25%-35% 0.25-0.35 0.2 of PPA rate
>35% >0.35 0.3 of PPA rate
Here the penalty band is discrete (not continuous), and it is easy show that
| | for |e| = 0.25, 0.35, 0.45. With some approximation we can assume
that k is approximately equals to PPA rate and the average cost per available capacity
transforms into
( )
For PPA rate = Rs. 5 / kW-Hr, the average cost per available capacity in Rs / MW-Hr can be
represented as
( )
The above analysis is basic statistical approximation on the cost of penalties due to deviation
charge of wind power forecasting. Similar analysis can be done in solar power forecasting. For
detail calculations, plant specific analysis and forecasting issues please contact us at
Scenario m C
(Rs / MW-Hr)
C
(% of PPA rate)
Weak forecast (Old Regulation) 0.30 0.25 459.37 9.19 %
Weak forecast (new Regulation) 0.15 0.25 677.34 13.55 %
Del2infintiy (old regulation) 0.30 0.90 61.25 1.2 %
Del2infinity (new regulation)
Worst Case
0.15 0.80 180.62 3.6 %
del2infinity (new regulation) 0.15 0.95 45.16 0.90 %
