D Apostolopoulou E A Paaso and K Anastasopoulos Commonwealth Edison Company 10122015 What has been done A stochastic framework to analyze Distributed Generation DG integration into a feeder ID: 645593
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Slide1
Assessing Feeder Hosting Capacity for Distributed Generation Integration
D. Apostolopoulou, E. A. Paaso, and K. AnastasopoulosCommonwealth Edison Company10/12/2015Slide2
What has been done?
A stochastic framework to analyze
Distributed Generation (DG)
integration into a feeder
has been developed.
Uncertainty in DG size and locationLoad ModelingMore analytical approach compared to FERC 15% rule
2Slide3
Significant increase in
DG deployment:
Decreasing cost of DG technologies
Customer
evolution
Financial incentives
supporting renewable
generation
Impacts
on system reliability and power quality
3
BackgroundSlide4
4
The maximum amount
of DG that can be accommodated by a feeder
without impacting its reliability and/or power quality
Every distribution feeder is unique
Hosting Capacity
No.
of Shunt Capacitors
No. of Customers
No.
of Overhead Lines
Hosting Capacity (kW)
Feeder 1
0
144
11
2,025
Feeder 2
3
95
187
1,125
Feeder 3
3
208
286
775Slide5
5
A stochastic approach is adopted to capture the impacts on the system of potential DG deployment scenarios
Scalability and
a
utomated
simulations
Stochastic
loading model based on the historical
data
Location and size of DG
Proposed Framework
Load
level
phase
a
DG
« input »
random
processes
Power Flow
on the feeder
Load
level
phase
b
Load level phase c
Hosting Capacity
« output »
random
process
Figure: Conceptual structure of proposed frameworkSlide6
6
Historical
data of the load for each phase are
collected:
Derive an empirical probability distribution function:
Modeling
of Load Uncertainty
Figure: Historical load data
Figure: Empirical pdfs of loadSlide7
7
Location and output of DG
For a given load level multiple scenarios and penetration levels of DG are developed to evaluate a feeder’s hosting capacity
Modeling of Distributed Generation Uncertainty
PV
PV
PV
substation
Figure: Voltage levels in a random feederSlide8
Penetration Level 1:
0%
of
DG
DG is randomly added
to
the feeder to create N different penetration levels
8
Distributed Generation Penetration Levels
Penetration Level 1
Penetration Level 2
Penetration Level N
…Slide9
9
Proposed Simulation FrameworkSlide10
10
Minimum
hosting
capacity: the
penetration level where the
FIRST
maximum voltage exceeds the ANSI voltage limit.
Maximum
hosting
capacity:
the penetration level where ALL the maximum voltages exceed the ANSI voltage limit
Minimum and Maximum Hosting
Capacity
Figure: Hosting CapacitySlide11
11
Numerical Results on a Real Utility Feeder
366 nodes and 365 lines
Historical load data over a two year period
100 scenarios and 70 penetration levels
Maximum
Hosting
Capacity
Minimum
Hosting
CapacitySlide12
12
Probability Distribution Function of Hosting Capacity
671kW, 15% Rule FERCSlide13
13
An
stochastic simulation framework that can determine the hosting capacity of a feeder
was developed
The
proposed
framework was used to
identify ideal locations for DG
installation
The hosting capacity of a real feeder was determined with the proposed framework. The estimated hosting capacity is higher than the 15% rule by FERC.
ConclusionsSlide14
14
Thank you!