US 12,015,271 B2Granted

Power distribution network reliability index calculation method and apparatus based on mixed integer linear programming, and medium

AssigneeTsinghua University

InventorsWenchuan Wu, Boming Zhang, Zihao Li, Hongbin Sun, Bin Wang, Qinglai Guo

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Abstract

The disclosure provides power distribution network reliability index calculation method based on mixed integer linear programming. The method includes: establishing a model for optimizing reliability indexes of a power distribution network based on a mixed integer linear programming model, wherein the model comprises an objective function and constraint conditions, the objective function is for minimizing a system average interruption duration index (SAIDI); solving the model based on the objective function and the constraint conditions to obtain reliability indexes of the power distribution network; and controlling operation of the power distribution network based on the reliability indexes.

Claims17

Dependent claims

A power distribution network reliability index calculation method based on mixed integer linear programming, comprising:

determining installation status of components, fault isolation, load transformation supply and action rules of fault recovery when there is a branch fault of the power distribution network, wherein the components include circuit breakers and switches installed at the end of each branch, which are used to isolate the faulty branch circuits and reconfigure the network after a branch circuit failure, and to recover the original power supply network structure after the faulty branch is repaired;
establishing a model for optimizing reliability indexes of a power distribution network based on a mixed integer linear programming model, wherein the model comprises an objective function and constraint conditions, the objective function is for minimizing a system average interruption duration index (SAIDI);
solving the model based on the objective function and the constraint conditions to obtain reliability indexes of the power distribution network;
and
determining the reliability of the power distribution network based on the reliability indexes, and controlling operation of the power distribution network based on the reliability indexes;
wherein establishing the model for optimizing reliability indexes of the power distribution network based on the mixed integer linear programming model comprises:
determining the objective function;
and
determining the constraint conditions;
wherein the constraint conditions comprise a reliability index calculation constraint;
wherein the reliability index calculation constraint is determined by:
CID
i
=
∑
xy
∈
ϒ
λ
xy
⁢
τ
xy
SW
⁢
p
i
xy
+
∑
xy
∈
ϒ
λ
xy
(
τ
xy
RP
-
τ
xy
SW
)
⁢
(
1
-
q
i
xy
)
,
∀
i
∈
Ψ
LN
⁢
CIF
i
=
∑
xy
∈
ϒ
λ
xy
⁢
p
i
xy
,
∀
i
∈
Ψ
LN
⁢
SAIDI
=
∑
i
∈
Ψ
LN
NC
i
⁢
CID
i
∑
i
∈
Ψ
LN
NC
i
⁢
SAIFI
=
∑
i
∈
Ψ
LN
NC
i
⁢
CIF
i
∑
i
∈
Ψ
LN
NC
i
⁢
ASAI
=
1
-
SAIDI
8760
⁢
EENS
=
∑
h
∈
B
Δ
h
8760
⁢
∑
i
∈
Ψ
LN
CID
i
⁢
μ
h
⁢
L
i
where, CIDi represents a customer interruption duration of a node i, λxy represents an annual fault rate of a branch xy, τxySW represents an interruption period of fault isolation action of the branch xy, τxyRP represents an interruption period of fault restore of the branch xy, CIFi represents a customer interruption frequency of the node i, NCi represents a given number of customers of the node i, SAIDI represents a system average interruption duration index, SAIFI represents a system average interruption frequency index, ASAI represents a system average service availability index, EENS represents an expected energy not supplied, B represents a collection of all load levels, Δh represents a number of hours lasted per year for a load level h, μh≤1 represents a peak load ratio of the level h, and Li represents a peak load ratio of the node i.

147 more elements

A power distribution network reliability index calculation apparatus based on mixed integer linear programming, comprising:

a processor;
and
a memory for storing instructions executable by the processor;
wherein the processor is configured to perform:
determining installation status of components, fault isolation, load transformation supply and action rules of fault recovery when there is a branch fault of the power distribution network, wherein the components include circuit breakers and switches installed at the end of each branch, which are used to isolate the faulty branch circuits and reconfigure the network after a branch circuit failure, and to recover the original power supply network structure after the faulty branch is repaired;
establishing a model for optimizing reliability indexes of a power distribution network based on a mixed integer linear programming model, wherein the model comprises an objective function and constraint conditions, the objective function is for minimizing a system average interruption duration index (SAIDI);
solving the model based on the objective function and the constraint conditions to obtain reliability indexes of the power distribution network;
and
determining the reliability of the power distribution network based on the reliability indexes, and controlling operation of the power distribution network based on the reliability indexes;
wherein the constraint conditions comprise a reliability index calculation constraint;
wherein the reliability index calculation constraint is determined by:
C
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⁢
I
⁢
⁢
D
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x
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C
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Δ
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8
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7
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L
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N
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C
⁢
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I
⁢
⁢
D
i
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μ
h
⁢
L
i
where, CIDi represents a customer interruption duration of a node i, λxy represents an annual fault rate of a branch xy, τxySW represents an interruption period of fault isolation action of the branch xy, τxyRP represents an interruption period of fault restore of the branch xy, CIFi represents a customer interruption frequency of the node i, NCi represents a given number of customers of the node i, SAIDI represents a system average interruption duration index, SAIFI represents a system average interruption frequency index, ASAI represents a system average service availability index, EENS represents an expected energy not supplied, B represents a collection of all load levels, Δh represents a number of hours lasted per year for a load level h, μh≤1 represents a peak load ratio of the level h, and Li represents a peak load ratio of the node i.

319 more elements

A non-transitory computer-readable storage medium having stored therein instructions that, when executed by a processor of a terminal, causes the terminal to perform a power distribution network reliability index calculation method based on mixed integer linear programming, the method comprising:

determining installation status of components, fault isolation, load transformation supply and action rules of fault recovery when there is a branch fault of the power distribution network, wherein the components include circuit breakers and switches installed at the end of each branch, which are used to isolate the faulty branch circuits and reconfigure the network after a branch circuit failure, and to recover the original power supply network structure after the faulty branch is repaired;
establishing a model for optimizing reliability indexes of a power distribution network based on a mixed integer linear programming model, wherein the model comprises an objective function and constraint conditions, the objective function is for minimizing a system average interruption duration index (SAIDI);
solving the model based on the objective function and the constraint conditions to obtain reliability indexes of the power distribution network;
and
determining the reliability of the power distribution network based on the reliability indexes, and controlling operation of the power distribution network based on the reliability indexes;
wherein establishing the model for optimizing reliability indexes of the power distribution network based on the mixed integer linear programming model comprises:
determining the objective function;
and
determining the constraint conditions;
wherein the constraint conditions comprise a reliability index calculation constraint;
wherein the reliability index calculation constraint is determined by:
C
⁢
⁢
I
⁢
⁢
D
i
=
∑
x
⁢
⁢
y
∈
Υ
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λ
x
⁢
⁢
y
⁢
τ
x
⁢
⁢
y
⁢
S
⁢
⁢
W
⁢
p
i
x
⁢
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y
+
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x
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∈
Υ
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λ
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)
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1
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)
,
∀
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F
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A
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C
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C
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∑
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N
⁢
N
⁢
⁢
C
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S
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A
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I
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=
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Ψ
L
⁢
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N
⁢
N
⁢
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C
⁢
i
⁢
C
⁢
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I
⁢
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F
i
∑
i
∈
Ψ
L
⁢
⁢
N
⁢
N
⁢
⁢
C
⁢
i
A
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S
⁢
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A
⁢
⁢
I
=
1
-
S
⁢
⁢
A
⁢
⁢
I
⁢
⁢
D
⁢
⁢
I
8
⁢
7
⁢
6
⁢
0
E
⁢
⁢
E
⁢
⁢
N
⁢
⁢
S
=
∑
h
∈
B
⁢
Δ
h
8
⁢
7
⁢
6
⁢
0
⁢
∑
i
∈
Ψ
L
⁢
⁢
N
⁢
C
⁢
⁢
I
⁢
⁢
D
i
⁢
μ
h
⁢
L
i
where, CIDi represents a customer interruption duration of a node i, λxy represents an annual fault rate of a branch xy, τxySW represents an interruption period of fault isolation action of the branch xy, τxyRP represents an interruption period of fault restore of the branch xy, CIFi represents a customer interruption frequency of the node i, NCi represents a given number of customers of the node i, SAIDI represents a system average interruption duration index, SAIFI represents a system average interruption frequency index, ASAI represents a system average service availability index, EENS represents an expected energy not supplied, B represents a collection of all load levels, Δn represents a number of hours lasted per year for a load level h, μh≤1 represents a peak load ratio of the level h, and Li represents a peak load ratio of the node i.

333 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/500,539Filed 13 Oct 2021 · continuation
Priority: CN 201910439195.224 May 2019
Published: US 2022/0037883 A13 Feb 2022
Granted: 18 Jun 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification13 codes

H02J 3/001
Circuit arrangements for AC mains or AC distribution networks: arrangements for handling faults or abnormalities, e.g. emergencies or contingencies
H02J 3/0012
Arrangements for handling faults or abnormalities, e.g. emergencies or contingencies: characterised by the contingency detection means in AC…
G05B 17/02
Systems involving the use of models or simulators of said systems: electric
G06F 17/12
For solving equations , e.g. nonlinear equations, general mathematical optimization problems: simultaneous equations , e.g. systems of linear…

Family

PCT/CN2019/101429Parent of this continuation · filed 19 Aug 2019
US 2022/0037883 A1Pre-grant publication · published 3 Feb 2022
US 12,015,271 B2This patent

From the US filing history. Foreign family members aren’t listed.

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