# US 2021/0344196 A1 · Method for adjusting power flow based on operation constraints

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- Number: US 2021/0344196 A1
- Document ID: US20210344196A1
- Status: Published application
- Kind: A1
- Application number: 17/240,561
- Filed: 2021-04-26
- Published: 2021-11-04
- Earliest claimed: 2020-04-29
- Assignees: Tsinghua University
- Applicants: Tsinghua University
- Inventors: Bin WANG; Hongbin SUN; Wenchuan WU; Qinglai GUO; Zongda MU
- Web page: https://patentgrep.com/patent/US20210344196A1

## CPC

- H02J 3/06: Controlling the transfer of power between connected networks; Controlling load sharing between connected networks
- H02J 3/12: Arrangements for adjusting voltage in AC networks by changing a characteristic of the network load
- G05B 13/042: {in which a parameter or coefficient is automatically adjusted to optimise the performance}
- H02J 2103/30: Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks
- H02J 2103/35: Grid-level management of power transmission or distribution systems, e.g. load flow analysis or active network management
- H02J: ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G)

## Abstract

Provided are method and device for adjusting a power flow based on operation constraints. The method includes: establishing a power flow adjusting model comprising an objective function and constraints; acquiring active power and reactive power of each node by using a two-stage optimization of active and reactive powers. In this method, the power flow adjusting model is divided into the active power optimization sub-model and the reactive power optimization sub-model. The active power optimization sub-model, where the linearized power flow constraint and the tie line section active power constraint are considered, may be regarded as quadratic programming. The reactive power flow optimization sub-model is solved on the basis of the active sub-model, and the AC power flow constraint, the grid voltage range constraint, and the pilot bus voltage setting value constraint are considered.

## Claims

### Claim 1

A method for adjusting a power flow based on operation constraints, comprising:
(1) establishing a power flow adjusting model comprising an objective function and constraints, comprising:
(1-1) determining the objective function of the model having a formula of
min
V
,
θ
,
Δ
⁢
⁢
P
i
G
,
Δ
⁢
⁢
Q
i
G
⁢
∑
i
=
1
N
⁢
λ
i
PG
⁡
(
Δ
⁢
⁢
P
i
G
)
2
+
λ
i
QG
⁡
(
Δ
⁢
⁢
Q
i
G
)
2
where N represents the number of nodes, i represents a node number, V represents a voltage amplitude, θ represents a voltage phase angle, ΔPiG represents an optimal adjustment amount of an active power injected into node i, ΔQiG represents an optimal adjustment amount of a reactive power injected into node i, λiPG represents an adjustment weight of the active power injected into node i, and λiQG represents an adjustment weight of the reactive power injected into node i;
(1-2) determining the constraints of the model, the constraints comprising:
(1-2-1) a power flow constraint having formulas of
P
i
+
Δ
⁢
⁢
P
i
G
=
V
i
2
⁢
G
ii
+
∑
j
∈
i
j
≠
i
⁢
V
i
⁢
V
j
⁡
(
G
ij
⁢
cos
⁢
⁢
θ
ij
+
B
ij
⁢
sin
⁢
⁢
θ
ij
)
Q
i
+
Δ
⁢
⁢
Q
i
G
=
-
V
i
2
⁢
B
ii
+
∑
j
∈
i
j
≠
i
⁢
V
i
⁢
V
j
⁡
(
G
ij
⁢
sin
⁢
⁢
θ
ij
-
B
ij
⁢
cos
⁢
⁢
θ
ij
)
where j∈i represents that node j belongs to a set of all nodes connected to node i, Gij and Bij represent a real part and an imaginary part of an upper triangular element of a node admittance matrix, respectively, Gii and Bii represent a real part and an imaginary part of a diagonal element of the node admittance matrix, respectively, Vi represents a voltage amplitude of node i, θij represents a phase angle difference of branch ij, Pi represents an active power injected into node i at a base state, and Qi represents a reactive power injected into node i at a base state;
(1-2-2) a grid voltage range constraint having a formula of
Vi≤Vi≤Vi
where Vi and Vi represent a lower limit and an upper limit of a voltage amplitude of node i, respectively;
(1-2-3) a voltage setting value constraint of a pilot bus, having a formula of
Vjp={circumflex over (V)}jp
where Vjp and {circumflex over (V)}jp represent an optimized voltage value and a set voltage value of an jth pilot bus, respectively; and
(1-2-4) a sectional transmission power constraint having formulas of
PkTd={circumflex over (P)}kTd
PmTc≤PmTc≤PmTc
where PkTd and {circumflex over (P)}kTd represent an optimized power value and a set power value of a kth target tie line, respectively, PmTc, PmTc and PmTc represent a power lower limit, an optimized power value and a power upper limit of an mth constrained tie line, respectively;
(2) acquiring active power and reactive power of each node by using a two-stage optimization of active and reactive powers, comprising:
(2-1) establishing an active power optimization sub-model comprising an objective function and constraints, comprising:
(2-1-1) determining the objective function of the active power optimization sub-model having a formula of
min
θ
,
Δ
⁢
⁢
P
i
G
⁢
∑
i
=
1
N
⁢
λ
i
PG
⁡
(
Δ
⁢
⁢
P
i
G
)
2
(2-1-2) determining the constraints of the active power optimization sub-model, the constraints comprising:
(2-1-2-1) a linearized power flow constraint having a formula of
P
i
+
Δ
⁢
⁢
P
i
G
=
V
i
2
⁢
G
ii
+
∑
j
∈
i
j
≠
i
⁢
V
i
⁢
V
j
⁡
(
G
ij
+
B
ij
⁢
θ
ij
)
(2-1-2-2) a tie line section power flow constraint having formulas of
PmTc≤PmTc≤PmTc
PkTd={circumflex over (P)}kTd
(2-2) solving the active power optimization sub-model to acquire optimal solutions of ΔPiG and θ;
(2-3) establishing a reactive power optimization sub-model comprising an objective function and constraints, comprising:
(2-3-1) determining the objective function of the reactive power optimization sub-model having a formula of
min
V
,
θ
,
Δ
⁢
⁢
Q
i
G
,
Δ
⁢
⁢
f
⁢
∑
i
=
1
N
⁢
λ
i
QG
⁡
(
Δ
⁢
⁢
Q
i
G
)
2
where Δf represents a frequency variation, wherein an optimal solution of θ obtained by solving the active power optimization sub-model is used as an initial value;
(2-3-2) determining the constraints of the reactive power optimization sub-model, the constraints comprising:
(2-3-2-1) an AC power flow constraint having formulas of
P
i
+
Δ
⁢
⁢
P
i
G
+
Δ
⁢
⁢
f
·
P
i
agc
=
V
i
2
⁢
G
ii
+
∑
j
∈
i
j
≠
i
⁢
V
i
⁢
V
j
⁡
(
G
ij
⁢
cos
⁢
⁢
θ
ij
+
B
ij
⁢
sin
⁢
⁢
θ
ij
)
⁢
⁢
Q
i
+
Δ
⁢
⁢
Q
i
G
=
-
V
i
2
⁢
B
ii
+
∑
j
∈
i
j
≠
i
⁢
V
i
⁢
V
j
⁡
(
G
ij
⁢
sin
⁢
⁢
θ
ij
-
B
ij
⁢
cos
⁢
⁢
θ
ij
)
where Piagc represents an unbalanced power analysis coefficient of node i participating in frequency response;
(2-3-2-2) a grid voltage range constraint having a formula of
Vi≤Vi≤Vi
(2-3-2-3) a voltage setting value constraint of a pilot bus, having a formula of
Vjp={circumflex over (V)}jp
(2-4) solving the reactive power optimization sub-model to acquire an optimal solution of ΔQiG; and
(2-5) acquiring the active power {circumflex over (P)}i and the reactive power {circumflex over (Q)}i of each node according to the optimal solutions of ΔPiG and ΔQiG:
{
P
^
i
=
P
i
+
Δ
⁢
⁢
P
i
G
+
Δ
⁢
⁢
f
·
P
i
agc
Q
^
i
=
Q
i
+
Δ
⁢
⁢
Q
i
G
.

### Claim 2 (depends on 1)

The method according to claim 1, wherein the adjustment weight of the active power is in a range of 0 to 1.

### Claim 3 (depends on 1)

The method according to claim 1, wherein the adjustment weight of the reactive power is in a range of 0 to 1.

### Claim 4 (depends on 1)

The method according to claim 1, wherein the active power optimization sub-model is solved by a linear programming algorithm.

### Claim 5 (depends on 1)

The method according to claim 1, wherein the unbalanced power analysis coefficient is a total capacity of a generator unit connected to node i.

### Claim 6 (depends on 1)

A device for adjusting a power flow based on operation constraints, comprising:
a processor; and
a memory having stored therein a computer program that, when executed by the processor, causes the processor to perform the method according to claim 1.

### Claim 7 (depends on 1)

A computer-readable storage medium having stored therein instructions that, when executed by a processor, are configured to perform the method according to claim 1.