# US 12,119,651 B2 · Resilience enhancement-oriented energy storage control method and system for distributed generator (DG) in distribution network

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- Number: US 12,119,651 B2
- Document ID: US12119651B2
- Status: Granted
- Kind: B2
- Application number: 17/923,947
- Filed: 2022-05-18
- Published: 2024-08-15
- Granted: 2024-10-15
- Earliest claimed: 2021-06-11
- Assignees: State Grid Shanghai Municipal Electric Power Company; East China Electric Power Test Research Institute Co., Ltd.; Shanghai Jiao Tong University
- Applicants: State Grid Shanghai Municipal Electric Power Company; East China Electric Power Test Research Institute Co., Ltd.; Shanghai Jiao Tong University
- Inventors: Saiyi Wang; Xin Huang; Weiguo He; Chaoran Fu; Haodong Shen; Tangyun Xu; Jie Chen; Xu Wang; Shichao Zhou; Zhan Xiong; Chuanwen Jiang
- Web page: https://patentgrep.com/patent/US12119651B2

## CPC

- H02J 3/28: Arrangements for balancing of the load in networks by storage of energy
- G06Q 50/06: Energy or water supply
- H02J 3/0075: {for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch}
- H02J 3/32: using batteries or super capacitors with converting means
- H02J 3/381: {Dispersed generators}
- H02J 2103/30: Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks
- Y02B 70/3225: Demand response systems, e.g. load shedding, peak shaving
- Y04S 20/222: Demand response systems, e.g. load shedding, peak shaving
- H02J: ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- Y02B: CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y04S: SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS

## Abstract

A resilience enhancement-oriented energy storage control method and system for a distributed generator (DG) in a distribution network. The method includes: determining an objective function including a first sub-objective function and a second sub-objective function; determining an outer-level constraint based on a quantity of configured energy storage systems (ESSs), a quantity of hardened lines, and a rated power and capacity configuration of an ESS; determining a middle-level constraint based on a line failure; determining an inner-level constraint based on node power of a distribution network, a line load capacity, a line power flow, a power output of a unit, a node voltage, climbing of the unit, operation of the ESS, and LS; determining parameters based on the outer-level constraint, the first sub-objective function, the middle-level constraint, the inner-level constraint, and the second sub-objective function; and controlling energy storage of a DG in the distribution network.

## Claims

### Claim 1

A resilience enhancement-oriented energy storage control method for a distributed generator (DG) in a distribution network, comprising:
determining an objective function, wherein the objective function comprises a first sub-objective function and a second sub-objective function, the first sub-objective function aims to minimize an investment cost at an outer level, and the second sub-objective function first aims to maximize a load shedding (LS) cost and a post-disaster operation cost at a middle level, and then minimize an LS cost and a post-disaster operation cost at an inner level;
determining an outer-level constraint based on a quantity of configured energy storage systems (ESSs), a quantity of hardened lines, and a rated power and capacity configuration of an ESS;
determining a middle-level constraint based on a line failure;
determining an inner-level constraint based on node power of a distribution network, a line load capacity, a line power flow, a power output of a unit, a node voltage, climbing of the unit, operation of the ESS, and LS;
determining, based on the outer-level constraint and the first sub-objective function, a unit hardening investment cost cijl of a line, a line length sij, a binary decision variable yij for line hardening, a first cost coefficient ce, a second cost coefficient cp, and a capacity EiR and rated power PiR of an ESS configured on node i; and determining a power output cgG of a DG, a unit cost coefficient cich of charging of the ESS, a unit cost coefficient cidis of discharging of the ESS, a unit LS cost ciLS after a load weight is considered, an LS ratio ρi,t of node i, and load pi,tD of node i based on the middle-level constraint, the inner-level constraint, and the second sub-objective function; and
controlling energy storage of the DG in the distribution network based on the obtained parameters.

### Claim 2 (depends on 1)

The method according to claim 1, wherein the outer-level constraint comprises: a sub-constraint on the quantity of configured ESSs, a sub-constraint on the quantity of hardened lines, and a sub-constraint on the rated power and capacity configuration of the ESS;
the sub-constraint on the quantity of configured ESSs comprises:
∑
i
∈
Ω
B
σ
j
≤
N
E
⁢
S
I
⁢
N
⁢
V
the sub-constraint on the quantity of hardened lines comprises:
∑
(
i
,
j
)
∈
Ω
L
y
ij
≤
N
L
I
⁢
N
⁢
V
;
and
the sub-constraint on the rated power and capacity configuration of the ESS comprises
0≤PiR≤σiPiR,max,∀i∈ΩB
0≤EiR≤σiEiR,max,∀i∈ΩB
wherein σi represents a binary decision variable for ESS configuration, wherein when a value of the variable is 1, node i is configured with the ESS, otherwise, the node is not configured with the ESS; NESINV represents a maximum allowable quantity of configured ESSs; NLINV represents a maximum quantity of hardened lines; PiR,max and EiR,max respectively represent upper limits of configurable rated power and a configurable capacity of the ESS; when σi=0, node i is not configured with the ESS, which is equivalent to setting both the rated power and the capacity of the ESS to 0; EiR and PiR respectively represent the capacity and the rated power of the ESS configured on node i; ΩB represents a node set of an alternating current (AC)/direct current (DC) distribution network; ΩL represents a line set of the AC/DC distribution network; and yij represents the binary decision variable for line hardening.

### Claim 3 (depends on 1)

The method according to claim 1, wherein the middle-level constraint comprises:
∑
(
i
,
j
)
∈
Ω
L
(
-
log
2
⁢
p
ij
d
⁢
a
⁢
m
)
⁢
z
tj
,
0
≤
W
ma
⁢
x
wherein pijdam represents a line failure rate; zij,0 represents a binary variable, indicating whether a failure occurs on the line, and a value of the binary variable is 1 when a failure occurs and 0 when no failure occurs; Wmax represents an upper limit of an uncertain entropy value of the line failure in the distribution network; and ΩL represents a line set of an AC/DC distribution network.

### Claim 4 (depends on 1)

The method according to claim 1, wherein the inner-level constraint comprises: a sub-constraint on the node power of the distribution network, a sub-constraint on the line load capacity, a sub-constraint on the line power flow, a power output sub-constraint of the unit, a node voltage sub-constraint, a climbing sub-constraint of the unit, a state sub-constraint of the ESS, and an LS sub-constraint;
the state sub-constraint of the ESS comprises:
S
i
(
t
)
=
S
i
(
t
-
1
)
+
p
i
ch
(
t
)
⁢
η
ch
⁢
Δ
⁢
t
-
p
i
dis
(
t
)
⁢
Δ
⁢
t
η
dis
,
∀
i
∈
Ω
B
,
∀
t
∈
T
SOC
i
,
m
⁢
i
⁢
n
≤
S
i
(
t
)
E
i
R
≤
SOC
i
,
ma
⁢
x
,
∀
i
∈
Ω
B
,
∀
t
∈
T
0
≤
p
i
ch
(
t
)
≤
P
i
R
,
∀
i
∈
Ω
B
,
∀
t
∈
T
0
≤
p
i
dis
(
t
)
≤
P
i
R
,
∀
i
∈
Ω
B
,
∀
t
∈
T
p
i
ch
(
t
)
·
p
i
dis
(
t
)
=
0
,
∀
i
∈
Ω
B
,
∀
t
∈
T
;
and
the LS sub-constraint comprises:
0≤ρi,t≤1,∀i∈ΩB,∀I∈T
wherein Si(t) represents a remaining electricity quantity at time t; ηch,ηdis represent charging efficiency and discharging efficiency respectively; Δt represents a time interval; pich(t) represents charging power; pidis(t) represents discharging power; and PiR represents an upper charging/discharging limit.

### Claim 5 (depends on 1)

The method according to claim 1, wherein the first sub-objective function comprises:
min
y
∈
Y
C
INV
C
INV
=
C
L
INV
+
C
ES
INV
C
L
INV
=
β
i
⁢
∑
(
i
,
j
)
∈
Ω
L
c
ij
l
⁢
s
ij
⁢
y
ij
C
ES
INV
=
β
es
(
∑
i
∈
Ω
B
c
e
⁢
E
i
R
+
c
p
⁢
P
i
R
)
;
and
the second sub-objective function comprises:
ρ
pre
⁢
τ
max
u
∈
U
min
x
∈
F
⁡
(
y
,
u
)
(
C
OPE
+
C
LS
)
C
OPE
=
∑
t
∈
T
[
∑
g
∈
Ω
G
c
g
G
⁢
p
g
,
t
G
+
∑
i
∈
Ω
B
(
c
i
dis
⁢
p
i
,
t
dis
+
c
i
ch
⁢
p
i
,
t
ch
)
]
C
LS
=
∑
i
∈
Ω
B
,
t
∈
T
c
i
LS
⁢
ρ
i
,
t
⁢
p
i
,
t
D
wherein Y,U,F represent variable sets of tri-level decision-making respectively; CINV represents an investment cost; COPE and CLS represent the post-disaster operation cost and the LS cost respectively; ρpre represents introduction of a resilience preference coefficient; CLINV represents an investment cost for line hardening; CESINV represents an investment cost for energy storage resource configuration; cijl represents the unit hardening investment cost of the line; sij represents the line length; yij represents the binary decision variable for line hardening; βl represents a coefficient for converting a total investment cost of the line into a one-year cost based on a planned period; ΩL represents a line set of an AC/DC distribution network; ce and cp represent cost coefficients; βes represents a coefficient for converting a total investment cost of the ESS into a one-year cost based on a planned period; ΩB represents a node set of the AC/DC distribution network; EiR and PiR respectively represent the capacity and the rated power of the ESS configured on node i; ciLS represents the unit LS cost after the load weight is considered; ρi,t represents the LS ratio of node i at time t; pi,tD represents the load of the node at the corresponding time; T represents duration of an extreme event; and cgG, cich, and cidis represent the power output of the DG, the unit cost coefficient for charging of the ESS, and the unit cost coefficient for discharging of the ESS respectively.

### Claim 6

A resilience enhancement-oriented energy storage control system for a DG in a distribution network, comprising:
an objective function determining unit configured to determine an objective function, wherein the objective function comprises a first sub-objective function and a second sub-objective function, the first sub-objective function aims to minimize an investment cost at an outer level, and the second sub-objective function first aims to maximize an LS cost and a post-disaster operation cost at a middle level, and then minimize an LS cost and a post-disaster operation cost at an inner level;
an outer-level constraint determining unit configured to determine an outer-level constraint based on a quantity of configured ESSs, a quantity of hardened lines, and a rated power and capacity configuration of an ESS;
a middle-level constraint determining unit configured to determine a middle-level constraint based on a line failure;
an inner-level constraint determining unit configured to determine an inner-level constraint based on node power of a distribution network, a line load capacity, a line power flow, a power output of a unit, a node voltage, climbing of the unit, operation of the ESS, and LS;
a parameter determining unit configured to determine, based on the outer-level constraint and the first sub-objective function, a unit hardening investment cost cich of a line, a line length sij, a binary decision variable yij for line hardening, a first cost coefficient ce, a second cost coefficient cp, and a capacity EiR and rated power PiR of an ESS configured on node i; and determine a power output cgG of a DG, a unit cost coefficient cich of charging of the ESS, a unit cost coefficient cidis of discharging of the ESS, a unit LS cost ciLS after a load weight is considered, an LS ratio ρi,t of node i, and load pi,tD of node i based on the middle-level constraint, the inner-level constraint, and the second sub-objective function; and
an energy storage control unit configured to control energy storage of the DG in the distribution network based on the obtained parameters.

### Claim 7 (depends on 6)

The system according to claim 6, wherein the outer-level constraint comprises: a sub-constraint on the quantity of configured ESSs, a sub-constraint on the quantity of hardened lines, and a sub-constraint on the rated power and capacity configuration of the ESS;
the sub-constraint on the quantity of configured ESSs comprises:
∑
t
∈
Ω
B
σ
j
≤
N
E
⁢
S
I
⁢
N
⁢
V
the sub-constraint on the quantity of hardened lines comprises:
∑
(
i
,
j
)
∈
Ω
L
y
ij
≤
N
L
I
⁢
N
⁢
V
;
and
the sub-constraint on the rated power and capacity configuration of the ESS comprises
0≤PiR≤σiPiR,max,∀i∈ΩB
0≤EiR≤σiEiR,max,∀i∈ΩB
wherein σi represents a binary decision variable for ESS configuration, where when a value of the variable is 1, node i is configured with the ESS, otherwise, the node is not configured with the ESS; NESINV represents a maximum allowable quantity of configured ESSs; NLINV represents a maximum quantity of hardened lines; PiR,max and EiR,max respectively represent upper limits of configurable rated power and a configurable capacity of the ESS; when σi=0, node i is not configured with the ESS, which is equivalent to setting both the rated power and the capacity of the ESS to 0; EiR and PiR respectively represent the capacity and the rated power of the ESS configured on node i; ΩB represents the node set of the AC/DC distribution network; ΩL represents the line set of the AC/DC distribution network; and yij represents the binary decision variable for line hardening.

### Claim 8 (depends on 6)

The system according to claim 6, wherein the middle-level constraint comprises:
∑
(
i
,
j
)
∈
Ω
L
(
-
log
2
⁢
p
ij
d
⁢
a
⁢
m
)
⁢
z
ij
,
0
≤
W
ma
⁢
x
wherein pijdam represents a line failure rate; zij,0 represents a binary variable, indicating whether a failure occurs on the line, and a value of the binary variable is 1 when a failure occurs and 0 when no failure occurs; Wmax represents an upper limit of an uncertain entropy value of the line failure in the distribution network; and ΩL represents a line set of an AC/DC distribution network.

### Claim 9 (depends on 6)

The system according to claim 6, wherein the inner-level constraint comprises: a sub-constraint on the node power of the distribution network, a sub-constraint on the line load capacity, a sub-constraint on the line power flow, a power output sub-constraint of the unit, a node voltage sub-constraint, a climbing sub-constraint of the unit, a state sub-constraint of the ESS, and an LS sub-constraint;
the state sub-constraint of the ESS comprises:
S
i
(
t
)
=
S
i
(
t
-
1
)
+
p
i
ch
(
t
)
⁢
η
ch
⁢
Δ
⁢
t
-
p
i
dis
(
t
)
⁢
Δ
⁢
t
η
dis
,
∀
i
∈
Ω
B
,
∀
t
∈
T
SOC
i
,
m
⁢
i
⁢
n
≤
S
i
(
t
)
E
i
R
≤
SOC
i
,
ma
⁢
x
,
∀
i
∈
Ω
B
,
∀
t
∈
T
0
≤
p
i
ch
(
t
)
≤
P
i
R
,
∀
i
∈
Ω
B
,
∀
t
∈
T
0
≤
p
i
dis
(
t
)
≤
P
i
R
,
∀
i
∈
Ω
B
,
∀
t
∈
T
p
i
ch
(
t
)
·
p
i
dis
(
t
)
=
0
,
∀
i
∈
Ω
B
,
∀
t
∈
T
;
and
the LS sub-constraint comprises:
0≤ρi,t≤1,∀i∈ΩB,∀t∈T
wherein Si(t) represents a remaining electricity quantity at time t; ηch,ηdis represent charging efficiency and discharging efficiency respectively; Δt represents a time interval; pich(t) represents charging power; pidis(t) represents discharging power; and PiR represents an upper charging/discharging limit.

### Claim 10 (depends on 6)

The system according to claim 6, wherein the first sub-objective function comprises:
min
y
∈
Y
C
INV
C
INV
=
C
L
INV
+
C
ES
INV
C
L
INV
=
β
l
⁢
∑
(
i
,
j
)
∈
Ω
L
c
ij
l
⁢
s
ij
⁢
y
ij
C
ES
INV
=
β
es
(
∑
i
∈
Ω
B
c
e
⁢
E
i
R
+
c
p
⁢
P
i
R
)
;
and
the second sub-objective function comprises:
ρ
pre
⁢
τ
max
u
∈
U
min
x
∈
F
⁡
(
y
,
u
)
(
C
OPE
+
C
LS
)
C
OPE
=
∑
t
∈
T
[
∑
g
∈
Ω
G
c
g
G
⁢
p
g
,
t
G
+
∑
i
∈
Ω
B
(
c
i
dis
⁢
p
i
,
t
dis
+
c
i
ch
⁢
p
i
,
t
ch
)
]
C
LS
=
∑
i
∈
Ω
B
,
t
∈
T
c
i
LS
⁢
ρ
i
,
t
⁢
p
i
,
t
D
wherein Y,U,F represent variable sets of tri-level decision-making respectively; CINV represents an investment cost; COPE and CLS represent the post-disaster operation cost and the LS cost respectively; ρpre represents introduction of a resilience preference coefficient; CLINV represents an investment cost for line hardening; CESINV represents an investment cost for energy storage resource configuration; cijl represents the unit hardening investment cost of the line; sij represents the line length; yij represents the binary decision variable for line hardening; βl represents a coefficient for converting a total investment cost of the line into a one-year cost based on a planned period; ΩL represents a line set of an AC/DC distribution network; ce and cp represent cost coefficients; βes represents a coefficient for converting a total investment cost of the ESS into a one-year cost based on a planned period; ΩB represents a node set of the AC/DC distribution network; EiR and PiR respectively represent the capacity and the rated power of the ESS configured on node i; ciLS represents the unit LS cost after the load weight is considered; ρi,t represents the LS ratio of node i at time t; ρi,tD represents the load of the node at the corresponding time; T represents duration of an extreme event; and cgG, cich, and cidis represent the power output of the DG, the unit cost coefficient for charging of the ESS, and the unit cost coefficient for discharging of the ESS respectively.