# US 2025/0167553 A1 · Shared energy storage system optimization method and system for comprehensive energy microgrids

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- Number: US 2025/0167553 A1
- Document ID: US20250167553A1
- Status: Published application
- Kind: A1
- Application number: 18/643,001
- Filed: 2024-04-23
- Published: 2025-05-22
- Earliest claimed: 2023-11-20
- Assignees: State Grid Nanjing Power Supply Company
- Applicants: State Grid Nanjing Power Supply Company
- Inventors: Hai Qing GAN; Yu WANG; Yucheng REN; Kun CHEN; Hangtong ZHANG; Baligen TALIHATI; Jie SONG; Yuanhui CHEN; Yaojie SUN
- Web page: https://patentgrep.com/patent/US20250167553A1

## CPC

- H02J 3/28: Arrangements for balancing of the load in networks by storage of energy
- H02J 3/008: Circuit arrangements for power supply or distribution technologies responsive to energy trading
- H02J 3/32: using batteries or super capacitors with converting means
- 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

## Abstract

The application discloses a shared energy storage system optimization method and system for comprehensive energy microgrids, which take into account a shared energy storage-multi-microgrid system model invested by a third party. The comprehensive energy microgrids are regional energy systems integrating multiple energy sources and adjustable loads, including CHP, heat storage, power storage and distributed renewable energy. Shared energy storage is invested by a third part, serve as a power price publisher, and is limited by power price boundaries. The method takes into account a carbon emission and trading model to reduce carbon emission. Costs of the microgrids include a power/gas buying cost, a demand response cost, a carbon trading cost, and an operating cost of CHP units. Finally, a minimum cost solution is resolved by a MILP algorithm. The invention realizes microgrid scheduling and improves the economic efficiency and environmental friendliness of the comprehensive energy microgrids.

## Claims

### Claim 1

A shared energy storage system optimization method for comprehensive energy microgrids, comprising the following steps:
constructing a cost model of a shared energy storage-multi-microgrid system taking into account third-party investment, and setting constraints; and
resolving optimal values of variables in the cost model, and controlling devices in the shared energy storage-multi-microgrid system according to the optimal values.

### Claim 2 (depends on 1)

The shared energy storage system optimization method for comprehensive energy microgrids according to claim 1, wherein the constraints of the shared energy storage-multi-microgrid system comprise:
in order to limit power prices, including a minimum power price, a maximum power price and an average power price, set by a shared energy storage supplier, as a power price publisher, to prevent the power prices from being too high, a boundary constraint of a power buying price:
γ
e
buy
min
≤
γ
e
buy
i
,
t
≤
γ
e
buy
max
(
1
)
where, γe_buyi,t is a power buying price at which a microgrid i buys power from shared energy storage; γe_buymin is a minimum value of the power buying price; γe_buymax buy is a maximum value of the power buying price;
a boundary constraint of a power selling price:
γ
e
s
⁢
e
⁢
l
⁢
l
min
≤
γ
e
s
⁢
e
⁢
l
⁢
l
i
,
t
≤
γ
e
s
⁢
e
⁢
l
⁢
l
max
(
2
)
where, γe_selli,t is a power selling price at which the microgrid i sells power to the shared energy storage; γe_sellmin is a minimum value of the power selling price; γe_sellmax is a maximum value of the power selling price;
constraints of an average power buying/selling price:
∑
t
=
1
2
⁢
4
⁢
γ
e
buy
i
,
t
2
⁢
4
≤
γ
e
buy
ave
⁢
_
⁢
max
(
3
)
∑
t
=
1
2
⁢
4
⁢
γ
e
s
⁢
e
⁢
l
⁢
l
i
,
t
2
⁢
4
≤
γ
e
s
⁢
e
⁢
l
⁢
l
ave
⁢
_
⁢
max
(
4
)
where γe_buyave_max is an upper limit of an average price at which the microgrid i buys power from the shared energy storage; γe_sellave_max is an upper limit of an average price at which the microgrid i sells power to the shared energy storage;
energy balance constraints of the shared energy storage:
E
S
⁢
E
⁢
S
1
=
E
S
⁢
E
⁢
S
0
+
μ
s
c
⁢
harge
⁢
P
s
c
⁢
harge
t
-
P
s
d
⁢
i
⁢
s
⁢
c
⁢
harge
t
μ
s
d
⁢
i
⁢
s
⁢
c
⁢
harge
(
5
)
E
S
⁢
E
⁢
S
t
=
E
S
⁢
E
⁢
S
t
+
μ
s
c
⁢
harge
⁢
P
s
charge
t
-
P
s
d
⁢
i
⁢
s
⁢
c
⁢
harge
t
μ
s
d
⁢
i
⁢
s
⁢
c
⁢
harge
(
6
)
where, ESES1 is a power quantity of the shared energy storage at a time t=1; ESES0 is an initial energy value of the shared energy storage; μs_charge is charge efficiency of the shared energy storage; Ps_charget is a charge power of the shared energy storage; Ps_discharget is a discharge power of the shared energy storage; μs_discharge is discharge efficiency of the shared energy storage;
an upper and lower boundary constraint of energy of the shared energy storage:
E
S
⁢
E
⁢
S
min
≤
E
S
⁢
E
⁢
S
t
≤
E
S
⁢
E
⁢
S
max
(
7
)
where, ESESt is an energy value of the shared energy storage at the time t, ESESmin is a minimum energy value of the shared energy storage; ESESmax is a maximum energy value of the shared energy storage;
constraints of the charge power and the discharge power:
0
≤
P
s
c
⁢
h
⁢
a
⁢
r
⁢
g
⁢
e
t
≤
S
flag
*
P
s
c
⁢
h
⁢
a
⁢
r
⁢
g
⁢
e
max
(
8
)
0
≤
P
s
d
⁢
i
⁢
s
⁢
c
⁢
h
⁢
a
⁢
r
⁢
g
⁢
e
t
≤
(
1
-
S
flag
)
*
P
s
discharge
max
(
9
)
where, Sflag is a charge and discharge flag of the shared energy storage, which is a variable from 0 to 1 and is configured to define that only charge/discharge is allowed within a same time; ps_chargemax is a maximum charge power of the shared energy storage; ps_dischargemax is a maximum discharge power of the shared energy storage;
a power balance constraint of the shared energy storage:
P
s
charge
t
-
P
s
dischage
t
=
P
s
buy
fG
t
-
P
s
sell
toG
t
+
∑
i
=
1
U
P
buy
fS
i
,
t
-
∑
i
=
1
U
P
sell
toS
i
,
t
(
10
)
where, Ps_buy_fGt is a buying power at which the shared energy storage buys power from a power grid of; Ps_sell_toGt is a selling power at which the shared energy storage sells power to the power grid; pbuyfSi,t is an electric power bought by the microgrid i from the shared energy storage by; pselltoSi,t is an electric power sold by the microgrid i to the shared energy storage; U is a total number of microgrids trading with the shared energy storage;
constraints for the shared energy storage to buy and sell power to a main power grid:
0
≤
P
s
buy
fG
t
≤
P
s
buy
fG
max
(
11
)
0
≤
P
s
sel
⁢
l
toG
t
≤
P
s
sell
toG
max
(
12
)
where, ps_buy_fGmax is a maximum power at which the shared energy storage buys power from the power grid; ps_sell_toGmax is a maximum power at which the shared energy storage sells power to the power grid.

### Claim 3 (depends on 1)

The shared energy storage system optimization method for comprehensive energy microgrids according to claim 1, wherein the method takes into account a CHP model combining CCS and P2G, and the shared energy storage-multi-microgrid system comprises the CHP model, and in the CHP model:
a gas turbine set burns natural gas to generate power, and for a microgrid i at a time t, a power generation model of the gas turbine set is:
P
CHP
i
,
t
=
V
CHP
i
,
t
⁢
η
⁢
Q
(
13
)
where, PCHPi,t is a power generation rate of the microgrid i at the time t; VCHPi,t is natural gas consumption, and η is power generation efficiency of the gas turbine set; Q is a heat value of the natural gas;
because of the characteristic of fixing power based on heat of the gas turbine set, an electrothermal coupling constraint is:
max
⁢
{
P
CHP
min
-
k
1
⁢
H
CHP
i
,
t
,
m
⁡
(
H
CHP
i
,
t
-
H
i
,
0
)
}
≤
P
CHP
i
,
t
≤
P
CHP
max
-
k
2
⁢
H
CHP
i
,
t
(
14
)
where, PCHPmin is a minimum power generation rate of a CHP unit; PCHPmax is a maximum power generation rate of the CHP unit; HCHPi,t is a heat generation rate of the CHP unit; k1 is an electrothermal conversion coefficient in case of the minimum power generation rate of the CHP unit; k2 is an electrothermal conversion coefficient in case of the maximum power generation rate of the CHP unit; m is a linear supply slope of a thermoelectric power of CHP; Hi,0 is a heat power in case of the minimum power generation rate of the CHP unit;
in the CHP system comprising a CCS and a P2G device, power generated by CHP is used for satisfying demand of conventional power loads, satisfying power demand of the CCS, and satisfying power demand of the P2G device, which is expressed as:
P
CHP
i
,
t
=
P
load
i
,
t
+
P
CCS
i
,
t
+
P
P
⁢
2
⁢
G
i
,
t
(
15
)
where, PCHPi,t is a power generation rate of the CHP unit; Ploadi,t is a power supply rate of the CHP unit, which is used for satisfying the demand of the conventional power loads in the microgrids; PCCSi,t is a power consumption rate of the CCS; PP2Gi,t is a power consumption rate of the P2G; the CCS captures carbon dioxide generated by the CHP system and transmits the captured carbon dioxide to the P2G device; the CCS reduces the quantity of carbon dioxide generated by the CHP system, and the P2G device is able to convert the captured carbon dioxide into natural gas which is used by the CHP system;
a constraint of the power supply rate of the CHP unit is:
P
load
min
≤
P
load
i
,
t
≤
P
load
max
(
16
)
where, Ploadmin is a minimum value of the power supply rate of the CHP unit; Ploadmax is a maximum value of the power supply rate of the CHP unit;
a ramp constraint of the CHP unit is:
P
ramp
min
≤
(
P
load
i
,
t
+
P
CCS
i
,
t
+
P
P
⁢
2
⁢
G
i
,
t
)
-
(
P
load
i
,
t
-
1
+
P
CCS
i
,
t
-
1
+
P
P
⁢
2
⁢
G
i
,
t
-
1
)
≤
P
ramp
max
(
17
)
where, Prampmin is a minimum value of a power ramp of the CHP unit; Prampmax is a maximum value of the power ramp of the CHP unit; (Ploadi,t+pCCSi,t+pP2Gi,t)−(ploadi,t-1+PCCSi,t-1+pP2Gi,t-1) is the power ramp of the CHP unit;
a power range constraint of the CCS is:
P
CCS
min
≤
P
CCS
i
,
t
≤
P
CCS
max
(
18
)
where, PCCSmin is a minimum operating power of the CCS; PCCSmax is a maximum operating power of the CCS;
a power range constraint of the P2G device is:
P
P
⁢
2
⁢
G
min
≤
P
P
⁢
2
⁢
G
i
,
t
≤
P
P
⁢
2
⁢
G
max
(
19
)
where, PP2Gmin is a minimum operating power of the P2G device; PP2Gmax is a maximum operating power of the P2G device;
a power at which the P2G device to generate natural gas by means of hydrogen and carbon dioxide by consuming power is:
V
P
⁢
2
⁢
G
i
,
t
=
α
⁢
P
P
⁢
2
⁢
G
i
,
t
(
20
)
where, VP2Gi,t is a gas generation power of the P2G device; α is a power-to-gas efficiency coefficient; PP2Gi,t is a power of the P2G device;
the quantity of carbon dioxide acquired by the P2G device from CCS to generate natural gas under a certain power of the P2G device is:
W
CCS
i
,
t
=
β
⁢
P
P
⁢
2
⁢
G
i
,
t
(
21
)
where, Wccsi,t is the quantity of carbon dioxide required by the P2G device under the power PP2Gi,t; β is a coefficient of relationship between WCCSi,t and PP2Gi,t;
a range constraint of the quantity of captured carbon dioxide is:
0
≤
W
CCS
i
,
t
≤
W
CCS
max
(
22
)
where, WCCSmax is a maximum quantity of carbon dioxide captured by the CCS, which is equal to carbon emission in a park;
carbon dioxide captured by the CCS is supplied to the P2G device, and a relationship between the power of the CCS and carbon dioxide required by the P2G device is:
P
CCS
i
,
t
=
γ
⁢
W
CCS
i
,
t
(
23
)
where, γ is a coefficient of relationship between PCCSi,t and WC02i,t;
a constraint of the natural gas consumption of the CHP unit is:
P
load
i
,
t
+
P
CCS
i
,
t
+
P
P
⁢
2
⁢
G
i
,
t
=
λ
CHP
⁢
V
CHP
i
,
t
(
24
)
where, λCHP is a coefficient of relationship between the power generation and the natural gas consumption of the CHP unit;
a constraint of gas consumption of a gas boiler is:
H
GB
i
,
t
=
λ
GB
⁢
V
GB
i
,
t
(
25
)
where, ΔGB is a coefficient of relationship between the heat generation rate and a natural gas consumption rate of the gas boiler;
a constraint of a total natural gas consumption rate of microgrids is:
V
i
,
t
=
V
CHP
i
,
t
+
V
GB
i
,
t
-
V
P
⁢
2
⁢
G
i
,
t
(
26
)
where, Vi,t is a gas consumption power of the microgrid i at the time t;
an upper and lower boundary constraint of heat production of the boiler is:
0
≤
H
GB
i
,
t
≤
H
GB
max
(
27
)
where, HGBi,t is a heat generation rate of the boiler; HGBmax is a maximum value of the heat generation rate of the boiler.

### Claim 4 (depends on 1)

The shared energy storage system optimization method for comprehensive energy microgrids according to claim 1, wherein the method takes into account a carbon emission and trading model, and the shared energy storage-multi-microgrid system comprises the carbon emission and trading model, and in the carbon emission and trading model:
a CHP unit generates carbon dioxide during operation, a gas boiler discharges carbon dioxide when producing heat, and a CSS is able to reduce direct emission of carbon dioxide; therefore, carbon dioxide emission of microgrids is obtained by subtracting carbon dioxide captured by the CCS from the sum of carbon dioxide generated by the CHP unit and carbon dioxide generated by the gas boiler;
W
i
,
t
=
δ
⁡
(
P
load
i
,
t
+
P
CCS
i
,
t
+
P
P
⁢
2
⁢
G
i
,
t
+
k
1
⁢
H
CHP
i
,
t
)
+
ε
⁢
H
GB
i
,
t
-
W
CCS
i
,
t
(
28
)
Wi,t is carbon emission of a microgrid i at a time t; δ is a coefficient of relationship between a power generation rate of the CHP unit and carbon dioxide; k1 is an electrothermal conversion coefficient in case of a minimum power generation rate of the CHP unit; ε is a carbon dioxide emission coefficient of the gas boiler; HGBi,t is a heat generation rate of the boiler;
carbon emission of the comprehensive energy microgrids in one day is:
W
i
=
∑
t
∈
1
24
W
i
,
t
(
29
)
Wi is carbon emission of the comprehensive energy microgrid i in one day;
carbon trading is an economic means for reducing carbon emission based on trading of carbon emission permits by defining carbon credits; a carbon quota, also referred to the carbon emission permit, is the quantity of carbon dioxide permitted to be discharged; the carbon quota of the microgrids is:
W
i
,
allo
=
η
⁢
∑
t
=
1
2
⁢
4
P
load
i
,
t
+
P
CCS
i
,
t
+
P
P
⁢
2
⁢
G
i
,
t
+
H
GB
i
,
t
(
30
)
where, Wi,allo is the carbon quota previously allocated to the microgrid i; η is a carbon quota allocation parameter;
a relationship between the carbon emission, the carbon quota and the carbon trading is:
W
i
-
W
i
,
allo
=
W
i
,
0
+
∑
j
=
1
j
=
N
W
buy
i
,
j
(
31
)
W
i
,
0
≤
0
(
32
)
where, Wi is the carbon emission of the microgrid i; Wi,allo is the carbon quota of the microgrid i, Wi,0 is a carbon quota for sale of the microgrid; Wbuyi,j, is a carbon quota bought by the microgrid i within an interval j;
heat of the microgrids is from a CHP system and the gas boiler, and a heat power balance constraint of the microgrids is:
H
CHP
i
,
t
+
H
GB
i
,
t
=
H
⁢
l
⁢
o
⁢
a
⁢
d
adjust
i
,
t
(
33
)
where, HCHPi,t is a heat generation rate of the CHP unit; HGBi,t is a heat generation rate of the boiler; Hloadadjusti,t is a heat load power after a demand response;
constraints of the quantity of power bought from and sold to shared energy storage (SES) by the microgrids are:
0
≤
P
sell
toS
i
,
≤
P
sell
toS
max
*
flag
(
34
)
0
≤
P
buy
fS
i
,
t
≤
P
buy
fS
max
*
(
1
-
flag
)
(
35
)
where, psell_toSi,t is a selling power between the microgrid i and the SES at the time t; ps_buy_fSi,t is a buying power between the microgrid i and the SES at the time t; Psell_toSmax is a maximum selling power between the microgrids and the SES; Pbuy_fSmax is a maximum buying power between the microgrids and the SES; flag is a power buying/selling flag, which is 0 or 1; when flag is 0, only power buying is allowed; when flag is 1, only power selling is allowed; in this way, only power selling or power buying is allowed at a same time.

### Claim 5 (depends on 1)

The shared energy storage system optimization method for comprehensive energy microgrids according to claim 1, wherein the cost model of microgrids in the shared energy storage-multi-microgrid system comprises a power/gas buying cost of the microgrids, a demand response cost of the microgrids, a carbon trading cost and an operating cost of CHP units in the microgrids:
the power/gas buying cost of the microgrids is:
C
buy
i
=
∑
t
=
1
t
=
24
P
buy
fS
i
,
t
*
γ
e
buy
i
,
t
-
P
s
⁢
e
⁢
l
⁢
l
t
⁢
o
⁢
G
i
,
t
*
γ
e
s
⁢
e
⁢
l
⁢
l
i
,
t
+
∑
t
=
1
t
=
24
V
i
,
t
*
γ
G
⁢
a
⁢
s
(
36
)
where, Cbuyi is the power/gas buying cost of a microgrid i; γe_buyi,t is a price at which the microgrid i buys power from shared energy storage at a time t; γe_selli,t is a price at which the microgrid i sells power to the shared energy storage at the time t; γGas is a price of natural gas;
the demand response cost of the microgrids is:
C
Dr
i
=
C
1
⁢
∑
t
=
1
T
E
⁢
l
⁢
o
⁢
a
⁢
d
cut
i
,
t
+
C
2
⁢
∑
t
=
1
T
❘
"\[LeftBracketingBar]"
Eload
transfer
i
,
t
❘
"\[RightBracketingBar]"
+
C
3
⁢
∑
t
=
1
T
H
⁢
l
⁢
o
⁢
a
⁢
d
cut
i
,
t
(
37
)
where, CDri is the demand response cost of the microgrid i; C1 is a cost coefficient of power load reduction of the microgrid i at the time t; C3 is a cost coefficient of heat load reduction of the microgrid i at the time t;
the carbon trading cost is:
C
c
⁢
a
⁢
r
⁢
b
⁢
o
⁢
n
i
=
W
i
,
0
*
γ
s
⁢
e
⁢
l
⁢
l
c
⁢
a
⁢
r
⁢
b
⁢
o
⁢
n
+
∑
j
=
1
N
γ
buy
carbon
j
⁢
W
buy
i
,
j
(
38
)
where, Ccarboni is the carbon trading cost of the microgrid i; γsell_carbon is a carbon quota selling price; γbuy_carboni is a carbon quota buying price at a time j; N is a maximum interval number of carbon trading intervals;
the operating cost of the CHP units in the microgrids is:
C
CHP
i
=
∑
t
=
1
T
a
1
(
P
load
i
,
t
+
P
CCS
i
,
t
+
P
P
⁢
2
⁢
G
i
,
t
)
+
∑
t
=
1
T
a
2
⁢
P
CCS
i
,
t
+
∑
t
=
1
T
a
3
⁢
P
P
⁢
2
⁢
G
i
,
t
(
39
)
where, CCHPi is the operating cost of the CHP unit in the microgrid i; α1 is a power generation cost coefficient of the microgrid i at the time t; α2 is an operating cost coefficient of a CCS; α3 is an operating cost coefficient of a P2G device;
the cost model of the microgrids is:
C
i
=
C
buy
i
+
C
Dr
i
+
C
carbon
i
+
C
CHP
i
(
40
)
where, Ci is a cost of the microgrid i;
an objective function of the cost model is:
min
⁢
∑
i
C
i
(
41
)
an optimal value of the objective function under the constraints is resolved by a MILP algorithm.

### Claim 6 (depends on 1)

A shared energy storage system optimization system for comprehensive energy microgrids, comprising:
a model construction unit configured to store the cost model and constraints of the shared energy storage-multi-microgrid system in the shared energy storage system optimization method for comprehensive energy microgrids according to claim 1;
a calculation unit configured to resolve an optimal value of the cost model by a MILP algorithm; and
a control unit configured to control devices in the shared energy storage-multi-microgrid system according to the optimal value obtained by the calculation unit.