US 2024/0191702 A1 · CAPACITY CONFIGURATION METHOD FOR PHOTOVOLTAIC/PHOTOTHERMAL/AA-CAES OF COMBINED COOLING, HEATING AND POWER

Abstract

A capacity configuration method for photovoltaic/photothermal/Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) of combined cooling, heating and power (CCHP). The method includes: establishing a CCHP micro integrated energy system model containing AA-CAES, and then solving the model by using a dual-level planning approach. The upper level plans capacity configuration is planned with an objective of minimizing a sum of capacity configuration costs and lower-level scheduling costs, while the lower level employs parameters obtained from the upper level to implement season-based scheduling, with an objective of minimizing a sum of energy supply costs and carbon mitigation costs, and returns a scheduling result to the upper level to assist in upper-level capacity decisions. This method takes a CCHP capability of a compressed air energy storage system into consideration, and establishes a model suitable for capacity planning and scheduling.

A capacity configuration method for photovoltaic/photothermal/Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) of combined cooling, heating and power (CCHP), comprising the following steps:

step 1:
establishing a CCHP micro integrated energy system model containing AA-CAES, which comprises inputs from renewable energy sources of wind power, photovoltaic power, and solar thermal collection, a combined heat and power (CHP) unit with a gas generator and a waste heat recovery boiler, refrigeration equipment for absorption cooling and electric cooling, and an energy storage device of AA-CAES, wherein it is assumed that in the system model, air behaves as an ideal gas, following an ideal gas state equation, an air storage chamber has a temperature approximately equal to ambient temperature, a thermal storage chamber has a temperature approximately equal to a rated temperature, and water serves as a heat transfer medium;
step 2:
establishing an upper-level objective function max Bbf, with an objective of maximizing a net benefit brought by AA-CAES:
max Bbf=CnoCAES−CCAES−CTCC−CO&M
wherein CnoCAES is energy costs without AA-CAES configuration;
CCAES is energy costs with AA-CAES configuration, derived from lower-level scheduling;
CTCC is annualized investment costs;
and CO&M is annualized operation and maintenance costs of a system;
upper-level decision variables x comprise:
x={APV,ASF,PCAESc,PCAESt,Vv,Vh,ωv,ωh}
wherein APV is the number of photovoltaic panels;
ASF is a ground area of a mirror field;
PCAESc is a rated power of a compressor;
PCAESt is an expansion power of an expander;
Vv is a volume of the air storage chamber;
Vh is a volume of the thermal storage chamber;
ωv is an initial gas proportion in the air storage chamber;
and ωh is an initial hot water proportion in the thermal storage chamber;
upper-level constraints are ground areas for photovoltaic panels and solar thermal collection:
APVSPV+ASF≤SMAX
wherein SPV is a ground area for a single photovoltaic panel;
and SMAX is a maximum total ground area;
step 3:
establishing a lower-level objective function, with a scheduling objective of minimizing energy supply costs and carbon mitigation costs after configuring AA-CAES:
C
CAES
=
D
spa
(
P
spa
⁢
C
e
+
P
spaGT
⁢
τ
⁢
C
gas
+
P
spab
⁢
ψ
e
⁢
C
co
2
+
P
spaGT
⁢
τ
⁢
ψ
g
⁢
C
co
2
)
+
D
su
(
P
sub
⁢
C
e
+
P
suGT
⁢
τ
⁢
C
gas
+
P
sub
⁢
ψ
e
⁢
C
co
2
+
P
suGT
⁢
τ
⁢
ψ
g
⁢
C
co
2
)
+
D
w
(
P
wb
⁢
C
e
+
P
wGT
⁢
τ
⁢
C
gas
+
P
wb
⁢
ψ
e
⁢
C
co
2
+
P
wGT
⁢
τ
⁢
ψ
g
⁢
C
co
2
)
wherein Dspa, Dsu, Dw represent the number of days in transitional seasons, summer, and winter, respectively, during one year;
Pspab, Psub, Pwb represent amounts of purchased electricity on typical days in transitional seasons, summer, and winter, respectively;
Ce is an electricity price, using time-of-use pricing;
PspaGT, PsuGT, PwGT represent outputs of a gas turbine on typical days in transitional seasons, summer, and winter, respectively;
τ is a correlation coefficient between the output of the gas turbine and natural gas;
Cgas is purchase costs of natural gas per unit;
ψe is a conversion coefficient of CO2 per unit of grid electricity;
ψe is a conversion coefficient of CO2 per unit of natural gas combustion;
and Cco2 is mitigation costs per unit of CO2;
lower-level decision variables x comprise:
x={PCAESc,t,PCAESg,t,PGT,t,Pb,t,Pcold,t,Prb,t,Mtesc,t,Mtesx,t,Mtescold,t}
wherein PCAESc,t is an output of the compressor at time t;
PCAESg,t is an output of the expander at time t;
PGT,t is an output of the gas turbine at time t;
Pb,t is an amount of electricity purchased from a power grid at time t;
Prb,t is an amount of electricity consumed by a heat pump at time t;
Pcold,t is an amount of electricity used for cooling at time t;
Mtesc,t is a mass of hot water stored into the thermal storage chamber at time t;
Mtesx,t is a mass of hot water supplied from the thermal storage chamber at time t;
and Mtescold,t is a mass of hot water used for absorption cooling at time t;
lower-level constraints comprise an electric power balance constraint, a thermal power balance constraint, a cold power balance constraint, AA-CAES module constraints, CHP constraints, thermal storage chamber constraints, heat pump and electric cooling constraints, and electricity purchase constraints;
and
step 4:
performing crossover and mutation on decision variables by using a genetic algorithm (NSGA-II) at the upper level, with an objective of minimizing total costs, selecting new parent capacity values based on the total costs by applying an elite retention strategy, and passing down results to the lower level, wherein at the lower level, a Gurobi solver is employed to schedule a lower-level model after the results from the upper level are received, and scheduling results are then returned to the upper level to assist in capacity decisions, achieving dual-level planning.

168 more elements

Capacity configuration method for photovoltaic/photothermal/aa-caes of combined cooling, heating and power

Life of this patent

Capacity configuration method for photovoltaic/photothermal/aa-caes of combined cooling, heating and power

Life of this patent

Abstract

Claims4