CN110991735A - Optimal scheduling method of combined heat and power system considering AA-CAES (advanced computer aided engineering) - Google Patents

Optimal scheduling method of combined heat and power system considering AA-CAES (advanced computer aided engineering) Download PDF

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CN110991735A
CN110991735A CN201911199077.5A CN201911199077A CN110991735A CN 110991735 A CN110991735 A CN 110991735A CN 201911199077 A CN201911199077 A CN 201911199077A CN 110991735 A CN110991735 A CN 110991735A
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蔡杰
张世旭
杜治
熊宇龙
杨东俊
李姚旺
方仍存
赵红生
郑旭
廖爽
苗世洪
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Huazhong University of Science and Technology
State Grid Corp of China SGCC
Economic and Technological Research Institute of State Grid Hubei Electric Power Co Ltd
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State Grid Corp of China SGCC
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Abstract

A heat and power combined supply system optimal scheduling method considering AA-CAES comprises the steps of firstly establishing a heat and power combined supply system day-ahead scheduling model taking the minimum sum of the operating energy consumption of a gas turbine, the operating energy consumption of a diesel engine, the equivalent energy consumption of waste photovoltaic and the equivalent scheduling energy consumption of transferable loads as an objective function, then inputting the acquired short-term prediction data of photovoltaic, thermal loads and electrical loads into the day-ahead scheduling model to obtain a day-ahead scheduling result of the heat and power combined supply system, and then scheduling the heat and power combined supply system according to the day-ahead scheduling result. The design not only improves the operation flexibility, stability and reliability of the combined heat and power system, but also improves the consumption capability of renewable energy sources of the system and reduces the operation energy consumption of the system.

Description

Optimal scheduling method of combined heat and power system considering AA-CAES (advanced computer aided engineering)
Technical Field
The invention belongs to the field of optimal scheduling of a combined heat and power system, and particularly relates to an optimal scheduling method of a combined heat and power system considering AA-CAES.
Background
Compared with the traditional micro-grid, the combined heat and power system can realize mutual conversion and complementary mutual assistance between heat energy and electric energy through combined storage and combined supply of the heat energy and the electric energy, enhance the reliability of system energy supply, and improve the comprehensive energy utilization rate and the energy supply quality.
In recent years, Advanced Adiabatic Compressed Air energy storage (AA-CAES) technology has gradually emerged. The AA-CAES has rapid adjustment and high system efficiency, and can provide various auxiliary services such as peak regulation, standby, reactive power adjustment and the like for the system besides good combined heat and power storage/supply capacity. The above advantages make the energy storage device one of the most potential physical energy storage technologies, and have received extensive attention from both academic and industrial fields. At present, no mature technology exists for a scheduling method of a combined heat and power system comprising an AA-CAES device, and the reliable and stable operation of the combined heat and power system comprising the energy storage device cannot be guaranteed.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides an AA-CAES-considered optimal scheduling method for a combined heat and power system, which can ensure the reliable and stable operation of the combined heat and power system.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a optimal scheduling method of a combined heat and power system considering AA-CAES sequentially comprises the following steps:
step A, establishing a day-ahead scheduling model of the combined heat and power system considering AA-CAES, wherein the model takes the minimum sum of the operating energy consumption of a gas turbine, the operating energy consumption of a diesel engine, the equivalent energy consumption of waste photovoltaic and the equivalent scheduling energy consumption of transferable loads as an objective function;
and step B, inputting the acquired short-term prediction data of the photovoltaic power, the thermal load and the electrical load into the day-ahead scheduling model to obtain a day-ahead scheduling result of the combined heat and power system, and then scheduling the combined heat and power system according to the day-ahead scheduling result.
In step a, the objective function of the day-ahead scheduling model is:
Figure BDA0002295406000000021
in the above formula, T is the number of time in the scheduling time period before day, NGT、NG、NPV、NDRRespectively the number of gas turbines, diesel engines, photovoltaic power stations, transferable load nodes, bGT,iIs the coefficient of energy consumption, H, of the gas turbine iGT,t,iPower produced by gas turbine i at time t, PG,t,sIs the output value of the diesel engine s at time t, bsA parameter of the power generation and coal consumption of the diesel engine s, csThe coal consumption parameter u for starting and stopping the diesel engine s and switchingt,sOn-off state of diesel engine s at time t, CDRTo be rotatableThe scheduling of load shifting is equivalent to an energy consumption parameter,
Figure BDA0002295406000000022
respectively the increasing load power and the decreasing load power of the jth transferable load node at the time t, cppvPenalizing the equivalent energy consumption coefficient for the abandoned photovoltaic, Ppva,t,kAnd the actual light abandoning power of the photovoltaic power station k at the moment t is obtained.
The constraint conditions of the objective function comprise the constraint that the AA-CAES device participates in the day-ahead scheduling and performs combined heat and power supply, the constraint that the gas turbine participates in the day-ahead scheduling operation, the constraint that the electric boiler participates in the day-ahead scheduling operation, the constraint that the diesel engine participates in the day-ahead scheduling operation, the power flow constraint of an AC/DC power distribution network, the constraint that the photovoltaic power station participates in the day-ahead scheduling operation, the constraint that the transferable load participates in the day-ahead scheduling operation, the heat energy balance constraint and the system standby constraint, wherein,
the restriction that the AA-CAES device participates in day-ahead scheduling and performs combined heat and power supply comprises the following steps:
AA-CAES general operating constraints:
uCAESc,t+uCAESg,t≤1
Figure BDA0002295406000000023
Figure BDA0002295406000000024
in the above formula, uCASEg,tIs a power generation state variable u of the AA-CAES device at the time tCASEc,tFor compression state variable, P, of AA-CAES devices at time tCASEg,t、PCASEc,tRespectively the power generation and compression power P of the AA-CAES device at the time tCAEScmax、PCAEScminUpper and lower limit values of compression power, P, of AA-CAES deviceCAESgmaxAnd PCAESgminRespectively an upper limit value and a lower limit value of the generated power, p, of the AA-CAES devicest,tAir pressure of air reservoir, p, of AA-CAES apparatus at time tstmax、pstminThe upper and lower limit values of the air pressure of the air storage chamber, △ pst,0△ p being the initial rate of change of air pressure in the reservoirst,τThe air pressure change rate of the air storage chamber at the time tau, △ t being the duration of a scheduling period;
AA-CAES expansion/compression heat exchange constraints:
Hg,m,t＝mg,tcp,a(Tg,,m,in,t-Tg,m-1,out,t)
Figure BDA0002295406000000031
in the above formula, Hg,m,tAnd Hg,tThe m-th stage expansion process at time t and the overall heat release power of the AA-CAES plant, cp,aIs the specific heat capacity of air, Tg,m,in,tAnd Tg,m-1,out,tRespectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, ngExpansion series of AA-CAES;
AA-CAES heating power constraint:
Figure BDA0002295406000000032
in the above formula, Hst,t、Hstout,tRespectively the heat energy loss power and the actual external heat output power of the heat reservoir at the time t, HstmaxFor the external heating power limit, k, of the heat reservoirstThe loss coefficient of heat supply for the heat reservoir to the outside;
AA-CAES residual heat constraint:
Figure BDA0002295406000000033
in the above formula, HHS,0And HHS,tRespectively is the initial heat value and the residual heat at the time t, H of the AA-CAES heat storage chamberc,τ、Hg,τ、Hst,τThe compression heat release power, the power generation heat consumption power and the external heat supply power of the AA-CAES device at the time of tau, HHSmax、HHsminThe upper limit value and the lower limit value of the heat storage quantity of the AA-CAES device are respectively set;
AA-CAES provides rotational standby constraints:
Figure BDA0002295406000000034
in the above formula, RCAES,tFor the rotational reserve, R, that the AA-CAES can provide for the system at time tCAESc,t、RCAESg,tCan provide a rotary standby for the system when the AA-CAES operates under the working conditions of compression and power generation at the time t respectively, khg、khcRespectively is the power coefficient k of the heat exchange power of the AA-CAES device in the power generation and compression processesg、kcThe power coefficients of the air pressure change rate of the air storage chamber of the AA-CAES device in the power generation and compression processes are respectively.
The constraints of the gas turbine participating in the day-ahead scheduling operation comprise thermoelectric output proportion constraint, thermoelectric output upper and lower limit constraint, fuel consumption upper and lower limit constraint and climbing constraint;
the constraint of the electric boiler participating in the day-ahead scheduling operation is as follows:
Figure BDA0002295406000000041
in the above formula, Heb,tIs the thermal output power, P, of the electric boiler at time tpv,t,kAnd Ppvh,t,kTotal generated power of photovoltaic plant k and electric power for heat production by electric boiler at time t, η respectivelypvhThe electric heat conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit and an output lower limit, a minimum on-off time constraint and a climbing rate constraint;
the load flow constraint of the alternating current and direct current power distribution network comprises a VSC converter station scheduling operation constraint, a branch load flow balance constraint based on DistFlow and a system safety constraint;
the constraint that the photovoltaic power station participates in day-ahead scheduling operation is as follows:
Figure BDA0002295406000000042
in the above formula, Ppva,t,kIs the actual light abandoning power, P, of the photovoltaic power station k at the moment tpve,t,kThe power for the photovoltaic power station k to meet the electrical load demand at time t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
Figure BDA0002295406000000043
Figure BDA0002295406000000044
Figure BDA0002295406000000045
in the above formula, the first and second carbon atoms are,
Figure BDA0002295406000000046
and
Figure BDA0002295406000000047
respectively a lower limit and an upper limit of the load transfer amount on the transferable load node j,
Figure BDA0002295406000000048
a state variable is scheduled for the forward load of the transferable load node j at time t,
Figure BDA0002295406000000049
a state variable is scheduled for the negative load of the transferable load node j at time t,
Figure BDA00022954060000000410
and
Figure BDA00022954060000000411
respectively a lower limit and an upper limit of the load transfer amount of the transferable load on the transferable load node j,
Figure BDA00022954060000000412
to be able to transfer loadThe upper limit of the single-day transfer amount of the load of the node j;
the thermal energy balance constraint is:
Figure BDA0002295406000000051
in the above formula, Hload,tIs the thermal load of the system at time t;
the system standby constraints are:
Figure BDA0002295406000000052
in the above formula, PGTmax,i、PGTmax,sUpper limit of output, P, for gas turbine i and diesel engine s, respectivelyT,t、PTmaxRespectively, the upper level grid support power and the upper limit value, R at the moment tL、RPVRespectively reserve the standby power for load and photovoltaic.
And in the step B, the day-ahead scheduling result comprises the start-stop state and the operating condition of the AA-CAES device, the gas turbine and the diesel engine, and the scheduling plan of the AA-CAES device, the gas turbine, the diesel engine, the electric boiler and the transferable load.
The combined heat and power system comprises an alternating current power distribution network, a direct current power distribution network, a converter station, a regional heating system and a thermoelectric coupling device, wherein the alternating current power distribution network comprises a diesel engine and an alternating current load, the direct current power distribution network comprises a direct current load and a photovoltaic power station, the regional heating system comprises a thermal load, and the thermoelectric coupling device comprises an AA-CAES device, a gas turbine and an electric boiler.
Compared with the prior art, the invention has the beneficial effects that:
the invention relates to a heat and power combined system optimal scheduling method considering AA-CAES, which comprises the steps of firstly establishing a heat and power combined system day-ahead scheduling model taking the minimum sum of the operating energy consumption of a gas turbine, the operating energy consumption of a diesel engine, the equivalent energy consumption of waste photovoltaic and the equivalent scheduling energy consumption of transferable loads as an objective function, then inputting the acquired short-term prediction data of photovoltaic, thermal loads and electrical loads into the day-ahead scheduling model to obtain a day-ahead scheduling result of the heat and power combined system, and then scheduling the heat and power combined system according to the day-ahead scheduling result, wherein the design faces to the operating scene of the heat and power combined system, the established heat and power combined system day-ahead scheduling model considers the coordinated interaction of an AA-CAES device, the transferable loads, the photovoltaic, the diesel engine and the gas turbine, the operating flexibility, the heat and power stability and the reliability of the heat and power combined system can be effectively improved, and the consumption capacity of renewable energy of the heat and, the operation energy consumption of the system is reduced. Therefore, the invention not only improves the operation flexibility, stability and reliability of the combined heat and power system, but also improves the consumption capability of renewable energy sources of the system and reduces the operation energy consumption of the system.
Drawings
FIG. 1 is a schematic diagram of the structure and power flow relationship of the cogeneration system of the invention.
Fig. 2 is a schematic view of a topology of the cogeneration system in embodiment 1 of the invention.
Fig. 3 is a short-term prediction data graph of the photovoltaic power generation amount, the thermal load and the electrical load of the system in embodiment 1 of the invention.
Fig. 4 is a system power output curve diagram of scenario 1 in embodiment 1 of the present invention.
Fig. 5 is a system energy output curve diagram of scenario 1 in embodiment 1 of the present invention.
Fig. 6 is a schematic diagram of a heat output situation of the system in scenario 1 in embodiment 1 of the present invention.
Fig. 7 is a schematic diagram of a heat output situation of the system in scenario 3 in embodiment 1 of the present invention.
Fig. 8 is a schematic diagram of the ratio of heat output of the systems of scene 1 and scene 3 in example 1 of the present invention.
Fig. 9 is a schematic diagram of backup power supply situations of the backup sources in scenario 1 in embodiment 1 of the present invention.
Fig. 10 is a schematic diagram of backup power supply of backup sources of scenario 4 in embodiment 1 of the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments.
Referring to fig. 1, a co-generation system optimal scheduling method considering AA-CAES includes the following steps in sequence:
step A, establishing a day-ahead scheduling model of the combined heat and power system considering AA-CAES, wherein the model takes the minimum sum of the operating energy consumption of a gas turbine, the operating energy consumption of a diesel engine, the equivalent energy consumption of waste photovoltaic and the equivalent scheduling energy consumption of transferable loads as an objective function;
and step B, inputting the acquired short-term prediction data of the photovoltaic power, the thermal load and the electrical load into the day-ahead scheduling model to obtain a day-ahead scheduling result of the combined heat and power system, and then scheduling the combined heat and power system according to the day-ahead scheduling result.
In step a, the objective function of the day-ahead scheduling model is:
Figure BDA0002295406000000061
in the above formula, T is the number of time in the scheduling time period before day, NGT、NG、NPV、NDRRespectively the number of gas turbines, diesel engines, photovoltaic power stations, transferable load nodes, bGT,iIs the coefficient of energy consumption, H, of the gas turbine iGT,t,iPower produced by gas turbine i at time t, PG,t,sIs the output value of the diesel engine s at time t, bsA parameter of the power generation and coal consumption of the diesel engine s, csThe coal consumption parameter u for starting and stopping the diesel engine s and switchingt,sOn-off state of diesel engine s at time t, CDRFor scheduling equivalent energy consumption parameters for transferable loads,
Figure BDA0002295406000000062
respectively the increasing load power and the decreasing load power of the jth transferable load node at the time t, cppvPenalizing the equivalent energy consumption coefficient for the abandoned photovoltaic, Ppva,t,kAnd the actual light abandoning power of the photovoltaic power station k at the moment t is obtained.
The constraint conditions of the objective function comprise the constraint that the AA-CAES device participates in the day-ahead scheduling and performs combined heat and power supply, the constraint that the gas turbine participates in the day-ahead scheduling operation, the constraint that the electric boiler participates in the day-ahead scheduling operation, the constraint that the diesel engine participates in the day-ahead scheduling operation, the power flow constraint of an AC/DC power distribution network, the constraint that the photovoltaic power station participates in the day-ahead scheduling operation, the constraint that the transferable load participates in the day-ahead scheduling operation, the heat energy balance constraint and the system standby constraint, wherein,
the restriction that the AA-CAES device participates in day-ahead scheduling and performs combined heat and power supply comprises the following steps:
AA-CAES general operating constraints:
uCAESc,t+uCAESg,t≤1
Figure BDA0002295406000000071
Figure BDA0002295406000000072
in the above formula, uCASEg,tIs a power generation state variable u of the AA-CAES device at the time tCASEc,tFor compression state variable, P, of AA-CAES devices at time tCASEg,t、PCASEc,tRespectively the power generation and compression power P of the AA-CAES device at the time tCAEScmax、PCAEScminUpper and lower limit values of compression power, P, of AA-CAES deviceCAESgmaxAnd PCAESgminRespectively an upper limit value and a lower limit value of the generated power, p, of the AA-CAES devicest,tAir pressure of air reservoir, p, of AA-CAES apparatus at time tstmax、pstminThe upper and lower limit values of the air pressure of the air storage chamber, △ pst,0△ p being the initial rate of change of air pressure in the reservoirst,τThe air pressure change rate of the air storage chamber at the time tau, △ t being the duration of a scheduling period;
AA-CAES expansion/compression heat exchange constraints:
Hg,m,t＝mg,tcp,a(Tg,,m,in,t-Tg,m-1,out,t)
Figure BDA0002295406000000073
in the above formula, Hg,m,tAnd Hg,tThe m-th stage expansion process at time t and the overall heat release power of the AA-CAES plant, cp,aIs the specific heat capacity of air, Tg,m,in,tAnd Tg,m-1,out,tRespectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, ngExpansion series of AA-CAES;
AA-CAES heating power constraint:
Figure BDA0002295406000000074
in the above formula, Hst,t、Hstout,tRespectively the heat energy loss power and the actual external heat output power of the heat reservoir at the time t, HstmaxFor the external heating power limit, k, of the heat reservoirstThe loss coefficient of heat supply for the heat reservoir to the outside;
AA-CAES residual heat constraint:
Figure BDA0002295406000000081
in the above formula, HHS,0And HHS,tRespectively is the initial heat value and the residual heat at the time t, H of the AA-CAES heat storage chamberc,τ、Hg,τ、Hst,τThe compression heat release power, the power generation heat consumption power and the external heat supply power of the AA-CAES device at the time of tau, HHSmax、HHsminThe upper limit value and the lower limit value of the heat storage quantity of the AA-CAES device are respectively set;
AA-CAES provides rotational standby constraints:
Figure BDA0002295406000000082
in the above formula, RCAES,tFor the rotational reserve, R, that the AA-CAES can provide for the system at time tCAESc,t、RCAESg,tCan provide a rotary standby for the system when the AA-CAES operates under the working conditions of compression and power generation at the time t respectively, khg、khcRespectively is the power coefficient of the heat exchange power of the AA-CAES device in the power generation and compression processes，kg、kcThe power coefficients of the air pressure change rate of the air storage chamber of the AA-CAES device in the power generation and compression processes are respectively.
The constraints of the gas turbine participating in the day-ahead scheduling operation comprise thermoelectric output proportion constraint, thermoelectric output upper and lower limit constraint, fuel consumption upper and lower limit constraint and climbing constraint;
the constraint of the electric boiler participating in the day-ahead scheduling operation is as follows:
Figure BDA0002295406000000083
in the above formula, Heb,tIs the thermal output power, P, of the electric boiler at time tpv,t,kAnd Ppvh,t,kTotal generated power of photovoltaic plant k and electric power for heat production by electric boiler at time t, η respectivelypvhThe electric heat conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit and an output lower limit, a minimum on-off time constraint and a climbing rate constraint;
the load flow constraint of the alternating current and direct current power distribution network comprises a VSC converter station scheduling operation constraint, a branch load flow balance constraint based on DistFlow and a system safety constraint;
the constraint that the photovoltaic power station participates in day-ahead scheduling operation is as follows:
Figure BDA0002295406000000091
in the above formula, Ppva,t,kIs the actual light abandoning power, P, of the photovoltaic power station k at the moment tpve,t,kThe power for the photovoltaic power station k to meet the electrical load demand at time t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
Figure BDA0002295406000000092
Figure BDA0002295406000000093
Figure BDA0002295406000000094
in the above formula, the first and second carbon atoms are,
Figure BDA0002295406000000095
and
Figure BDA0002295406000000096
respectively a lower limit and an upper limit of the load transfer amount on the transferable load node j,
Figure BDA0002295406000000097
a state variable is scheduled for the forward load of the transferable load node j at time t,
Figure BDA0002295406000000098
a state variable is scheduled for the negative load of the transferable load node j at time t,
Figure BDA0002295406000000099
and
Figure BDA00022954060000000910
respectively a lower limit and an upper limit of the load transfer amount of the transferable load on the transferable load node j,
Figure BDA00022954060000000911
the upper limit of the single-day transfer amount of the load of the transferable load node j;
the thermal energy balance constraint is:
Figure BDA00022954060000000912
in the above formula, Hload,tIs the thermal load of the system at time t;
the system standby constraints are:
Figure BDA00022954060000000913
in the above formula, PGTmax,i、PGTmax,sUpper limit of output, P, for gas turbine i and diesel engine s, respectivelyT,t、PTmaxRespectively, the upper level grid support power and the upper limit value, R at the moment tL、RPVRespectively reserve the standby power for load and photovoltaic.
And in the step B, the day-ahead scheduling result comprises the start-stop state and the operating condition of the AA-CAES device, the gas turbine and the diesel engine, and the scheduling plan of the AA-CAES device, the gas turbine, the diesel engine, the electric boiler and the transferable load.
The combined heat and power system comprises an alternating current power distribution network, a direct current power distribution network, a converter station, a regional heating system and a thermoelectric coupling device, wherein the alternating current power distribution network comprises a diesel engine and an alternating current load, the direct current power distribution network comprises a direct current load and a photovoltaic power station, the regional heating system comprises a thermal load, and the thermoelectric coupling device comprises an AA-CAES device, a gas turbine and an electric boiler.
The principle of the invention is illustrated as follows:
the invention provides an AA-CAES-considered optimal scheduling method for a combined heat and power system, which aims at an established scheduling architecture of the combined heat and power system containing AA-CAES, and constructs a day-ahead scheduling model of the combined heat and power system considering AA-CAES according to the operating characteristics of an AA-CAES device in key links such as heat storage, heat exchange and heat supply and the operating characteristics of other scheduling resources in the combined heat and power system, wherein the scheduling architecture of the combined heat and power system comprises an alternating current distribution network, a direct current distribution network, a converter station, a regional heat supply system and a thermoelectric coupling device, the alternating current distribution network comprises a diesel engine and alternating current loads (one part of the alternating current loads is set as a transferable load), the direct current distribution network comprises a direct current load and a photovoltaic power station, and the converter station realizes power transmission and port voltage control between the alternating current distribution network and the direct current distribution network, the district heating system comprises a heat load, and the thermoelectric coupling device comprises an AA-CAES device, a gas turbine and an electric boiler, so that the conversion between thermoelectric energy flows is realized.
Day-ahead scheduling model: the scheduling objective is the minimization of the operation energy consumption of the cogeneration system, and in order to improve the photovoltaic absorption rate, the light rejection equivalent energy consumption is considered in the objective function of the model.
AA-CAES general operating constraints: mainly refers to the single operation condition constraint, the power upper and lower limit value constraint and the air pressure limit value constraint of the AA-CAES.
The AA-CAES heat reservoir residual heat is restricted; the premise of external heat supply of the AA-CAES is that the residual heat of the heat reservoir is sufficient to support the requirement of expansion power generation in a subsequent period of time, meanwhile, the heat reservoir cannot continuously store heat after the heat storage value of the heat reservoir reaches the upper limit of the capacity, and the heat recovered in the compression process can only be dissipated and wasted. The constraint condition can ensure that the residual heat of the AA-CAES heat reservoir meets the follow-up power generation requirement and the utilization rate of the compression recovery heat energy, thereby improving the energy efficiency of the system.
AA-CAES provides rotational standby constraints: the residual air pressure and heat of the AA-CAES must be maintained above a certain level to ensure that sufficient back-up power is available to the system in emergency situations such as power shortages. Thus, the AA-CAES provides rotational redundancy, accounting for charge and discharge power constraints, residual air pressure, and residual heat constraints.
The constraint that the photovoltaic power station participates in day-ahead scheduling operation: for photovoltaic power supply balance constraint, the function is represented as: the electric energy of the photovoltaic power station is mainly used for power supply and heat production of an electric boiler, and surplus photovoltaic electric energy is abandoned. Therefore, the sum of the photovoltaic power supply quantity, the heat generation power consumption quantity of the electric boiler and the light abandoning quantity is equal to the photovoltaic power generation quantity.
And (3) heat energy balance constraint: the constraint condition is used for ensuring the balance of heat generation quantity and heat load quantity of heat sources such as a gas turbine, an electric boiler, an AA-CAES device and the like in the system and avoiding load shortage or heat generation waste.
And (3) system standby constraint, namely reserving certain rotary standby power for the system according to the load and the predicted value of the photovoltaic in order to ensure that the system can safely operate when the power fluctuates or an accident occurs.
Example 1:
referring to fig. 2, an optimal scheduling method for a combined heat and power system considering AA-CAES takes the combined heat and power system shown in fig. 2 as an object (wherein an IEEE-14 node system is adopted for an alternating current/direct current hybrid power distribution network part of the system, an alternating current power distribution network part mainly comprises nodes 1-9, a gas turbine, a diesel engine and AA-CAES devices, and users of alternating current loads of a node 5 and a node 7 can participate in excitation type demand response and can be used for transferring loads, a direct current power distribution network part mainly comprises nodes 10-14 and a photovoltaic power station, the gas turbine directly supplies heat to a thermal energy bus, the AA-CAES devices supply heat to the thermal energy bus through an AA-CAES heat reservoir, part of generated energy of the photovoltaic power station supplies heat to an electric boiler, and further supplies heat to the thermal energy bus), and sequentially comprises the following steps:
step 1, establishing a day-ahead scheduling model of the combined heat and power system considering AA-CAES, wherein the model takes the minimum sum of the operating energy consumption of a gas turbine, the operating energy consumption of a diesel engine, the equivalent energy consumption of waste photovoltaic and the equivalent scheduling energy consumption of transferable loads as an objective function:
Figure BDA0002295406000000111
in the above formula, T is the number of time in the scheduling time period before day, NGT、NG、NPV、NDRRespectively the number of gas turbines, diesel engines, photovoltaic power stations, transferable load nodes, bGT,iIs the coefficient of energy consumption, H, of the gas turbine iGT,t,iPower produced by gas turbine i at time t, PG,t,sIs the output value of the diesel engine s at time t, bsA parameter of the power generation and coal consumption of the diesel engine s, csThe coal consumption parameter u for starting and stopping the diesel engine s and switchingt,sOn-off state of diesel engine s at time t, CDRFor scheduling equivalent energy consumption parameters for transferable loads,
Figure BDA0002295406000000112
respectively the increasing load power and the decreasing load power of the jth transferable load node at the time t, cppvPenalizing the equivalent energy consumption coefficient for the abandoned photovoltaic, Ppva,t,kActual light abandoning power of the photovoltaic power station k at the time t;
the constraint conditions of the objective function comprise the constraint that the AA-CAES device participates in the day-ahead scheduling and performs combined heat and power supply, the constraint that the gas turbine participates in the day-ahead scheduling operation, the constraint that the electric boiler participates in the day-ahead scheduling operation, the constraint that the diesel engine participates in the day-ahead scheduling operation, the power flow constraint of an AC/DC power distribution network, the constraint that the photovoltaic power station participates in the day-ahead scheduling operation, the constraint that the transferable load participates in the day-ahead scheduling operation, the heat energy balance constraint and the system standby constraint, wherein,
the restriction that the AA-CAES device participates in day-ahead scheduling and performs combined heat and power supply comprises the following steps:
AA-CAES general operating constraints:
uCAESc,t+uCAESg,t≤1
Figure BDA0002295406000000121
Figure BDA0002295406000000122
in the above formula, uCASEg,tIs a power generation state variable u of the AA-CAES device at the time tCASEc,tFor compression state variable, P, of AA-CAES devices at time tCASEg,t、PCASEc,tRespectively the power generation and compression power P of the AA-CAES device at the time tCAEScmax、PCAEScminUpper and lower limit values of compression power, P, of AA-CAES deviceCAESgmaxAnd PCAESgminRespectively an upper limit value and a lower limit value of the generated power, p, of the AA-CAES devicest,tAir pressure of air reservoir, p, of AA-CAES apparatus at time tstmax、pstminThe upper and lower limit values of the air pressure of the air storage chamber, △ pst,0△ p being the initial rate of change of air pressure in the reservoirst,τThe air pressure change rate of the air storage chamber at the time tau, △ t being the duration of a scheduling period;
AA-CAES expansion/compression heat exchange constraints:
Hg,m,t＝mg,tcp,a(Tg,,m,in,t-Tg,m-1,out,t)
Figure BDA0002295406000000123
in the above formula, Hg,m,tAnd Hg,tThe m-th stage expansion process at time t and the overall heat release power of the AA-CAES plant, cp,aIs the specific heat capacity of air, Tg,m,in,tAnd Tg,m-1,out,tRespectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, ngExpansion series of AA-CAES;
AA-CAES heating power constraint:
Figure BDA0002295406000000124
in the above formula, Hst,t、Hstout,tRespectively the heat energy loss power and the actual external heat output power of the heat reservoir at the time t, HstmaxFor the external heating power limit, k, of the heat reservoirstThe loss coefficient of heat supply for the heat reservoir to the outside;
AA-CAES residual heat constraint:
Figure BDA0002295406000000131
in the above formula, HHS,0And HHS,tRespectively is the initial heat value and the residual heat at the time t, H of the AA-CAES heat storage chamberc,τ、Hg,τ、Hst,τThe compression heat release power, the power generation heat consumption power and the external heat supply power of the AA-CAES device at the time of tau, HHSmax、HHsminThe upper limit value and the lower limit value of the heat storage quantity of the AA-CAES device are respectively set;
AA-CAES provides rotational standby constraints:
Figure BDA0002295406000000132
in the above formula, RCAES,tFor the rotational reserve, R, that the AA-CAES can provide for the system at time tCAESc,t、RCAESg,tCan provide the rotation standby for the system when the AA-CAES operates under the working conditions of compression and power generation at the time t，khg、khcRespectively is the power coefficient k of the heat exchange power of the AA-CAES device in the power generation and compression processesg、kcThe power coefficients are respectively the air pressure change rate of the air storage chamber of the AA-CAES device in the power generation and compression processes;
the constraints of the gas turbine participating in the day-ahead scheduling operation comprise thermoelectric output proportion constraint, thermoelectric output upper and lower limit constraint, fuel consumption upper and lower limit constraint and climbing constraint;
the constraint of the electric boiler participating in the day-ahead scheduling operation is as follows:
Figure BDA0002295406000000133
in the above formula, Heb,tIs the thermal output power, P, of the electric boiler at time tpv,t,kAnd Ppvh,t,kTotal generated power of photovoltaic plant k and electric power for heat production by electric boiler at time t, η respectivelypvhThe electric heat conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit and an output lower limit, a minimum on-off time constraint and a climbing rate constraint;
the load flow constraint of the alternating current and direct current power distribution network comprises a VSC converter station scheduling operation constraint, a branch load flow balance constraint based on DistFlow and a system safety constraint;
the constraint that the photovoltaic power station participates in day-ahead scheduling operation is as follows:
Figure BDA00022954060000001413
in the above formula, Ppva,t,kIs the actual light abandoning power, P, of the photovoltaic power station k at the moment tpve,t,kThe power for the photovoltaic power station k to meet the electrical load demand at time t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
Figure BDA0002295406000000141
Figure BDA0002295406000000142
Figure BDA0002295406000000143
in the above formula, the first and second carbon atoms are,
Figure BDA0002295406000000144
and
Figure BDA0002295406000000145
respectively a lower limit and an upper limit of the load transfer amount on the transferable load node j,
Figure BDA0002295406000000146
a state variable is scheduled for the forward load of the transferable load node j at time t,
Figure BDA0002295406000000147
a state variable is scheduled for the negative load of the transferable load node j at time t,
Figure BDA0002295406000000148
and
Figure BDA0002295406000000149
respectively a lower limit and an upper limit of the load transfer amount of the transferable load on the transferable load node j,
Figure BDA00022954060000001410
the upper limit of the single-day transfer amount of the load of the transferable load node j;
the thermal energy balance constraint is:
Figure BDA00022954060000001411
in the above formula, Hload,tIs the thermal load of the system at time t;
the system standby constraints are:
Figure BDA00022954060000001412
in the above formula, PGTmax,i、PGTmax,sUpper limit of output, P, for gas turbine i and diesel engine s, respectivelyT,t、PTmaxRespectively, the upper level grid support power and the upper limit value, R at the moment tL、RPVRespectively reserving standby power for load and photovoltaic;
step 2, inputting the acquired short-term prediction data (see fig. 3) of the photovoltaic load, the thermal load and the electrical load into the day-ahead scheduling model to obtain a day-ahead scheduling result of the cogeneration system, and then scheduling the cogeneration system according to the day-ahead scheduling result, wherein the day-ahead scheduling is executed every 24 hours, the unit scheduling time is 15 minutes, the scheduling time window is 24 hours, the day-ahead scheduling result comprises the start-stop state and the operating condition of an AA-CAES device, a gas turbine and a diesel engine, and the scheduling plan of the AA-CAES device, the gas turbine, the diesel engine, the electric boiler and the transferable load, and the scheduling parameters of the AA-CAES device, the gas turbine and the diesel engine are shown in tables 1-3:
TABLE 1 scheduling parameters for AA-CAES devices
Item of parameter Numerical value
Maximum generated Power/MW 16
Minimum generated Power/MW 6.4
Maximum compression power/MW 8
Minimum compression power/MW 3.2
Minimum boot time/min 45
Minimum off time/min 45
Maximum number of power-on/off times per day 5
Power coefficient of power generation air pressure change rate/(Pa.kW)-1) 2.17
Power coefficient of compression pressure change rate/(Pa. kW)-1) 2.68
Air pressure variation range/MPa of air storage chamber 4.5～5.5
Loss coefficient of heat energy of heat storage for external heat supply 0.7
Minimum power factor 0.8
TABLE 2 gas turbine scheduling parameters
Figure BDA0002295406000000151
Figure BDA0002295406000000161
TABLE 3 scheduling parameters for diesel engines
Item of parameter Numerical value
Maximum active output value/MW 15
Minimum active output value/MW 2
Maximum reactive output value/MW 5
Minimum reactive output value/MW 1
Climbing rate/(MW. h-1) 1
Minimum boot time/h 2
Minimum off time/h 2
Linear consumption parameter/(m 3. MW)-1·h-1) 0.089
Fixed consumption parameter/(m 3. MW)-1) 0.57
。
To verify the effectiveness of the method of the present invention, the present embodiment sets 4 operation scenarios as shown in table 4. Wherein, the system in scene 1 comprises an AA-CAES device and participates in the standby and heat supply of the system at the same time; scene 2 does not contain an AA-CAES device; the AA-CAES device in the scene 3 does not participate in system heat supply; the AA-CAES device does not participate in standby in scenario 4.
TABLE 4 settings for the operational scenarios
Figure BDA0002295406000000162
Fig. 4 and 5 are graphs of system power output and system energy output of scene 1, and it can be seen from the graphs that in a time period from 00:00 to 08:30, the system electrical load and photovoltaic output values are low, and the thermal load level is high, and in the time period, the AA-CAES thermal storage keeps full heat output and shares part of the thermal load for the gas turbine. Along with the lapse of time, the electrical load level is gradually increased and the thermal load level is reduced, the AA-CAES maintains the thermal output of the gas turbine unchanged, the electrical output of the gas turbine is synchronously reduced along with the reduction of the thermal output, and the AA-CAES is switched into the power generation working condition to provide the electric energy support for the system. In the period of 08:30-17:30, the system is low in heat load level and high in electric load level, and meanwhile, the photovoltaic power generation amount is increased sharply and reaches a peak value at 12:30 and exceeds the electric load in the period of 09:45-15: 00. In the time period, in order to improve the operating economy of the system, the primary goal of scheduling is to reduce the light waste, so that the output of the AA-CAES is gradually reduced after 08:30, the AA-CAES is switched to a compression working condition to store surplus photovoltaic electric quantity in the time period of 09:30-15:30, meanwhile, part of the photovoltaic electric quantity is used for heat generation of an electric boiler, and the heat output of a gas turbine and the AA-CAES are reduced. In the time period of 17:30-24:00, the thermal load and the electric load both enter a peak period, and the photovoltaic power generation amount is gradually reduced to 0. After the photovoltaic drops to 0, the AA-CAES and gas turbine take over the entire thermal load of the system. In order to ensure that the residual air pressure and heat are maintained within certain levels, the AA-CAES does not generate electricity for a long time and release energy after the photovoltaic is reduced to 0. It is worth noting that during the time period from 15:45 to 17:15, the photovoltaic drops rapidly, the electrical load value has reached a higher level, while the thermal load value has not yet risen. AA-CAES is to maintain residual gas pressure and heat in a shutdown state, while the gas turbine output is kept at a low level due to thermal load limitations, and the system needs a diesel engine to provide a higher output to meet the electrical load requirements. Therefore, the AA-CAES can not provide the standby in the period, the standby which can be provided by the diesel engine is correspondingly reduced, the standby resources of the system are in the most scarce state in the day, and the reasonable configuration of the standby resources in the period can become an important target of scheduling. In general, the electric output curve of the AA-CAES device meets the output characteristic of energy storage of low energy storage and high energy discharge, the energy is compressed in the low valley period of the net load of the system, and the energy is expanded and released in the high peak period, so that the effects of reducing light abandon and enriching the standby are achieved; the AA-CAES device provides a large amount of thermal power for the system, shares the capacity burden of the gas turbine, and plays the roles of combined heat and power storage/supply and reduction of the energy consumption of the system operation.
Fig. 6, 7 and 8 show the heat output of the system in scene 1 and scene 3. AA-CAES participates in system heat supply, mainly carries out heat energy output in the photovoltaic valley period, and bears 17.35% of heat load of the system every day. After the AA-CAES participates in system heat supply, the heat output of the electric boiler is reduced slightly, and the heat output of the gas turbine is reduced greatly. In the full period of the photovoltaic power station with output, namely the time period from 05:45 to 19:45, partial photovoltaic electric quantity is used for heat production of the electric boiler. In the time period of 09:15-15:30, the photovoltaic output is high, the photovoltaic bears the main electric load and partial heat load of the system, and the gas turbine keeps the minimum output. The heat output of the AA-CAES is mainly distributed in the time periods of 00:00-10:15 and 15:00-24:00, wherein in the time periods of 00:00-8:45 and 17:30-24:00, the heat reservoir of the AA-CAES fully generates heat, the heat output of the gas turbine is greatly reduced, and in the time periods of 08:45-10:15 and 15:00-17:30, the system has no outstanding photovoltaic absorption problem, so that the AA-CAES provides certain heat energy, the photovoltaic heat output is reduced, a larger proportion of photovoltaic power generation is used for meeting the system electrical load, and the system operation energy consumption is further reduced.
Fig. 9 and fig. 10 are schematic diagrams of backup power supply situations of backup sources in scenario 1 and scenario 4, respectively, and it can be known from the diagrams that the backup resources of the system are sufficient, and the gas turbine and the diesel engine can already sufficiently meet the backup requirements of the system, so that whether the AA-CAES power station provides the backup has a small influence on the operation strategy of the system. However, the investment of the AA-CAES can provide more sufficient standby resources for the system, can provide more scheduling and emergency resources for the system in an emergency situation, and enhances the safety and reliability of the system operation. Meanwhile, the AA-CAES has higher starting speed and rapid working condition conversion, has wider application potential in the aspects of downward standby, accident standby and black start, and can provide stronger support for the safe and stable operation of the system.
Through the analysis, the peak of the photovoltaic output of the system is concentrated in the time period of 09:15-15:30, and the main application of the system comprises 1) meeting the electrical load requirement of the system; 2) the system is used for generating heat by an electric boiler to meet the heat load requirement of the system; 3) AA-CAES compressed energy storage. The light energy that cannot be fully utilized after the above requirements are met is discarded. Because the system is left out of consideration for standby, light rejection will only occur if the photovoltaic output exceeds the total electrical load. In scene 2 (without AA-CAES), the light abandon is generated within the time period of 12:30-14:15, and the total light abandon amount is 3.8MW & h; after the AA-CAES is added into the system to operate, energy is stored in a ratio of 09:30-15:15, light abandoning of the system is completely reduced, and photovoltaic absorption capacity of the system is improved.
In addition, the daily schedule operation energy consumption specification of the system of scenarios 1, 2, and 3 is shown in table 5 (for comparison, the energy consumption of each part of the system has been converted into natural gas volume):
TABLE 5 System daily schedule operation energy consumption Specification
Figure BDA0002295406000000181
As can be seen from table 5, the daily scheduled operation energy consumption of scenario 1 and scenario 3 is reduced by 17.78% and 1.70% respectively compared to scenario 2. Based on the analysis, the AA-CAES participates in the system operation, and mainly plays roles in combined heat and power storage and co-supply, improving the photovoltaic absorption capacity of the system and enriching the standby resources of the system. In combination with Table 2, the economic benefits of AA-CAES are most evident in terms of heat supply. The energy consumption of system heat supply can be equivalent to the energy consumption of the gas turbine, and the operation energy consumption of the gas turbine under the scene 1 is reduced by 28.03% and 26.28% compared with the scene 2 and the scene 3 respectively. In the above 3 scenarios, the scheduled energy consumption of the gas turbine accounts for 94.54%, 99.51% and 99.86% of the total energy consumption of its daily scheduled operation, respectively. The introduction of AA-CAES can share 17.35% of heat load of the system, thus having obvious effect on reducing the heat supply energy consumption of the system. And secondly, after the AA-CAES is put into the system, the system light rejection is completely reduced, and the light rejection equivalent energy consumption is reduced by 100%. However, since photovoltaic electricity can be used to generate heat, the amount of light rejected by the system itself is low, and therefore the economic benefit of AA-CAES in this respect has a relatively small impact on the total energy consumption. In addition, the investment of AA-CAES improves the flexibility of system scheduling operation, the scheduling requirement of transferable loads is correspondingly reduced, and the scheduling equivalent energy consumption of the transferable loads in scene 1 and scene 3 is respectively reduced by 38.54% and 3.81% compared with that in scene 2.
In summary, the optimal scheduling method provided by the invention has effectiveness and rationality.

Claims (6)

1. A optimal scheduling method of a combined heat and power system considering AA-CAES is characterized in that:
the method comprises the following steps in sequence:
step A, establishing a day-ahead scheduling model of the combined heat and power system considering AA-CAES, wherein the model takes the minimum sum of the operating energy consumption of a gas turbine, the operating energy consumption of a diesel engine, the equivalent energy consumption of waste photovoltaic and the equivalent scheduling energy consumption of transferable loads as an objective function;
and step B, inputting the acquired short-term prediction data of the photovoltaic power, the thermal load and the electrical load into the day-ahead scheduling model to obtain a day-ahead scheduling result of the combined heat and power system, and then scheduling the combined heat and power system according to the day-ahead scheduling result.
2. The optimal scheduling method for the combined heat and power system considering AA-CAES as claimed in claim 1, wherein:
in step a, the objective function of the day-ahead scheduling model is:
Figure FDA0002295405990000011
in the above formula, T is the number of time in the scheduling time period before day, NGT、NG、NPV、NDRRespectively the number of gas turbines, diesel engines, photovoltaic power stations, transferable load nodes, bGT,iIs the coefficient of energy consumption, H, of the gas turbine iGT,t,iPower produced by gas turbine i at time t, PG,t,sIs the output value of the diesel engine s at time t, bsA parameter of the power generation and coal consumption of the diesel engine s, csThe coal consumption parameter u for starting and stopping the diesel engine s and switchingt,sOn-off state of diesel engine s at time t, CDRFor scheduling equivalent energy consumption parameters for transferable loads,
Figure FDA0002295405990000012
respectively the increasing load power and the decreasing load power of the jth transferable load node at the time t, cppvPenalizing the equivalent energy consumption coefficient for the abandoned photovoltaic, Ppva,t,kAnd the actual light abandoning power of the photovoltaic power station k at the moment t is obtained.
3. The optimal scheduling method for the combined heat and power system considering AA-CAES as claimed in claim 2, wherein:
the constraint conditions of the objective function comprise the constraint that the AA-CAES device participates in the day-ahead scheduling and performs combined heat and power supply, the constraint that the gas turbine participates in the day-ahead scheduling operation, the constraint that the electric boiler participates in the day-ahead scheduling operation, the constraint that the diesel engine participates in the day-ahead scheduling operation, the power flow constraint of an AC/DC power distribution network, the constraint that the photovoltaic power station participates in the day-ahead scheduling operation, the constraint that the transferable load participates in the day-ahead scheduling operation, the heat energy balance constraint and the system standby constraint, wherein,
the restriction that the AA-CAES device participates in day-ahead scheduling and performs combined heat and power supply comprises the following steps:
AA-CAES general operating constraints:
uCAESc,t+uCAESg,t≤1
Figure FDA0002295405990000021
Figure FDA0002295405990000022
in the above formula, uCASEg,tIs a power generation state variable u of the AA-CAES device at the time tCASEc,tFor compression state variable, P, of AA-CAES devices at time tCASEg,t、PCASEc,tRespectively the power generation and compression power P of the AA-CAES device at the time tCAEScmax、PCAEScminUpper and lower limit values of compression power, P, of AA-CAES deviceCAESgmaxAnd PCAESgminRespectively an upper limit value and a lower limit value of the generated power, p, of the AA-CAES devicest,tAir pressure of air reservoir, p, of AA-CAES apparatus at time tstmax、pstminThe upper and lower limit values of the air pressure of the air storage chamber, △ pst,0△ p being the initial rate of change of air pressure in the reservoirst,τThe air pressure change rate of the air storage chamber at the time tau, △ t being the duration of a scheduling period;
AA-CAES expansion/compression heat exchange constraints:
Hg,m,t＝mg,tcp,a(Tg,,m,in,t-Tg,m-1,out,t)
Figure FDA0002295405990000023
in the above formula, Hg,m,tAnd Hg,tThe m-th stage expansion process at time t and the overall heat release power of the AA-CAES plant, cp,aIs the specific heat capacity of air, Tg,m,in,tAnd Tg,m-1,out,tRespectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, ngExpansion series of AA-CAES;
AA-CAES heating power constraint:
Figure FDA0002295405990000024
in the above formula, Hst,t、Hstout,tRespectively the heat energy loss power and the actual external heat output power of the heat reservoir at the time t, HstmaxFor the external heating power limit, k, of the heat reservoirstThe loss coefficient of heat supply for the heat reservoir to the outside;
AA-CAES residual heat constraint:
Figure FDA0002295405990000025
in the above formula, HHS,0And HHS,tRespectively is the initial heat value and the residual heat at the time t, H of the AA-CAES heat storage chamberc,τ、Hg,τ、Hst,τThe compression heat release power, the power generation heat consumption power and the external heat supply power of the AA-CAES device at the time of tau, HHSmax、HHsminThe upper limit value and the lower limit value of the heat storage quantity of the AA-CAES device are respectively set;
AA-CAES provides rotational standby constraints:
Figure FDA0002295405990000031
in the above formula, RCAES,tFor the rotational reserve, R, that the AA-CAES can provide for the system at time tCAESc,t、RCAESg,tCan provide a rotary standby for the system when the AA-CAES operates under the working conditions of compression and power generation at the time t respectively, khg、khcRespectively is the power coefficient k of the heat exchange power of the AA-CAES device in the power generation and compression processesg、kcThe power coefficients of the air pressure change rate of the air storage chamber of the AA-CAES device in the power generation and compression processes are respectively.
4. The optimal scheduling method for the combined heat and power system considering AA-CAES as claimed in claim 3, wherein:
the constraints of the gas turbine participating in the day-ahead scheduling operation comprise thermoelectric output proportion constraint, thermoelectric output upper and lower limit constraint, fuel consumption upper and lower limit constraint and climbing constraint;
the constraint of the electric boiler participating in the day-ahead scheduling operation is as follows:
Figure FDA0002295405990000032
in the above formula, Heb,tIs the thermal output power, P, of the electric boiler at time tpv,t,kAnd Ppvh,t,kTotal generated power of photovoltaic plant k and electric power for heat production by electric boiler at time t, η respectivelypvhThe electric heat conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit and an output lower limit, a minimum on-off time constraint and a climbing rate constraint;
the load flow constraint of the alternating current and direct current power distribution network comprises a VSC converter station scheduling operation constraint, a branch load flow balance constraint based on DistFlow and a system safety constraint;
the constraint that the photovoltaic power station participates in day-ahead scheduling operation is as follows:
Figure FDA0002295405990000041
in the above formula, Ppva,t,kIs the actual light abandoning power, P, of the photovoltaic power station k at the moment tpve,t,kThe power for the photovoltaic power station k to meet the electrical load demand at time t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
Figure FDA0002295405990000042
Figure FDA0002295405990000043
Figure FDA0002295405990000044
in the above formula, the first and second carbon atoms are,
Figure FDA0002295405990000045
and
Figure FDA0002295405990000046
respectively a lower limit and an upper limit of the load transfer amount on the transferable load node j,
Figure FDA0002295405990000047
a state variable is scheduled for the forward load of the transferable load node j at time t,
Figure FDA0002295405990000048
a state variable is scheduled for the negative load of the transferable load node j at time t,
Figure FDA0002295405990000049
and
Figure FDA00022954059900000410
respectively a lower limit and an upper limit of the load transfer amount of the transferable load on the transferable load node j,
Figure FDA00022954059900000411
the upper limit of the single-day transfer amount of the load of the transferable load node j;
the thermal energy balance constraint is:
Figure FDA00022954059900000412
in the above formula, Hload,tIs the thermal load of the system at time t;
the system standby constraints are:
Figure FDA00022954059900000413
in the above formula, PGTmax,i、PGTmax,sUpper limit of output, P, for gas turbine i and diesel engine s, respectivelyT,t、PTmaxRespectively, the upper level grid support power and the upper limit value, R at the moment tL、RPVRespectively reserve the standby power for load and photovoltaic.
5. The optimal scheduling method for the AA-CAES considered cogeneration system according to any one of claims 1-4, wherein:
and in the step B, the day-ahead scheduling result comprises the start-stop state and the operating condition of the AA-CAES device, the gas turbine and the diesel engine, and the scheduling plan of the AA-CAES device, the gas turbine, the diesel engine, the electric boiler and the transferable load.
6. The optimal scheduling method for the AA-CAES considered cogeneration system according to any one of claims 1-4, wherein:
the combined heat and power system comprises an alternating current power distribution network, a direct current power distribution network, a converter station, a regional heating system and a thermoelectric coupling device, wherein the alternating current power distribution network comprises a diesel engine and an alternating current load, the direct current power distribution network comprises a direct current load and a photovoltaic power station, the regional heating system comprises a thermal load, and the thermoelectric coupling device comprises an AA-CAES device, a gas turbine and an electric boiler.
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