CN110991735B - Optimal scheduling method of combined heat and power system considering AA-CAES - Google Patents
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Abstract
A method for optimizing and dispatching a combined heat and power system by considering AA-CAES includes setting up a combined heat and power system day-ahead dispatching model taking minimum sum of energy consumption of operation of a gas turbine, energy consumption of operation of a diesel engine, energy consumption of waste photovoltaic and equivalent dispatching energy consumption of transferable load as an objective function, inputting obtained photovoltaic, thermal load and short-term predication data of electrical load into the day-ahead dispatching model to obtain day-ahead dispatching result of the combined heat and power system, and dispatching the combined heat and power system according to the day-ahead dispatching result. The design not only improves the operation flexibility, stability and reliability of the cogeneration system, but also improves the capacity of absorbing renewable energy sources of the system and reduces the operation energy consumption of the system.
Description
Technical Field
The invention belongs to the field of optimal scheduling of a cogeneration system, and particularly relates to an optimal scheduling method of the cogeneration system considering AA-CAES.
Background
Compared with the traditional micro-grid, the cogeneration system can realize the mutual conversion and complementary mutual utilization between the heat energy and the electric energy through the combined storage and the combined supply of the heat energy and the electric energy, thereby enhancing the energy supply reliability of the system and improving the comprehensive energy utilization rate and the energy supply quality.
In recent years, advanced adiabatic compressed air energy storage (Advanced Adiabatic Compressed Air Energy Storage, AA-CAES) technology has evolved. The AA-CAES is rapid in regulation, the system efficiency is high, and the system has good thermoelectric coupling storage/capacity, and can provide various auxiliary services such as peak regulation, standby and reactive regulation for the system. The above advantages make the energy storage device one of the most developed physical energy storage technologies at present, and the energy storage device is widely paid attention to the academia and industry. However, there is no mature technology for the dispatching method of the cogeneration system comprising the AA-CAES device, and reliable and stable operation of the cogeneration system comprising the energy storage device cannot be ensured.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provide the optimal scheduling method of the combined heat and power system taking the AA-CAES into consideration, which can ensure the reliable and stable operation of the combined heat and power system.
In order to achieve the above object, the technical scheme of the present invention is as follows:
an optimal scheduling method of a cogeneration system considering AA-CAES sequentially comprises the following steps:
step A, a day-ahead scheduling model of a combined heat and power system taking AA-CAES into consideration is established, and the model takes the minimum sum of energy consumption of gas turbine operation, diesel engine operation, waste photovoltaic and other energy consumption and transferable load equivalent scheduling energy consumption as an objective function;
and B, inputting the obtained short-term prediction data of the photovoltaic load, the thermal load and the electric load into the day-ahead dispatching model to obtain a day-ahead dispatching result of the cogeneration system, and dispatching the cogeneration system according to the day-ahead dispatching result.
In the step a, the objective function of the day-ahead scheduling model is:
in the above, T is the number of time in the day-ahead scheduling time period, N GT 、N G 、N PV 、N DR The number of transferable load nodes, b GT,i Is the energy consumption coefficient of the gas turbine i, H GT,t,i For the heat production power of the gas turbine i at time t, P G,t,s The output value of the diesel engine s at the moment t is b s C, the consumption parameter of the generated power fuel coal of the diesel engine s s Coal consumption parameter u for diesel engine s start-up and shut-down condition and switching t,s The on-off state of the diesel engine s at the moment t is C DR For the scheduling equivalent energy consumption parameter of the transferable load,increasing and decreasing load power of j-th transferable load node at t moment respectively, c ppv To waste photovoltaic punishment equivalent energy consumption coefficient, P pva,t,k The actual light rejection power of the photovoltaic power plant 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 dispatching and performs cogeneration, the constraint that the gas turbine participates in the day-ahead dispatching operation, the constraint that the electric boiler participates in the day-ahead dispatching operation, the constraint that the diesel engine participates in the day-ahead dispatching operation, the tidal current constraint of the AC/DC power distribution network, the constraint that the photovoltaic power station participates in the day-ahead dispatching operation, the constraint that the transferable load participates in the day-ahead dispatching operation, the thermal energy balance constraint and the system standby constraint,
the constraint that the AA-CAES device participates in day-ahead scheduling and performs cogeneration comprises:
AA-CAES general operation constraints:
u CAESc,t +u CAESg,t ≤1
in the above, u CASEg,t Is the power generation state variable of the AA-CAES device at the time t, u CASEc,t Is the compression state variable of the AA-CAES device at the time t, P CASEg,t 、P CASEc,t The power generation and compression power of the AA-CAES device at the time t are respectively as follows, P CAEScmax 、P CAEScmin Compression power upper and lower limit values, P of the AA-CAES device respectively CAESgmax And P CAESgmin The upper limit value and the lower limit value of the generated power of the AA-CAES device and p are respectively st,t Air pressure of air storage chamber of AA-CAES device at t moment, p stmax 、p stmin Respectively the upper limit value and the lower limit value of the air pressure of the air storage chamber, delta p st,0 For the initial air pressure change rate of the air storage chamber, deltap st,τ The air pressure change rate of the air storage chamber at tau is the duration of a scheduling period;
AA-CAES expansion/compression heat exchange constraint:
H g,m,t ＝m g,t c p,a (T g,,m,in,t -T g,m-1,out,t )
in the above, H g,m,t And H g,t The mth stage expansion process at time t and the overall heat release power of the AA-CAES device, c p,a Is the specific heat capacity of air, T g,m,in,t And T g,m-1,out,t Respectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, n g Expansion progression for AA-CAES;
AA-CAES heating power constraint:
in the above, H st,t 、H stout,t Respectively the heat energy loss power and the actual external heat output power of the heat reservoir at the moment t, H stmax For the limit value, k of the external heating power of the heat accumulator st The loss coefficient of the heat reservoir for external heat supply;
AA-CAES residual heat constraint:
in the above, H HS,0 And H HS,t Respectively the initial heat value and the residual heat at the moment t of the AA-CAES heat storage chamber, H c,τ 、H g,τ 、H st,τ The compression heat release power, the power consumption heat power and the external heat supply power of the AA-CAES device at tau moment are respectively H HSmax 、H Hsmin The upper limit value and the lower limit value of the heat storage capacity of the AA-CAES device are respectively set;
AA-CAES provides a rotational redundancy constraint:
in the above, R CAES,t A rotational reserve provided for the system for time t AA-CAES, R CAESc,t 、R CAESg,t Rotation reserve which can be provided for system when AA-CAES operates under compression and power generation working conditions at time t respectively，k hg 、k hc Respectively the power coefficients, k of heat exchange power of the AA-CAES device in the power generation and compression process g 、k c The 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 shown.
The constraints of the gas turbine participating in the day-ahead dispatch operation comprise a thermoelectric output proportion constraint, a thermoelectric output upper limit and lower limit constraint, a fuel consumption upper limit and lower limit constraint and a climbing constraint;
the constraint that the electric boiler participates in the day-ahead scheduling operation is as follows:
in the above, H eb,t For the heat output power of the electric boiler at the time t, P pv,t,k And P pvh,t,k The total power of the photovoltaic power station k at the moment t and the power for generating heat of the electric boiler are respectively, eta pvh The electric heating conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit constraint, a lower limit constraint, a minimum on-off time constraint and a climbing rate constraint;
the power flow constraint of the AC/DC power distribution network comprises a VSC converter station scheduling operation constraint, a DistFlow-based branch power flow balance constraint and a system security constraint;
the photovoltaic power station participates in the constraint of scheduling operation in the future:
in the above, P pva,t,k For the actual light rejection power of the photovoltaic power station k at the moment t, P pve,t,k The power for satisfying the electric load requirement for the photovoltaic power station k at the moment t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
in the above-mentioned method, the step of,and->The lower limit and the upper limit of the load transfer quantity on the transferable load node j are respectively,scheduling a state variable for the forward load of the transferable load node j at time t,/for the load node j>Scheduling a state variable for the negative load of the transferable load node j at time t,/>And->A lower limit and an upper limit of a load transfer amount of a transferable load on the transferable load node j, respectively,/->An upper limit of a single-day transfer amount for transferring the load of the load node j;
the thermal energy balance constraint is:
in the above, H load,t The thermal load of the system at time t;
the system standby constraint is:
in the above, P GTmax,i 、P GTmax,s The upper limit value of the output of the gas turbine i and the diesel engine s, P T,t 、P Tmax Respectively supporting power and upper limit value R of upper power grid at t moments L 、R PV The reserve power reserved for the load and the photovoltaic is reserved respectively.
In the step B, the day-ahead dispatching result comprises the starting and stopping states and the running working conditions of the AA-CAES device, the gas turbine and the diesel engine, and dispatching plans of the AA-CAES device, the gas turbine, the diesel engine, the electric boiler and the transferable loads.
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 heat 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 an optimal scheduling method of a cogeneration system, which is characterized in that a day-ahead scheduling model of the cogeneration system taking the minimum sum of energy consumption of gas turbine operation, diesel engine operation, waste photovoltaic and other energy consumption and energy consumption of transferable load equivalent scheduling as an objective function is firstly established, then the obtained photovoltaic, thermal load and short-term prediction data of the electrical load are input into the day-ahead scheduling model to obtain a day-ahead scheduling result of the cogeneration system, and then the cogeneration system is scheduled according to the day-ahead scheduling result. Therefore, the invention not only improves the operation flexibility, stability and reliability of the cogeneration system, but also improves the capacity of absorbing 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 energy flow relationship of the cogeneration system of the invention.
Fig. 2 is a schematic diagram of the cogeneration system according to embodiment 1 of the invention.
Fig. 3 is a graph of short-term predictive data for photovoltaic power generation, thermal load, electrical load of the system of example 1 of this invention.
Fig. 4 is a graph of the system power output of scenario 1 of example 1 of the present invention.
Fig. 5 is a graph of the system power output of scenario 1 of example 1 of the present invention.
Fig. 6 is a schematic diagram of the system heat source output of scenario 1 in embodiment 1 of the present invention.
Fig. 7 is a schematic diagram of the system heat source output of scenario 3 in embodiment 1 of the present invention.
Fig. 8 is a schematic diagram of the system heat source output ratio of scenario 1 and scenario 3 in embodiment 1 of the present invention.
Fig. 9 is a schematic diagram of providing standby power of each standby source in scenario 1 in embodiment 1 of the present invention.
Fig. 10 is a schematic diagram of providing standby power of each standby source in scenario 4 in embodiment 1 of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following embodiments.
Referring to fig. 1, a thermoelectric co-generation system optimization scheduling method considering AA-CAES sequentially includes the following steps:
step A, a day-ahead scheduling model of a combined heat and power system taking AA-CAES into consideration is established, and the model takes the minimum sum of energy consumption of gas turbine operation, diesel engine operation, waste photovoltaic and other energy consumption and transferable load equivalent scheduling energy consumption as an objective function;
and B, inputting the obtained short-term prediction data of the photovoltaic load, the thermal load and the electric load into the day-ahead dispatching model to obtain a day-ahead dispatching result of the cogeneration system, and dispatching the cogeneration system according to the day-ahead dispatching result.
In the step a, the objective function of the day-ahead scheduling model is:
in the above, T is the number of time in the day-ahead scheduling time period, N GT 、N G 、N PV 、N DR The number of transferable load nodes, b GT,i Is the energy consumption coefficient of the gas turbine i, H GT,t,i For the heat production power of the gas turbine i at time t, P G,t,s The output value of the diesel engine s at the moment t is b s C, the consumption parameter of the generated power fuel coal of the diesel engine s s Coal consumption parameter u for diesel engine s start-up and shut-down condition and switching t,s The on-off state of the diesel engine s at the moment t is C DR For the scheduling equivalent energy consumption parameter of the transferable load,increasing and decreasing load power of j-th transferable load node at t moment respectively, c ppv To waste photovoltaic punishment equivalent energy consumption coefficient, P pva,t,k The actual light rejection power of the photovoltaic power plant 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 dispatching and performs cogeneration, the constraint that the gas turbine participates in the day-ahead dispatching operation, the constraint that the electric boiler participates in the day-ahead dispatching operation, the constraint that the diesel engine participates in the day-ahead dispatching operation, the tidal current constraint of the AC/DC power distribution network, the constraint that the photovoltaic power station participates in the day-ahead dispatching operation, the constraint that the transferable load participates in the day-ahead dispatching operation, the thermal energy balance constraint and the system standby constraint,
the constraint that the AA-CAES device participates in day-ahead scheduling and performs cogeneration comprises:
AA-CAES general operation constraints:
u CAESc,t +u CAESg,t ≤1
in the above, u CASEg,t Is the power generation state variable of the AA-CAES device at the time t, u CASEc,t Is the compression state variable of the AA-CAES device at the time t, P CASEg,t 、P CASEc,t The power generation and compression power of the AA-CAES device at the time t are respectively as follows, P CAEScmax 、P CAEScmin Compression power upper and lower limit values, P of the AA-CAES device respectively CAESgmax And P CAESgmin The upper limit value and the lower limit value of the generated power of the AA-CAES device and p are respectively st,t Air pressure of air storage chamber of AA-CAES device at t moment, p stmax 、p stmin Respectively the upper limit value and the lower limit value of the air pressure of the air storage chamber, delta p st,0 For the initial air pressure change rate of the air storage chamber, deltap st,τ The air pressure change rate of the air storage chamber at tau is the duration of a scheduling period;
AA-CAES expansion/compression heat exchange constraint:
H g,m,t ＝m g,t c p,a (T g,,m,in,t -T g,m-1,out,t )
in the above, H g,m,t And H g,t The mth stage expansion process at time t and the overall heat release power of the AA-CAES device, c p,a Is the specific heat capacity of air, T g,m,in,t And T g,m-1,out,t Respectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, n g Expansion progression for AA-CAES;
AA-CAES heating power constraint:
in the above, H st,t 、H stout,t Respectively the heat energy loss power and the actual external heat output power of the heat reservoir at the moment t, H stmax For the limit value, k of the external heating power of the heat accumulator st The loss coefficient of the heat reservoir for external heat supply;
AA-CAES residual heat constraint:
in the above, H HS,0 And H HS,t Respectively the initial heat value and the residual heat at the moment t of the AA-CAES heat storage chamber, H c,τ 、H g,τ 、H st,τ The compression heat release power, the power consumption heat power and the external heat supply power of the AA-CAES device at tau moment are respectively H HSmax 、H Hsmin The upper limit value and the lower limit value of the heat storage capacity of the AA-CAES device are respectively set;
AA-CAES provides a rotational redundancy constraint:
in the above, R CAES,t A rotational reserve provided for the system for time t AA-CAES, R CAESc,t 、R CAESg,t The rotation reserve, k, provided for the system when the AA-CAES operates in compression and power generation working conditions at the moment t respectively hg 、k hc Respectively the power coefficients, k of heat exchange power of the AA-CAES device in the power generation and compression process g 、k c The air pressure of the air storage chamber of the AA-CAES device is changed in the power generation and compression processPower coefficient of the conversion rate.
The constraints of the gas turbine participating in the day-ahead dispatch operation comprise a thermoelectric output proportion constraint, a thermoelectric output upper limit and lower limit constraint, a fuel consumption upper limit and lower limit constraint and a climbing constraint;
the constraint that the electric boiler participates in the day-ahead scheduling operation is as follows:
in the above, H eb,t For the heat output power of the electric boiler at the time t, P pv,t,k And P pvh,t,k The total power of the photovoltaic power station k at the moment t and the power for generating heat of the electric boiler are respectively, eta pvh The electric heating conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit constraint, a lower limit constraint, a minimum on-off time constraint and a climbing rate constraint;
the power flow constraint of the AC/DC power distribution network comprises a VSC converter station scheduling operation constraint, a DistFlow-based branch power flow balance constraint and a system security constraint;
the photovoltaic power station participates in the constraint of scheduling operation in the future:
in the above, P pva,t,k For the actual light rejection power of the photovoltaic power station k at the moment t, P pve,t,k The power for satisfying the electric load requirement for the photovoltaic power station k at the moment t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
in the above-mentioned method, the step of,and->The lower limit and the upper limit of the load transfer quantity on the transferable load node j are respectively,scheduling a state variable for the forward load of the transferable load node j at time t,/for the load node j>Scheduling a state variable for the negative load of the transferable load node j at time t,/>And->A lower limit and an upper limit of a load transfer amount of a transferable load on the transferable load node j, respectively,/->An upper limit of a single-day transfer amount for transferring the load of the load node j;
the thermal energy balance constraint is:
in the above, H load,t The thermal load of the system at time t;
the system standby constraint is:
in the above, P GTmax,i 、P GTmax,s The upper limit value of the output of the gas turbine i and the diesel engine s, P T,t 、P Tmax Respectively supporting power and upper limit value R of upper power grid at t moments L 、R PV The reserve power reserved for the load and the photovoltaic is reserved respectively.
In the step B, the day-ahead dispatching result comprises the starting and stopping states and the running working conditions of the AA-CAES device, the gas turbine and the diesel engine, and dispatching plans of the AA-CAES device, the gas turbine, the diesel engine, the electric boiler and the transferable loads.
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 heat load, and the thermoelectric coupling device comprises an AA-CAES device, a gas turbine and an electric boiler.
The principle of the invention is explained as follows:
the invention provides an AA-CAES considered optimal scheduling method of a cogeneration system, which aims at an established AA-CAES-containing cogeneration system scheduling framework, and constructs a AA-CAES considered day-ahead scheduling model of the cogeneration system according to the operation characteristics of an AA-CAES device in key links such as heat storage, heat exchange and heat supply and the operation characteristics of other scheduling resources in the cogeneration system, wherein the AA-CAES considered optimal scheduling framework 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, the alternating current power distribution network comprises a diesel engine and an alternating current load (part of the alternating current load is set as a transferable load), the direct current power distribution network comprises a direct current load and a photovoltaic power station, the converter station realizes power transmission and port voltage control between the alternating current power distribution network and the direct current power distribution network, the regional heating system comprises a thermal load, and the thermoelectric coupling device comprises an AA-CAES device, a gas turbine and a boiler, and conversion between energy flows is realized.
Day-ahead scheduling model: the scheduling target is to minimize the operation energy consumption of the cogeneration system, and in order to improve the light Fu Xiaona rate, the objective function of the model considers the energy consumption of the light rejection and the like.
AA-CAES general operation constraints: mainly refers to single operation condition constraint, power upper and lower limit constraint and air pressure limit constraint of AA-CAES.
AA-CAES heat reservoir residual heat constraint; the AA-CAES has the precondition of supplying heat to the outside that the residual heat of the heat reservoir must be enough to support the requirement of expansion power generation in a subsequent period of time, and meanwhile, the heat reservoir cannot continue to store heat after the heat storage value of the heat reservoir reaches the upper limit of 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 subsequent power generation requirement and the utilization rate of compression recovery heat energy, thereby improving the energy efficiency of the system.
AA-CAES provides a rotational redundancy constraint: the residual air pressure and heat of the AA-CAES must be maintained above a certain level to ensure that sufficient standby power is available for the system in case of emergency such as power shortage. Thus, AA-CAES provides rotational redundancy, taking into account charge and discharge power constraints, residual air pressure and residual heat constraints.
Photovoltaic power plants participate in the constraint of day-ahead dispatch operation: the balance constraint is supplied for the photovoltaic electric quantity, and the function is as follows: the electric energy of the photovoltaic power station is mainly used for supplying power and generating heat by an electric boiler, and surplus photovoltaic electric energy is abandoned. Therefore, the sum of the photovoltaic power supply quantity, the heat-generating power consumption quantity of the electric boiler and the light rejection quantity is equal to the photovoltaic power generation quantity.
Thermal energy balance constraint: the constraint condition is used for guaranteeing the balance of the heat generation quantity and the heat load quantity of heat sources such as a gas turbine, an electric boiler and an AA-CAES device in the system, and avoiding load shortage or heat generation waste.
The system reserve constraint is that in order to ensure that the system can safely run when the power fluctuates or accidents happen, certain rotary reserve power is reserved for the system according to the predicted values of the load and the photovoltaic.
Example 1:
referring to fig. 2, an optimal scheduling method of a cogeneration system taking an AA-CAES into consideration is disclosed, the method targets the cogeneration system shown in fig. 2 (wherein, an ac-dc hybrid power distribution network part of the system adopts an IEEE-14 node system, the ac power distribution network part mainly comprises nodes 1-9, a gas turbine, a diesel engine and an AA-CAES device, and ac load users of node 5 and node 7 can participate in excitation type demand response, and is a transferable load, the dc power distribution network part mainly comprises nodes 10-14 and a photovoltaic power station, the gas turbine supplies heat directly to a thermal energy bus, the AA-CAES device supplies heat to the thermal energy bus through an AA-CAES heat reservoir, and part of generated energy of the photovoltaic power station supplies heat to an electric boiler to supply heat to the thermal energy bus), and the method sequentially comprises the following steps:
step 1, a day-ahead scheduling model of a combined heat and power system considering AA-CAES is established, and the model takes the minimum sum of energy consumption of gas turbine operation, diesel engine operation, waste photovoltaic and other energy consumption and transferable load equivalent scheduling energy consumption as an objective function:
in the above, T is the number of time in the day-ahead scheduling time period, N GT 、N G 、N PV 、N DR The number of transferable load nodes, b GT,i Is the energy consumption coefficient of the gas turbine i, H GT,t,i For the heat production power of the gas turbine i at time t, P G,t,s The output value of the diesel engine s at the moment t is b s C, the consumption parameter of the generated power fuel coal of the diesel engine s s Coal consumption parameter u for diesel engine s start-up and shut-down condition and switching t,s The on-off state of the diesel engine s at the moment t is C DR For the scheduling equivalent energy consumption parameter of the transferable load,increasing and decreasing load power of j-th transferable load node at t moment respectively, c ppv To waste photovoltaic punishment equivalent energy consumption coefficient, P pva,t,k For the time t, photovoltaic power station kIs the actual optical power of the light rejection;
the constraint conditions of the objective function comprise the constraint that the AA-CAES device participates in the day-ahead dispatching and performs cogeneration, the constraint that the gas turbine participates in the day-ahead dispatching operation, the constraint that the electric boiler participates in the day-ahead dispatching operation, the constraint that the diesel engine participates in the day-ahead dispatching operation, the tidal current constraint of the AC/DC power distribution network, the constraint that the photovoltaic power station participates in the day-ahead dispatching operation, the constraint that the transferable load participates in the day-ahead dispatching operation, the thermal energy balance constraint and the system standby constraint,
the constraint that the AA-CAES device participates in day-ahead scheduling and performs cogeneration comprises:
AA-CAES general operation constraints:
u CAESc,t +u CAESg,t ≤1
in the above, u CASEg,t Is the power generation state variable of the AA-CAES device at the time t, u CASEc,t Is the compression state variable of the AA-CAES device at the time t, P CASEg,t 、P CASEc,t The power generation and compression power of the AA-CAES device at the time t are respectively as follows, P CAEScmax 、P CAEScmin Compression power upper and lower limit values, P of the AA-CAES device respectively CAESgmax And P CAESgmin The upper limit value and the lower limit value of the generated power of the AA-CAES device and p are respectively st,t Air pressure of air storage chamber of AA-CAES device at t moment, p stmax 、p stmin Respectively the upper limit value and the lower limit value of the air pressure of the air storage chamber, delta p st,0 For the initial air pressure change rate of the air storage chamber, deltap st,τ The air pressure change rate of the air storage chamber at tau is the duration of a scheduling period;
AA-CAES expansion/compression heat exchange constraint:
H g,m,t ＝m g,t c p,a (T g,,m,in,t -T g,m-1,out,t )
in the above, H g,m,t And H g,t The mth stage expansion process at time t and the overall heat release power of the AA-CAES device, c p,a Is the specific heat capacity of air, T g,m,in,t And T g,m-1,out,t Respectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, n g Expansion progression for AA-CAES;
AA-CAES heating power constraint:
in the above, H st,t 、H stout,t Respectively the heat energy loss power and the actual external heat output power of the heat reservoir at the moment t, H stmax For the limit value, k of the external heating power of the heat accumulator st The loss coefficient of the heat reservoir for external heat supply;
AA-CAES residual heat constraint:
in the above, H HS,0 And H HS,t Respectively the initial heat value and the residual heat at the moment t of the AA-CAES heat storage chamber, H c,τ 、H g,τ 、H st,τ The compression heat release power, the power consumption heat power and the external heat supply power of the AA-CAES device at tau moment are respectively H HSmax 、H Hsmin The upper limit value and the lower limit value of the heat storage capacity of the AA-CAES device are respectively set;
AA-CAES provides a rotational redundancy constraint:
in the above, R CAES,t A rotational reserve provided for the system for time t AA-CAES, R CAESc,t 、R CAESg,t The rotation reserve, k, provided for the system when the AA-CAES operates in compression and power generation working conditions at the moment t respectively hg 、k hc Respectively the power coefficients, k of heat exchange power of the AA-CAES device in the power generation and compression process g 、k c The power coefficients of the air pressure change rate of the air storage chamber of the AA-CAES device in the power generation and compression process are respectively shown;
the constraints of the gas turbine participating in the day-ahead dispatch operation comprise a thermoelectric output proportion constraint, a thermoelectric output upper limit and lower limit constraint, a fuel consumption upper limit and lower limit constraint and a climbing constraint;
the constraint that the electric boiler participates in the day-ahead scheduling operation is as follows:
in the above, H eb,t For the heat output power of the electric boiler at the time t, P pv,t,k And P pvh,t,k The total power of the photovoltaic power station k at the moment t and the power for generating heat of the electric boiler are respectively, eta pvh The electric heating conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit constraint, a lower limit constraint, a minimum on-off time constraint and a climbing rate constraint;
the power flow constraint of the AC/DC power distribution network comprises a VSC converter station scheduling operation constraint, a DistFlow-based branch power flow balance constraint and a system security constraint;
the photovoltaic power station participates in the constraint of scheduling operation in the future:
in the above, P pva,t,k For the actual light rejection power of the photovoltaic power station k at the moment t, P pve,t,k The power for satisfying the electric load requirement for the photovoltaic power station k at the moment t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
in the above-mentioned method, the step of,and->The lower limit and the upper limit of the load transfer quantity on the transferable load node j are respectively,scheduling a state variable for the forward load of the transferable load node j at time t,/for the load node j>Scheduling a state variable for the negative load of the transferable load node j at time t,/>And->A lower limit and an upper limit of a load transfer amount of a transferable load on the transferable load node j, respectively,/->An upper limit of a single-day transfer amount for transferring the load of the load node j;
the thermal energy balance constraint is:
in the above, H load,t The thermal load of the system at time t;
the system standby constraint is:
in the above, P GTmax,i 、P GTmax,s The upper limit value of the output of the gas turbine i and the diesel engine s, P T,t 、P Tmax Respectively supporting power and upper limit value R of upper power grid at t moments L 、R PV The standby power reserved for load and photovoltaic is respectively;
step 2, firstly inputting the obtained short-term prediction data (see fig. 3) of the photovoltaic, thermal load and electric load into the day-ahead dispatching model to obtain a day-ahead dispatching result of the cogeneration system, and then dispatching the cogeneration system according to the day-ahead dispatching result, wherein the day-ahead dispatching is performed once every 24 hours, the unit dispatching time is 15 minutes, the dispatching time window is 24 hours, the day-ahead dispatching result comprises the starting and stopping states and the operation working conditions of an AA-CAES device, a gas turbine and a diesel engine, and dispatching plans of the AA-CAES device, the gas turbine, the diesel engine, an electric boiler and transferable loads, and dispatching parameters of the AA-CAES device, the gas turbine and the diesel engine are shown in tables 1-3:
table 1 AA-scheduling parameters for CAES devices
| Parameter item | Numerical value |
| Maximum power generation/MW | 16 |
| Minimum power generation/MW | 6.4 |
| Maximum compression power/MW | 8 |
| Minimum compression power/MW | 3.2 |
| Minimum on time/min | 45 |
| Minimum shutdown time/min | 45 |
| Maximum number of on/off per day | 5 |
| Power coefficient of power generation air pressure change rate/(Pa.kW) -1 ) | 2.17 |
| Power coefficient of variation rate of compressed air pressure/(Pa.kW) -1 ) | 2.68 |
| Air pressure variation range/MPa of air storage chamber | 4.5～5.5 |
| Heat energy loss coefficient of heat accumulator for external heat supply | 0.7 |
| Minimum ofPower factor | 0.8 |
TABLE 2 scheduling parameters for gas turbines
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Table 3 scheduling parameters for diesel engines
| Parameter item | Numerical value |
| Maximum active force value/MW | 15 |
| Minimum active force value/MW | 2 |
| Maximum reactive power value/MW | 5 |
| Minimum reactive power value/MW | 1 |
| Climbing rate/(MW h-1) | 1 |
| Minimum start-upTime/h | 2 |
| Minimum shutdown time/h | 2 |
| Linear consumption parameter/(m3.MW) -1 ·h -1 ) | 0.089 |
| Fixed consumption parameter/(m3.MW) -1 ) | 0.57 |
。
To verify the effectiveness of the method of the present invention, 4 operating scenarios as shown in table 4 were set up in this example. Wherein, the system in scenario 1 comprises an AA-CAES device and participates in both standby and heating of the system; scene 2 does not contain AA-CAES devices; the AA-CAES device in scenario 3 does not participate in system heating; the AA-CAES device in scenario 4 is not engaged in standby.
TABLE 4 settings for various operation scenarios
Fig. 4 and 5 are graphs of the system power output and the system energy output of scenario 1, and it can be seen from the graphs that the system electric load and the photovoltaic output value are lower and the heat load level is higher in a period of 00:00-08:30, and the AA-CAES heat storage device keeps full heat output and shares part of the heat load for the gas turbine in the period. Over time, the electric load level gradually increases and the heat load level decreases, the AA-CAES maintains the heat output unchanged, the electric output of the gas turbine synchronously decreases along with the decrease of the heat output, and the AA-CAES shifts to the power generation working condition to provide electric energy support for the system. The system thermal load level is lower and the electrical load level is higher during the 08:30-17:30 period, while photovoltaic power generation is ramped up, peaking at 12:30 and exceeding the electrical load during the 09:45-15:00 period. In this period, to improve the system operation economy, the primary goal of scheduling is to cut the waste light, so the AA-CAES output gradually decreases after 08:30, and the AA-CAES output gradually decreases after 09:30-15:30, and the AA-CAES output gradually decreases when the AA-CAES output gradually decreases, and the AA-CAES output gradually decreases. In the period of 17:30-24:00, the thermal load and the electric load enter a peak period, and the photovoltaic power generation capacity gradually weakens to 0. After a photovoltaic drop of 0, the AA-CAES and gas turbine bear the full thermal load of the system. In order to ensure that the residual air pressure and heat are maintained within a certain level, AA-CAES does not generate electricity and release energy for a long time after the photovoltaic is reduced to 0. Notably, the photovoltaic drops rapidly in the 15:45-17:15 period, the electrical load value has reached a higher level, and the thermal load value has not yet risen. AA-CAES is designed to maintain residual air pressure and heat at shutdown while the gas turbine output thermal load limit is maintained at a low level, and the system requires a diesel engine to provide a high output to meet electrical load demands. Thus, during this period, the AA-CAES is unable to provide redundancy, and the diesel engine is able to provide redundancy which is correspondingly reduced, and the spare resources of the system are in the most scarce state in the day, and the reasonable allocation of spare resources during this period will become an important target for scheduling. In general, the electric output curve of the AA-CAES device meets the output characteristic of energy storage of 'low storage and high release', compresses energy storage in the low valley period of the net load of the system, expands and releases energy in the peak period, and plays roles of reducing light rejection and enriching standby; the AA-CAES device provides a large amount of heat power for the system, shares the productivity burden of the gas turbine, plays a role in thermoelectric coupling storage/supply and reduces the running energy consumption of the system.
Fig. 6, 7, 8 show the system heat source output for scenario 1 and scenario 3. The AA-CAES participates in the heat supply of the system, mainly outputs heat energy in the photovoltaic valley period, and bears 17.35% of the heat load of the system every day. After the AA-CAES participates in the system heat supply, the heat output of the electric boiler is reduced to a small extent, and the heat output of the gas turbine is reduced to a large extent. In the full period of the power output of the photovoltaic power station, namely in the period of 05:45-19:45, part of photovoltaic electric quantity is used for generating heat of the electric boiler. The photovoltaic output is higher in the period of 09:15-15:30, the photovoltaic bears the main electric load and part of the 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 the heat storage of the AA-CAES fully emits heat in the time periods of 00:00-8:45 and 17:30-24:00, the heat output of the gas turbine is greatly reduced, and the system has no outstanding photovoltaic absorption problem in the time periods of 08:45-10:15 and 15:00-17:30, so that the AA-CAES provides certain heat energy, the photovoltaic heat output is reduced, the photovoltaic power generation amount of a larger proportion is used for meeting the system electric load, and the system operation energy consumption is further reduced.
Fig. 9 and 10 are schematic diagrams of the standby power supply situations of each standby source in scenario 1 and scenario 4, respectively, and it can be seen from the diagrams that the standby resources of the system are sufficient, and the gas turbine and the diesel engine can fully meet the standby requirement of the system, so whether the AA-CAES power station supplies the standby has less influence on the operation strategy of the system. However, the investment of the AA-CAES can provide more sufficient standby resources for the system, more scheduling and emergency resources can be provided for the system in emergency, and the operation safety and reliability of the system are enhanced. Meanwhile, the AA-CAES is high in starting speed, the working condition is quickly converted, and the AA-CAES has wider application potential in aspects of downward standby, accident standby and black starting, so that stronger support can be provided for safe and stable operation of the system.
Through the analysis, the peak of the photovoltaic output of the system is concentrated in the period of 09:15-15:30, and the main purposes of the system include that 1) the system electric load requirement is met; 2) The heat-generating device is used for generating heat of an electric boiler to meet the heat load requirement of the system; 3) AA-CAES compresses the stored energy. The light energy that is still not fully utilized after meeting the above-mentioned needs is discarded. Because the system is left unattended, light rejection only occurs if the photovoltaic output exceeds the total electrical load. In scene 2 (without AA-CAES), generating waste light within a period of 12:30-14:15, wherein the total amount of waste light is 3.8 MW.h; after the AA-CAES is added into the system to run, energy is stored in 09:30-15:15, the system waste light is completely reduced, and the photovoltaic digestion capacity of the system is improved.
In addition, the daily scheduled operating energy consumption details of the systems of scenarios 1, 2, 3 are shown in table 5 (for comparison purposes, the energy consumption of each part of the system has been converted to natural gas volume):
table 5 System daily scheduled operation energy consumption details
As can be seen from table 5, the daily scheduled operation energy consumption of scenario 1 and scenario 3 was 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 of combined heat and power storage, improving the photovoltaic digestion capability 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 energy supply. The energy consumption of the system heat supply can be equivalent to the energy consumption of the gas turbine, and the operation energy consumption of the gas turbine in the scene 1 is reduced by 28.03 percent and 26.28 percent compared with that in the scenes 2 and 3 respectively. In the 3 scenarios described above, the scheduled energy consumption of the gas turbine accounts for 94.54%, 99.51% and 99.86% of its total daily scheduled operating energy consumption, respectively. The introduction of AA-CAES can share 17.35% of the heat load of the system, so that the effect is remarkable in reducing the heat supply energy consumption of the system. And secondly, after the AA-CAES is put into the system, the system waste light is completely reduced, and the equivalent energy consumption of waste light is reduced by 100%. However, since photovoltaic power can be used to generate heat, the system itself has a low amount of waste, and therefore the economic benefit generated by AA-CAES in this respect has a relatively small impact on overall energy consumption. Besides, the input of the AA-CAES improves the flexibility of the scheduling operation of the system, the scheduling requirement of the transferable load is correspondingly reduced, and the scheduling equivalent energy consumption of the transferable load in the scene 1 and the scene 3 is respectively reduced by 38.54 percent and 3.81 percent compared with that in the scene 2.
In summary, the optimized scheduling method provided by the invention has effectiveness and rationality.
Claims (1)
1. An optimal scheduling method of a cogeneration system considering AA-CAES is characterized in that:
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 heat load, and the thermoelectric coupling device comprises an AA-CAES device, a gas turbine and an electric boiler;
the method sequentially comprises the following steps:
a, establishing a solar heat and power combined supply system solar heat and power dispatching model considering AA-CAES, wherein the model takes the minimum sum of energy consumption of gas turbine operation, diesel engine operation, waste photovoltaic and other energy consumption and transferable load equivalent dispatching energy consumption as an objective function, constraint conditions of the objective function comprise constraint that an AA-CAES device participates in solar heat and power combined supply, constraint that the gas turbine participates in solar heat and power combined supply operation, constraint that an electric boiler participates in solar heat and power combined supply operation, constraint that the diesel engine participates in solar heat and power combined supply operation, tidal current constraint of an AC/DC power distribution network, constraint that a photovoltaic power station participates in solar heat and power combined supply operation, constraint that transferable load participates in solar heat and power combined supply operation, constraint that AA-CAES expands/compresses heat and power combined supply constraint that AA-CAES provides rotary standby constraint;
the objective function of the day-ahead scheduling model is as follows:
in the above, T is the number of time in the day-ahead scheduling time period, N GT 、N G 、N PV 、N DR The number of transferable load nodes, b GT,i Is the energy consumption coefficient of the gas turbine i, H GT,t,i For the heat production power of the gas turbine i at time t, P G,t,s The output value of the diesel engine s at the moment t is b s C, the consumption parameter of the generated power fuel coal of the diesel engine s s Coal consumption parameter u for diesel engine s start-up and shut-down condition and switching t,s At time tThe on-off state of the diesel engine s, C DR For the scheduling equivalent energy consumption parameter of the transferable load,increasing and decreasing load power of j-th transferable load node at t moment respectively, c ppv To waste photovoltaic punishment equivalent energy consumption coefficient, P pva,t,k The actual light rejection power of the photovoltaic power station k at the moment t is;
the AA-CAES general operational constraints are:
u CAESc,t +u CAESg,t ≤1
in the above, u CASEg,t Is the power generation state variable of the AA-CAES device at the time t, u CASEc,t Is the compression state variable of the AA-CAES device at the time t, P CASEg,t 、P CASEc,t The power generation and compression power of the AA-CAES device at the time t are respectively as follows, P CAEScmax 、P CAEScmin Compression power upper and lower limit values, P of the AA-CAES device respectively CAESgmax And P CAESgmin The upper limit value and the lower limit value of the generated power of the AA-CAES device and p are respectively st,t Air pressure of air storage chamber of AA-CAES device at t moment, p stmax 、p stmin Respectively the upper limit value and the lower limit value of the air pressure of the air storage chamber, delta p st,0 For the initial air pressure change rate of the air storage chamber, deltap st,τ The air pressure change rate of the air storage chamber at tau is the duration of a scheduling period;
the AA-CAES expansion/compression heat exchange constraint is:
H g,m,t ＝m g,t c p,a (T g,,m,in,t -T g,m-1,out,t )
in the above, H g,m,t And H g,t The mth stage expansion process at time t and the overall heat release power of the AA-CAES device, c p,a Is the specific heat capacity of air, T g,m,in,t And T g,m-1,out,t Respectively the inlet temperature of the m-stage expander and the outlet temperature of the m-1 stage expander, n g Expansion progression for AA-CAES;
the AA-CAES heating power constraint is as follows:
in the above, H st,t 、H stout,t Respectively the heat energy loss power and the actual external heat output power of the heat reservoir at the moment t, H stmax For the limit value, k of the external heating power of the heat accumulator st The loss coefficient of the heat reservoir for external heat supply;
the AA-CAES residual heat constraint is:
in the above, H HS,0 And H HS,t Respectively the initial heat value and the residual heat at the moment t of the AA-CAES heat storage chamber, H c,τ 、H g,τ 、H st,τ The compression heat release power, the power consumption heat power and the external heat supply power of the AA-CAES device at tau moment are respectively H HSmax 、H Hsmin The upper limit value and the lower limit value of the heat storage capacity of the AA-CAES device are respectively set;
the AA-CAES provides rotational redundancy constraints as:
in the above, R CAES,t At time tAA-CAES can provide rotational redundancy for the system, R CAESc,t 、R CAESg,t The rotation reserve, k, provided for the system when the AA-CAES operates in compression and power generation working conditions at the moment t respectively hg 、k hc Respectively the power coefficients, k of heat exchange power of the AA-CAES device in the power generation and compression process g 、k c The power coefficients of the air pressure change rate of the air storage chamber of the AA-CAES device in the power generation and compression process are respectively shown;
the constraints of the gas turbine participating in the day-ahead dispatch operation comprise a thermoelectric output proportion constraint, a thermoelectric output upper limit and lower limit constraint, a fuel consumption upper limit and lower limit constraint and a climbing constraint;
the constraint that the electric boiler participates in the day-ahead scheduling operation is as follows:
in the above, H eb,t For the heat output power of the electric boiler at the time t, P pv,t,k And P pvh,t,k The total power of the photovoltaic power station k at the moment t and the power for generating heat of the electric boiler are respectively, eta pvh The electric heating conversion efficiency of the electric boiler;
the constraints of the diesel engine participating in the day-ahead scheduling operation comprise an output upper limit constraint, a lower limit constraint, a minimum on-off time constraint and a climbing rate constraint;
the power flow constraint of the AC/DC power distribution network comprises a VSC converter station scheduling operation constraint, a DistFlow-based branch power flow balance constraint and a system security constraint;
the photovoltaic power station participates in the constraint of scheduling operation in the future:
in the above, P pva,t,k For the actual light rejection power of the photovoltaic power station k at the moment t, P pve,t,k The power for satisfying the electric load requirement for the photovoltaic power station k at the moment t;
the constraint that the transferable load participates in the day-ahead scheduling operation is as follows:
in the above-mentioned method, the step of,and->The lower limit and the upper limit of the load transfer quantity on the transferable load node j are respectively +.>Scheduling a state variable for the forward load of the transferable load node j at time t,/for the load node j>Scheduling a state variable for the negative load of the transferable load node j at time t,/>And->A lower limit and an upper limit of a load transfer amount of a transferable load on the transferable load node j, respectively,/->An upper limit of a single-day transfer amount for transferring the load of the load node j;
the thermal energy balance constraint is:
in the above, H load,t The thermal load of the system at time t;
the system standby constraint is:
in the above, P GTmax,i 、P GTmax,s The upper limit value of the output of the gas turbine i and the diesel engine s, P T,t 、P Tmax Respectively supporting power and upper limit value R of upper power grid at t moments L 、R PV The standby power reserved for load and photovoltaic is respectively;
and B, inputting the obtained short-term prediction data of the photovoltaic load, the thermal load and the electric 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 result comprises the starting and stopping states and the operating conditions of the AA-CAES device, the gas turbine and the diesel engine, and a scheduling plan of the AA-CAES device, the gas turbine, the diesel engine, the electric boiler and the transferable load.
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