Park comprehensive energy scheduling method, device, equipment and medium

Abstract

The invention relates to the technical field of energy management, in particular to a park comprehensive energy scheduling method, device and equipment and a medium. According to the method, classification and grading modeling is carried out on electric heating and cooling adjusting resources such as energy storage, air conditioners, ice storage, ground source heat pumps, heat storage type electric boilers and electric vehicle charging piles in the park comprehensive energy system, and grading proportion parameters of the electric heating and cooling adjusting resources in the day-ahead, day-intraday and real-time optimization stages are optimized and adjusted. According to the invention, through modeling analysis and grading utilization of the electric heating and cooling regulation resources of the park integrated energy system, the electric heating and cooling regulation resource classification and grading optimal matching strategy suitable for the day-ahead / intra-day / real-time power market is provided by combining the regulation speeds of different types of resources and the adaptability of the resources to the regulation requirements; and finally, graded utilization and complementary coordinated scheduling of electric heating and cold resources are realized. According to the invention, economy, flexibility and reliability of the park integrated energy system are improved, consumption of new energy is promoted, and safe and stable operation of a power grid is ensured.

Description

Technical Field

[0001] The present disclosure relates to the technical field of energy management, and particularly to a comprehensive energy scheduling method, device, equipment and medium for a park. Background Art

[0002] Although the existing technical methods can focus on the operation optimization of multiple types of adjustable resources in the comprehensive energy system of a park under a single electricity market, or the optimal scheduling of a single type of adjustable resource in the spot market, they cannot effectively study the regulation characteristics and complementary coupling mechanism of different types of electric, heat and cold resources, and there is a lack of a classification and grading optimization scheduling method for multiple types of regulation resources in the comprehensive energy system of a park to promote the consumption of new energy in the spot market. Therefore, there is an urgent need to propose a classification and grading optimization scheduling method for electric, heat and cold regulation resources in the comprehensive energy system of a park based on the evaluation of the regulation ability and classification and grading utilization of electric, heat and cold resources, which is suitable for the optimization of day-ahead, intra-day and real-time markets, so as to achieve more efficient and sustainable energy management, improve the flexibility, reliability and economy of the comprehensive energy system of the park, and promote the consumption of new energy and distributed energy.

[0003] In summary, there is an urgent need for a classification and grading optimization scheduling scheme for electric, heat and cold regulation resources in the comprehensive energy system of a park based on the spot market. Summary of the Invention

[0004] In view of the above problems, the present disclosure provides a comprehensive energy scheduling method, device, equipment and medium for a park.

[0005] In a first aspect, a comprehensive energy scheduling method for a park, the method includes:

[0006] Construct a classification and grading regulation ability model for electric, heat and cold regulation resources participating in the spot market, including: energy storage device model, electric vehicle charging pile model, air conditioner model, ice storage cooling device model, ground source heat pump model and heat storage type electric boiler model;

[0007] Based on the classification and grading regulation ability model, construct a classification and grading optimization scheduling model for electric, heat and cold regulation resources in the comprehensive energy system of the park under the spot market, optimize and solve the proportionality coefficients set for each regulation resource to participate in day-ahead, intra-day and real-time market regulations, and obtain the optimal regulation proportionality coefficients;

[0008] According to the spot market signals, based on the optimal regulation proportionality coefficients, with the goal of minimizing the comprehensive energy consumption cost in each stage, solve the classification and grading optimization scheduling model for electric, heat and cold regulation resources in the comprehensive energy system of the park in the day-ahead, intra-day and real-time stages, output the scheduling plan for classification and grading resources, and schedule the comprehensive energy of the park according to the scheduling plan.

[0009] Further, the classification and grading regulation ability model includes:

[0010] The regulation ability model is classified according to the speed of regulation ability into fast-regulation type regulation resources and slow-regulation type regulation resources.

[0011] Furthermore, the classified and graded regulation ability model also includes:

[0012] The fast-regulation type regulation resources and slow-regulation type regulation resources are graded according to the degree of participation in the spot market, and the shallow, middle or deep regulation ratio coefficients are respectively divided.

[0013] Furthermore, it also includes:

[0014] Set the initial values of the shallow, middle or deep regulation ratio coefficients of various electric, heat and cold regulation resources in the spot market;

[0015] Set the initial value of the deep regulation ratio coefficient of the slow-regulation type resources to 0, and the initial values of the shallow and middle regulation ratio coefficients are both set to 50%;

[0016] Set the initial value of the shallow regulation ratio of the fast-regulation type resources to 40%, and the initial values of the shallow and middle regulation ratio coefficients are both set to 30%.

[0017] Furthermore, the energy storage device model formula and corresponding operation constraints are expressed as follows:

[0018]

[0019] P se,t = P se,c,t - P se,d,t

[0020]

[0021] In the formula, E se,t and E se,t-1 are the remaining energies of the energy storage device at the end of times t and t-1; σ is the self-loss coefficient of the energy storage device; η se,in and η se,d are the charge and discharge efficiencies of the energy storage device; P se,c,t and Pse,d,t are the charge and discharge powers of the energy storage device; are respectively the upper and lower limits of the stored energy of the energy storage device; are respectively the upper limits of the charge and discharge powers of the energy storage device; are respectively the 0 / 1 variables of the charge and discharge states of the energy storage device; the energy storage device can only operate in the charge or discharge mode at the same moment; m is the time scale type parameter of the power market; DAM, IDM, RTM respectively represent the day-ahead market, intraday market, real-time market; and are the electric power adjustment amount and energy adjustment amount of the energy storage device participating in the day-ahead, intraday and real-time market regulations at time t; αse，IDM and α se,IDM and α se,IDM are respectively the set values of the shallow, medium, and deep electric power regulation ratio coefficients for the energy storage device participating in the day-ahead, intraday, and real-time markets; α Ese,DAM and α Ese,IDM and α Ese,IDM are respectively the set values of the shallow, medium, and deep electricity regulation ratio coefficients for the energy storage device participating in the day-ahead, intraday, and real-time markets.

[0022] Furthermore, the model formula and corresponding operation constraints of the electric vehicle charging pile are expressed as follows:

[0023]

[0024] In the formula, is the power of the k-th vehicle at time t; is the power of the i-th vehicle at time t; is the charging and discharging power of the k-th vehicle at time t; are respectively the rated charging and discharging powers of the k-th vehicle at time t; is the 0 / 1 variable of the charging and discharging state of the k-th vehicle at time t; are respectively the charging and discharging efficiencies of the k-th vehicle at time t; S t,k , are respectively the state of charge and rated battery capacity of the k-th vehicle at time t; are respectively the upper and lower limits of the state of charge of the electric vehicle charging pile; are respectively the upper and lower limits of the charging power of the electric vehicle charging pile; are respectively the upper and lower limits of the discharging power of the electric vehicle charging pile; are respectively the 0 / 1 variables of the charging and discharging states of the electric vehicle charging pile; the electric vehicle charging pile can only operate in the charging or discharging mode at the same time; and are the electric power adjustment amount and electricity adjustment amount for the electric vehicle charging pile to participate in the day-ahead, intraday, and real-time market regulations at time t; α EV,DAM and α EV,IDM and α EV,IDM are respectively the set values of the shallow, medium, and deep electric power regulation ratio coefficients for the electric vehicle charging pile to participate in the day-ahead, intraday, and real-time markets; α EEV,DAM and α EEV,IDM and α EEV,IDM are respectively the set values of the shallow, medium, and deep electricity regulation ratio coefficients for the electric vehicle charging pile to participate in the day-ahead, intraday, and real-time markets; m is the time scale type parameter of the power market; DAM, IDM, and RTM respectively represent the day-ahead market, intraday market, and real-time market.

[0025] Furthermore, the air conditioner model is modeled based on the equivalent thermal parameter model, and its formula and corresponding operating constraints are expressed as follows:

[0026]

[0027] In the formula, and are the indoor and outdoor temperatures of the i-th air conditioner at time t; Q, R, and C are the equivalent thermal resistance, equivalent thermal capacitance, and equivalent thermal ratio, respectively; is the working state 0 / 1 value of the i-th air conditioner at time t; P i A 、 are the power consumption and rated cooling performance coefficient of the i-th air conditioner at time t, respectively; P t A are the total cooling power and total power consumption of the air conditioner at time t, respectively; is the cooling power of the i-th air conditioner at time t; is the power consumption of the i-th air conditioner at time t; N A is the number of air conditioners in the park; is the upper limit of the cooling power of the air conditioner; is the upper limit of the power consumption when a single air conditioner is cooling; is the adjustment amount of the cooling power of the air conditioner participating in the day-ahead and intraday market regulation at time t. The air conditioner is a slow-regulation type of regulation resource and does not participate in the real-time market regulation; βC,A,DAM and βC,A,IDM are the setting values of the shallow and middle-layer cooling power regulation ratio coefficients of the air conditioner participating in the day-ahead and intraday markets, respectively; m is the time-scale type parameter of the power market; DAM and IDM represent the day-ahead market and the intraday market, respectively.

[0028] Furthermore, the ice storage equipment model realizes cold storage and refrigeration based on the phase change of water and ice, and its formula and operating constraints are expressed as follows:

[0029]

[0030]

[0031] In the formula, C WC,t is the total cooling power of the dual-mode chiller at time t; C WC，t，i is the ice-making power of the i-th dual-mode chiller at time t; C si，t，i is the ice-making power of the i-th ice storage tank at time t; N WC is the number of ice storage equipment in the park; I WC,t is the total ice-making power of the dual-mode chiller at time t; N c is the number of dual-mode chillers; is the refrigeration power consumption and ice - making power consumption of the j - th dual - mode chiller at time t; is the refrigeration energy efficiency ratio and ice - making energy efficiency ratio of the j - th dual - mode chiller at time t; B si,t and B si,t-1 is the total ice storage amount of the ice storage tank when the dual - mode chiller operates in the ice - making state at the end of time t and t - 1; δ is the self - loss efficiency of the ice storage tank; I WC,t is the total ice - making power of the dual - mode chiller at time t; I RC,t is the ice - melting power of the ice storage tank at time t; η t is the efficiency of the ice - making power of the dual - mode chiller being conducted to the ice storage tank; η si,c 、η si,d are the ice - making and ice - melting efficiencies of the ice storage tank; are the upper and lower limits of the cooling power of the j - th dual - mode chiller; are the upper and lower limits of the ice - supply power of the j - th dual - mode chiller; C si,t is the cooling power of the ice storage tank at time t; η c is the cooling efficiency of the ice storage tank; is the adjustment amount of the cooling power of the ice - storage cold - storage equipment participating in the day - ahead and intra - day market regulation at time t. The ice - storage cold - storage equipment is a slow - adjustment type of regulation resource and does not participate in real - time market regulation; β C,WC,DAM 、β C,WC,IDM are the setting values of the shallow - layer and middle - layer cooling power regulation ratio coefficients of the ice - storage cold - storage equipment participating in the day - ahead and intra - day markets respectively; m is the time - scale type parameter of the power market; DAM and IDM represent the day - ahead market and the intra - day market respectively.

[0032] Furthermore, the ground - source heat pump model uses the formation as the cold and heat source, releasing heat in summer and extracting heat in winter. Its formula and operation constraints are as follows:

[0033] Q hp,t =P hp,t ·cop h ·(1 - Z hp )

[0034] C hp,t =P hp,t ·cop c ·Z hp

[0035]

[0036] In the formula, P hp,t is the input electric power of the ground - source heat pump at time t; C hp,t is the output cooling power of the ground - source heat pump at time t; Q hp,t is the output heating power of the ground - source heat pump at time t; Q hp，t，i is the output heating power of the i - th ground - source heat pump at time t; Chp，t，i is the output cooling power of the i-th ground source heat pump at time t; N hp is the number of ground source heat pumps in the park; copc is the cooling energy efficiency ratio of the ground source heat pump; coph is the heating energy efficiency ratio of the ground source heat pump; Z hp is the cooling and heating state 0 / 1 variable of the ground source heat pump, Z hp = 0 indicates that the ground source heat pump is in the heating state on this typical day, Z hp = 1 indicates that the ground source heat pump is in the cooling state on this typical day; are the upper and lower limits of the output heat power of the ground source heat pump; are the upper and lower limits of the output cooling power of the ground source heat pump; is the adjustment amount of the heating power of the ground source heat pump participating in the day-ahead and intraday market regulations at time t; is the adjustment amount of the cooling power of the ground source heat pump participating in the day-ahead and intraday market regulations at time t; The ground source heat pump is a slow-regulation type of regulation resource and does not participate in real-time market regulation; β Q,hp,DAM , β Q,hp,IDM are the set values of the shallow and middle-layer heating power regulation ratio coefficients of the ground source heat pump participating in the day-ahead and intraday markets respectively; β C,hp,DAM , β C,hp,IDM are the set values of the shallow and middle-layer cooling power regulation ratio coefficients of the ground source heat pump participating in the day-ahead and intraday markets respectively; m is the time-scale type parameter of the power market; DAM and IDM represent the day-ahead market and the intraday market respectively.

[0037] Furthermore, the heat storage type electric boiler model includes: an electric boiler and a heat storage tank, and its formula and operation constraints are expressed as follows:

[0038] Q EB,t = P EB,t ·η eh

[0039]

[0040] Q HS,t = Q HS,c,t - Q HS,d,t

[0041]

[0042] In the formula, P EB,t is the input electric power of the electric boiler at time t; Q EB,t is the output heat power of the electric boiler at time t; Q EB，t，i is the output heat power of the i-th electric boiler at time t; Q HS，t，i is the heat release power of the i-th heat storage water tank at time t; N EB is the number of heat storage type electric boilers in the park; ηeh is the electro-thermal conversion efficiency of the electric boiler; H HS,t and HHS,t-1 is the heat storage capacity value of the heat storage water tank at the end of time t and t-1; μ is the heat dissipation loss rate of the heat storage water tank; η HS,c and η HS,d are the heat absorption and release efficiency of the heat storage water tank; Q HS,c,t and Q HS,d,t are the heat absorption and release power of the heat storage water tank at time t; are the upper and lower limits of the heat storage capacity of the heat storage water tank respectively; are the upper limits of the charging and discharging power of the heat storage water tank respectively; are the 0 / 1 variables of the heat absorption and release states of the heat storage water tank respectively; the heat storage water tank can only operate in the heat absorption or release mode at the same time; is the adjustment amount of the heating power for the heat storage electric boiler to participate in the day-ahead and intra-day market regulation at time t; β Q,EB,DAM 、β Q,EB,IDM are the setting values of the shallow and middle layer heating power regulation ratio coefficients for the heat storage electric boiler to participate in the day-ahead and intra-day markets respectively; m is the time scale type parameter of the power market; DAM and IDM represent the day-ahead market and the intra-day market respectively.

[0043] Furthermore, a classification and hierarchical optimization dispatching model of the electric, heat and cold regulation resources of the park integrated energy system in the spot market is constructed, and the ratio coefficients set for each regulation resource to participate in the day-ahead, intra-day and real-time market regulations are optimized to obtain the optimal regulation ratio coefficients, including:

[0044] The classification and hierarchical optimization dispatching model of the electric, heat and cold regulation resources of the park integrated energy system constructed in the spot market has the objective function of minimizing the comprehensive energy consumption cost of the system, and the constraint conditions include: the power balance constraints of electricity, heat and cold of the park integrated energy system and the operation constraints of various electric, heat and cold regulation resources;

[0045] Set the initial values of the shallow, middle and deep layer regulation ratio coefficients of various electric, heat and cold regulation resources in the spot market, and solve to obtain the optimal regulation ratio coefficients;

[0046] Among them, the power balance constraints of electricity, heat and cold of the park integrated energy system are expressed as follows:

[0047]

[0048] m ∈ {DAM, IDM, RTM}

[0049]

[0050] m ∈ {DAM, IDM}

[0051]

[0052] m ∈ {DAM, IDM}

[0053] α se,0,DAM = α EV,0,DAM = 0.4

[0054] α se,0,IDM = α EV,0,IDM = α se,0,RTM = α EV,0,RTM = 0.3

[0055] β C,A,0,DAM = β C,A,0,IDM = 0.5

[0056] β C,WC,0,DAM = β C,WC,0,IDM = 0.5

[0057] β C,hp,0,DAM = β C,hp,0,IDM = 0.5

[0058] β Q,hp,0,DAM = β Q,hp,0,IDM = 0.5

[0059] β Q,EB,0,DAM = β Q,EB,0,IDM = 0.5

[0060] α se,DAM + α se,IDM + α se,RTM ≤ 1

[0061] α EV,DAM + α EV,IDM + α EV,RTM ≤ 1

[0062] β C,A,DAM + β C,A,IDM ≤ 1

[0063] β C,WC,DAM + β C,WC,IDM ≤ 1

[0064] β C,hp,DAM + β C,hp,IDM ≤ 1

[0065] β Q,hp,DAM + β Q,hp,IDM ≤ 1

[0066] β Q,EB,DAM + β Q,EB,IDM ≤ 1

[0067] where is the electrical, heating, and cooling load of the park at time t; P t PV is the output value of the distributed photovoltaic at time t; P t grid is the power purchase from the superior power grid by the park at time t; is the power of the i-th vehicle at time t; is the power consumption of the i-th air conditioner at time t; is the cooling power consumption of the i-th dual-mode chiller at time t; is the ice-making power consumption of the i-th dual-mode chiller at time t; N WC is the number of ice storage cooling equipment in the park; is the input electric power of the i-th ground source heat pump at time t; is the input electric power of the i-th electric boiler at time t; N A is the number of air conditioners in the park; N HP is the number of ground source heat pumps in the park; N EB is the number of heat storage electric boilers in the park; Q hp，t，i is the output heat power of the i-th ground source heat pump at time t; Q EB，t，i is the output heat power of the i-th electric boiler at time t; Q HS，t，i is the heat release power of the i-th hot water storage tank at time t; C hp，t，i is the output cooling power of the i-th ground source heat pump at time t; N WC is the number of ice storage cooling equipment in the park; C WC，t，i is the ice-making power of the i-th dual-mode chiller at time t; C si，t，i is the ice-making power of the i-th ice storage tank at time t; is the cooling power of the i-th air conditioner at time t; α se,0,DAM 、α se,0,IDM 、α se,0,IDM are the initial setting values of the shallow, middle and deep electric power regulation ratio coefficients of the energy storage device participating in the day-ahead, intra-day and real-time markets respectively. Set the initial electric power regulation ratio coefficient of the energy storage device as α se,0,DAM =0.4, α se,0,IDM =α se,0,RTM =0.3, and add the constraint α se,DAM +α se,IDM +α se,RTM ≤1; α EV,0,DAM 、α EV,0,IDM 、α EV,0,IDM are the initial setting values of the shallow, middle and deep electric power regulation ratio coefficients of the electric vehicle charging pile participating in the day-ahead, intra-day and real-time markets respectively. Set the initial electric power regulation ratio coefficient of the electric vehicle charging pile as α EV，0，IDM =0.4, α EV,0,IDM =α EV,0,RTM =0.3, and add the constraint α EV,DAM +α EV,IDM +α EV,RTM≤1; The cooling and heating energy regulation resources are slow-regulation resources, the deep regulation ratio is set to 0, and air conditioners, ice storage cooling equipment, ground source heat pumps, and heat storage electric boilers do not participate in the regulation of the real-time market; β C,A,0,DAM and β C,A,0,IDM are the initial setting values of the shallow / medium cooling power regulation ratio coefficients for air conditioners participating in the day-ahead and intraday markets respectively. Set the initial regulation ratio coefficient of the cooling power of the air conditioner to β C,A,0,DAM = β C,A,0,IDM = 0.5, and add the constraint β C,A,DAM + β C,A,IDM ≤1; β C,WC,0,DAM and β C,WC,0,IDM are the initial setting values of the shallow and medium cooling power regulation ratio coefficients for ice storage cooling equipment participating in the day-ahead and intraday markets respectively. Set the initial regulation ratio coefficient of the ice storage cooling equipment to β C,WC,0,DAM = β C,WC,0,IDM = 0.5, and add the constraint β C,WC,DAM + β C,WC,IDM ≤1; β C,hp,0,DAM and β C,hp,0,IDM are the initial setting values of the shallow and medium regulation cooling power ratios for ground source heat pumps participating in the day-ahead and intraday markets respectively. Set the initial regulation ratio coefficient of the cooling power of the ground source heat pump to β C,hp,0,DAM = β C,hp,0,IDM = 0.5, and add the constraint β C,hp,DAM + β C,hp,IDM ≤1; β Q,hp,0,DAM and β Q,hp,0,IDM are the initial setting values of the shallow and medium regulation heating power ratios for ground source heat pumps participating in the day-ahead and intraday markets respectively. Set the initial regulation ratio coefficient of the heating power of the ground source heat pump to β Q,hp,0,DAM = β Q,hp,0,IDM = 0.5, and add the constraint β Q,hp,DAM + β Q,hp,IDM ≤1; β Q,EB,0,DAM and β Q,EB,0,IDM are the initial setting values of the shallow and medium regulation ratio coefficients for heat storage electric boilers participating in the day-ahead and intraday markets respectively. Set the initial regulation ratio coefficient of the heating power of the heat storage electric boiler to β Q,EB,0,DAM = β Q,EB,0,IDM = 0.5, and add the constraint β Q,EB,DAM + β Q,EB,IDM ≤1; m is the time-scale type parameter of the power market; DAM, IDM, and RTM represent the day-ahead market, intraday market, and real-time market respectively.

[0068] Furthermore, aiming at minimizing the comprehensive energy consumption cost in each stage, solve the classification and grading optimization scheduling model of the electro-thermal-cooling regulation resources of the campus integrated energy system in the day-ahead, intraday, and real-time stages, including:

[0069] For the classification and grading optimization scheduling model of electro-thermal-cooling regulation resources, in the day-ahead optimization stage, based on the optimal regulation ratio coefficient, with the minimum comprehensive energy consumption cost in the park on the second day as the objective function, the constraint conditions include: the operation constraints of various electro-thermal-cooling regulation resources; the optimal power purchase curve of the power grid on the second day is obtained through solution as the scheduling plan, which is used for the scheduling operation in the day-ahead market.

[0070] Furthermore, with the minimum comprehensive energy consumption cost in each stage as the objective, solving the classification and grading optimization scheduling model of electro-thermal-cooling regulation resources in the day-ahead, intra-day, and real-time stages of the park's integrated energy system also includes:

[0071] For the classification and grading optimization scheduling model of electro-thermal-cooling regulation resources, in the intra-day optimization stage, based on the optimal regulation ratio coefficient, with the minimum overall energy consumption cost within the day as the objective function, the power generation and consumption arrangements in the intra-day optimization stage are corrected based on the cleared day-ahead electricity price. The power generation and consumption arrangements in the intra-day optimization stage include: the intra-day power purchase plan curve and the intra-day energy scheduling plan of each electro-thermal-cooling regulation resource, which are used for the scheduling operation in the intra-day market.

[0072] Furthermore, with the minimum comprehensive energy consumption cost in each stage as the objective, solving the classification and grading optimization scheduling model of electro-thermal-cooling regulation resources in the day-ahead, intra-day, and real-time stages of the park's integrated energy system also includes:

[0073] For the classification and grading optimization scheduling model of electro-thermal-cooling regulation resources, in the real-time optimization stage, based on the optimal regulation ratio coefficient, with the minimum comprehensive energy consumption cost as the objective function, the intra-day power generation and consumption plan is corrected every 15 minutes based on the ultra-short-term prediction of photovoltaic power output, and the power generation and consumption arrangements in the real-time stage are obtained, which are used for the scheduling operation in the real-time stage.

[0074] In the second aspect, a park integrated energy scheduling device includes: an adjustment capacity model construction unit, a scheduling model construction unit, and a scheduling solution unit;

[0075] The adjustment capacity model construction unit is used to construct a classification and grading adjustment capacity model for electro-thermal-cooling regulation resources participating in the spot market, including: a energy storage device model, an air conditioner model, an ice storage cooling device model, a ground source heat pump model, a heat storage type electric boiler model, an electric vehicle charging pile model;

[0076] The scheduling model construction unit is used to construct a classification and grading optimization scheduling model for electro-thermal-cooling regulation resources in the park integrated energy system under the spot market based on the classification and grading adjustment capacity model, optimize and solve the ratio coefficients set for each adjustment resource to participate in the day-ahead, intra-day, and real-time market regulations, and obtain the optimal regulation ratio coefficient;

[0077] A solution scheduling unit is used to solve the classification and grading optimization scheduling model of the electro-thermal-cooling regulation resources of the park integrated energy system in the day-ahead, intraday, and real-time stages based on the spot market signals and the optimal regulation ratio coefficient, with the goal of minimizing the comprehensive energy consumption cost in each stage, output the scheduling plan of the classified and graded resources, and schedule the park integrated energy according to the scheduling plan.

[0078] In a third aspect, an electronic device includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus;

[0079] The memory stores a computer program;

[0080] The processor is used to implement the above-mentioned park integrated energy scheduling method when executing the computer program stored on the memory.

[0081] In a fourth aspect, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned park integrated energy scheduling method is implemented.

[0082] The present disclosure at least includes the following beneficial effects:

[0083] The present disclosure conducts classification and grading modeling of electro-thermal-cooling regulation resources such as energy storage, air conditioners, ice storage cooling, ground source heat pumps, heat storage electric boilers, and electric vehicle charging piles in the park integrated energy system, and optimizes and adjusts the grading ratio parameters of electro-thermal-cooling regulation resources in the day-ahead, intraday, and real-time optimization stages.

[0084] Through the modeling analysis and hierarchical utilization of electro-thermal-cooling regulation resources in the park integrated energy system, and combining the regulation speed of different types of resources and their adaptability to regulation requirements, the present disclosure proposes an optimal matching strategy for classified and graded electro-thermal-cooling regulation resources suitable for the day-ahead / intraday / real-time power market, and finally realizes the hierarchical utilization and complementary coordinated scheduling of electro-thermal-cooling resources. The present disclosure improves the economy, flexibility, and reliability of the park integrated energy system, promotes the consumption of new energy, and ensures the safe and stable operation of the power grid.

[0085] Other features and advantages of the present disclosure will be described in the following specification, and some will be obvious from the specification or understood by implementing the present disclosure. The objectives and other advantages of the present disclosure can be achieved and obtained through the structures pointed out in the specification and the drawings. Description of the Drawings

[0086] To more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0087] Figure 1 Schematic flowchart of the scheduling method according to the embodiment of the present disclosure;

[0088] Figure 2 Schematic structural diagram of the electronic device according to the embodiment of the present disclosure. Detailed implementation manners

[0089] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present disclosure with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present disclosure without creative efforts fall within the scope of protection of the present disclosure.

[0090] As Figure 1 shown, a comprehensive energy scheduling method for a park, the method includes:

[0091] Construct a classification and grading regulation capacity model for electro-thermal-cooling regulation resources participating in the spot market, including: energy storage device model, electric vehicle charging pile model, air conditioner model, ice storage cooling device model, ground source heat pump model, and heat storage electric boiler model;

[0092] Based on the classification and grading regulation capacity model, construct a classification and grading optimization scheduling model for electro-thermal-cooling regulation resources in the park's comprehensive energy system under the spot market, optimize and solve the proportionality coefficients set for each regulation resource to participate in the day-ahead, intraday, and real-time market regulations, and obtain the optimal regulation proportionality coefficients;

[0093] According to the spot market signals, based on the optimal regulation proportionality coefficients, with the goal of minimizing the comprehensive energy consumption cost in each stage, solve the classification and grading optimization scheduling model for electro-thermal-cooling regulation resources in the park's comprehensive energy system in the day-ahead, intraday, and real-time stages, output the scheduling plans for the classification and grading resources, and schedule the park's comprehensive energy according to the scheduling plans.

[0094] During specific implementation, the introduction is as follows:

[0095] Step 1: Construct a classification and grading regulation capacity model for electro-thermal-cooling regulation resources such as energy storage, air conditioner, ice storage cooling, ground source heat pump, heat storage electric boiler, and electric vehicle charging pile participating in the spot market.

[0096] Step 2: Construct a classification and grading optimization scheduling model for the electric, heating and cooling regulation resources of the park's integrated energy system under the spot market, optimize and solve the proportional coefficients of each regulation resource participating in the day-ahead, intraday and real-time market regulation settings, and obtain the optimal regulation proportional coefficient.

[0097] Step 3: Based on the spot market signals, solve the classification and grading optimization scheduling model of the electric, heating and cooling regulation resources of the park's comprehensive energy system in the day-ahead, intraday and real-time stages. With the goal of minimizing the comprehensive energy cost in each stage, determine the power generation and consumption plan of the classified and graded resources to achieve low-error response.

[0098] In step 1, the classification of electric, heating and cooling regulation resources specifically refers to dividing the above electric, heating and cooling regulation resources into two categories according to the speed of regulation capacity: fast regulation type and slow regulation type regulation resources. Considering that there is a delay in the dispatch of heat and cold energy and the dispatch cycle is relatively long, the electric energy regulation resources such as energy storage and electric vehicle charging piles are classified as fast regulation type regulation resources, while the heat and cold energy regulation resources such as air conditioners, ice storage, ground source heat pumps, and thermal storage electric boilers are classified as slow regulation type regulation resources; the classification of electric, heating and cooling regulation resources refers to further classifying the fast / slow regulation type regulation resources into three levels: shallow / medium / deep according to the degree of participation in the spot market. Specifically, the part of the regulation resources participating in the day-ahead market dispatch can be classified as shallow, which is mainly used to balance the medium- and long-term supply and demand of the power system; the part of the regulation resources participating in the intraday market dispatch can be classified as medium, which is mainly used to cope with short-term supply and demand fluctuations; the part of the regulation resources participating in the real-time market dispatch can be classified as deep, which requires it to have higher flexibility and response speed to cope with instantaneous supply and demand changes.

[0099] In step 1, the initial values ​​of the shallow / medium / deep adjustment ratios of various types of electric heating and cooling adjustment resources in the spot market are set, and then this ratio is optimized and adjusted in step 2. Among them, the slow-adjusting resources cannot achieve minute-level demand response, and the initial value of the deep adjustment ratio of the slow-adjusting resources is set to 0, and the initial values ​​of the shallow and medium adjustment ratios are both set to 50%; the fast-adjusting resources are more involved in the scheduling of the real-time market, so the initial value of the shallow adjustment ratio of the fast-adjusting resources is set to 40%, and the initial values ​​of the shallow and medium adjustment ratios are both set to 30%.

[0100] The basic models and operating constraints of electric heating and cooling regulation resources such as energy storage, air conditioning, ice storage, ground source heat pumps, thermal storage electric boilers, and electric vehicle charging piles are as follows:

[0101] The basic model and operating constraints of energy storage equipment are:

[0102]

[0103] P se,t =P se,c,t -P se,d,t

[0104]

[0105] In the formula, E se,t and E se,t-1 are the remaining energies of the energy storage device at the end of times t and t - 1; σ is the self - loss coefficient of the energy storage device; η se,in and η se,d are the charge - discharge efficiencies of the energy storage device; P se,c,t and P se,d,t are the charge - discharge powers of the energy storage device; are the upper and lower limits of the energy storage capacity of the energy storage device respectively; are the upper limits of the charge - discharge powers of the energy storage device respectively; are the charge - discharge state 0 / 1 variables of the energy storage device respectively; the energy storage device can only operate in the charging or discharging mode at the same time; m is the time - scale type parameter of the power market; DAM, IDM, and RTM respectively refer to the day - ahead market, intraday market, and real - time market; and are the electric - power adjustment amount and energy adjustment amount of the energy storage device participating in the day - ahead / intraday / real - time market regulation at time t; α se,DAM , α se,IDM , α se,IDM are the set values of the shallow / medium / deep electric - power regulation ratios of the energy storage device participating in the day - ahead / intraday / real - time market respectively; α Ese,DAM , α Ese,IDM , α Ese,IDM are the set values of the shallow / medium / deep energy regulation ratios of the energy storage device participating in the day - ahead / intraday / real - time market respectively.

[0106] The basic model and operation constraints of the electric - vehicle charging pile are as follows:

[0107]

[0108]

[0109] In the formula, is the power of the k - th vehicle at time t; is the power of the i - th vehicle at time t; is the charge - discharge power of the k - th vehicle at time t; are the rated charge - discharge powers of the k - th vehicle at time t respectively; is the charge - discharge state 0 / 1 variable of the k - th vehicle at time t; are the charge - discharge efficiencies of the k - th vehicle at time t respectively; S t,k , are the state of charge and rated energy value of the k - th vehicle at time t respectively; are the upper and lower limits of the charge of the electric - vehicle charging pile respectively; are the upper and lower limits of the charging power of the electric vehicle charging pile, respectively; are the upper and lower limits of the discharging power of the electric vehicle charging pile, respectively; are the charge / discharge state 0 / 1 variables of the electric vehicle charging pile, respectively; the electric vehicle charging pile can only operate in the charging or discharging mode at the same moment; and are the electric power adjustment amount and the electricity adjustment amount for the electric vehicle charging pile to participate in the day-ahead / intraday / real-time market regulation at time t; α EV,DAM 、α EV,IDM 、α EV,IDM are the setting values of the shallow / medium / deep electric power regulation ratios for the electric vehicle charging pile to participate in the day-ahead / intraday / real-time market, respectively; α EEV,DAM 、α EEV,IDM 、α EEV,IDM are the setting values of the shallow / medium / deep electricity regulation ratios for the electric vehicle charging pile to participate in the day-ahead / intraday / real-time market, respectively; m is the time scale type parameter of the power market; DAM, IDM, and RTM represent the day-ahead market, intraday market, and real-time market, respectively.

[0110] The mathematical model of the air conditioner is modeled based on the equivalent thermal parameter model, and its specific formula and operation constraints are as follows:

[0111]

[0112] In the formula, and are the indoor and outdoor temperatures of the i-th air conditioner at time t; Q, R, and C are the equivalent thermal resistance, equivalent thermal capacitance, and equivalent thermal ratio, respectively; is the 0 / 1 value of the working state of the i-th air conditioner at time t; P i A 、 are the power consumption of the i-th air conditioner and the rated cooling performance coefficient at time t, respectively; P t A are the total cooling power and total power consumption of the air conditioner at time t, respectively; is the cooling power of the i-th air conditioner at time t; is the power consumption of the i-th air conditioner at time t; N A is the number of air conditioners in the park; is the upper limit of the cooling power of the air conditioner; is the upper limit of the power consumption when a single air conditioner is cooling; is the adjustment amount of the cooling power for the air conditioner to participate in the day-ahead / intraday market regulation at time t. Since the air conditioner is a slow-regulation type of regulation resource, it does not participate in the real-time market regulation; β C,A,DAM 、β C,A,IDMThey are the set values of the shallow / medium refrigeration power adjustment ratios for the air conditioner to participate in the day-ahead / intraday market; m is the time scale type parameter of the power market; DAM and IDM represent the day-ahead market and the intraday market respectively.

[0113] The ice storage equipment uses the phase change of water and ice to achieve cold storage and refrigeration. The specific formulas and operation constraints of its model are as follows:

[0114]

[0115] In the formula, C WC,t is the total refrigeration power of the dual-mode chiller at time t; C WC，t，i is the ice-making power of the i-th dual-mode chiller at time t; C si，t，i is the ice-making power of the i-th ice storage tank at time t; N WC is the number of ice storage equipment in the park; I WC,t is the total ice-making power of the dual-mode chiller at time t; N c is the number of dual-mode chillers; is the refrigeration power consumption and ice-making power consumption of the j-th dual-mode chiller at time t; is the refrigeration energy efficiency coefficient and ice-making energy efficiency coefficient of the j-th dual-mode chiller at time t; B si,t and B si,t-1 are the total ice storage amounts of the ice storage tanks when the dual-mode chiller is operating in the ice-making state at the end of time t and t-1; δ is the self-loss efficiency of the ice storage tank; I WC,t is the total ice-making power of the dual-mode chiller at time t; I RC,t is the ice melting power of the ice storage tank at time t; η t is the efficiency of the ice-making power of the dual-mode chiller being conducted to the ice storage tank; η si,c and η si,d are the ice-making and ice-melting efficiencies of the ice storage tank; are the upper and lower limits of the cooling power of the j-th dual-mode chiller; are the upper and lower limits of the ice supply power of the j-th dual-mode chiller; C si,t is the refrigeration power of the ice storage tank at time t; η c is the refrigeration efficiency of the ice storage tank; is the adjustment amount of the refrigeration power for the ice storage equipment to participate in the day-ahead / intraday market regulation. Since the ice storage equipment is a slow-adjustment type of regulation resource, it does not participate in the real-time market regulation; β C,WC,DAM and β C,WC,IDM are the set values of the shallow / medium refrigeration power adjustment ratios for the ice storage equipment to participate in the day-ahead / intraday market; m is the time scale type parameter of the power market; DAM and IDM represent the day-ahead market and the intraday market respectively.

[0116] The ground source heat pump uses the stratum as the cold and heat source, releasing heat in summer and extracting heat in winter. The specific formulas and operation constraints are as follows:

[0117] Q hp,t = P hp,t ·cop h ·(1 - Z hp )

[0118] C hp,t = P hp,t ·cop c ·Z hp

[0119]

[0120]

[0121] In the formula, P hp,t is the input electric power of the ground source heat pump at time t; C hp,t is the output cooling power of the ground source heat pump at time t; Q hp,t is the output heating power of the ground source heat pump at time t; Q hp，t，i is the output heating power of the i-th ground source heat pump at time t; C hp，t，i is the output cooling power of the i-th ground source heat pump at time t; N hp is the number of ground source heat pumps in the park; cop c is the cooling energy efficiency ratio of the ground source heat pump; cop h is the heating energy efficiency ratio of the ground source heat pump; Z hp is the cooling / heating state 0 / 1 variable of the ground source heat pump. Z hp = 0 indicates that the ground source heat pump is in the heating state on this typical day, and Z hp = 1 indicates that the ground source heat pump is in the cooling state on this typical day; are the upper and lower limits of the output heating power of the ground source heat pump; are the upper and lower limits of the output cooling power of the ground source heat pump; is the adjustment amount of the heating power for the ground source heat pump to participate in the day-ahead / intraday market regulation at time t; is the adjustment amount of the cooling power for the ground source heat pump to participate in the day-ahead / intraday market regulation at time t. The ground source heat pump is a slow-regulation type of regulation resource and does not participate in real-time market regulation; β Q,hp,DAM , β Q,hp,IDM are the set values of the shallow / medium heating power regulation ratios for the ground source heat pump to participate in the day-ahead / intraday market respectively; β C,hp,DAM , β C,hp,IDM are the set values of the shallow / medium cooling power regulation ratios for the ground source heat pump to participate in the day-ahead / intraday market respectively; m is the time-scale type parameter of the power market; DAM and IDM represent the day-ahead market and the intraday market respectively.

[0122] The heat storage electric boiler is divided into two components: an electric boiler and a heat storage tank. The specific formulas and operation constraints are as follows:

[0123] Q EB,t = P EB,t · η eh

[0124]

[0125] Q HS,t = Q HS,c,t -Q HS,d,t

[0126]

[0127] Wherein, P EB,t is the input electric power of the electric boiler at time t; Q EB,t is the heat power output by the electric boiler at time t; Q EB，t，i is the heat power output by the i-th electric boiler at time t; Q HS，t，i is the heat release power of the i-th hot water storage tank at time t; N EB is the number of heat storage electric boilers in the park; η eh is the electro-thermal conversion efficiency of the electric boiler; H HS,t and H HS,t-1 are the heat storage capacity values of the hot water storage tank at the end of times t and t-1; μ is the heat dissipation loss rate of the hot water storage tank; η HS,c and η HS,d are the heat absorption and release efficiencies of the hot water storage tank; Q HS,c,t and Q HS,d,t are the heat absorption and release powers of the hot water storage tank at time t; are respectively the upper and lower limits of the heat storage of the hot water storage tank; are respectively the upper limits of the charging and discharging powers of the hot water storage tank; are respectively the heat absorption and release state 0 / 1 variables of the hot water storage tank; the hot water storage tank can only operate in the heat absorption or heat release mode at the same time; is the adjustment amount of the heating power for the heat storage electric boiler to participate in the day-ahead / intraday market regulation at time t; β Q,EB,DAM , β Q,EB,IDM are respectively the setting values of the shallow / medium heating power adjustment ratios for the heat storage electric boiler to participate in the day-ahead / intraday market; m is the time scale type parameter of the power market; DAM and IDM respectively represent the day-ahead market and the intraday market.

[0128] In Step 2, the objective function of the classification and grading optimization dispatching model for the electric, heat, and cooling regulation resources in the park integrated energy system under the spot market is to minimize the comprehensive energy consumption cost of the system. The constraint conditions include the power balance constraints of electricity, heat, and cooling in the park integrated energy system and the operation constraints of various electric, heat, and cooling regulation resources, etc. The initial values of the adjustment amounts of the electric, heat, and cooling powers of the electric, heat, and cooling regulation resources participating in the day-ahead / intra-day / real-time market conform to the settings in Step 1 and are gradually optimized and approximated in specific scenarios. The optimal regulation coefficients are obtained through model solution.

[0129] Among them, the specific formulas for the power balance constraints of electricity, heat, and cooling in the park integrated energy system are:

[0130]

[0131] m ∈ {DAM, IDM, RTM}

[0132]

[0133] m ∈ {DAM, IDM}

[0134]

[0135] m ∈ {DAM, IDM}

[0136] α se,0,DAM = α EV,0,DAM = 0.4

[0137] α se,0,IDM = α EV,0,IDM = α se,0,RTM = α EV,0,RTM = 0.3

[0138] β C,A,0,DAM = β C,A,0,IDM = 0.5

[0139] β C,WC,0,DAM = β C,WC,0,IDM = 0.5

[0140] β C,hp,0,DAM = β C,hp,0,IDM = 0.5

[0141] β Q,hp,0,DAM = β Q,hp,0,IDM = 0.5

[0142] β Q,EB,0,DAM = β Q,EB,0,IDM = 0.5

[0143] α se,DAM + α se,IDM + α se,RTM ≤ 1

[0144] αEV,DAM +α EV,IDM +α EV,RTM ≤1

[0145] β C,A,DAM +β C,A,IDM ≤1

[0146] β C,WC,DAM +β C,WC,IDM ≤1

[0147] β C,hp,DAM +β C,hp,IDM ≤1

[0148] β Q,hp,DAM +β Q,hp,IDM ≤1

[0149] β Q,EB,DAM +β Q,EB,IDM ≤1

[0150] wherein, is the electrical, heating, and cooling load of the park at time t; P t PV is the output value of the distributed photovoltaic at time t; P t grid is the power purchase from the superior power grid by the park at time t; is the power of the i-th vehicle at time t; is the power consumption of the i-th air conditioner at time t; is the cooling power consumption of the i-th dual-condition host at time t; is the ice-making power consumption of the i-th dual-condition host at time t; N WC is the number of ice storage cooling equipment in the park; is the input electrical power of the i-th ground source heat pump at time t; is the input electrical power of the i-th electric boiler at time t; N A is the number of air conditioners in the park; N HP is the number of ground source heat pumps in the park; N EB is the number of heat storage electric boilers in the park; Q hp,t，i is the output heat power of the i-th ground source heat pump at time t; Q EB，t，i is the output heat power of the i-th electric boiler at time t; Q HS，t，i is the heat release power of the i-th hot water storage tank at time t; C hp，t，i is the output cooling power of the i-th ground source heat pump at time t; N WC is the number of ice storage cooling equipment in the park; C WC，t，i is the ice-making power of the i-th dual-condition host at time t; C si，t,i is the ice-making power of the i-th ice storage tank at time t; is the cooling power of the i-th air conditioner at time t; αse,0,DAM and α se,0,IDM and α se,0,IDM are the initial setting values of the shallow / medium / deep electric power regulation ratios for the energy storage device participating in the day-ahead / intraday / real-time market, respectively. Set the initial electric power regulation ratio of the energy storage device to α se,0,DAM = 0.4, α se,0,IDM = α se,0,RTM = 0.3, and in order to ensure that the sum of the electric power adjustment amounts of the energy storage devices participating in the day-ahead, intraday, and real-time markets is less than the actual maximum adjustable electric power, it is necessary to add the constraint α se,DAM + α se,IDM + α se,RTM ≤ 1; α EV,0,DAM and α EV,0,IDM and α EV,0,IDM are the initial setting values of the shallow / medium / deep electric power regulation ratios for the electric vehicle charging pile participating in the day-ahead / intraday / real-time market, respectively. Set the initial electric power regulation ratio of the electric vehicle charging pile to α EV,0,DAM = 0.4, α EV,0,IDM = α EV,0,RTM = 0.3. In order to ensure that the sum of the electric power adjustment amounts of the electric vehicle charging piles participating in the day-ahead, intraday, and real-time markets is less than the actual maximum adjustable electric power, it is necessary to add the constraint α EV,DAM + α EV,IDM + α EV,RTM ≤ 1; Since the cold and heat energy regulation resources are slow-regulation resources, the deep regulation ratio is set to 0. Therefore, air conditioners, ice storage equipment, ground-source heat pumps, and heat storage electric boilers do not participate in the real-time market regulation; β C,A,0,DAM and β C,A,0,IDM are the initial setting values of the shallow / medium refrigeration power regulation ratios for the air conditioner participating in the day-ahead / intraday market, respectively. Set the initial refrigeration power regulation ratio of the air conditioner to β C,A,0,DAM = β C,A,0,IDM = 0.5. In order to ensure that the sum of the refrigeration power adjustment amounts of the air conditioners participating in the day-ahead and intraday markets is less than the actual maximum adjustable refrigeration power, it is necessary to add the constraint β C,A,DAM + β C,A,IDM ≤ 1; β C,WC,0,DAM and β C,WC,0,IDM are the initial setting values of the shallow / medium refrigeration power regulation ratios for the ice storage equipment participating in the day-ahead / intraday market, respectively. Set the initial regulation ratio of the ice storage equipment to β C,WC,0,DAM = β C,WC,0,IDM = 0.5. In order to ensure that the sum of the refrigeration power adjustment amounts of the ice storage equipment participating in the day-ahead and intraday markets is less than the actual maximum adjustable refrigeration power, it is necessary to add the constraint β C,WC,DAM + β C,WC,IDM ≤ 1; β C,hp,0,DAM and β C,hp,0,IDMThey are the initial set values of the shallow / medium regulation cooling power ratios of the ground source heat pump participating in the day-ahead / intraday market respectively. Set the initial cooling power regulation ratio of the ground source heat pump as β C,hp,0,DAM = β C,hp,0,IDM = 0.5. To ensure that the sum of the adjusted cooling power of the ground source heat pump participating in the day-ahead and intraday markets is less than the actual maximum adjustable cooling power, it is necessary to add the constraint β C,hp,DAM + β C,hp,IDM ≤ 1; β Q,hp,0,DAM and β Q,hp,0,IDM They are the initial set values of the shallow / medium regulation heating power ratios of the ground source heat pump participating in the day-ahead / intraday market respectively. Set the initial heating power regulation ratio of the ground source heat pump as β Q,hp,0,DAM = β Q,hp,0,IDM = 0.5. To ensure that the sum of the adjusted heating power of the ground source heat pump participating in the day-ahead and intraday markets is less than the actual maximum adjustable heating power, it is necessary to add the constraint β Q,hp,DAM + β Q,hp,IDM ≤ 1; β Q,EB,0,DAM and β Q,EB,0,IDM They are the initial set values of the shallow / medium regulation ratios of the heat storage electric boiler participating in the day-ahead / intraday market respectively. Set the initial heating power regulation ratio of the heat storage electric boiler as β Q,EB,0,DAM = β Q,EB,0,IDM = 0.5. To ensure that the sum of the adjusted heating power of the heat storage electric boiler participating in the day-ahead and intraday markets is less than the actual maximum adjustable heating power, it is necessary to add the constraint β Q,EB,DAM + β Q,EB,IDM ≤ 1; m is the time scale type parameter of the power market; DAM, IDM, and RTM represent the day-ahead market, intraday market, and real-time market respectively.

[0151] It should be noted that in step 3, in the day-ahead optimization stage, the integrated energy system electro-thermal-cooling regulation resource classification and grading optimization scheduling model in the park takes the minimum comprehensive energy consumption cost of the park on the second day as the objective function, and takes into account the operation constraints and operation economic costs of the electro-thermal-cooling regulation resources. The optimal power purchase curve of the power grid calculated by the day-ahead optimization model on the second day can be used for the electricity declaration in the day-ahead market. Since the response speed requirement for the regulation resources in the day-ahead optimization stage is not high, only the electricity balance needs to be achieved, and all electro-thermal-cooling resources can participate in the regulation in the day-ahead optimization stage, and the regulation coefficient is set as γ DAM , γ ∈ {α, β}, where α refers to fast-regulation type resources such as energy storage and electric vehicle charging piles, and β refers to slow-regulation type resources such as air conditioners, ice storage, ground source heat pumps, and heat storage electric boilers. These regulation coefficients are decision variables in the day-ahead optimization model, and the regulation plans of the day-ahead electro-thermal-cooling regulation resources and the optimal power purchase curve of the power grid on the second day are obtained by solving the day-ahead optimization model.

[0152] In the intraday optimization stage, the classification and grading optimization scheduling model of the electro-thermal-cooling regulation resources in the park integrated energy system aims to minimize the overall intraday energy consumption cost. Based on the cleared day-ahead electricity price, the power generation and consumption arrangements in the intraday optimization stage are obtained, including the intraday power purchase plan curve and the intraday energy regulation plans of various electro-thermal-cooling resources. The intraday optimization model involves the power balance of electricity, heat, and cooling. The electro-thermal-cooling resources can still participate in the regulation in the intraday optimization stage, and the regulation coefficient is set as γ IDM , where γ ∈ {α, β}. The optimal regulation plan of the intraday electro-thermal-cooling regulation resources and the intraday 24-hour power plan curve are obtained by solving the intraday optimization model.

[0153] In the real-time optimization stage, the classification and grading optimization scheduling model of the electro-thermal-cooling regulation resources in the park integrated energy system aims to minimize the comprehensive energy consumption cost. Based on the ultra-short-term prediction of the photovoltaic power output, the intraday power generation and consumption plan are corrected every 15 minutes to achieve the coordination of the global optimization in the intraday stage and the local optimization in the real-time stage. Since the real-time optimization model has a 15-minute cycle and requires a high regulation speed for the regulation resources, only the fast-regulation type electric energy regulation resources participate in the regulation, and the regulation coefficient is set as α RTM , and the optimal regulation plan of the real-time electro-thermal-cooling regulation resources is obtained by solving the real-time optimization model, updating the power generation and consumption plan and the real-time market electricity price of the park integrated energy system to minimize the energy consumption cost.

[0154] A park integrated energy scheduling device includes: a regulation capacity model construction unit, a scheduling model construction unit, and a scheduling solution unit;

[0155] The regulation capacity model construction unit is used to construct a classification and grading regulation capacity model for electro-thermal-cooling regulation resources participating in the spot market, including: a energy storage device model, an air conditioner model, an ice storage cooling device model, a ground source heat pump model, a heat storage type electric boiler model, an electric vehicle charging pile model;

[0156] The scheduling model construction unit is used to construct a classification and grading optimization scheduling model of electro-thermal-cooling regulation resources in the park integrated energy system under the spot market based on the classification and grading regulation capacity model, optimize and solve the proportionality coefficients set for each regulation resource to participate in the day-ahead, intraday, and real-time market regulations, and obtain the optimal regulation proportionality coefficients;

[0157] The scheduling solution unit is used to solve the classification and grading optimization scheduling model of electro-thermal-cooling regulation resources in the park integrated energy system in the day-ahead, intraday, and real-time stages based on the optimal regulation proportionality coefficients with the goal of minimizing the comprehensive energy consumption cost in each stage according to the spot market signals, output the scheduling plans of the classification and grading resources, and schedule the park integrated energy according to the scheduling plans.

[0158] As Figure 2As shown, the present disclosure provides an electronic device, including a processor 201, a communication interface 202, a memory 203, and a communication bus 204. Among them, the processor 201, the communication interface 202, and the memory 203 complete communication with each other through the communication bus 204;

[0159] The memory 203 stores a computer program;

[0160] The processor 201 is configured to implement the above method when executing the computer program stored on the memory 203.

[0161] The present disclosure provides a computer-readable storage medium storing a computer program, and the computer program, when executed by a processor, implements the above method.

[0162] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist alone without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to the embodiments of the present disclosure is implemented.

[0163] According to the embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or device.

[0164] Although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A park comprehensive energy scheduling method, characterized in that: The method comprises: Construct a classification and grading regulation capacity model for electric heating and cooling regulation resources participating in the spot market, including: energy storage equipment model, electric vehicle charging pile model, air conditioning model, ice storage equipment model, ground source heat pump model and thermal storage electric boiler model; Based on the classification and grading regulation capability model, a classification and grading optimization scheduling model for the electric, heating and cooling regulation resources of the park's comprehensive energy system under the spot market is constructed, and the proportion coefficients of each regulation resource participating in the day-ahead, intraday and real-time market regulation settings are optimized and solved to obtain the optimal regulation proportion coefficient; According to the spot market signals, based on the optimal regulation ratio coefficient, with the goal of minimizing the comprehensive energy cost in each stage, the classification and grading optimization scheduling model of the electric, heating and cooling regulation resources of the park's comprehensive energy system in the day-ahead, intraday and real-time stages is solved, the scheduling plan of the classified and graded resources is output, and the park's comprehensive energy is scheduled according to the scheduling plan.

2. A park comprehensive energy scheduling method according to claim 1, characterized in that: Classification and grading regulation capability model, including: The regulatory capacity model is classified according to the speed of the regulatory capacity, into fast-adjusting regulatory resources and slow-adjusting regulatory resources.

3. A park comprehensive energy scheduling method according to claim 2, characterized in that: The classification and grading regulation capability model also includes: Fast-adjusting regulatory resources and slow-adjusting regulatory resources are graded according to the degree of participation in the spot market, and are divided into shallow, medium or deep regulation ratio coefficients respectively.

4. A park comprehensive energy scheduling method according to claim 3, characterized in that: Also includes: Set the initial value of the shallow, medium or deep adjustment ratio coefficient of various types of electric heating and cooling adjustment resources in the spot market; The initial value of the deep adjustment ratio coefficient of slow-adjusting resources is set to 0, and the initial values ​​of the shallow and middle adjustment ratio coefficients are both set to 50%; The initial value of the shallow adjustment ratio for fast-adjustment resources is set to 40%, and the initial values ​​of the shallow and middle adjustment ratio coefficients are both set to 30%.

5. A park comprehensive energy scheduling method according to claim 1, characterized in that: The energy storage equipment model formula and corresponding operation constraints are expressed as follows: In the formula, E se,t and E se,t-1 is the residual energy of the energy storage device at the end of time t and t-1; σ is the self-loss coefficient of the energy storage device; η se,in and η se,d is the charging and discharging efficiency of the energy storage device; P se,c,t and P se,d,t is the charging and discharging power of the energy storage device; They are the upper and lower limits of the energy storage capacity of the energy storage device respectively; are the upper limits of charge and discharge power of energy storage equipment; f t c 、f t d are 0 / 1 variables for the charging and discharging states of the energy storage device; the energy storage device can only operate in the charging or discharging mode at the same time; m is the time scale type parameter of the power market; DAM, IDM, and RTM represent the day-ahead market, intraday market, and real-time market, respectively; and The power adjustment and quantity adjustment of energy storage equipment participating in the day-ahead, intraday and real-time market regulation at time t; α se,DAM , α se,IDM , α se,IDM They are respectively the setting values ​​of the shallow, medium and deep electric power regulation ratio coefficients of energy storage equipment participating in the day-ahead, intraday and real-time markets; α Ese,DAM , α Ese,IDM , α Ese,IDM These are respectively setting values ​​for the shallow, medium and deep power regulation ratio coefficients of energy storage equipment participating in the day-ahead, intraday and real-time markets.

6. A park comprehensive energy scheduling method according to claim 1, characterized in that: The electric vehicle charging pile model formula and corresponding operation constraints are expressed as follows: In the formula, is the power of the kth car at time t; is the power of the i-th car at time t; is the charging and discharging power of the kth car at time t; are the rated charge and discharge power of the kth car at time t; is a 0 / 1 variable representing the charging and discharging status of the kth car at time t; are the charging and discharging efficiencies of the kth car at time t; S t,k , are the state of charge and rated power value of the kth car at time t respectively; They are the upper and lower limits of the charge of the electric vehicle charging pile; They are the upper and lower limits of the charging power of the electric vehicle charging pile; They are the upper and lower limits of the discharge power of the electric vehicle charging pile respectively; the electric vehicle charging pile can only operate in the charging or discharging mode at the same time; and is the electric power adjustment and quantity adjustment of the electric vehicle charging pile participating in the day-ahead, intraday and real-time market regulation at time t; α EV,DAM , α EV,IDM , α EV,IDM They are the setting values ​​of the shallow, medium and deep electric power regulation ratio coefficients for electric vehicle charging piles participating in the day-ahead, intraday and real-time markets respectively; α EEV,DAM , α EEV,IDM , α EEV,IDM are the setting values ​​of the shallow, medium and deep power regulation ratio coefficients for electric vehicle charging piles participating in the day-ahead, intraday and real-time markets respectively; m is the time scale type parameter of the electricity market; DAM, IDM and RTM represent the day-ahead market, intraday market and real-time market respectively.

7. A park comprehensive energy scheduling method according to claim 1, characterized in that: The air conditioning model is based on the equivalent thermal parameter model, and its formula and corresponding operation constraints are expressed as follows: In the formula, and is the indoor and outdoor temperature of the i-th air conditioner at time t; Q, R, and C are the equivalent thermal resistance, equivalent thermal capacitance, and equivalent thermal ratio, respectively; is the working state 0 / 1 value of the i-th air conditioner at time t; P i A , are the power consumption and rated refrigeration performance coefficient of the i-th air conditioner at time t respectively; P t A are the total cooling power and total power consumption of the air conditioner at time t respectively; is the cooling power of the i-th air conditioner at time t; is the power consumption of the i-th air conditioner at time t; N A is the number of air conditioners in the park; The upper limit of the cooling power of the air conditioner; The upper limit of power consumption of a single air conditioner during cooling; is the cooling power adjustment of the air conditioner participating in the day-ahead and intraday market regulation at time t; C,A,DAM , β C,A,IDM are the setting values ​​of the shallow and middle cooling power adjustment ratio coefficients for air conditioners participating in the day-ahead and intraday markets respectively; m is the time scale type parameter of the electricity market; DAM and IDM represent the day-ahead market and intraday market respectively.

8. A park comprehensive energy scheduling method according to claim 1, characterized in that: The ice storage equipment model realizes cold storage and refrigeration based on the phase change of water and ice. Its formula and operation constraints are expressed as follows: In the formula, C WC,t is the total cooling power of the dual-mode host at time t; C WC，t，i is the ice-making power of the i-th dual-mode host at time t; C si，t，i is the ice-making power of the i-th ice storage tank at time t; N WC is the number of ice storage equipment in the park; I WC,t is the total ice-making power of the dual-operating host at time t; N c is the number of dual-mode hosts; is the cooling power consumption and ice-making power consumption of the j-th dual-mode host at time t; B is the refrigeration energy efficiency coefficient and ice-making energy efficiency coefficient of the j-th dual-mode host at time t; si,t and B si,t-1 is the total ice storage capacity of the ice storage tank when the dual-mode host is running in the ice-making state at the end of time t and t-1; δ is the self-consumption efficiency of the ice storage tank; I RC,t is the ice melting power of the ice storage tank at time t; η t The efficiency of the dual-operating main ice machine power being transferred to the ice storage tank; η si,c , η si,d The ice making and melting efficiency of the ice storage tank; are the upper and lower limits of the cooling power of the jth dual-mode host; C is the upper and lower limits of ice supply power of the jth dual-operating host; si,t is the cooling power of the ice storage tank at time t; η c is the refrigeration efficiency of the ice storage tank; is the cooling power adjustment of the ice storage equipment participating in the day-ahead and intraday market regulation at time t; C,WC,DAM , β C,WC,IDM are the setting values ​​of the shallow and middle cooling power adjustment proportional coefficients of ice storage equipment participating in the day-ahead and intraday markets respectively; m is the time scale type parameter of the power market; DAM and IDM represent the day-ahead market and intraday market respectively.

9. A park comprehensive energy scheduling method according to claim 1, characterized in that: The ground source heat pump model uses the ground as the cold and heat source, releasing heat in summer and taking heat in winter. Its formula and operation constraints are expressed as follows: Q hp,t =P hp,t ·head h ·(1-Z hp ) C hp,t =P hp,t ·head c ·Z hp Where P hp,t is the input power of the ground source heat pump at time t; C hp,t is the output cooling power of the ground source heat pump at time t; Q hp,t is the output thermal power of the ground source heat pump at time t; Q hp，t，i is the output thermal power of the i-th ground source heat pump at time t; C hp，t，i is the output cooling power of the i-th ground source heat pump at time t; N hp is the number of heat pumps in the park; cop c is the cooling energy efficiency ratio of the ground source heat pump; cop h is the heating energy efficiency ratio of the ground source heat pump; Z hp is the cooling and heating state 0 / 1 variable of the ground source heat pump, Z hp =0 means the ground source heat pump is in heating state, Z hp =1 means the ground source heat pump is in cooling state; The upper and lower limits of the thermal power output of the ground source heat pump; The upper and lower limits of the cooling power output of the ground source heat pump; The heating power adjustment amount of the ground source heat pump participating in the day-ahead and intraday market regulation at time t; is the cooling power adjustment of the ground source heat pump participating in the day-ahead and intraday market regulation at time t; β Q,hp,DAM , β Q,hp,IDM β is the set value of the shallow and middle heating power adjustment ratio coefficient of the ground source heat pump participating in the day-ahead and intraday markets respectively; C,hp,DAM , β C,hp,IDM are the setting values ​​of the shallow and middle cooling power adjustment proportional coefficients for ground source heat pumps participating in the day-ahead and intraday markets respectively; m is the time scale type parameter of the electricity market; DAM and IDM represent the day-ahead market and intraday market respectively.

10. A park comprehensive energy dispatching method according to claim 1, characterized in that: The thermal storage electric boiler model includes: electric boiler and thermal storage tank. Its formula and operation constraints are expressed as follows: Q EB,t =P EB,t ·η eh Q HS,t =Q HS,c,t -Q HS,d,t Where P EB,t is the input power of the electric boiler at time t; Q EB,t is the thermal power output of the electric boiler at time t; Q EB，t，i is the output thermal power of the i-th electric boiler at time t; Q HS，t，i is the heat release power of the i-th hot water storage tank at time t; N EB is the number of thermal storage electric boilers in the park; η eh is the electric-to-heat conversion efficiency of the electric boiler; H HS,t and H HS,t-1 is the heat storage capacity of the hot water storage tank at the end of time t and t-1; μ is the heat loss rate of the hot water storage tank; η HS,c and η HS,d is the heat absorption and release efficiency of the hot water storage tank; Q HS,c,t and Q HS,d,t is the heat absorption and heat release power of the hot water storage tank at time t; They are the upper and lower limits of the heat storage capacity of the hot water storage tank respectively; They are respectively the upper limits of the charging and discharging power of the hot water storage tank; They are 0 / 1 variables representing the heat absorption and heat release states of the hot water storage tank. The hot water storage tank can only operate in the heat absorption or heat release mode at the same time. is the heating power adjustment of the thermal storage electric boiler participating in the day-ahead and intraday market regulation at time t; Q,EB,DAM , β Q,EB,IDM are the setting values ​​of the shallow and middle heating power regulation coefficients of thermal storage electric boilers participating in the day-ahead and intraday markets respectively; m is the time scale type parameter of the power market; DAM and IDM represent the day-ahead market and intraday market respectively.

11. A park comprehensive energy dispatching method according to claim 1, characterized in that: Construct a classification and grading optimization scheduling model for the electric, heating and cooling regulation resources of the park's comprehensive energy system under the spot market, optimize and solve the proportion coefficients of each regulation resource participating in the day-ahead, intraday and real-time market regulation settings, and obtain the optimal regulation proportion coefficient, including: The classification and grading optimization scheduling model of the electric, heating and cooling regulation resources of the park comprehensive energy system under the spot market is constructed. The objective function is to minimize the comprehensive energy cost of the system. The constraints include: the balance constraints of the electric, heating and cooling power of the park comprehensive energy system and the operation constraints of various electric, heating and cooling regulation resources; Set the initial values ​​of shallow, medium and deep adjustment ratio coefficients of various types of electric heating and cooling adjustment resources in the spot market, and solve to obtain the optimal adjustment ratio coefficient; Among them, the power balance constraints of electricity, heat and cooling of the park's comprehensive energy system are expressed as follows: m∈{DAM,IDM,RTM} m∈{DAM,IDM} m∈{DAM,IDM} α se,0,DAM ＝α EV,0,DAM ＝0.4 α se,0,IDM ＝α EV,0,IDM ＝α se,0,RTM ＝α EV,0,RTM ＝0.3 β C,A,0,DAM ＝β C,A,0,IDM ＝0.5 β C,WC,0,DAM ＝β C,WC,0,IDM ＝0.5 β C,hp,0,DAM ＝β C,hp,0,IDM ＝0.5 β Q,hp,0,DAM ＝β Q,hp,0,IDM ＝0.5 β Q,EB,0,DAM ＝β Q,EB,0,IDM ＝0.5 α se,DAM +α se,IDM +α se,RTM ≤1 α EV,DAM +α EV,IDM +α EV,RTM ≤1 β C,A,DAM +β C,A,IDM ≤1 β C,WC,DAM +β C,WC,IDM ≤1 β C,hp,DAM +β C,hp,IDM ≤1 β Q,hp,DAM +β Q,hp,IDM ≤1 β Q,EB,DAM +β Q,EB,IDM ≤1 Where P t L , P is the electricity, heating and cooling load of the park at time t; t PV is the output value of distributed photovoltaic at time t; P t grid is the power purchased by the park from the upper power grid at time t; is the power of the i-th car at time t; is the power consumption of the i-th air conditioner at time t; is the cooling power consumption of the i-th dual-mode host at time t; is the ice-making power consumption of the i-th dual-mode host at time t; N WC The number of ice storage equipment in the park; is the input power of the i-th ground source heat pump at time t; is the input power of the i-th electric boiler at time t; N A is the number of air conditioners in the park; N HP N is the number of heat pumps in the park; EB is the number of thermal storage electric boilers in the park; Q hp，t，i is the output thermal power of the i-th ground source heat pump at time t; Q EB，t，i is the output thermal power of the i-th electric boiler at time t; Q HS，t，i is the heat release power of the i-th hot water storage tank at time t; C hp，t，i is the output cooling power of the i-th ground source heat pump at time t; N WC is the number of ice storage equipment in the park; C WC，t，i is the ice-making power of the i-th dual-mode host at time t; C si，t，i is the ice-making power of the i-th ice storage tank at time t; is the cooling power of the i-th air conditioner at time t; α se,0,DAM , α se,0,IDM , α se,0,IDM The initial setting values ​​of the shallow, medium and deep electric power regulation coefficients of the energy storage equipment participating in the day-ahead, intraday and real-time markets are set respectively. The initial electric power regulation coefficient of the energy storage equipment is set to α se,0,DAM =0.4,α se,0,IDM =α se,0,RTM = 0.3, and add constraint α se,DAM +α se,IDM +α se,RTM ≤1; α EV,0,DAM , α EV,0,IDM , α EV,0,IDM The initial setting values ​​of the shallow, medium and deep electric power adjustment coefficients for electric vehicle charging piles participating in the day-ahead, intraday and real-time markets are set respectively. The initial adjustment coefficient of the electric power of electric vehicle charging piles is set to α EV,0,DAM =0.4,α EV,0,IDM =α EV,0,RTM = 0.3, and add constraint α EV,DAM +α EV,IDM +α EV,RTM ≤1; β C,A,0,DAM , β C,A,0,IDM The initial setting values ​​of the shallow / medium cooling power adjustment coefficients for air conditioners participating in the day-ahead and intraday markets are β, and the initial adjustment coefficient of the cooling power of the air conditioner is set to C,A,0,DAM =β C,A,0,IDM = 0.5, and add constraint β C,A,DAM +β C,A,IDM ≤1; β C,WC,0,DAM , β C,WC,0,IDM The initial setting values ​​of the shallow and middle cooling power adjustment coefficients of the ice storage equipment participating in the day-ahead and intraday markets are β, and the initial adjustment coefficient of the ice storage equipment is set to C,WC,0,DAM =β C,WC,0,IDM = 0.5, and add constraint β C,WC,DAM +β C,WC,IDM ≤1; β C,hp,0,DAM , β C,hp,0,IDM The initial setting values ​​of the cooling power ratio of the shallow and middle layers for the ground source heat pump to participate in the day-ahead and intraday markets are set respectively, and the initial cooling power adjustment ratio coefficient of the ground source heat pump is set to β C,hp,0,DAM =β C,hp,0,IDM = 0.5, and add constraint β C,hp,DAM +β C,hp,IDM ≤1; β Q,hp,0,DAM , β Q,hp,0,IDM The initial setting values ​​of the shallow and middle-level heating power ratios for the ground source heat pump to participate in the day-ahead and intraday markets are set respectively, and the initial heating power adjustment ratio coefficient of the ground source heat pump is set to β Q,hp,0,DAM =β Q,hp,0,IDM = 0.5, and add constraint β Q,hp,DAM +β Q,hp,IDM ≤1; β Q,EB,0,DAM , β Q,EB,0,IDM are the initial setting values ​​of the shallow and medium adjustment ratio coefficients of the thermal storage electric boiler participating in the day-ahead and intraday markets, respectively. The initial heating power adjustment ratio coefficient of the thermal storage electric boiler is set to β Q,EB,0,DAM =β Q,EB,0,IDM = 0.5, and add constraint β Q,EB,DAM +β Q,EB,IDM ≤1; m is the time scale type parameter of the power market; DAM, IDM, and RTM represent the day-ahead market, intraday market, and real-time market, respectively.

12. A park comprehensive energy scheduling method according to claim 1, characterized in that: With the goal of minimizing the comprehensive energy cost at each stage, the classification and grading optimization scheduling model of the electric, heating and cooling regulation resources of the park comprehensive energy system in the day-ahead, intra-day and real-time stages is solved, including: For the classification and grading optimization scheduling model of electric, heating and cooling regulation resources, in the day-ahead optimization stage, based on the optimal regulation ratio coefficient, the objective function is to minimize the comprehensive energy consumption cost in the park on the second day. The constraints include: the operation constraints of various electric, heating and cooling regulation resources; the optimal power purchase curve of the power grid on the second day is solved as the scheduling plan, which is used for the scheduling operations in the day-ahead market.

13. A park comprehensive energy dispatching method according to claim 1, characterized in that: With the goal of minimizing the comprehensive energy cost at each stage, the classification and grading optimization scheduling model of the electric, heating and cooling regulation resources of the park comprehensive energy system in the day-ahead, intra-day and real-time stages is solved, including: For the classification and grading optimization scheduling model of electric, heating and cooling regulation resources, in the intraday optimization stage, based on the optimal regulation ratio coefficient, with the minimization of the overall intraday energy cost as the objective function, the power generation and consumption arrangement in the intraday optimization stage is obtained based on the cleared day-ahead electricity price correction. The power generation and consumption arrangement in the intraday optimization stage includes: the intraday power purchase plan curve and the intraday energy scheduling plan of each electric, heating and cooling regulation resource, which is used for scheduling operations in the intraday market.

14. A park comprehensive energy dispatching method according to claim 1, characterized in that: With the goal of minimizing the comprehensive energy cost at each stage, the classification and grading optimization scheduling model of the electric, heating and cooling regulation resources of the park comprehensive energy system in the day-ahead, intra-day and real-time stages is solved, including: For the classification and grading optimization scheduling model of electric heating and cooling regulation resources, in the real-time optimization stage, based on the optimal regulation ratio coefficient and taking the minimum comprehensive energy cost as the objective function, the daily power generation and consumption plan is corrected with a 15-minute cycle based on the ultra-short-term prediction of photovoltaic power generation output to obtain the power generation and consumption arrangement in the real-time stage, which is used for scheduling operations in the real-time stage.

15. A park comprehensive energy dispatching device, characterized in that: include: A regulating capability model building unit, a scheduling model building unit and a scheduling solution unit; The regulation capacity model building unit is used to build a classification and grading regulation capacity model for electric heating and cooling regulation resources to participate in the spot market, including: energy storage equipment model, air conditioning model, ice storage equipment model, ground source heat pump model, thermal storage electric boiler model, and electric vehicle charging pile model; The dispatch model construction unit is used to construct a classified and graded optimization dispatch model for the electric, heating and cooling regulation resources of the park comprehensive energy system under the spot market based on the classified and graded regulation capability model, optimize and solve the proportion coefficients of each regulation resource participating in the day-ahead, intraday and real-time market regulation settings, and obtain the optimal regulation proportion coefficient; The solution scheduling unit is used to solve the classification and grading optimization scheduling model of the electric, heating and cooling regulation resources of the park's comprehensive energy system in the day-ahead, intraday and real-time stages according to the spot market signal, based on the optimal adjustment ratio coefficient and with the goal of minimizing the comprehensive energy cost in each stage, output the scheduling plan of the classified and graded resources, and schedule the park's comprehensive energy according to the scheduling plan.

16. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; a memory storing a computer program; The processor is used to implement a park comprehensive energy scheduling method according to any one of claims 1 to 14 when executing a computer program stored in a memory.

17. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a comprehensive energy scheduling method for a park is implemented as described in any one of claims 1-14.

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