An optimization scheduling method for a combined power generation system of ammonia-blended combustion, pumped storage and wind power

Abstract

The present application belongs to the field of micro-grid dispatching operation method, and is an ammonia-doped combustion, pumped storage and wind power combined power generation system optimal dispatching operation method. The method comprises constructing an ammonia-doped combustion, pumped storage and wind power combined power generation optimal dispatching operation model; the objective function of the optimal dispatching operation model comprises an ammonia-doping proportion γ t related combustion stability penalty term; the constraint condition of the optimal dispatching operation model comprises the constraint condition of the ammonia-doping proportion γ t ; the optimal dispatching operation model is solved by the objective function within the constraint condition, and in the solving process, the optimal ammonia-doping proportion is solved under the constraint condition of the ammonia-doping proportion γ t to maximize the fuel cost reduction rate. The present application sets multiple constraint conditions to cope with these complex factors, so as to ensure that the combined power generation system can operate stably and efficiently under various conditions.

Description

Technical Field

[0001] The present invention belongs to a microgrid dispatching operation method, and is an optimized dispatching operation method for an ammonia-blended combustion, pumped storage and wind power combined power generation system. Background Art

[0002] Against the backdrop of global efforts to promote energy transition and sustainable development, reducing reliance on traditional fossil fuels and increasing the share of renewable energy in the energy mix have become key initiatives in addressing climate change and the energy crisis. Wind power, as a clean, renewable energy source, has experienced rapid growth globally in recent years, with installed capacity continuing to climb. However, wind power is characterized by significant intermittency, volatility, and unpredictability, posing significant challenges to the stable supply of power systems.

[0003] Pumped storage, as a mature large-scale energy storage technology, effectively regulates the balance of power supply and demand and improves the stability and reliability of the power system by pumping water from the lower reservoir to the upper reservoir to store energy when there is excess electricity, and releasing water to generate electricity when there is a power shortage. However, the combination of pumped storage and wind power alone still has certain limitations when it comes to meeting complex and changing electricity demand. At the same time, ammonia-blended combustion technology is gradually coming into people's attention as a new combustion method. Ammonia (NH3), as a hydrogen-containing compound, has a high hydrogen content and produces almost no carbon dioxide emissions during combustion, making it a highly promising low-carbon or even zero-carbon fuel. Introducing ammonia-blended combustion technology into power generation systems can not only reduce the use of traditional fossil fuels and reduce carbon emissions, but also provide a more flexible energy supply method for power generation systems.

[0004] Therefore, the integration of ammonia-blended combustion, pumped hydro storage, and wind power into a combined power generation system and its optimized operation are crucial for improving energy efficiency, ensuring stable and reliable power system operation, and achieving sustainable energy development goals. However, the optimal operation methods for this new type of combined power generation system are still in the exploratory stage, and in-depth research is urgently needed to address a series of key issues, such as coordinated system operation and optimal energy allocation. Summary of the Invention

[0005] The purpose of the present invention is to provide an optimized scheduling and operation method for an ammonia-blended combustion, pumped storage and wind power combined power generation system to solve the technical problems raised in the above background technology.

[0006] In order to solve the above problems, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for optimizing the scheduling of an ammonia-blended combustion, pumped storage, and wind power combined power generation system, comprising:

[0008] An optimal dispatching operation model of ammonia-doped combustion, pumped storage and wind power combined generation is constructed.

[0009] The objective function of the optimal dispatching operation model includes a combustion stability penalty term t and a penalty term related to the ammonia-doped ratio γ t .

[0010] The constraint conditions of the optimal dispatching operation model include a constraint condition of the ammonia-doped ratio γ t .

[0011] The optimal dispatching operation model is solved by the objective function under the constraint conditions, and in the solving process, the optimal ammonia-doped ratio is solved under the constraint condition of the ammonia-doped ratio γ t to maximize the fuel cost reduction rate.

[0012] As a preferred embodiment, the combustion stability penalty term and the calculation formula of the ammonia-doped ratio are as follows:

[0013]

[0014] 0≤γ max ≤γ stab .

[0015]

[0016] Wherein, C t represents the combustion stability penalty term, γ safe represents the ammonia-doped ratio, γ coal is a safety threshold, k is a penalty coefficient, and Q t are the low calorific values of ammonia and coal respectively; a1, b1 and c1 are the consumption characteristic coefficients of the thermal power unit respectively; P th ,th is the output power of the thermal power unit in the t period. and are the coal consumption and ammonia-doped amount of the thermal power unit in the t period respectively, γ max is the maximum allowed ammonia-doped ratio, and α is an ammonia-coal calorific value equivalent replacement factor.

[0017] As a preferred embodiment, the method further comprises:

[0018] When the ammonia-doped ratio is greater than the safety threshold, the minimum output of the thermal power unit is increased to a preset ratio of the rated value;

[0019] When the ammonia-doped ratio is equal to the maximum allowed ammonia-doped ratio, a correction coefficient is used for compensation, and the formula is as follows:

[0020]

[0021] wherein k η represents a correction coefficient.

[0022] As a preferred embodiment, the constraint condition of the optimization scheduling operation model further comprises a multi-energy climbing collaborative constraint, which is expressed as:

[0023]

[0024] wherein P t th,th Pte represents the power generation of pumped storage at t time.

[0025] As a preferred embodiment, the objective function of the optimization scheduling operation model is expressed as:

[0026]

[0027]

[0028] wherein C represents the total cost; C wt represents the wind power operation cost; C pv represents the photovoltaic operation cost; C ab represents the abandoned wind and light cost; C th represents the coal-fired unit operation cost; represents the carbon emission cost; C ep represents the environmental cost; P t wt , P t pv , P t ab , P t th , P t ep respectively represent the power output of the corresponding system at t period; Δt represents the period interval; and respectively represent the operation cost of the coal-fired unit and the cogeneration unit;

[0029] As a preferred embodiment, the operation cost of the cogeneration unit is calculated by the following formula:

[0030]

[0031] wherein: is the coal consumption of the cogeneration unit at t period; a2, b2, c2 and c ν1 are characteristic coefficients of the cogeneration unit; and Pheat(t) and P(t) are the heat and electricity output of the combined heat and power unit at time t, respectively;

[0032] Operating cost of the thermal power unit The calculation method is as follows:

[0033] When the thermal power unit is in the RPR stage, the loss cost of the thermal power unit is negligible, and when the thermal power unit is in the DPR stage, the calculation formula of the operating cost of the thermal power unit is:

[0034]

[0035] Where τ1 and τ2 are the operating loss coefficients of DPR1 and DPR2 stages, respectively; c unit is the unit cost of the unit; is the loss cost of the thermal power unit at time t, c coal is the unit price of coal.

[0036] As a preferred embodiment, the carbon emission cost The calculation formula is as follows:

[0037]

[0038] Where e G and e H are the carbon emission quota per unit of electricity supply and the carbon emission quota per unit of heat supply, respectively; E is the carbon emission quota; is the CO2 emission at time t; is the amount of CO2 emitted per unit of coal combustion; c e is the carbon emission quota penalty cost coefficient;

[0039] The calculation formula of the environmental cost C ep is as follows:

[0040]

[0041] Where J is the type of taxable pollutants; K is the tax amount per pollution equivalent; m j is the mass of the jth pollutant produced per unit of coal combustion; η j is the removal efficiency of the jth pollutant by the environmental protection device; G j is the pollution equivalent number of the jth pollutant.

[0042] As a preferred embodiment, the optimization scheduling operation model is solved using an improved mixed integer second-order cone programming (MI-SOCP) algorithm, in which the ammonia blending ratio and the thermal power unit output are combined into an equivalent coal consumption variable to reduce the dimension of the decision variable, represented as:

[0043]

[0044] represents the equivalent coal consumption variable.

[0045] As a preferred embodiment, the formula for calculating the fuel cost reduction rate is:

[0046]

[0047] wherein c coal represents the unit price of coal.

[0048] As a preferred embodiment, the ammonia blending ratio γ t is solved by using a hierarchical solving strategy, the outer loop solves the integer combination of the ammonia blending ratio γ t using a genetic algorithm, the population size and the number of iterations are pre-set, the inner loop is used to call the CPLEX solver to solve the continuous variable optimization for a fixed combination of the ammonia blending ratio γ t , and the objective function value of the optimal scheduling operation model is calculated to determine the optimal ammonia blending ratio γ t .

[0049] Compared with the prior art, the present application has the following beneficial effects:

[0050] The present application uses an optimal scheduling method to improve the operation efficiency of the ammonia blending combustion-pumped storage-wind power combined power generation system under the consideration of various complex factors, and detailed modeling is performed on the characteristics of various power generation equipment and energy conversion links in the combined power generation system. In the implementation process, since the change of the ammonia blending combustion ratio will change the combustion condition and power generation efficiency of the thermal power unit, the present application introduces an ammonia-coal heat value equivalent replacement factor and a thermal power unit processing mode under different ammonia blending ratios, and through the setting of various constraint conditions, the complex factors are dealt with, so that the combined power generation system can be stably and efficiently operated under various conditions. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 is the flow diagram of the ammonia blending combustion-pumped storage-wind power combined power generation system optimization scheduling in the present application;

[0052] Figure 2 is the ammonia blending combustion schematic diagram in the present application. DETAILED DESCRIPTION

[0053] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more. In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0054] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0055] Example 1

[0056] Combine Figure 1 As previously explained, the energy flow relationship of the integrated energy system used in this embodiment includes: the integrated energy system is supplied by the upper power grid, ammonia-blended combustion of thermal power units, and new energy power generation. The source-side input energy meets the load demand through the system's internal coupling equipment. The source-side cogeneration unit generates electricity, and part of the thermal power generated by the gas turbine is supplied to the thermal load through the waste heat boiler, and the other part is used to generate electricity to supply the electrical load, realizing the thermal and electrical flexibility of the cogeneration. Pumped storage is used as a storage unit to further increase the flexibility of the system. The principle diagram of ammonia-blended combustion is shown as follows. Figure 2 .

[0057] This embodiment provides an optimized scheduling operation method for an ammonia-blended combustion, pumped storage, and wind power combined power generation system, which includes:

[0058] Step S1, constructing an optimal dispatching operation model for ammonia-blended combustion, pumped storage and wind power combined generation; the objective function of the optimal dispatching operation model includes the ammonia-blended ratio γ of the thermal power unit ta related combustion stability penalty term; the constraint condition of the optimization scheduling operation model includes an ammonia blending ratio γ t ;

[0059] The objective function expression of the ammonia-blended combustion-pumped storage combined power system optimization scheduling operation model is:

[0060]

[0061] wherein C represents the total cost; C wt represents the wind power operation cost; C pv represents the photovoltaic operation cost; C ab represents the abandoned wind and light cost; C th represents the coal-fired unit operation cost; represents the carbon emission cost; C ep represents the environmental cost; P t wt , P t pv , P t ab , P t th , P t ep respectively represent the power output of the corresponding system at the t period; Δt represents the time interval.

[0062] According to the operation characteristics of the coal-fired unit, the operation cost (fuel cost and loss cost) of the thermal power unit and the operation cost (fuel cost) of the combined heat and power unit are calculated respectively, and the operation cost of the coal-fired unit is

[0063]

[0064] wherein and are the operation costs of the thermal power unit and the combined heat and power unit respectively.

[0065] The combustion stability penalty term is represented as:

[0066]

[0067] wherein γ safe = 15% is a safety threshold, and k is a penalty coefficient. When γ t > 15%, the minimum output of the thermal power unit is forced to increase to 50% (originally 30%) of the rated value to avoid insufficient ammonia-blended combustion leading to NOx exceeding the standard under low load conditions; when γ t = 20%, the boiler efficiency decreases by about 2.3%, which is compensated by a correction coefficient k η = 0.977, that is,

[0068]

[0069] For thermal power units modified with ammonia-blended combustion technology, ammonia replaces part of the pulverized coal in a certain heat ratio before entering the boiler. The actual coal consumption of the thermal power unit is:

[0070]

[0071] Where: a1, b1 and c1 are the consumption characteristic coefficients of thermal power units respectively; P t th,th is the output power of the thermal power unit during period t; and Q coal are the lower heating values ​​of ammonia and coal, respectively; and are the coal consumption and ammonia content of the thermal power unit during period t respectively.

[0072] Establish ammonia blending ratio γ t With the thermal power unit output P t th,th The coupling equation of γ is solved by nonlinear programming to obtain the optimal ammonia ratio. max =20% constraint, fuel cost reduction rate maximize;

[0073] In addition, the ammonia blending ratio γ of the thermal power unit during period t is defined as t for

[0074]

[0075] Introducing the equivalent substitution factor α of ammonia-coal calorific value. When wind power output exceeds load demand, the ammonia blending ratio γ is increased first. t To reduce coal consumption, and at the same time trigger the pumping mode of the pumped storage power station to store excess wind power.

[0076] Ammonia-coal calorific value equivalent substitution factor:

[0077]

[0078] During the operation of thermal power units, the rotor will suffer losses and increase costs. When the unit is in the RPR stage, this part can be ignored; but when it is in the DPR (Rated Power Regulation Range) stage, the alternating thermal stress of the rotor shaft system is too large, causing low-cycle fatigue loss and creep loss of the unit body, and the loss cost is too large to be ignored. In addition, according to the degree of loss, DPR (Deep Peak Regulation Range) is divided into DPR1 and DPR2. The rotor cycle cracking cycle L (Pt th,th ), and combined with the unit purchase cost to calculate the loss cost:

[0079]

[0080] wherein τ1 and τ2 are the operation loss coefficients of DPR1 and DPR2 stages respectively; c unit is the unit cost of the unit; is the loss cost of the thermal power unit in t period.

[0081] The operation cost of the thermal power unit is:

[0082]

[0083] wherein c coal is the unit price of coal;

[0084] After introducing the ammonia-doping combustion retrofit unit, the CO2 emission of the thermal power unit can be reduced, and the reduction rate is equal to the fuel replacement rate based on the heat value. The carbon emission cost is:

[0085]

[0086] wherein e G and e H are the carbon emission quota per unit of power supply and the carbon emission quota per unit of heat supply respectively; E is the carbon emission quota; is the CO2 emission in t period; is the CO2 emission per unit of coal combustion; c e is the carbon emission quota penalty cost coefficient.

[0087]

[0088] wherein: is the coal consumption of the cogeneration unit in t period; a2, b2, c2 and c ν1 are the characteristic coefficients of the cogeneration unit; and are the electric power and thermal power output by the cogeneration unit in t period respectively.

[0089] The thermal power unit will emit SO2 and NOx to the environment during operation. Although ammonia-doping combustion will bring the risk of NOx emission, it can be effectively regulated by combustion staging, combustion organization, etc. Assuming that the calculation method of NOx emission after ammonia-doping combustion of the thermal power unit is the same as that under pure coal combustion, the calculation formula of the environmental cost is as follows:

[0090]

[0091] Wherein: J is the type of taxable pollutants; K is the tax amount per pollution equivalent; m j is the mass of the jthpollutant generated by the unit coal combustion; η j is the removal efficiency of the jthpollutant by the environmental protection device; G j is the pollution equivalent number of the jthpollutant.

[0092] In the embodiment, the constraint condition of the ammonia-doped combustion-pumped storage combined power generation system optimization scheduling operation model is expressed as:

[0093] The output constraints of wind power, photovoltaic and coal-fired units are:

[0094]

[0095] P t wt,N and P t pv,N are the output powers of wind power and photovoltaic directly supplying the electrical load demand at the t period; Pmin is the minimum output power of the coal-fired unit.

[0096] The WHB collects the waste heat generated by the GT and provides the user heat load, and the model of the WHB can be expressed as:

[0097] P WHB,t = Q th,t η WHB (18)

[0098] U WHB,t P WHBmin ≤ P WHB,t ≤ U WHB,t P WHB,max (19)

[0099] Pumped storage constraints are:

[0100]

[0101] Wherein, are the minimum reservoir capacity, the t period reservoir capacity and the maximum reservoir capacity of the pumped storage power station respectively; Q h,in (t), Q h,out (t) are the t period inflow and outflow of the pumped storage power station respectively; η c,cx , η d,cx are the pumping and power generation efficiencies of the pumped storage power station respectively.

[0102] In a specific embodiment, the pumped storage power station constraints are linearly approximated, and the reservoir capacity change is expressed as an affine function of P t o / P t e .

[0103] Pumping and power generation constraints:

[0104]

[0105] Pumped storage ramping constraints

[0106]

[0107] Constraints on abandoned wind and solar power.

[0108]

[0109] Where: P t wt,ab and P t pv,ab are the wind power curtailment and solar power curtailment respectively; and The maximum allowable curtailment rates for wind power and photovoltaic power are 15% and 10% respectively

[0110] P t th,th +P t th,chp =P t th (twenty four)

[0111]

[0112] In the formula is the required power of the heat load during period t.

[0113] Electric load balance constraints. Electric load balance constraints must be met in each dispatch period:

[0114] P t wt,N +P t pv,N +P t th =P WHB,t =Q GT,t η WHB (26)

[0115] Where P t load is the power demanded by the electric load during period t.

[0116] Since the addition of ammonia to thermal power units will have a certain impact on the internal combustion conditions, it is necessary to restrict the ammonia addition ratio:

[0117] 0≤γ t ≤γ max (27) Where: γ maxThe maximum allowable ammonia blending ratio is 20%.

[0118] Coal-fired unit ramping constraint:

[0119]

[0120] wherein and are the maximum allowable ramping power of the thermal power unit and the combined heat and power unit, respectively.

[0121] Multi-energy ramping coordination constraint:

[0122] Joint constraint of thermal power and pumped storage ramping rate

[0123]

[0124] Operation region constraint:

[0125]

[0126] wherein: and are the lower and upper limits of the power generation of the extraction steam combined heat and power unit under the condensing condition, respectively; is the upper limit of the heat supply power of the combined heat and power unit.

[0127] Step S2: solving the optimization scheduling operation model under the constraint conditions with the target function, wherein the optimal ammonia blending ratio is solved under the constraint condition of the ammonia blending ratio γ t to maximize the fuel cost reduction rate.

[0128] The solving of the optimization scheduling operation model is performed by using an improved mixed integer second-order cone programming (MI-SOCP) algorithm, wherein the ammonia blending ratio and the thermal power unit output are combined into an equivalent coal consumption variable to reduce the dimension of the decision variable, and is expressed as:

[0129]

[0130] wherein, represents the equivalent coal consumption variable;

[0131] The solving of the ammonia blending ratio γ t is performed by using a hierarchical solving strategy, wherein the outer loop is used to solve the integer combination of the ammonia blending ratio γ t by using a genetic algorithm, the population size and the iteration number are pre-set, the inner loop is used to fix the ammonia blending ratio γ t combination, the CPLEX solver is called to perform continuous variable optimization, the target function value of the optimization scheduling operation model is calculated to determine the optimal ammonia blending ratio γ t .

[0132]

[0133] where c coal represents the unit price of coal.

[0134] In a specific embodiment, the hierarchical solution strategy includes: outer loop: solving the integer combination of ammonia blending ratio γ t with genetic algorithm (GA), population size = 50, iteration number = 100; inner loop: for fixed ammonia blending ratio γ t combination, calling CPLEX solver for continuous variable optimization, calculating the objective function value.

[0135] In another specific embodiment, a robustness enhancement mechanism is added, and a wind power output fluctuation interval is introduced:

[0136] P t wt ∈ [0.9P t wt,pre , 1.1P t wt,pre ], a two-stage robust optimization model is constructed to ensure that the system still satisfies the constraint conditions under the worst wind power scenario;

[0137] The wind power consumption robustness index is defined as ξ > 85% in the optimization process.

[0138]

[0139] In summary, the working principle of the embodiment is system initialization and parameter setting. First, the initialization of each component of the combined power generation system is completed, including the thermal power unit, pumped storage power station, wind power and photovoltaic system, and the key operating parameters are set, such as unit output limit, pumped storage capacity, combined heat and power characteristic coefficient, etc. Then the optimization scheduling model is established. Based on the economic and environmental protection objectives, a multi-objective function is constructed, including wind and photovoltaic operation cost, abandoned wind and light cost, fuel and loss cost of coal-fired units, carbon emission and environmental cost. The physical constraint conditions of system operation are set, including unit output, pumped storage charging and discharging efficiency, electric / thermal load balance, ammonia blending ratio limit and climbing rate, etc., and a high-efficiency optimization algorithm is selected to solve the model. Then the system optimization scheduling is performed. Using real-time data and prediction results, the optimal output scheme of each unit is obtained by model solving, the ammonia blending ratio of thermal power unit is dynamically adjusted to reduce carbon emissions, and the pumped storage pumping / generating strategy is optimized to balance power supply and demand. Under the premise of ensuring the demand of electric and thermal load, wind power / photovoltaic is preferentially consumed to reduce the abandoned wind and light rate, and multi-energy collaborative operation is realized. Finally, performance evaluation and iterative optimization are performed. The scheduling results are evaluated in multiple dimensions, including economic cost, carbon emission, system reliability and other indicators. Based on the evaluation data, the model parameters and constraint conditions are optimized, and the scheduling strategy is iteratively improved. The operation data is recorded and the law is analyzed to provide data support for long-term system upgrade or policy making, and finally the efficient use of sustainable energy is realized.

[0140] The above only describes the preferred embodiments of the present application, and it should be noted that for ordinary skilled persons in the technical field, several improvements and modifications can be made without departing from the technical principles of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims

1. A method for optimizing the scheduling of a combined ammonia combustion, pumped storage and wind power generation system, characterized in that: include: Construct an optimized dispatching and operation model for combined power generation of ammonia-blended combustion, pumped storage, and wind power; The objective function of the optimization scheduling operation model includes the ammonia blending ratio γ of the thermal power unit. t Related combustion stability penalty terms; The constraints of the optimal scheduling operation model include the ammonia blending ratio γ t Constraints; The optimization scheduling operation model is solved by the objective function within the constraints. During the solution process, the ammonia ratio γ t Under the constraints of , the optimal ammonia blending ratio is solved to maximize the fuel cost reduction rate; The calculation formulas for the combustion stability penalty term and the ammonia blending ratio are as follows: 0≤γ t ≤γ max Among them, C stab represents the combustion stability penalty term, γ t Indicates the ammonia mixing ratio, γ safe is the safety threshold, k is the penalty coefficient, and Q coal are the lower calorific values ​​of ammonia and coal respectively; a1, b1 and c1 are the consumption characteristic coefficients of thermal power units respectively; P t th,th is the output power of the thermal power unit during period t; and are the coal consumption and ammonia content of the thermal power unit in period t, γ max is the maximum allowable ammonia blending ratio, and α is the ammonia-coal calorific value equivalent substitution factor.

2. The optimization scheduling method according to claim 1, characterized in that: The method further comprises: When the ammonia blending ratio is greater than the safety threshold, increasing the minimum output of the thermal power unit to a preset ratio of the rated value; When the ammonia blending ratio is equal to the maximum allowable ammonia blending ratio, compensation is performed using a correction coefficient, which is expressed as follows: Where k η Indicates the correction factor.

3. The optimization scheduling method according to claim 1, characterized in that: The constraints of the optimization scheduling operation model also include multi-energy ramp coordination constraints, which are expressed as: Where, P t th,th is the output power of the thermal power unit in period t, and Pte is the power generation power of the pumped storage in period t.

4. The optimization scheduling method according to claim 1, characterized in that: The objective function of the optimization scheduling operation model is expressed as: minC=C wt +C pv +C ab +C th +C CO2 +C ep Where C represents the total cost; C wt represents the operating cost of wind power; C pv represents the photovoltaic operation cost; C ab represents the cost of abandoned wind and solar power; C th represents the operating cost of coal-fired units; represents the carbon emission cost; C ep represents environmental cost; P t wt 、P t pv 、P t ab 、P t th P t ep They represent the power output of the corresponding system in time period t; Δt represents the time interval; and are the operating costs of thermal power units and cogeneration units respectively.

5. The optimization scheduling method according to claim 4, characterized in that: The operating cost of the cogeneration unit The calculation formula is: Where: is the coal consumption of the cogeneration unit during period t; a2, b2, c2 and c ν1 is the characteristic coefficient of the cogeneration unit; and are the electric power and thermal power output of the cogeneration unit in period t, respectively; Operating costs of thermal power units The calculation is as follows: When the thermal power unit is in the RPR stage, the loss cost of the thermal power unit is negligible. When the thermal power unit is in the DPR stage, the calculation formula for the operating cost of the thermal power unit is: Where τ1 and τ2 are the operating loss coefficients of DPR1 and DPR2 stages respectively; c unit The unit cost of the unit; is the loss cost of thermal power unit in period t, c coal is the unit price of coal.

6. The optimization scheduling method according to claim 5, characterized in that: The carbon emission costs The calculation formula is: Where: e G and e H They are the carbon emission quota of power supply units and the carbon emission electricity quota of heating units respectively; E is the carbon emission quota; is the CO2 emission during period t; is the amount of CO2 emitted per unit of coal combustion; c e Penalty cost coefficient for carbon emission quota; Environmental cost C ep The calculation formula is as follows: Where: J is the type of taxable pollutant; K is the tax amount to be paid per pollution equivalent; m j is the mass of the jth pollutant produced when burning unit coal; η j G is the efficiency of the environmental protection device in removing the jth pollutant; j is the pollution equivalent number of the jth pollutant.

7. The optimization scheduling method according to claim 1, characterized in that: The optimized scheduling operation model is solved by using the improved mixed integer second-order cone programming MI-SOCP algorithm, in which the ammonia blending ratio and the output of the thermal power unit are combined into equivalent coal consumption variables to reduce the dimension of the decision variables, which is expressed as: Represents the equivalent coal consumption variable.

8. The optimization scheduling method according to claim 7, characterized in that: The calculation formula for the fuel cost reduction rate is: Among them, c coal Indicates the unit price of coal.

9. The optimization scheduling method according to claim 8, characterized in that: The ammonia blending ratio γ t The solution is carried out using a hierarchical solution strategy, and the outer loop uses a genetic algorithm to solve the ammonia ratio γ t The population size and number of iterations are pre-set, and the inner loop is fixed for the ammonia ratio γ t Combine, call CPLEX solver to perform continuous variable optimization, calculate the objective function value of the optimization scheduling operation model to determine the optimal ammonia blending ratio γ t .

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