A comprehensive energy scheduling method for a park with full-cycle carbon emission ladder carbon trading

Abstract

The invention discloses a low-carbon economic dispatch optimization method for a park comprehensive energy system considering full-cycle carbon emissions, which relates to the technical field of energy dispatching, including establishing an operation framework of a park comprehensive energy system, covering electricity, gas, heat load and energy conversion parts; constructing a ladder carbon trading mechanism considering the whole cycle, including a carbon emission quota model, an actual carbon emission model and a ladder carbon trading model; establishing a park comprehensive energy low-carbon economic optimization operation model considering the full-cycle ladder carbon trading mechanism, including objective functions of energy purchase cost, full-cycle ladder carbon trading cost and wind abandonment cost, as well as constraints such as wind power output constraint, energy conversion equipment operation constraint, energy storage operation constraint and electricity, heat, gas and hydrogen power balance constraint; adopting piecewise linearization processing and mixed integer linear programming method to solve the model, using Yalmip toolbox configured by MATLAB and CPLEX solver to perform optimization calculation, and verifying the effectiveness of the proposed ladder carbon trading mechanism for full-cycle carbon emissions.

Description

Technical Field

[0001] The present invention relates to the field of energy management and scheduling, and in particular to a method for optimizing the scheduling of comprehensive energy and low-carbon economy in a park that can take full-cycle carbon emissions into consideration. Background Art

[0002] As the global climate change problem becomes increasingly serious, reducing carbon emissions has become an important task for all countries. As an important unit of energy consumption, the energy management and scheduling of the park are of great significance to the realization of a low-carbon economy. Most existing technologies only consider carbon emissions during the energy use stage, ignoring carbon emissions during energy production, transportation, conversion and use, which limits the low-carbon potential of optimizing the scheduling of the park energy system.

[0003] In existing park energy management systems, centralized or distributed energy supply methods are usually adopted, including but not limited to electricity, natural gas, thermal energy and hydrogen energy. These systems tend to focus on improving energy utilization efficiency and reducing operating costs, but do not take carbon emissions into account comprehensively. For example, some systems may reduce energy costs by increasing the proportion of coal-fired power generation, but this will significantly increase carbon emissions, which is contrary to the goal of low-carbon development.

[0004] In addition, the existing carbon trading market mechanism also has certain limitations. Most carbon trading mechanisms only consider direct carbon emissions, such as emissions from burning fossil fuels, but do not fully consider indirect carbon emissions, such as losses and conversion efficiency issues during power transmission. This results in the allocation and trading of carbon emission rights possibly not being able to truly reflect the carbon emissions of the energy system throughout its entire cycle.

[0005] In order to more effectively promote the low-carbon transformation of the park’s energy system, a new energy management and scheduling method is needed that can comprehensively consider the carbon emissions in the energy production, transportation, conversion and use processes, and optimize the scheduling strategy on this basis to achieve dual optimization of carbon emissions and economic costs.

[0006] The present invention is proposed in this context, aiming to solve the problems of incomplete carbon emission management and insufficient low-carbon energy scheduling in the existing technology. By constructing a comprehensive energy scheduling method for the park with a full-cycle carbon emission ladder carbon trading, the present invention can not only improve energy utilization efficiency and reduce operating costs, but also significantly reduce carbon emissions and promote the sustainable development of the park energy system. Summary of the invention

[0007] In view of the above problems, the present invention is proposed

[0008] Therefore, the technical problem solved by the present invention is: how to consider the full-cycle carbon emissions of the park's integrated energy system, so as to optimize the operation of the park's integrated energy system and achieve lower carbon emissions and economic costs.

[0009] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for optimizing the low-carbon economy of comprehensive energy in a park considering the full-cycle carbon emissions, which comprises the following steps:

[0010] Establish an operating framework for the park’s comprehensive energy system, including electricity, gas, heat loads and energy conversion parts, such as gas turbines, gas boilers, two-stage power-to-gas equipment, etc.

[0011] Build a tiered carbon trading mechanism that takes into account full-cycle carbon emissions, covering carbon emission quota model, actual carbon emission model and tiered carbon trading model.

[0012] A comprehensive energy low-carbon economic optimization operation model for the park is established taking into account the full-cycle step-by-step carbon trading mechanism, including objective functions of energy purchase cost, full-cycle step-by-step carbon trading cost and wind abandonment cost, as well as constraints such as wind power output constraints, energy conversion equipment operation constraints, energy storage operation constraints and electricity, heat, gas and hydrogen power balance constraints.

[0013] The piecewise linearization and mixed integer linear programming methods are used to solve the model, and the Yalmip toolbox and CPLEX solver configured by MATLAB are used for optimization calculation.

[0014] As a preferred solution of the park comprehensive energy low-carbon economic optimization scheduling method considering the full-cycle carbon emissions described in the present invention, the carbon emission quota model in the ladder carbon trading mechanism of the full-cycle carbon emissions is as follows:

[0015]

[0016] Where: E PIES 、E e,buy 、E CHP 、E GB are the carbon emission quotas of PIES, power purchase from higher authorities, CHP, and GB, respectively. e , χ g are the carbon emission quotas per unit electricity consumption of a single coal-fired unit and per unit natural gas consumption of a natural gas-fired unit; P e,buy (t) is the power purchased by the superior during period t; P GB,h (t) is the thermal energy output by GB during period t; T is the scheduling period.

[0017] The actual carbon emission model in the ladder carbon trading mechanism of the whole cycle carbon emission is as follows:

[0018]

[0019] Where: E PIES,a ,E e,buy,a ,EG,a ,E W,a ,E MR,a are the actual carbon emissions of PIES, upstream power purchase, CHP, wind turbines and methane reactors; ω is the CO2 absorption parameter in the process of converting hydrogen into natural gas in the MR equipment. Therefore, the actual carbon emission trading volume ΔE PIES for:

[0020] ΔE PIES =E PIES,a -E PIES

[0021] The ladder carbon trading model in the ladder carbon trading mechanism of the whole cycle carbon emissions is as follows:

[0022]

[0023] Where: is the full-cycle carbon trading cost; λ is the unit carbon price; ξ is the price growth rate; l is the length of the carbon emission interval.

[0024] As a preferred solution of the park comprehensive energy low-carbon economic optimization scheduling method considering the full-cycle carbon emissions described in the present invention, the total operating cost F objective function including the energy purchase cost, the full-cycle step-by-step carbon trading cost and the wind abandonment cost is shown as follows:

[0025]

[0026] Where: f buy For energy purchase cost, is the full-cycle tiered carbon trading cost, The cost of purchasing energy f is the cost of abandoning wind power buy As shown below:

[0027]

[0028] Where: P e,buy , P g,buy (t) are the electricity and gas purchases during period t; α t , β t are the electricity price and gas price in period t respectively.

[0029] The full-cycle tiered carbon trading costs Described in the ladder carbon trading model.

[0030] The cost of wind curtailment As shown below:

[0031]

[0032] Where:DG P is the penalty cost for unit wind curtailment; DG,cut (t) is the wind power abandoned during period t.

[0033] As an optimal solution of the method for optimizing the low-carbon economy of comprehensive energy in a park taking into account full-cycle carbon emissions as described in the present invention, the constraints include wind power output constraints, energy conversion equipment operation constraints, energy storage operation constraints, and electricity, heat, gas, and hydrogen power balance constraints.

[0034] The wind power output constraint is as follows:

[0035]

[0036] Where: P DG (t)) is the wind power output power in period t; The upper limit of wind power output.

[0037] The energy conversion equipment operation constraints include EL, HFC, MR, CHP, and GB constraints as shown below:

[0038] The EL constraint is as follows:

[0039]

[0040] Where: P e,EL (t) is the electric energy input to EL during period t; is the hydrogen energy output by EL during period t; η EL is the energy conversion efficiency of EL; They are the upper and lower limits of the electric energy of the input EL respectively; They are the upper and lower limits of EL climbing respectively.

[0041] The HFC constraint is as follows:

[0042]

[0043] Where: P H2 , HFC (t) is the hydrogen energy input into HFC during period t; P HFC ,e(t),P HFC ,h(t) are the electricity and heat energy output by HFC in period t respectively; are the efficiency of HFC conversion into electricity and heat, respectively; They are the upper and lower limits of hydrogen energy for input HFC respectively; They are the upper and lower limits of HFC climbing respectively; They are the upper and lower limits of the heat-to-electricity ratio of HFC respectively.

[0044] The MR constraint is as follows:

[0045]

[0046] Where: P is the hydrogen energy of MR input during period t; MR,g (t) is the natural gas power output by MR during period t; η MR is the energy conversion efficiency of MR; are the upper and lower limits of hydrogen energy input to MR, respectively; They are the upper and lower limits of MR climbing respectively.

[0047] The CHP constraint is as follows:

[0048]

[0049] Where: P g,CHP P is the natural gas power input to CHP during period t; CHP,e , P CHP,h are the electricity and heat energy output by CHP during period t, respectively; are the efficiency of CHP conversion into electricity and heat, respectively; They are the upper and lower limits of natural gas power input to CHP respectively; They are the upper and lower limits of CHP climbing respectively; They are the upper and lower limits of the thermal-to-electricity ratio of CHP respectively.

[0050] The GB constraint is as follows:

[0051]

[0052] Where: η GB is the energy conversion efficiency of GB; P g,GB (t) is the power input to GB during period t; P GB,h is the thermal power output of GB during period t; They are the upper and lower limits of GB input power respectively; They are the upper and lower limits of GB’s climbing slope respectively.

[0053] The energy storage device operation constraints are as follows:

[0054] Energy storage devices have similar structures. Taking electric energy storage devices as an example, constraints are established, and the heat, gas, and hydrogen storage conditions are the same.

[0055]

[0056] Where: are the charging and discharging powers of the nth type of energy storage device during period t respectively; The maximum single charge and discharge power of the nth energy storage device; are binary variables, which are the charging and discharging state parameters of the nth energy storage device in period t. Indicates that it is in charging state. Indicates that it is in the state of releasing energy; P ES,n (t) is the final output power of the nth energy storage device during period t; are the charging and discharging efficiencies of the nth energy storage device; S n (t) is the capacity of the nth energy storage device during time period t; is the rated capacity of the nth type of energy storage device; They are respectively the upper and lower limits of the capacity of the nth type of energy storage device.

[0057] The electricity, heat, gas and hydrogen balance constraints are as follows:

[0058] Considering the large randomness and volatility of wind power, in order to reduce the pressure on the main grid, this paper does not consider PIES selling electricity to the upper-level power grid and gas to the upper-level gas grid.

[0059]

[0060] Where: P e_load (t) is the electrical load during period t; P is the power input to the storage during period t; h_load (t) is the heat load during period t; P is the power input to the heat storage during period t; g_load (t) is the gas load during period t; The power of natural gas storage input for period t; The power input to the hydrogen storage during period t; The power purchase limit for each time period; It is the gas purchase limit for each time period.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] It comprehensively considers carbon emissions in the processes of energy production, transportation, conversion and use, and improves the comprehensiveness and accuracy of carbon emission management.

[0063] By optimizing scheduling, lower carbon emissions and economic costs are achieved, promoting the low-carbon transformation of the park's energy system.

[0064] The use of advanced mathematical programming methods and tools has improved the efficiency and accuracy of solving scheduling models. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0066] Figure 1 The schematic diagram of the structure of the park comprehensive energy system is a park comprehensive energy scheduling method for full-cycle carbon emission ladder carbon trading.

[0067] Figure 2 This is a load and fan prediction diagram for a comprehensive energy scheduling method for a park with a full-cycle carbon emission ladder carbon trading.

[0068] Figures 3 to 6 Schematic diagram of the electricity, heat, gas and hydrogen balance of the park's comprehensive energy system DETAILED DESCRIPTION

[0069] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0071] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0072] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0073] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the 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 direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0074] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0075] Example 1

[0076] Reference Figures 1 to 6 , which is the first embodiment of the present invention, and provides a low-carbon economic dispatching method for a park integrated energy system considering full-cycle carbon emissions, including:

[0077] S1: Establish the operation framework of the park's comprehensive energy system, in which the load side includes electricity, gas, and heat loads. The energy conversion part includes gas turbines, gas boilers, and two-stage power-to-gas equipment. The power load in the system is provided by wind turbines WT, gas turbines GT, energy storage equipment, and large power grids. The heat load is provided by gas turbines GT, gas boilers GB, and heat storage equipment. At the same time, electrolyzers EL, hydrogen fuel cells HFC, and methane reactors MR are important components for realizing two-stage power-to-gas, which can produce hydrogen and methane to supply gas loads.

[0078] S2: Construct a tiered carbon trading mechanism that takes into account full-cycle carbon emissions, covering carbon emission quota model, actual carbon emission model and tiered carbon trading model.

[0079] Carbon emission quota model:

[0080]

[0081] Where: E PIES 、E e,buy 、E CHP 、E GB are the carbon emission quotas of PIES, power purchase from higher authorities, CHP, and GB, respectively. e , χ g are the carbon emission quotas per unit electricity consumption of a single coal-fired unit and per unit natural gas consumption of a natural gas-fired unit; P e,buy(t) is the power purchased by the superior during period t; P GB,h (t) is the thermal energy output by GB during period t; T is the scheduling period.

[0082] Actual carbon emission model:

[0083]

[0084] Where: E PIES,a ,E e,buy,a ,E G,a ,E W,a ,E MR,a are the actual carbon emissions of PIES, upstream power purchase, CHP, wind turbines and methane reactors; ω is the CO2 absorption parameter in the process of converting hydrogen into natural gas in the MR equipment. Therefore, the actual carbon emission trading volume ΔE PIES for:

[0085] ΔE PIES =E PIES,a -E PIES

[0086] Ladder carbon trading model:

[0087]

[0088] Where: f CO2 is the full-cycle carbon trading cost; λ is the unit carbon price; ξ is the price growth rate; l is the length of the carbon emission interval.

[0089] S3: Establish a low-carbon economic optimization model for the park’s integrated energy system and construct corresponding constraints.

[0090] Optimization goal: Minimize the total operating cost consisting of energy purchase cost, full-cycle carbon trading cost, and wind abandonment cost:

[0091]

[0092] Where: F is the total operating cost; f buy The cost of purchasing energy; is the full-cycle carbon trading cost; The cost of wind curtailment.

[0093] Energy purchase cost:

[0094]

[0095] Where: P e,buy , P g,buy (t) are the electricity and gas purchases during period t; α t , β t are the electricity price and gas price in period t respectively.

[0096] Full-cycle tiered carbon trading costs CO2 Already described in the step-by-step carbon trading model in step 2.

[0097] Cost of curtailment

[0098]

[0099] Where: DG P is the penalty cost for unit wind curtailment; DG,cut (t) is the wind power abandoned during period t.

[0100] Constraints: wind power output constraints, energy conversion equipment operation constraints, energy storage operation constraints, and electricity, heat, gas, and hydrogen power balance constraints.

[0101] Wind power output constraints:

[0102]

[0103] Where: P DG (t)) is the wind power output power in period t; The upper limit of wind power output.

[0104] Energy conversion equipment operation constraints include EL, HFC, MR, CHP, and GB constraints:

[0105] EL Constraints:

[0106]

[0107] Where: P e,EL (t) is the electric energy input to EL during period t; is the hydrogen energy output by EL during period t; η EL is the energy conversion efficiency of EL; They are the upper and lower limits of the electric energy of the input EL respectively; They are the upper and lower limits of EL climbing respectively.

[0108] HFC Constraints:

[0109]

[0110] Where: P is the hydrogen energy input into HFC during period t; HFC,e (t), P HFC,h (t) are the electricity and heat energy output by HFC in period t, respectively; are the efficiency of HFC conversion into electricity and heat, respectively; They are the upper and lower limits of hydrogen energy for input HFC respectively; They are the upper and lower limits of HFC climbing respectively; They are the upper and lower limits of the heat-to-electricity ratio of HFC respectively.

[0111] MR Constraints:

[0112]

[0113] Where: P is the hydrogen energy of MR input during period t; MR,g (t) is the natural gas power output by MR during period t; η MR is the energy conversion efficiency of MR; are the upper and lower limits of hydrogen energy input to MR, respectively; They are the upper and lower limits of MR climbing respectively.

[0114] CHP Constraints:

[0115]

[0116] Where: P g,CHP P is the natural gas power input to CHP during period t; CHP,e , P CHP,h are the electricity and heat energy output by CHP during period t, respectively; are the efficiency of CHP conversion into electricity and heat, respectively; They are the upper and lower limits of natural gas power input to CHP respectively; They are the upper and lower limits of CHP climbing respectively; They are the upper and lower limits of the thermal-to-electricity ratio of CHP respectively.

[0117] GB Constraint:

[0118]

[0119] Where: η GB is the energy conversion efficiency of GB; P g,GB (t) is the power input to GB during period t; P GB,h is the thermal power output of GB during period t; They are the upper and lower limits of GB input power respectively; They are the upper and lower limits of GB’s climbing slope respectively.

[0120] Energy storage equipment operation constraints include electric heat, gas, hydrogen, and energy storage constraints:

[0121] Energy storage devices have similar structures. Taking electric energy storage devices as an example, constraints are established, and the heat, gas, and hydrogen storage conditions are the same.

[0122]

[0123] Where: are the charging and discharging powers of the nth type of energy storage device during period t respectively; The maximum single charge and discharge power of the nth energy storage device; are binary variables, which are the charging and discharging state parameters of the nth energy storage device in period t. Indicates that it is in charging state. Indicates that it is in the state of releasing energy; P ES,n (t) is the final output power of the nth energy storage device during period t; are the charging and discharging efficiencies of the nth energy storage device; S n (t) is the capacity of the nth energy storage device during time period t; is the rated capacity of the nth type of energy storage device; They are respectively the upper and lower limits of the capacity of the nth type of energy storage device.

[0124] The electricity, heat, gas and hydrogen balance constraints are as follows:

[0125] Considering the large randomness and volatility of wind power, in order to reduce the pressure on the main grid, this paper does not consider PIES selling electricity to the upper-level power grid and gas to the upper-level gas grid.

[0126]

[0127] Where: P e_load (t) is the electrical load during period t; P is the power input to the storage during period t; h_load (t) is the heat load during period t; P is the power input to the heat storage during period t; g_load (t) is the gas load during period t; The power of natural gas storage input for period t; The power input to the hydrogen storage during period t; The power purchase limit for each time period; It is the gas purchase limit for each time period.

[0128] S4: The model is solved by piecewise linearization and mixed integer linear programming methods, and the Yalmip toolbox and CPLEX solver configured by MATLAB are used for optimization calculation. The effectiveness of the ladder carbon trading mechanism considering the full-cycle carbon emissions is verified to achieve low-carbon economic dispatch of the park's integrated energy system.

[0129] Table 1 Comparison of benefits of full-cycle tiered carbon trading mechanisms

[0130]

[0131]

[0132] In order to verify the effectiveness of the full-cycle step-by-step carbon trading mechanism proposed in this paper, let the interval length l = 2t, the price growth rate ξ = 30%, the carbon trading base price λ = 300 yuan / t, and set three operation scenarios for comparative analysis. Scenario 1 is a traditional economic dispatch scenario under the full-cycle step-by-step carbon trading mechanism, where the optimization target does not consider the carbon trading cost, but only considers the energy purchase cost and wind abandonment cost; Scenario 2 is a low-carbon economic dispatch scenario under the traditional step-by-step carbon trading mechanism, where the optimization target considers the energy purchase cost, carbon trading cost, and wind abandonment cost; Scenario 3 is a low-carbon economic dispatch scenario under the full-cycle step-by-step carbon trading mechanism, where the optimization target considers the energy purchase cost, carbon trading cost, and wind abandonment cost. Table 1 shows the dispatch results under the three operation scenarios. It can be seen from the table that the carbon emissions when the optimization target considers the carbon trading cost are much smaller than when the optimization target does not consider the carbon trading cost. Among them, the carbon emissions in Scenario 2 were reduced by 19.96% compared with Scenario 1; the carbon emissions in Scenario 3 were reduced by 22.95% compared with Scenario 1, and Scenario 3 reduced carbon emissions by 732kg, or 3.73%, compared with Scenario 2. It can be seen that the full-cycle tiered carbon trading mechanism can constrain carbon emissions to a greater extent and achieve better emission reduction benefits compared with the traditional tiered carbon trading mechanism.

[0133] Combining the time-of-use electricity price and gas price, it can be seen that scenario 1 takes the traditional economic operation optimization as its goal. Since the gas price in each period is cheaper than the electricity price, the system will purchase as much natural gas as possible to supply power to the electrical load through CHP, so the total energy purchase cost is minimized. However, the large-scale purchase of natural gas results in the actual carbon emissions generated by burning natural gas far exceeding the carbon emission quota. Combined with the actual carbon emission model, it can be seen that when the combustion of natural gas reaches a certain level, continuing to burn natural gas will greatly increase carbon emissions. This is the reason why Scenario 1 has a lot of carbon emissions. At this time, a large amount of carbon emission quotas need to be purchased from the carbon trading market, so the total cost is the largest; Scenario 2 takes into account the carbon trading cost during optimization. Due to the use of a stepped carbon trading method, the purchase price of its carbon emission quota increases in a step-by-step manner. Although purchasing gas is cheaper than purchasing electricity, since the system is burning natural gas at this time, the cost saved by choosing to purchase gas instead of purchasing electricity is already lower than the cost of purchasing carbon emission quotas from the carbon trading market due to the high carbon emissions generated by burning natural gas. Therefore, compared with Scenario 1, Scenario 2 reduces gas purchases and increases electricity purchases; and due to the full-cycle stepped carbon trading mechanism in Scenario 3, the actual carbon emission model takes into account the carbon emissions in the production, transportation, conversion and use of energy in the system. At the same time, the purchase price of carbon emission quotas also increases in a step-by-step manner, which further limits the system's carbon emissions to a certain extent. Therefore, Scenario 3 reduces gas purchases again and increases electricity purchases to reach a new balance. At this time, the electricity, heat, gas and hydrogen balances of the park's comprehensive energy system are Figure 3 ,4,5,6. Time-of-use electricity prices, equipment parameters, and energy storage equipment parameters are shown in Tables 2 to 4

[0134] Table 2 Time-of-use electricity prices

[0135]

[0136] Table 3 Equipment parameters

[0137]

[0138] Table 4 Energy storage equipment parameters

[0139]

[0140] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A comprehensive energy scheduling method for a park with full-cycle carbon emission ladder carbon trading, characterized in that: The following steps are involved: 1) Establish the operation framework of the park's comprehensive energy system, including electricity, gas, heat loads and energy conversion parts, such as gas turbines, gas boilers, two-stage power-to-gas equipment, etc.; 2) Construct a tiered carbon trading mechanism that takes into account full-cycle carbon emissions, covering carbon emission quota model, actual carbon emission model and tiered carbon trading model; 3) Establish a comprehensive energy low-carbon economic optimization operation model for the park that takes into account the full-cycle tiered carbon trading mechanism. Includes objective function and constraints; 4) Solve the low-carbon economic dispatch model of the park's integrated energy system to obtain the objective function that optimizes the total system cost, verify the effectiveness of the proposed step-by-step carbon trading mechanism that considers the entire carbon cycle, and achieve low-carbon economic dispatch of the park's integrated energy system.

2. The scheduling method according to claim 1, characterized in that: The operation framework of the park's comprehensive energy system includes electricity, gas, heat loads and energy conversion parts. The energy conversion part includes gas turbines, gas boilers, and two-stage power-to-gas equipment.

3. The scheduling method according to claim 1, characterized in that: The ladder carbon trading mechanism that takes full-cycle carbon emissions into consideration includes a carbon emission quota model, an actual carbon emission model and a ladder carbon trading model. The carbon emission quota model is shown as follows: There are three main sources of carbon emissions: electricity purchased from higher authorities, GB, and CHP. At present, the main quota method used in China is free quota, and it is believed that electricity purchased from higher authorities comes from coal-fired units: Where: E PIES 、E e,buy 、E CHP 、E GB are the carbon emission quotas of PIES, power purchase from higher authorities, CHP, and GB, respectively. e , χ g are the carbon emission quotas per unit electricity consumption of a single coal-fired unit and per unit natural gas consumption of a natural gas-fired unit; P e,buy (t) is the power purchased by the superior during period t; P GB,h (t) is the heat energy output by GB during period t; T is the scheduling period; The actual carbon emission model is as follows: Where: E PIES,a ,E e,buy,a ,E G,a ,E W,a ,E MR,a are the actual carbon emissions of PIES, upstream power purchase, CHP, wind turbines and methane reactors; ω is the CO2 absorption parameter in the process of converting hydrogen into natural gas in the MR equipment. Therefore, the actual carbon emission trading volume ΔE PIES for: ΔE PIES =E PIES,a -E PIES The ladder carbon trading model considering the full-cycle carbon emissions is as follows: Where: is the full-cycle carbon trading cost; λ is the unit carbon price; ξ is the price growth rate; l is the length of the carbon emission interval.

4. The scheduling method according to claim 1, characterized in that: The objective function of the park comprehensive energy low-carbon economic optimization operation model includes energy purchase cost, full-cycle step-by-step carbon trading cost and wind abandonment cost. The objective function is shown in the following formula: Where: f buy For energy purchase cost, is the full-cycle tiered carbon trading cost. The energy purchase cost for wind curtailment cost is as follows: Where: P e,buy , P g,buy (t) are the electricity and gas purchases during period t; α t , β t are the electricity price and gas price in period t, The full-cycle tiered carbon trading cost is described in claim 3. The wind curtailment cost is shown in the following formula: Where: DG P is the penalty cost for unit wind curtailment; DG,cut (t) is the wind power abandoned during period t.

5. The scheduling method according to claim 1, characterized in that: The constraints of the model include wind power output constraints, energy conversion equipment operation constraints, energy storage operation constraints, and electricity, heat, gas, and hydrogen power balance constraints. The wind power output constraint is as follows: Where: P DG (t)) is the wind power output power in period t; is the upper limit of wind power output power; The energy conversion equipment operation constraints include EL, HFC, MR, CHP, and GB constraints as shown below: 1) EL Constraints Where: P e,EL (t) is the electric energy input to EL during period t; is the hydrogen energy output by EL during period t; η EL is the energy conversion efficiency of EL; They are the upper and lower limits of the electric energy of the input EL respectively; They are the upper and lower limits of EL climbing respectively; 2) HFC constraints Where: P is the hydrogen energy input into HFC during period t; HFC,e (t), P HFC,h (t) are the electricity and heat energy output by HFC in period t, respectively; are the efficiency of HFC conversion into electricity and heat, respectively; They are the upper and lower limits of hydrogen energy for input HFC respectively; They are the upper and lower limits of HFC climbing respectively; They are the upper and lower limits of the heat-to-power ratio of HFC respectively; 3) MR Constraints Where: P is the hydrogen energy of MR input during period t; MR,g (t) is the natural gas power output by MR during period t; η MR is the energy conversion efficiency of MR; are the upper and lower limits of hydrogen energy input to MR, respectively; They are the upper and lower limits of MR climbing respectively; 4) CHP Constraint Where: P g,CHP P is the natural gas power input to CHP during period t; CHP,e , P CHP,h are the electricity and heat energy output by CHP during period t, respectively; are the efficiency of CHP conversion into electricity and heat, respectively; They are the upper and lower limits of natural gas power input to CHP respectively; They are the upper and lower limits of the CHP climbing slope, respectively; They are the upper and lower limits of the thermal-to-electricity ratio of CHP, respectively; 5) GB Constraints The energy storage operation constraints are as follows: Where: η GB is the energy conversion efficiency of GB; P g,GB (t) is the power input to GB during period t; P GB,h is the thermal power output of GB during period t; They are the upper and lower limits of GB input power respectively; They are the upper and lower limits of GB climbing respectively; The energy storage equipment operation constraints include electricity, heat, gas, and hydrogen energy storage constraints as shown in the following formula: Energy storage devices have similar structures. Taking electric energy storage devices as an example, constraints are established, and the heat, gas, and hydrogen storage conditions are the same. Where: are the charging and discharging powers of the nth type of energy storage device during period t respectively; The maximum single charge and discharge power of the nth energy storage device; are binary variables, which are the charging and discharging state parameters of the nth energy storage device in period t. Indicates that it is in charging state. Indicates that it is in a state of releasing energy; P ES,n (t) is the final output power of the nth energy storage device during period t; are the charging and discharging efficiencies of the nth energy storage device; S n (t) is the capacity of the nth energy storage device during time period t; is the rated capacity of the nth type of energy storage device; are the upper and lower limits of the capacity of the nth type of energy storage device, respectively; The electricity, heat, gas and hydrogen balance constraints are as follows: Considering the large randomness and volatility of wind power, in order to reduce the pressure on the main grid, this paper does not consider PIES selling electricity to the upper grid and gas to the upper gas grid. Where: P e_load (t) is the electrical load during period t; P is the power input to the storage during period t; h_load (t) is the heat load during period t; P is the power input to the heat storage during period t; g_load (t) is the gas load during period t; The power of natural gas storage input for period t; The power input to the hydrogen storage during period t; The power purchase limit for each time period; It is the gas purchase limit for each time period.

6. The scheduling method according to claim 1, characterized in that: The model is solved by piecewise linearization and mixed integer linear programming methods, and is solved by the Yalmip toolbox and CPLEX solver configured in MATLAB.

7. A park integrated energy system for implementing the method according to any one of claims 1 to 6, characterized in that: Includes software and hardware components for performing the methods.

8. A computer program product, characterized in that The program is designed to implement the park comprehensive energy low-carbon economic optimization scheduling method as described in any one of claims 1 to 6, and is stored on a computer-readable medium.

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