An optimal scheduling method for a multi-regional integrated energy system considering carbon emission reduction

Abstract

This invention discloses an optimal scheduling method for multi-regional integrated energy systems that considers carbon emission reduction. The method aims to tap the carbon reduction potential of carbon trading in the scheduling problem of multi-regional integrated energy systems. It proposes a joint calculation model for carbon trading costs, then constructs a comprehensive scheduling model for the multi-regional integrated energy system considering carbon emission reduction, and finally solves this model to obtain the optimal scheduling plan. This invention considers the purchase ceiling of carbon emission rights during carbon trading and the supply and demand interaction between different regional integrated energy systems. It not only improves the carbon reduction capacity of low-carbon emission intensity systems in multi-regional integrated energy systems but also reduces the economic costs of high-carbon emission intensity systems. This provides guidance for the optimized production, operation, and carbon emission reduction of multi-regional integrated energy systems.

Description

Technical Field

[0001] This invention relates to a scheduling method for integrated energy utilization, specifically to a scheduling method for a multi-regional integrated energy system that takes carbon emission reduction factors into account. Background Technology

[0002] Against the backdrop of vigorously developing a low-carbon economy, setting the "dual carbon" goals of achieving carbon peaking and carbon neutrality, and launching a carbon trading market, have become new driving forces for accelerating the green and low-carbon transformation of economic development. As an important vehicle for implementing energy conservation and emission reduction, regional integrated energy systems (RIES) incorporate carbon trading costs into the factors affecting the optimal operation of the system, which can not only reduce the system's carbon emissions but also ensure good economic efficiency. However, in the scheduling problem of multi-regional integrated energy systems, the carbon trading costs of RIES are often calculated independently. While this achieves a good balance between the economic efficiency and low carbon emissions of each RIES, the overall economic efficiency and low carbon emissions of the multi-regional integrated energy system are not optimal. Therefore, it is necessary to further explore the carbon reduction potential of carbon trading in multi-regional integrated energy systems and formulate new scheduling plans. Summary of the Invention

[0003] The purpose of this invention is to address the shortcomings of existing technologies and propose an optimized scheduling method for multi-regional integrated energy systems that considers carbon emission reduction in order to explore the carbon reduction potential of carbon trading in the scheduling problem of multi-regional integrated energy systems.

[0004] The objective of this invention is achieved through the following technical solution:

[0005] An optimal scheduling method for a multi-regional integrated energy system considering carbon emission reduction is proposed. The method first constructs a joint calculation model of carbon trading costs for the multi-regional integrated energy system by taking into account the supply and demand interaction of carbon emission rights in the carbon trading market; then constructs an optimal scheduling model with the goal of minimizing total cost; and finally obtains the optimal scheduling result of the multi-regional integrated energy system by solving the optimal scheduling model.

[0006] The optimization scheduling method for multi-regional integrated energy systems that considers carbon emission reduction, as described above, includes the following construction of the joint calculation model for carbon trading costs:

[0007] The baseline method is used to calculate the free carbon allowance for a single RIES:

[0008]

[0009] In the formula, E is the carbon quota for a single RIES; λ e It is the free carbon allowance coefficient per unit of electricity generated; t represents the time period; Ω GIt is a collection of coal-fired generators in RIES; k is the generator number; P Gk,t It is the power output of a coal-fired generator; λ h It is the free carbon quota coefficient per unit of heat supply; K is the conversion factor for converting electricity generation into heat supply; It is the power generation capacity of the combined heat and power unit; It is the heating capacity of the combined heat and power unit; It refers to the heating capacity of the gas-fired boiler.

[0010] Calculate the carbon emissions of a single RIES:

[0011]

[0012] In the formula, D represents the carbon emissions of a single RIES; λ Gk It is the carbon emission coefficient of generator k; This refers to the operating power of the carbon capture system equipped with generator k. When generator k is a coal-fired unit... λ r It is the amount of electricity required by the carbon capture system to capture a unit of carbon emissions; λ P2G It is the conversion coefficient of the electro-pneumatic equipment; P P2G,t It is the power consumption of the electro-gas conversion equipment; λ CHP It is the carbon emission coefficient of the combined heat and power unit; λ GB It is the carbon emission coefficient of a gas-fired boiler.

[0013] The above-mentioned optimized scheduling method for a multi-regional integrated energy system considering carbon emission reduction requires that the carbon emission rights purchase cap in the carbon market be considered when a single RIES conducts carbon trading. Therefore, the carbon trading cost calculation formula for the i-th RIES in the multi-regional integrated energy system is as follows:

[0014]

[0015] In the formula, y car,i C is the carbon trading cost of the i-th RIES; car It is the carbon price; D i and E i These are the carbon emissions and carbon allowance for the i-th RIES, respectively; τ is the ratio of the penalty price to the carbon price; D b,i It refers to the amount of carbon emission rights purchased; D c,i It is the upper limit for purchasing carbon emission rights.

[0016] The above-mentioned optimal scheduling method for multi-regional integrated energy systems considering carbon emission reduction takes into account the interaction between the supply and demand of carbon emission rights among the various RIES within the multi-regional integrated energy system. Therefore, the carbon emission right purchase ceiling of the i-th RIES is jointly determined by the other RIES in the multi-regional integrated energy system. Thus, the joint calculation formula for the carbon trading cost of the i-th RIES is as follows:

[0017]

[0018] In the formula, n is the set of RIES; D j and E j These are the carbon emissions and carbon allowances for the j-th RIES, respectively; The carbon emission rights sold by other RIES to the carbon market determine the carbon emission rights purchase limit for the i-th RIES.

[0019] Linearizing the above equation, we have:

[0020]

[0021] In the formula, m1 and m2 are infinite positive numbers; n1 and n2 are two 0-1 decision variables.

[0022] The above-mentioned optimization scheduling method for multi-regional integrated energy systems that considers carbon emission reduction, when constructing an optimization scheduling model for multi-regional integrated energy systems with the goal of minimizing total cost, includes constraints on generator operation, wind power output, photovoltaic power generation, natural gas transmission, power-to-gas conversion equipment, electric boilers, combined heat and power units, gas boilers, energy storage devices, and power balance constraints on electric load, heat load, and gas load.

[0023] The above-mentioned optimization scheduling method for a multi-regional integrated energy system considering carbon emission reduction uses the commercial solver GUROBI to solve the optimization model.

[0024] Beneficial effects

[0025] This invention proposes an optimal scheduling method for multi-regional integrated energy systems that considers carbon emission reduction. Based on a comprehensive consideration of the purchase ceiling of carbon emission rights during carbon trading and the supply and demand interaction between different regional integrated energy systems, this method constructs a joint calculation model for carbon trading costs and builds an optimal scheduling model for multi-regional integrated energy systems with the objective of minimizing total costs. This invention strengthens the connection between integrated energy systems and carbon trading, considering energy optimal scheduling in conjunction with the power generation, operation, carbon emissions, and emission costs of different regional integrated energy systems. It explores the carbon reduction potential of carbon trading in multi-regional integrated energy system scheduling problems, improves the calculation of carbon trading costs, and reduces system carbon emissions while ensuring good system economics. Attached Figure Description

[0026] The invention will now be further described with reference to the accompanying drawings.

[0027] Figure 1 This is a structural diagram of the three-zone integrated energy system of the present invention;

[0028] Figure 2 Forecast the load power of RIES1;

[0029] Figure 3 Forecasting wind power, solar power generation, and load power for RIES2;

[0030] Figure 4 For RIES3, wind power, solar power generation, and load power prediction;

[0031] Figure 5 The power optimization scheduling results for RIES1;

[0032] Figure 6 The power optimization scheduling results for RIES2;

[0033] Figure 7 The power optimization scheduling results for RIES3. Detailed Implementation

[0034] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0035] See Figure 1 This invention illustrates a three-region integrated energy system, where each RIES purchases natural gas from a natural gas network. RIES1's electricity is entirely derived from coal-fired power plants, resulting in high carbon emission intensity; RIES2's electricity is derived from coal-fired power plants, wind power, and photovoltaic power, resulting in moderate carbon emission intensity; and RIES3's electricity is derived from carbon capture units, wind power, and photovoltaic power, resulting in low carbon emission intensity. The multi-region integrated energy system optimization scheduling method in this invention includes the following steps:

[0036] Step 1: Construct a joint calculation model for carbon trading costs, considering carbon emission reduction;

[0037] (1) Calculation of free carbon allowances for RIES based on the baseline method:

[0038]

[0039] In the formula, E is the carbon quota for a single RIES; λ e It is the free carbon allowance coefficient per unit of electricity generated; t represents the time period; Ω G It is a collection of coal-fired generators in RIES; k is the generator number; P Gk,t It is the power output of a coal-fired generator; λ h It is the free carbon quota coefficient per unit of heat supply; K is the conversion factor for converting electricity generation into heat supply; It is the power generation capacity of the combined heat and power unit; It is the heating capacity of the combined heat and power unit; It refers to the heating capacity of the gas-fired boiler.

[0040] (2) Calculate the carbon emissions of RIES:

[0041]

[0042] In the formula, D represents the carbon emissions of a single RIES; λ Gk It is the carbon emission coefficient of generator k; This refers to the operating power of the carbon capture system equipped with generator k. When generator k is a coal-fired unit... λ r It is the amount of electricity required by the carbon capture system to capture a unit of carbon emissions; λ P2G It is the conversion coefficient of the electro-pneumatic equipment; P P2G,t It is the power consumption of the electro-gas conversion equipment; λ CHP It is the carbon emission coefficient of the combined heat and power unit; λ GB It is the carbon emission coefficient of a gas-fired boiler.

[0043] (3) When trading RIES carbon credits, the carbon emission rights purchase cap in the carbon market must be considered, and the amount of carbon emission rights purchased cannot exceed this cap. Based on this, the carbon trading cost of the i-th RIES is calculated as follows:

[0044]

[0045] In the formula, y car,i C is the carbon trading cost of the i-th RIES; car It is the carbon price; D i and E i These are the carbon emissions and carbon allowance for the i-th RIES, respectively; τ is the ratio of the penalty price to the carbon price; D b,i It refers to the amount of carbon emission rights purchased; D c,i It is the upper limit for purchasing carbon emission rights.

[0046] (4) During carbon trading, there is an interaction between the supply and demand of carbon emission rights among the various RIES in the multi-regional integrated energy system. The carbon emission right purchase limit of the i-th RIES is jointly determined by the other RIES in the multi-regional integrated energy system. Based on this, the carbon trading cost of the i-th RIES is jointly calculated based on (3):

[0047]

[0048] In the formula, n is the set of RIES; D j and E j These are the carbon emissions and carbon allowances for the j-th RIES, respectively; The carbon emission rights sold by other RIES to the carbon market determine the carbon emission rights purchase limit for the i-th RIES.

[0049] (5) Linearize equation (4) to reduce computational difficulty:

[0050] D v,i =max{D i -E i -D b,i To linearize the process, we introduce an infinite positive number m1 and a 0-1 decision variable n1:

[0051]

[0052] When n1 = 0, we have: D i -E i -D b,i ≤0, D v,i =0;

[0053] When n1 = 1, we have: D i -E i -D b,i ≥0,D v,i =D i -E i -D b,i ;

[0054] Similarly, for Introducing an infinite positive number m² and a 0-1 decision variable n² for processing:

[0055]

[0056] Substituting equations (5) and (6) into equation (4) yields the linearized joint calculation formula for carbon trading costs:

[0057]

[0058] Step 2: Construct a multi-regional integrated energy system scheduling model with the goal of minimizing total cost;

[0059] (1) Objective function for optimal scheduling of multi-regional integrated energy systems considering carbon emission reduction:

[0060]

[0061]

[0062]

[0063]

[0064]

[0065] y G,i It is the power generation cost of the i-th RIES; α i,kβ i,k and δ i,k These are the fuel cost coefficients for coal-fired generator k in the i-th RIES; P i,Gk,t Let C be the power of coal-fired unit k in the i-th RIES; cap For carbon capture prices; Let C be the operating power of the carbon capture system of the coal-fired generator k in the i-th RIES; i,Gk This is the unit start-up cost coefficient; u i,Gk,t This represents a 0-1 variable for unit start-up and shutdown; in this invention, the carbon capture unit is formed by adding a carbon capture system to a coal-fired unit. When there is no carbon capture unit in the RIES... Conversely, the power generation cost of a carbon capture unit is the sum of the power generation cost of a coal-fired unit and the operating cost of the carbon capture system.

[0066] y new,i P is the cost of renewable energy generation for the i-th RIES; i,w,t and These are the actual and predicted power outputs of the i-th RIES wind power generation, respectively; P i,pv,t and These are the actual power and predicted power of the i-th RIES photovoltaic power generation, respectively; C iw and C ipv These are the operation and maintenance prices for the i-th RIES wind power and photovoltaic power generation, respectively; and These are the wind and solar curtailment penalty prices for the i-th RIES wind power and solar power generation, respectively.

[0067] y g,i C is the natural gas purchase cost of the i-th RIES; gas P represents the unit price of natural gas. i,g,t Let q be the gas purchasing power of the i-th RIES; gas It represents the lower heating value of natural gas.

[0068] y ou,i C is the maintenance cost of the coupled device of the i-th RIES; P2G C EB C CHP and C GB The respective operation and maintenance prices are for power-to-gas conversion equipment, electric boilers, combined heat and power units, and gas-fired boilers; P i,P2G,t P i,EB,t P i,CHP,t and P i,GB,t These represent the input power of the i-th RIES electric-to-gas conversion device, electric boiler, combined heat and power unit, and gas boiler, respectively.

[0069] y car,i It is the carbon trading cost of the i-th RIES, and the calculation formula is detailed in equations (1)-(7).

[0070] (2) Model constraints

[0071] The constraints of the multi-regional integrated energy system optimization scheduling model considering carbon emission reduction include generator operation constraints, wind power output constraints, photovoltaic power generation constraints, natural gas transmission constraints, power-to-gas equipment constraints, electric boiler constraints, combined heat and power unit constraints, gas boiler constraints, energy storage device constraints, electricity load balance constraints, heat load balance constraints, and gas load balance constraints.

[0072] Step 3: Solve the multi-region integrated energy system optimization scheduling model to obtain the optimal scheduling result.

[0073] Example

[0074] The present invention is illustrated using a three-zone integrated energy system as an example.

[0075] A three-zone integrated energy system, such as Figure 1 As shown, the proposed model is validated. Figure 2 Forecasting the electricity, heat, and gas loads for RIES1 Figure 3 For RIES2, electricity, heat, and gas load forecasts and wind and solar power generation forecasts are provided. Figure 4 For RIES3's electricity, heat, and gas load forecasting and wind and solar power generation forecasting, Figures 2-4 Load data and wind and solar power generation data are imported into the model and solved using the commercial solver GUROBI to obtain the optimal scheduling calculation results for RIES1, RIES2, and RIES3. Adjusting the scheduling plan for the next day based on these calculation results can improve the economic efficiency of the integrated energy system in the three regions. The optimal scheduling results for electrical power are used as an example for illustration here. Figure 5 The figure shows the optimal power scheduling results for RIES1. As can be seen from the figure, in RIES1, coal-fired unit 3 needs to undertake the main power generation task. During most periods, the electric-to-gas equipment and electric boiler need to consume a lot of electrical energy to output thermal power and gas power respectively. Figure 6 This is the optimal power scheduling result for RIES2. It can be seen that in RIES2, wind power and photovoltaic power generation need to undertake a portion of the power generation task, while energy storage devices need to charge during some periods and discharge during others, thus performing load shifting. Figure 7 The figure shows the optimal power scheduling results for RIES3. As can be seen from the figure, in RIES3, the carbon capture unit, wind power generation, and photovoltaic power generation need to share the power generation task, and the electric boiler needs to continuously convert electrical power into thermal power.

[0076] In addition, to verify the effectiveness of the model proposed in this invention in carbon reduction, the calculation results of the following two scenarios were compared based on the above embodiments, as shown in Table 1.

[0077] Scenario 1: Joint calculation of carbon trading costs;

[0078] Scenario 2: Carbon trading costs are calculated independently (first calculate the carbon trading costs of RIES3 to determine the number of tradable carbon emission rights in the carbon market, and then calculate the carbon trading costs of RIES2 and RIES1 in sequence);

[0079] Table 1 Comparison of Results

[0080]

[0081] As shown in Table 1, in both scenarios, RIES1 and RIES2 require the purchase of carbon emission rights, while RIES3 sells its carbon emission rights. Compared to Scenario 2, Scenario 1 saw a 9.46% decrease in cost for RIES1, while RIES2 and RIES3 increased by 0.02% and 5.77% respectively, yet the total system cost decreased by 3.57%. Simultaneously, total carbon emissions in Scenario 1 decreased by 1.92% compared to Scenario 2. Furthermore, in Scenario 1, all RIES met their carbon emission targets, while in Scenario 2, RIES1 exceeded its carbon emission limit by 370.77 tons. These results demonstrate that the model proposed in this invention reduces both the total cost of the three-region integrated energy system and total carbon emissions, while also preventing carbon emission exceedances.

[0082] After calculation using the multi-region integrated energy system optimization scheduling method proposed in this invention, corresponding scheduling measures can be implemented. Various scheduling methods can be adopted, including: adjusting the output of coal-fired units or carbon capture units; adjusting the grid-connected power of wind power or photovoltaic power generation; adjusting the input power of coupled equipment such as electric boilers, power-to-gas conversion equipment, combined heat and power units, or gas boilers to achieve power conversion between different forms of energy; and adjusting the charging and discharging behavior of energy storage, thermal storage, or gas storage devices to achieve load shifting.

[0083] In summary, the model proposed in this invention has certain reference value for improving the economy and low-carbon performance of multi-regional integrated energy systems.

Claims

1. A method for optimal scheduling of multi-regional integrated energy system considering carbon emission reduction, characterized in that, The method first constructs a multi-region integrated energy system carbon trading cost joint calculation model by considering the purchase upper limit of carbon emission rights in the carbon trading process and the supply and demand interaction among different regional integrated energy systems; then constructs an optimal scheduling model with the minimum total cost as the target; and finally obtains the optimal multi-region integrated energy system scheduling result by solving the optimal scheduling model; The construction of the carbon trading cost joint calculation model is as follows: The baseline method is used to calculate the free carbon quota of a single RIES: ； wherein, E is the carbon quota of a single RIES; is the free carbon quota coefficient per unit of electricity generation; t denotes a time period; is the set of coal-fired generators in a RIES; k is the number of a generator; is the power of a coal-fired generator; is the free carbon quota coefficient per unit of heat supply; K is the conversion coefficient of electricity generation into heat supply; is the electricity generation power of a cogeneration unit; is the heat supply power of a cogeneration unit; is the heat supply power of a gas boiler; The carbon emission of a single RIES is calculated: ； wherein D is the carbon emission of a single RIES; is the carbon emission coefficient of a generator k ; is the carbon emission coefficient of a generator k equipped with a carbon capture system, when the generator k is a coal-fired unit, ; is the electricity consumption of a carbon capture system to capture a unit of carbon emission; is the conversion coefficient of an electricity-to-gas facility; is the electricity consumption of an electricity-to-gas facility; is the carbon emission coefficient of a combined heat and power unit; is the carbon emission coefficient of a gas-fired boiler; When a single RIES carries out carbon trading, the carbon emission right purchase upper limit of the carbon market needs to be considered, and the carbon emission right purchase amount cannot exceed the upper limit; Therefore, the carbon trading cost calculation formula of the first RIES in the multi-region integrated energy system is as follows: i ​ ； wherein, is the carbon trading cost of the i-th RIES; i is the carbon price; and are the carbon emission and carbon quota of the i-th RIES, respectively; i is the ratio of the penalty price to the carbon price; is the purchase amount of carbon emission rights; is the upper limit of carbon emission rights purchase;​​ Carbon emission rights supply and demand interactions exist among the various RIES within a multi-regional integrated energy system. i The carbon emission rights purchase cap for each RIES is determined jointly by other RIES within the multi-regional integrated energy system; thus, the [number]th [RIES] is determined. i The joint calculation formula for the carbon trading costs of each RIES is as follows: ； In the formula, n It is a collection of RIES; and They are the first j Carbon emissions and carbon allowances for each RIES; It is the first one jointly determined by the other RIES. i The maximum carbon emission credit purchase limit for each RIES; Linearization is performed on the above formula, and there is: ； wherein and is an infinite positive number; and are two 0-1 decision variables; Ccaris the carbon price.

2. The method for optimal scheduling of carbon emission reduction considering multi-regional integrated energy system according to claim 1, characterized in that, In the construction of the multi-region integrated energy system comprehensive scheduling model with the minimum total cost as the target, the constraint conditions of the model include generator operation constraints, wind power output constraints, photovoltaic power generation constraints, natural gas transmission constraints, electric-gas conversion equipment constraints, electric boiler constraints, combined heat and power unit constraints, gas boiler constraints, energy storage device constraints, and power balance constraints of electric load, thermal load, and gas load.

3. The method of claim 1, wherein The optimization model is solved by using the commercial solver GUROBI.

4. The multi-region integrated energy system optimal scheduling method of claim 1, wherein, The scheduling means that can be adopted in the optimal scheduling method include: adjusting the output of a coal-fired unit or a carbon capture unit; adjusting the grid-connected power of wind power generation or photovoltaic power generation; adjusting the input power of an electric boiler, an electric-gas conversion device, a combined heat and power unit, or a gas boiler coupling device to realize power conversion among different forms of energy; and adjusting the charging and discharging behavior of an electric storage, thermal storage, or gas storage device to realize load shifting.

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