A multi-stage planning method and device for carbon-electricity synergy considering construction sequence and load growth.

Abstract

This invention relates to a carbon-electricity coordinated multi-stage planning method and apparatus that considers construction sequence and load growth. The method involves acquiring operational parameter data of an integrated energy system (IES), inputting it into a multi-stage mixed integer programming model with the objective function of minimizing the total present value cost (TPV) of the IES over its entire lifecycle; the multi-stage mixed integer programming model integrates the operational characteristic models of carbon-electricity coupling units; considering the dynamic load growth constraints, the equipment configuration at each planning stage dynamically meets the increasing demands of electricity, heat, and gas loads; by setting decision variables for the year of equipment construction and introducing a retirement mechanism after the economic life of the equipment expires, the optimal capacity and construction sequence of each piece of equipment within the IES are coordinated and optimized to obtain the final planning result. Compared with existing technologies, this invention achieves coordinated planning of the optimal capacity and construction sequence of each piece of equipment within the IES, and obtains an overall IES planning scheme that balances long-term economics, low-carbon goals, and load growth through a single solution.

Description

Technical Field

[0001] This invention relates to the field of regional integrated energy system capacity configuration planning technology, and in particular to a carbon-electricity coordinated multi-stage planning method that takes into account construction sequence and load growth. Background Technology

[0002] As the energy and power industry accelerates its transformation towards cleaner and lower-carbon energy, Integrated Energy Systems (IES), characterized by the coupling of multiple energy sources such as electricity, heat, and gas, have become an important supporting means for achieving efficient energy utilization and carbon emission reduction. IES achieves multi-energy complementarity and coordinated operation by configuring diverse equipment such as photovoltaic, combined heat and power units, and energy storage. However, existing IES planning studies have major technical shortcomings in addressing long-term development needs and complex constraints. The planning cycle for IES is typically ten years or even longer. During this period, the region's load demand (including electricity, heat, and gas) will exhibit dynamic and non-linear growth with economic development, and the penetration rate of new energy sources will continue to increase.

[0003] Traditional single-stage planning methods struggle to accurately match ever-changing load demands, easily leading to redundant upfront investments or insufficient capacity in later stages, thus impacting investment economics. While some scholars have attempted multi-stage planning, most pre-set the construction and decommissioning years of equipment to fixed values, lacking flexibility and optimization. This fails to achieve dynamic decision-making regarding the optimal equipment construction sequence and lacks precise modeling of decommissioning mechanisms after equipment reaches the end of its lifespan, making it unsuitable for long-term planning. Furthermore, to meet stringent carbon constraints, IES planning objectives have evolved from the traditional "economic optimization" to "economic-low-carbon synergistic optimization." However, existing research often focuses on simple energy substitution or merely introduces linear carbon trading mechanisms, failing to fully integrate and utilize the potential for deep coupling between electricity and carbon flows through advanced technologies such as carbon capture and storage (CCS) and power-to-gas conversion. This simplification fails to reflect the urgency of carbon reduction tasks, and the high costs of carbon reduction and complex coupling relationships require IES planning models to achieve synergistic optimization of investment and low-carbon operation throughout the entire lifecycle.

[0004] Existing planning models often neglect the precise calculation of decommissioning costs or residual values ​​after equipment reaches the end of its lifespan, resulting in inaccurate economic calculations of the objective function and insufficient reliability in guiding actual investment. In summary, to overcome these technical shortcomings, it is necessary to design a new multi-stage IES planning method that integrates optimal construction timing decisions, equipment decommissioning mechanisms, long-term load growth, and deep carbon-electricity synergy into a unified mathematical optimization framework. This will provide effective guidance for long-term low-carbon and economical IES planning under the new power system. Summary of the Invention

[0005] The purpose of this invention is to address the problems of rigid investment timing, static load forecasting, and insufficient carbon-electricity coupling coordination in the long-term planning of existing integrated energy systems, and to provide a multi-stage planning method for carbon-electricity coordination that considers construction timing and load growth.

[0006] The objective of this invention can be achieved through the following technical solutions: As a first aspect of the present invention, a carbon-electricity coordinated multi-stage planning method considering construction timing and load growth is provided, the steps of which include: Under the long-term goal of carbon emissions, several construction time segments are selected and the planning stages are divided. At each time segment, a mixed integer programming model with the objective function of minimizing the total present value cost of the integrated energy system throughout its entire life cycle is adopted to carry out multi-stage collaborative planning of carbon and electricity. The hybrid integer programming model integrates the operating characteristic model of the carbon-electric coupling unit, taking into account the dynamic load growth constraints and the dynamic equipment configuration at each planning stage to meet the growing demand for electricity, heat, and gas loads. By setting decision variables for the year of equipment construction and introducing a retirement mechanism after the economic life of the equipment expires, the optimal capacity and construction sequence of each piece of equipment in the integrated energy system are coordinated and optimized to obtain the final planning result.

[0007] As a preferred technical solution, the total present value cost over the entire life cycle includes the cost of new equipment investment, operating costs, maintenance costs, carbon trading costs, and the residual value of equipment at the end of the planning period. All costs are then accumulated by discounting them to the same time dimension using an equal value factor or a present value factor.

[0008] As a preferred technical solution, the planning model aims to minimize the total present value cost. The objective function is expressed as: in, For the total planning period, For the first Present value factor for the year The annual interest rate; For the first Annual new equipment investment cost; This is the difference between the annual operating fuel purchase cost and the revenue from energy sales; Annual maintenance cost; Annual carbon trading costs; The residual value of equipment at the end of the planning period depends on the equipment's service life and net residual value rate; For the first N The present value factor for the year.

[0009] As a preferred technical solution, the carbon trading cost is calculated based on a tiered carbon trading mechanism: The cost of carbon trading equals the tiered carbon trading price multiplied by the difference between the actual total carbon emissions of the integrated energy system and the benchmark carbon allowance.

[0010] As a preferred technical solution, the constraints of the multi-stage mixed integer programming model include regional carbon peaking constraints and carbon neutrality constraints: When the year is greater than or equal to the set carbon peak year, the actual comprehensive carbon emissions of the integrated energy system are less than the set peak value; When the set carbon neutrality year is reached, the actual integrated carbon emissions of the integrated energy system will be zero.

[0011] As a preferred technical solution, the hybrid integer programming model integrates the operating characteristic models of carbon capture and storage devices, power-to-gas devices, and combined heat and power units; based on energy conservation and efficiency parameter description, it constrains the energy and material balance between electrical energy flow, heat energy flow, gas energy flow, and carbon flow. The capture rate parameter of carbon capture and storage devices is introduced into the carbon emission calculation to form a mapping relationship between original emissions, captured emissions and net emissions. Based on this, a quantitative correlation between original energy flow and carbon emissions is established by multiplying by the corresponding carbon emission factor, and incorporated into the tiered carbon trading cost and long-term carbon constraints to achieve energy-carbon synergistic optimization.

[0012] As a preferred technical solution, the constraints of the mixed integer programming model are based on the predictable growth curves of electricity, heat, and gas loads, constraining the equipment capacity configuration of each planning stage to meet the dynamic demand of electricity, heat, and gas loads corresponding to that stage.

[0013] As a preferred technical solution, the mixed-integer programming model sets decision variables. To characterize the device During the planning stage The construction year is determined and its relationship to the total capacity is established through time-series and capacity constraints. Correlation, and use of this to make equipment decisions i The optimal year for construction; The model establishes an equipment retirement mechanism, which constrains the equipment to be taken out of operation after it has reached its preset economic lifespan.

[0014] As a second aspect of the present invention, a carbon-electricity coordinated multi-stage planning device considering construction timing and load growth is provided, comprising a memory, a processor, and a program stored in the memory, wherein the processor executes the program to implement the carbon-electricity coordinated multi-stage planning method considering construction timing and load growth as described above.

[0015] As a third aspect of the invention, a storage medium is provided having a program stored thereon, which, when executed, implements the carbon-electricity coordinated multi-stage planning method described above, taking into account construction timing and load growth.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1) The proposed solution of this invention realizes the collaborative planning of the optimal capacity and construction sequence of each device in the IES, as well as the dynamic decision-making of the optimal construction sequence, effectively avoiding the investment redundancy and asset waste caused by traditional static planning, and significantly improving the economic efficiency of planning.

[0017] 2) This invention achieves coordinated planning of carbon current by deeply integrating low-carbon coupling units such as P2G and CCS with a tiered carbon trading mechanism, which strongly supports the low-carbon transformation goals of IES under strict carbon constraints.

[0018] 3) This invention, through the embedded long-term load growth curve and equipment retirement mechanism, ensures that the planning scheme can dynamically adapt to long-term development needs and guarantee the continued feasibility of the plan. This is achieved by ensuring that the equipment configuration at each planning stage can dynamically match the actual growth demand of electricity, heat, and gas loads over time. Attached Figure Description

[0019] Figure 1 The flowchart illustrates the carbon-electricity coordinated multi-stage planning method for this invention, which considers construction timing and load growth. Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0021] Example 1 Step 1: Establish a multi-stage optimization planning model. Establish a planning model with the objective function of minimizing the total present value cost of the integrated energy system (IES) over its entire life cycle. Under the long-term goal of carbon emissions, select several construction time segments and reuse the constructed planning model at these time segments to conduct carbon-electricity coordinated planning.

[0022] The total present value cost over the entire life cycle includes the cost of new equipment investment, operating costs, maintenance costs, carbon trading costs, and the residual value of equipment at the end of the planning period. All costs are discounted to the same time dimension and accumulated using an equal-annual value factor or a present value factor. A multi-stage mixed integer programming model is used with constraints of IES energy balance, equipment operation constraints, and grid security constraints.

[0023] In this embodiment, present value factors are used for discounting. The model adopts a mixed-integer programming form to accurately describe the discrete decisions of equipment construction and the continuous characteristics of system operation.

[0024] Minimize total present value cost The objective function is expressed as: in, For the total planning period, For the first Present value factor for the year ( (Annual interest rate). For the first Annual new equipment investment cost; This is the difference between the annual operating fuel purchase cost and the revenue from energy sales; Annual maintenance cost; The annual carbon trading cost (see step two for details); The residual value of equipment at the end of the planning period depends on the equipment's service life and net residual value rate; For the first N The present value factor for the year.

[0025] Step Two: Integrating the Carbon-Electric Coupling Model. The optimization model integrates the operational characteristic models of key low-carbon coupling units such as carbon capture and storage (CCS) devices, power-to-gas (P2G) devices, and combined heat and power (CHP) units. The relationships between electrical, gas, and heat energy flows are described based on energy conservation constraints and efficiency parameters, achieving energy and material balance among electrical, heat, gas, and carbon flows. Specifically, the CCS device at a certain moment... carbon replenishment amount It can be represented as: In the formula: for Carbon capture rate parameters of the CCS device at any given time; for The initial carbon emissions at any given time when CCS is connected.

[0026] At the same time, the carbon trading costs calculated based on the tiered carbon trading mechanism will be included, and the carbon emissions of IES will be linked to the tiered carbon trading mechanism as a key component in the calculation of annual operating costs. It will also be incorporated into the constraints of long-term goals such as regional carbon peaking and carbon neutrality, so as to achieve deep synergy between carbon and electricity.

[0027] The IES system includes at least P2G, CCS and CHP coupling units, and the tiered carbon trading mechanism dynamically adjusts the unit carbon emission cost based on the difference between the IES' annual comprehensive carbon emissions and the benchmark carbon quota and incorporates it into the objective function. At the same time, long-term carbon emission targets such as regional carbon peaking and carbon neutrality are included in the constraints.

[0028] Carbon trading costs Calculations and low-carbon constraints: in, For the first The actual combined carbon emissions of the IES in a given year mainly come from the converted emissions of purchased electricity and the combustion emissions of gas-fired equipment within the IES (such as CHP and GB). For free carbon allowances allocated based on the baseline method, For the first The annual carbon trading price is calculated using a step function or a piecewise function. Actual IES carbon emissions are affected by CCS capture volume, and the relationship can be expressed as: in, This represents the total emissions from IES. The amount of carbon captured and stored by CCS.

[0029] The IES planning results must meet long-term carbon constraints: in, This represents the upper limit of the permitted peak carbon emissions during the planning period; The planned years for achieving the carbon peak target; This represents the carbon emissions for the carbon neutrality target year.

[0030] Step 3: Taking into account dynamic load growth. A predictable long-term load growth curve is embedded in the constraints of the planning model. This curve is used to calculate the electricity, heat, and gas load demand for each planning year, ensuring that the cumulative installed capacity for each planning phase is greater than or equal to the dynamic load demand corresponding to that phase. By accurately characterizing load demand over time, the long-term adaptability of the planning scheme is guaranteed.

[0031] IES load balance constraints (based on electrical load) (For example) in, Purchase electricity from external sources. To provide power to the generators within the IES. For power consumption of equipment within the IES; s Typical days representing different seasonst Representative time period. Among them, the first Annual electricity load demand Based on baseline load and year-on-year growth rate This decision reflects the dynamic nature of the load: In addition, the model must also meet the basic constraints of safe operation of the power grid, such as line current carrying capacity constraints, to ensure the safety and reliability of system operation under the premise of load growth.

[0032] The growth in demand for heat and gas loads is also based on their respective baseline loads and annual growth rates, following the same compound annual growth pattern. Their balance constraints are similar to those for electrical loads, taking into account the energy conversion equipment involved.

[0033] Step 4: Optimize the construction sequence. In the planning model, a 0-1 decision variable is set for the year of equipment construction, and a retirement mechanism after the economic life of the equipment is reached is introduced. This is then linked to the total capacity through time-series constraints and capacity constraints. Correlation. Enables collaborative planning of optimal capacity and deployment timing for all devices within the IES.

[0034] By setting 0-1 decision variables To characterize the device At each planning stage The construction year is determined and its relationship to the total capacity is established through time-series and capacity constraints. Correlation, for decision-making devices The optimal year for construction. The decommissioning mechanism after the economic life of equipment is based on the equipment... Preset economic life This restricts the equipment's operation after the first year of operation. In 2010, its operational capacity was zero.

[0035] Construction constraints and operational status of equipment capacity : in, For equipment Total configuration capacity For equipment In the The newly added capacity in the phase, For equipment The maximum total configuration capacity, This refers to the total investment, construction phases, or number of investments within the planning period. Equipment. In the Actual operational capacity per year Depends on its cumulative construction capacity and commissioning status : Among them, operational status Lifespan taken into consideration and the year of construction : Example 2 As a second aspect of the present invention, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the carbon-electricity coordinated multi-stage planning method as described above, which takes into account construction timing and load growth. In addition to the processors, memory, and interfaces described above, any data processing device in the embodiments may also include other hardware depending on the actual function of the data processing device, which will not be elaborated further.

[0036] Example 3 As a third aspect of the present invention, this application also provides a computer-readable storage medium storing computer instructions thereon, which, when executed by a processor, implement the carbon-electricity coordinated multi-stage planning method considering construction timing and load growth as described above. The computer-readable storage medium can be an internal storage unit of any data-processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data-processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data-processing device, and can also be used to temporarily store data that has been output or will be output.

[0037] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A carbon-electricity coordinated multi-stage planning method considering construction timing and load growth, characterized by the steps of include: Under the long-term goal of carbon emissions, several construction time segments are selected and the planning stages are divided. At each time segment, a mixed integer programming model with the objective function of minimizing the total present value cost of the integrated energy system throughout its entire life cycle is adopted to carry out multi-stage collaborative planning of carbon and electricity. The hybrid integer programming model integrates the operating characteristic model of the carbon-electric coupling unit, taking into account the dynamic load growth constraints and the dynamic equipment configuration at each planning stage to meet the growing demand for electricity, heat, and gas loads. By setting decision variables for the year of equipment construction and introducing a retirement mechanism after the economic life of the equipment expires, the optimal capacity and construction sequence of each piece of equipment in the integrated energy system are coordinated and optimized to obtain the final planning result.

2. The method of claim 1, wherein, The total present value cost over the entire life cycle includes the cost of new equipment investment, operating costs, maintenance costs, carbon trading costs, and the residual value of equipment at the end of the planning period. All costs are discounted to the same time dimension and accumulated using an equal value factor or present value factor.

3. The carbon-electricity coordinated multi-stage planning method considering construction sequence and load growth according to claim 2, characterized in that, The planning model is expressed as an objective function that minimizes total present value cost F = ∑(C + D) wherein, is the present value factor for the total planning period, is the present value factor for the first year, is the annual interest rate; is the incremental equipment investment cost for the first year; is the difference between the annual fuel purchase cost and the annual energy sale revenue; is the annual maintenance cost; is the annual carbon trading cost; is the equipment salvage value at the end of the planning period, which depends on the equipment’s operational life and net salvage rate; is the present value factor for the first N year.

4. The method of claim 3, wherein, The carbon trading cost is calculated based on the tiered carbon trading mechanism: The cost of carbon trading equals the tiered carbon trading price multiplied by the difference between the actual total carbon emissions of the integrated energy system and the benchmark carbon allowance.

5. The method of claim 1, wherein, The constraints of the multi-stage mixed integer programming model include regional carbon peaking constraints and carbon neutrality constraints: When the year is greater than or equal to the set carbon peak year, the actual comprehensive carbon emissions of the integrated energy system are less than the set peak value; When the set carbon neutrality year is reached, the actual integrated carbon emissions of the integrated energy system will be zero.

6. The method of claim 1, wherein, The mixed integer programming model integrates the operating characteristic models of carbon capture and storage devices, power-to-gas devices, and combined heat and power units; based on energy conservation and efficiency parameter descriptions, it constrains the energy and material balance among electrical energy flow, heat energy flow, gas energy flow, and carbon flow. The capture rate parameter of carbon capture and storage devices is introduced into the carbon emission calculation to form a mapping relationship between original emissions, captured emissions and net emissions. Based on this, a quantitative correlation between original energy flow and carbon emissions is established by multiplying by the corresponding carbon emission factor, and incorporated into the tiered carbon trading cost and long-term carbon constraints to achieve energy-carbon synergistic optimization.

7. The method of claim 1, wherein, The constraints of the mixed integer programming model are based on the predictable growth curves of electricity, heat, and gas loads, constraining the equipment capacity configuration of each planning stage to meet the dynamic demand of electricity, heat, and gas loads corresponding to that stage.

8. The carbon-electricity coordinated multi-stage planning method considering construction sequence and load growth according to claim 1, characterized in that, The mixed integer programming model is characterized by setting decision variables to represent the equipment In the planning phase The construction year is associated with the total capacity by time sequence constraints and capacity constraints, and the optimal construction year of the equipment i is determined by the decision. The model establishes an equipment retirement mechanism, which constrains the equipment to be taken out of operation after it has reached its preset economic lifespan. 9.A device for carbon-electricity co-syndication multi-stage planning considering construction timing and load growth, comprising a memory, a processor, and a program stored in the memory, wherein, When the processor executes the program, it implements the carbon-electricity coordinated multi-stage planning method as described in any one of claims 1-8, which takes into account construction timing and load growth.

10. A storage medium having a program stored thereon, characterized in that, When the program is executed, it implements the carbon-electricity coordinated multi-stage planning method as described in any one of claims 1-8, which takes into account construction timing and load growth.

Images