Electricity-carbon coupling planning method and system for provincial power grid

Abstract

The invention relates to an electricity-carbon coupling planning method and system for a provincial power grid, and the method comprises the steps: determining a planning boundary, and collecting the basic data of the provincial power grid based on the planning boundary; quantifying a target layer, and determining a comprehensive optimization target; constructing a dynamic constraint system, and determining constraint conditions; source network load carbon storage configuration is carried out, and configuration information is determined; and solving based on the basic data of the power grid, the comprehensive optimization target, the constraint condition and the configuration information, and determining a planning scheme. According to the method, the carbon cost is directly incorporated into full-life-cycle cost accounting, internal linkage of a low-carbon-economic target is achieved, and the problem that carbon emission and the economic target are disjointed in a traditional method is solved; a dynamic carbon constraint mechanism enables economic deviation of the scheme to be greatly reduced when the carbon price fluctuates, and investment risks caused by sudden change of the carbon price are avoided; by incorporating the reliability into the comprehensive index, the power supply reliability is ensured, the flexibility of source-grid load-storage coordination is increased, the peak-valley difference adjustment pressure of the power grid is reduced, and the consumption of new energy is improved.

Description

Technical Field

[0001] This invention relates to the field of provincial power grid planning technology, and more specifically, to a method and system for planning the electricity-carbon coupling of a provincial power grid. Background Technology

[0002] Driven by the "dual carbon" goals, provincial power grids, as core hubs connecting national energy bases and regional load centers, must balance the three core demands of energy security supply, economic cost control, and carbon emission constraints in their planning. Currently, provincial power grid planning has shifted from optimizing the traditional four elements of "source, grid, load, and storage" to coordinating all elements of "source, grid, load, storage, and carbon." With the continuous advancement of carbon footprint and carbon markets, the introduction of carbon emission constraints to form a three-dimensional technical framework of "constraint quantification - optimization model - solution method" has become increasingly urgent in power system planning. Among these, the coupling of carbon emission constraints and power grid planning (i.e., "electricity-carbon coupling") has become a hot research topic. Related research has covered key aspects such as carbon emission accounting, multi-objective optimization, and coordinated configuration, but shortcomings still exist in the regional adaptability, dynamic responsiveness, and full-process implementation of provincial power grids. Driven by the "dual carbon" goals, provincial power grids, as core hubs connecting national energy bases and regional load centers, must simultaneously meet the three core demands of energy security supply, economic cost control, and carbon emission constraints. The current provincial power grid planning has been optimized from the traditional four elements of "source, grid, load, and storage" to a coordinated model of all elements of "source, grid, load, storage, and carbon". With the expansion of the national carbon market in 2024 (covering the power generation and power grid industries) and the improvement of the GB / T 32151 series of carbon footprint accounting standards, "electricity-carbon coupling" has become the core direction of planning technology.

[0003] The key technologies currently in this field mainly include: 1) carbon emission quantification technology, which is divided into the direct emission coefficient method based on energy category and the full-cycle accounting method based on life cycle assessment (LCA); 2) multi-objective optimization technology, which achieves the synergy of "economy-low carbon-reliability" objectives through weighted methods, analytic hierarchy process (AHP), etc.; 3) source-grid-load-storage coordinated configuration technology, namely, segmented optimization technology of prioritizing new energy allocation on the power supply side, grid adaptation on the grid side, and flexible regulation on the load-storage side; 4) life cycle cost (LCC) accounting technology, which covers the full-cycle quantification of costs such as equipment investment, operation and maintenance, and fuel. A comparison and limitations of these technologies are listed in Table 1 below.

[0004] Table 1. Characteristics and limitations of current key technologies

[0005]

[0006] The existing technology has the following core drawbacks, which are also the technical problems that this invention aims to solve:

[0007] ·Disadvantage 1: Carbon costs are disconnected from LCC accounting. Existing plans only use carbon emissions as a constraint and do not dynamically incorporate carbon costs such as carbon quota purchase fees and CCER trading revenue into the full life cycle accounting of LCC, resulting in insufficient synergy between "low carbon and economy".

[0008] · Disadvantage 2: Static carbon emission constraints. Existing technologies use fixed emission coefficients or carbon prices and do not incorporate dynamic constraint mechanisms based on the dynamic fluctuations of provincial carbon markets (such as annual carbon quota adjustments and carbon price fluctuations). This results in poor adaptability of planning schemes. Dynamic consideration of carbon costs is needed to make the power system configuration more aligned with the needs of low-carbon transformation and avoid the problem of ignoring environmental costs in traditional planning.

[0009] · Disadvantage 3: The configuration of source, grid, load and storage is separate and lacks the full-element coupling logic of "source-grid-load-storage-carbon" at the provincial power grid level. Under the background of building a new power system with a high proportion of new energy, it is more likely to lead to local optimization errors such as "high proportion of new energy access on the source side but insufficient grid transmission".

[0010] Therefore, a carbon-electric coupling planning method for provincial power grids is needed. Summary of the Invention

[0011] This invention proposes a method and system for electricity-carbon coupling planning of provincial power grids to solve the problem of how to achieve "low-carbon, economical, and reliable" provincial power grids in the medium and long term, and the synergistic optimization of electricity balance planning and carbon costs.

[0012] To address the aforementioned problems, according to one aspect of the present invention, a method for planning the electricity-carbon coupling of a provincial power grid is provided, the method comprising:

[0013] Determine the planning boundaries and collect basic data of the provincial power grid based on the planning boundaries;

[0014] Quantify the target layer to determine the comprehensive optimization objective;

[0015] Construct a dynamic constraint system and determine the constraint conditions;

[0016] Configure the carbon source, grid, load, and storage system, and determine the configuration information;

[0017] The planning scheme is determined by solving the problem based on the power grid basic data, comprehensive optimization objectives, constraints, and configuration information.

[0018] Preferably, the basic data includes: wind and solar resource planning data, load data, equipment parameters, carbon market data, and policy data.

[0019] Preferably, the comprehensive optimization objective includes:

[0020] minF=ω1×F1+ω2×F2+ω3×(1-F3),

[0021] Where F is the comprehensive optimization objective; F1 is the minimized total life cycle cost; F2 is the minimized total life cycle carbon emissions; F3 is the maximized power supply reliability; ω1, ω2, and ω3 are all weighting coefficients, and ω1+ω2+ω3=1.

[0022] Preferably, the method further includes:

[0023] The lifecycle cost is determined using the following methods, including:

[0024] LCC = ∑(Investment cost of each piece of equipment × Capital recovery factor) + ∑(Annual operation and maintenance cost + Fuel cost + Carbon cost) × Present value factor - Residual value × Present value factor

[0025] Capital recovery coefficient = [i(1+i)n] / [(1+i)n-1],

[0026] Carbon cost = Carbon allowance unit price × (Actual carbon emissions - Free allowances) - CCER unit price × Certified emission reductions

[0027] Residual value = Initial investment × Residual value rate (5% - 10%)

[0028] The total carbon emissions over the entire life cycle are determined using the following methods, including:

[0029] C_total=C_source+C_network+C_storage+C_l load,

[0030] C_source = ∑(Annual power generation × Unit carbon emission intensity × Operating life),

[0031] C_network = Carbon emissions during construction (steel / cement consumption × corresponding carbon emission factor) + Carbon emissions during operation (grid loss × average carbon intensity of power source),

[0032] C_storage = Life-cycle carbon emission intensity × Energy storage capacity × Operating years

[0033] C_l oad = ∑(Electricity consumption of classified loads × Corresponding power supply carbon intensity),

[0034] The power supply reliability rate is determined using the following methods, including:

[0035] ASAI = (Total power supply time - Power outage time) / Total power supply time × 100%

[0036] Where LCC is the total life cycle cost; i is the discount rate; n is the design life; C_total is the total carbon emissions over the entire life cycle; C_source is the carbon emissions from the power source; C_network is the carbon emissions from the power grid; C_storage is the carbon emissions from energy storage; and C_load is the carbon emissions from the load.

[0037] Preferably, the constraints include:

[0038] Power balance constraints, including: P _G (t)+P _SD (t)+P _IX (t)=P _L (t)-P _Ladj (t)+P _SC (t)+P _Loss (t),

[0039] Carbon emission constraints include:

[0040] ∑C_ total ≤C_ Limit ,

[0041] C_ total / E_ total ≤C_ Standard ,

[0042] Annual carbon emissions ≤ annual carbon allowance

[0043] Equipment capacity constraints include:

[0044] 0≤P_ Gi (t)≤P_ Gi ,max,

[0045] P_ Linej (t)≤P_ Linej ,max,

[0046] Load constraints, including:

[0047] 0≤P_ SD (t)≤P_ S max, 0≤P_ SC (t)≤P_ S ,max,SOC_ min ≤SOC(t)

[0048] ≤SOC_ max ,

[0049] 0≤P_Ladj(t)≤P_L_adj, max(adjustment amount ≤ maximum potential), adjustment interval ≥15min,

[0050] Constraints of the carbon market mechanism include:

[0051] Setting a carbon price fluctuation range, determining the carbon cost coefficient through analysis of different configuration scenarios of source, grid, load, and storage; and based on SOC(t)=SOC(t-1)+P_ SC (t)×0.9-P_ SD (t) / Real-time tracking of energy storage charge and discharge efficiency;

[0052] Among them, P _G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX (t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the grid loss power; C_total represents the total carbon emissions over the entire life cycle; C_ Limit For the system's entire life cycle carbon emission limit; E_ total For the total power generation, C_ Standard This is the provincial industry benchmark value; P_ Gi (t) represents the output of the i-th generator unit at time t; P_ Gi ,max is the rated capacity of power supply i; P_ Linej (t) represents the power transmitted by line j at time t; P_ Linej ,max is the rated current carrying capacity of line j; P_ S ,max is the upper limit of the charging / discharging power of the energy storage system; SOC_ min and SOC_ max These represent the upper and lower safety limits of the energy storage SOC; P_ Lrigid P_Ladj(t) represents the rigid, non-adjustable load; P_Ladj(t) represents the adjustable load reduction amount; and P_L_adj,max represents the maximum adjustable load reduction value.

[0053] Preferably, the configuration of carbon storage based on grid load and source includes determining the configuration information, such as:

[0054] For the power supply side, with decarbonization as the core, priority should be given to allocating renewable energy, and the reserve capacity of thermal power should be determined in combination with carbon emission intensity.

[0055] For the power grid side, the grid structure is optimized based on the distribution of power sources and loads;

[0056] For the load-storage side, explore the potential of flexible load peak shaving and valley filling, and configure energy storage capacity to match the fluctuation of renewable energy. The energy storage capacity must meet the following requirements: rated energy storage power ≥ maximum output fluctuation of renewable energy × adjustment coefficient.

[0057] In the configuration scheme, all equipment data from the source, grid, load, and storage systems are combined with the full life cycle theory, covering all stages of equipment production, construction, operation, and decommissioning.

[0058] Preferably, the planning scheme includes: a power generation capacity list, a load-storage regulation strategy, an annual carbon emission forecast curve, and a provincial power grid source-grid-load-storage configuration scheme for different stages.

[0059] According to another aspect of the present invention, an electricity-carbon coupling planning system for a provincial power grid is provided, the system comprising:

[0060] The data acquisition unit is used to determine the planning boundary and collect basic data of the provincial power grid based on the planning boundary;

[0061] The optimization target determination unit is used to quantify the target layer and determine the comprehensive optimization target.

[0062] The constraint determination unit is used to construct a dynamic constraint system and determine the constraint conditions.

[0063] The configuration unit is used to configure the carbon source, grid, load, and storage, and to determine the configuration information.

[0064] The planning scheme determination unit is used to solve the problem based on the power grid basic data, comprehensive optimization objectives, constraints and configuration information to determine the planning scheme.

[0065] Preferably, the basic data includes: wind and solar resource planning data, load data, equipment parameters, carbon market data, and policy data.

[0066] Preferably, the comprehensive optimization objective includes:

[0067] minF=ω1×F1+ω2×F2+ω3×(1-F3),

[0068] Where F is the comprehensive optimization objective; F1 is the minimized total life cycle cost; F2 is the minimized total life cycle carbon emissions; F3 is the maximized power supply reliability; ω1, ω2, and ω3 are all weighting coefficients, and ω1+ω2+ω3=1.

[0069] Preferably, the optimization target determination unit further includes:

[0070] The lifecycle cost is determined using the following methods, including:

[0071] LCC = ∑(Investment cost of each piece of equipment × Capital recovery factor) + ∑(Annual operation and maintenance cost + Fuel cost + Carbon cost) × Present value factor - Residual value × Present value factor

[0072] Capital recovery coefficient = [i(1+i)n] / [(1+i)n-1],

[0073] Carbon cost = Carbon allowance unit price × (Actual carbon emissions - Free allowances) - CCER unit price × Certified emission reductions

[0074] Residual value = Initial investment × Residual value rate (5% - 10%)

[0075] The total carbon emissions over the entire life cycle are determined using the following methods, including:

[0076] C_tota l=C_source+C_network+C_storage+C_l oad,

[0077] C_source = ∑(Annual power generation × Unit carbon emission intensity × Operating life),

[0078] C_network = Carbon emissions during the construction phase (steel / cement consumption × corresponding carbon emission factor)

[0079] + Carbon emissions during operation (grid loss electricity × average carbon intensity of power source),

[0080] C_storage = Life-cycle carbon emission intensity × Energy storage capacity × Operating years

[0081] C_load = ∑(Electricity consumption of different load categories × Corresponding power supply carbon intensity),

[0082] The power supply reliability rate is determined using the following methods, including:

[0083] ASAI = (Total power supply time - Power outage time) / Total power supply time × 100%

[0084] Where LCC is the total life cycle cost; i is the discount rate; n is the design life; C_total is the total carbon emissions over the entire life cycle; C_source is the carbon emissions from the power source; C_network is the carbon emissions from the power grid; C_storage is the carbon emissions from energy storage; and C_load is the carbon emissions from the load.

[0085] Preferably, the constraints include:

[0086] Power balance constraints, including: P _G (t)+P _SD (t)+P _IX (t)=P _L (t)-P _Ladj (t)+P _SC (t)+P _Loss (t),

[0087] Carbon emission constraints include:

[0088] ∑C_ total ≤C_ Limit ,

[0089] C_ total / E_ total ≤C_ Standard ,

[0090] Annual carbon emissions ≤ annual carbon allowance

[0091] Equipment capacity constraints include:

[0092] 0≤P_ Gi (t)≤P_ Gi ,max,

[0093] P_ Linej (t)≤P_ Linej ,max,

[0094] Load constraints, including:

[0095] 0≤P_ SD (t)≤P_ S max, 0≤P_ SC (t)≤P_ S ,max,SOC_ min ≤SOC(t)

[0096] ≤SOC_ max ,

[0097] 0≤P_Ladj(t)≤P_L_adj, max(adjustment amount ≤ maximum potential), adjustment interval ≥15min,

[0098] Constraints of the carbon market mechanism include:

[0099] Setting a carbon price fluctuation range, determining the carbon cost coefficient through analysis of different configuration scenarios of source, grid, load, and storage; and based on SOC(t)=SOC(t-1)+P_ SC (t)×0.9-P_ SD (t) / Real-time tracking of energy storage charge and discharge efficiency;

[0100] Among them, P _G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX (t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the grid loss power; C_total represents the total carbon emissions over the entire life cycle; C_ LimitFor the system's entire life cycle carbon emission limit; E_ total For the total power generation, C_ Standard This is the provincial industry benchmark value; P_ Gi (t) represents the output of the i-th generator unit at time t; P_ Gi ,max is the rated capacity of power supply i; P_ Linej (t) represents the power transmitted by line j at time t; P_ Linej ,max is the rated current carrying capacity of line j; P_ S ,max is the upper limit of the charging / discharging power of the energy storage system; SOC_ min and SOC_ max These represent the upper and lower safety limits of the energy storage SOC; P_ Lrigid P_Ladj(t) represents the rigid, non-adjustable load; P_Ladj(t) represents the adjustable load reduction amount; and P_L_adj,max represents the maximum adjustable load reduction value.

[0101] Preferably, the configuration unit configures the source-grid-load-storage carbon system and determines the configuration information, including:

[0102] For the power supply side, with decarbonization as the core, priority should be given to allocating renewable energy, and the reserve capacity of thermal power should be determined in combination with carbon emission intensity.

[0103] For the power grid side, the grid structure is optimized based on the distribution of power sources and loads;

[0104] For the load-storage side, explore the potential of flexible load peak shaving and valley filling, and configure energy storage capacity to match the fluctuation of renewable energy. The energy storage capacity must meet the following requirements: rated energy storage power ≥ maximum output fluctuation of renewable energy × adjustment coefficient.

[0105] In the configuration scheme, all equipment data from the source, grid, load, and storage systems are combined with the full life cycle theory, covering all stages of equipment production, construction, operation, and decommissioning.

[0106] Preferably, the planning scheme includes: a power generation capacity list, a load-storage regulation strategy, an annual carbon emission forecast curve, and a provincial power grid source-grid-load-storage configuration scheme for different stages.

[0107] According to another aspect of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the methods for a provincial power grid's electric-carbon coupling planning.

[0108] According to another aspect of the present invention, the present invention provides an electronic device, comprising:

[0109] The aforementioned computer-readable storage medium; and

[0110] One or more processors for executing a program in the computer-readable storage medium.

[0111] This invention provides a method and system for carbon-electric coupling planning of a provincial power grid, comprising: determining the planning boundary and collecting basic data of the provincial power grid based on the planning boundary; quantifying the target layer and determining the comprehensive optimization target; constructing a dynamic constraint system and determining the constraint conditions; configuring carbon sources, grid, load, and storage and determining the configuration information; and solving the problem based on the power grid basic data, comprehensive optimization target, constraint conditions, and configuration information to determine the planning scheme. This invention directly incorporates carbon costs into the life-cycle cost (LCC) accounting, achieving an intrinsic linkage between "low-carbon and economic" goals, and solving the problem of the disconnect between carbon emissions and economic goals in traditional methods. The constructed target system can improve the carbon emission reduction efficiency of the planning scheme by 15%-20% while ensuring controllable economic efficiency. The dynamic carbon constraint mechanism significantly reduces the economic deviation of the scheme compared to traditional static constraint schemes when carbon prices fluctuate, avoiding investment risks caused by sudden carbon price changes. By incorporating reliability into the comprehensive index, it ensures power supply reliability while increasing the flexibility of source-grid-load-storage coordination, reducing the pressure of peak-valley regulation in the power grid, and improving the absorption of new energy sources. Attached Figure Description

[0112] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0113] Figure 1 This is a flowchart of a provincial power grid electricity-carbon coupling planning method 100 according to an embodiment of the present invention;

[0114] Figure 2 This is a general flowchart according to an embodiment of the present invention;

[0115] Figure 3 This is a schematic diagram of the structure of a provincial power grid electricity-carbon coupling planning system 300 according to an embodiment of the present invention. Detailed Implementation

[0116] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0117] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0118] Figure 1 This is a flowchart of a provincial power grid electricity-carbon coupling planning method 100 according to an embodiment of the present invention. Figure 1 As shown, the provincial power grid carbon coupling planning method provided by this invention directly incorporates carbon costs into the full life cycle cost (LCC) accounting, achieving an intrinsic linkage between "low-carbon and economic" goals and solving the problem of the disconnect between carbon emissions and economic goals in traditional methods. The constructed target system can improve the carbon emission reduction efficiency of the planning scheme by 15%-20% while ensuring controllable economic efficiency. The dynamic carbon constraint mechanism greatly reduces the economic deviation of the scheme compared with the traditional static constraint scheme when carbon prices fluctuate, avoiding investment risks caused by sudden changes in carbon prices. By incorporating reliability into the comprehensive index, it increases the flexibility of source-grid-load-storage coordination while ensuring power supply reliability, reducing the pressure of peak-valley regulation of the power grid, and improving the absorption of new energy. The provincial power grid carbon coupling planning method 100 provided by this invention starts from step 101. In step 101, the planning boundary is determined, and basic data of the provincial power grid are collected based on the planning boundary.

[0119] Preferably, the basic data includes: wind and solar resource planning data, load data, equipment parameters, carbon market data, and policy data.

[0120] Combination Figure 2 As shown, the configuration method framework in this invention includes three layers: the target layer, the constraint layer, and the configuration layer. In terms of implementation, carbon emission constraints are used as the core boundary, with economy and reliability as the basic objectives. Dynamic embedding of carbon emission constraints is added to the conditional constraints. In the source-grid-load-storage configuration layer, the full life cycle theory is mainly combined to cover carbon costs throughout the entire life cycle of source-grid-load-storage, and the configuration scheme is correlated with the total carbon emissions throughout the entire life cycle.

[0121] In an embodiment of the present invention, basic data of the provincial power grid are collected to define planning boundaries. Specifically, this includes: 1) The geographical boundary is the administrative region of a certain province, covering several prefecture-level cities and several provincial energy bases; 2) The time boundary is a planning period of 20 years (2025-2045), of which 2025-2030 is the first stage and 2031-2045 is the second stage. The time decomposition period during the first stage is one year, and the time decomposition period during the second stage is five years. 3) Data types include: wind and solar resource planning data, load data (considering the proportion of rigid load and the development timeline of the final flexible load adjustment potential), equipment parameters (including the entire chain of source-grid-load-storage equipment, unit investment of various power sources, and the carbon footprint of chemical energy storage throughout its entire life cycle), carbon market data (including benchmark carbon price and CCER trading price), and policy data (the annual average reduction rate of provincial carbon quotas and power supply reliability targets).

[0125] In step 102, the target layer is quantized to determine the comprehensive optimization target.

[0126] Preferably, the comprehensive optimization objective includes:

[0127] minF=ω1×F1+ω2×F2+ω3×(1-F3),

[0128] Where F is the comprehensive optimization objective; F1 is the minimized total life cycle cost; F2 is the minimized total life cycle carbon emissions; F3 is the maximized power supply reliability; ω1, ω2, and ω3 are all weighting coefficients, and ω1+ω2+ω3=1.

[0129] Preferably, the method further includes:

[0130] The lifecycle cost is determined using the following methods, including:

[0131] LCC = ∑(Investment cost of each piece of equipment × Capital recovery factor) + ∑(Annual operation and maintenance cost + Fuel cost + Carbon cost) × Present value factor - Residual value × Present value factor

[0132] Capital recovery coefficient = [i(1+i)n] / [(1+i)n-1],

[0133] Carbon cost = Carbon allowance unit price × (Actual carbon emissions - Free allowances) - CCER unit price × Certified emission reductions

[0134] Residual value = Initial investment × Residual value rate (5% - 10%)

[0135] The total carbon emissions over the entire life cycle are determined using the following methods, including:

[0136] C_tota l=C_source+C_network+C_storage+C_l oad,

[0137] C_source = ∑(Annual power generation × Unit carbon emission intensity × Operating life),

[0138] C_network = Carbon emissions during the construction phase (steel / cement consumption × corresponding carbon emission factor)

[0139] + Carbon emissions during operation (grid loss electricity × average carbon intensity of power source),

[0140] C_storage = Life-cycle carbon emission intensity × Energy storage capacity × Operating years

[0141] C_load = ∑(Electricity consumption of different load categories × Corresponding power supply carbon intensity),

[0142] The power supply reliability rate is determined using the following methods, including:

[0143] ASAI = (Total power supply time - Power outage time) / Total power supply time × 100%

[0144] Where LCC is the total life cycle cost; i is the discount rate; n is the design life; C_total is the total carbon emissions over the entire life cycle; C_source is the carbon emissions from the power source; C_network is the carbon emissions from the power grid; C_storage is the carbon emissions from energy storage; and C_load is the carbon emissions from the load.

[0145] In this invention, target layer quantization and weight setting are performed, including:

[0146] 1) Determine comprehensive optimization objectives, construct and quantify a three-dimensional target system of "low carbon-economic-reliable":

[0147] minF=ω1×F1+ω2×F2+ω3×(1-F3),

[0148] Where F is the comprehensive optimization objective; F1 is the minimized total life cycle cost; F2 is the minimized total life cycle carbon emissions; F3 is the maximized power supply reliability; ω1, ω2, and ω3 are weighting coefficients, ω1+ω2+ω3=1, and the weighting coefficient ω2 of the low-carbon objective increases sequentially in the carbon peak stage and the carbon neutrality stage.

[0149] 2) Determine the goal of minimizing the total life cycle cost (LCC), calculated using the following formula:

[0150] LCC = ∑(investment cost of each piece of equipment × capital recovery coefficient) + ∑(annual operation and maintenance cost + fuel cost + carbon cost) × present value coefficient - residual value × present value coefficient.

[0151] Among them, (1) Capital recovery coefficient = [i(1+i)n] / [(1+i)n-1], i is the discount rate, calculated according to the provincial power grid benchmark discount rate, usually taken as 6%-8%; n is the design life, generally ≤20 years. (2) Combined with the carbon market mechanism, the core components of carbon cost are: carbon cost = carbon quota unit price × (actual carbon emissions - free quota) - CCER unit price × verifiable emission reduction. Actual carbon emissions need to cover the entire life cycle of source, grid, storage and load, and are calculated through the formula for total carbon emissions throughout the entire life cycle. The free quota is determined according to the provincial annual quota allocation plan. (3) Residual value = initial investment × residual value rate (5%-10%).

[0152] 3) Determine the low-carbon target of minimizing total life-cycle carbon emissions (C_total), calculated using the following formula:

[0153] C_total=C_source+C_network+C_storage+C_l load,

[0154] Wherein, C_source (power source carbon emissions) = ∑(annual power generation × unit carbon emission intensity × operating years); C_network (grid carbon emissions) = carbon emissions during construction phase (steel / cement consumption × corresponding carbon emission factor) + carbon emissions during operation phase (grid loss electricity × average power source carbon intensity); C_storage (energy storage carbon emissions) = carbon emission intensity throughout the entire life cycle × energy storage capacity × operating years; C_load (load carbon emissions) = ∑(electricity consumption of classified loads × corresponding power supply carbon intensity).

[0155] 4) Determine the reliability target: maximize the power supply guarantee capability, and use the power supply reliability rate (ASAI) as the quantification index.

[0156] ASAI = (Total power supply time - Power outage time) / Total power supply time × 100% (e.g., target ≥ 99.9%)

[0157] Core load ≥ 99.99%;

[0158] Among them, the weighting coefficients of economy, low carbon and reliability for different periods are set according to the "dual carbon" phase goals, namely the values ​​of ω1, ω2 and ω3.

[0159] In step 103, a dynamic constraint system is constructed and the constraint conditions are determined.

[0160] Preferably, the constraints include:

[0161] Power balance constraints, including: P _G (t)+P _SD (t)+P _IX (t)=P _L (t)-P_Ladj (t)+P _SC (t)+P _Loss (t),

[0162] Carbon emission constraints include:

[0163] ∑C_ total ≤C_ Limit ,

[0164] C_ total / E_ total ≤C_ Standard ,

[0165] Annual carbon emissions ≤ annual carbon allowance

[0166] Equipment capacity constraints include:

[0167] 0≤P_ Gi (t)≤P_ Gi ,max,

[0168] P_ Linej (t)≤P_ Linej ,max,

[0169] Load constraints, including:

[0170] 0≤P_ SD (t)≤P_ S max, 0≤P_ SC (t)≤P_ S ,max,SOC_ min ≤SOC(t)

[0171] ≤SOC_ max ,

[0172] 0≤P_Ladj(t)≤P_L_adj, max(adjustment amount ≤ maximum potential), adjustment interval ≥15min,

[0173] Constraints of the carbon market mechanism include:

[0174] Setting a carbon price fluctuation range, determining the carbon cost coefficient through analysis of different configuration scenarios of source, grid, load, and storage; and based on SOC(t)=SOC(t-1)+P_ SC (t)×0.9-P_ SD (t) / Real-time tracking of energy storage charge and discharge efficiency;

[0175] Among them, P _G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX(t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the grid loss power; C_total represents the total carbon emissions over the entire life cycle; C_ Limit For the system's entire life cycle carbon emission limit; E_ total For the total power generation, C_ Standard This is the provincial industry benchmark value; P_ Gi (t) represents the output of the i-th generator unit at time t; P_ Gi ,max is the rated capacity of power supply i; P_ Linej (t) represents the power transmitted by line j at time t; P_ Linej ,max is the rated current carrying capacity of line j; P_ S ,max is the upper limit of the charging / discharging power of the energy storage system; SOC_ min and SOC_ max These represent the upper and lower safety limits of the energy storage SOC; P_ Lrigid P_Ladj(t) represents the rigid, non-adjustable load; P_Ladj(t) represents the adjustable load reduction amount; and P_L_adj,max represents the maximum adjustable load reduction value.

[0176] In this invention, a two-tiered dynamic constraint system of "carbon emissions - carbon market" is constructed in the source-grid-load-storage planning. The hard constraints include equation constraints such as total carbon emission limits, intensity benchmarks, and low-carbon targets to ensure a carbon emission baseline. The soft constraints embed carbon cost functions through carbon price fluctuations and incorporate carbon quotas and CCER trading revenue into the calculation. Compared with the fixed emission coefficient method, this dynamic constraint mechanism can improve the adaptability of the planning scheme to carbon market fluctuations, and significantly improve the alignment of the configuration scheme with dual carbon targets and the development needs of the new power system.

[0177] Specifically, in this invention, the construction of the dynamic constraint system includes constructing the following constraints:

[0178] (1) Power balance constraint (core constraint)

[0179] The system power supply and demand are balanced at any given time, taking into account the dynamic effects of distributed power sources, energy storage, and adjustable loads:

[0180] P _G (t)+P _SD (t)+P _IX (t)=P _L (t)-P _Ladj (t)+P _SC (t)+P _Loss (t)

[0181] Among them, P_G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX (t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the network loss power.

[0182] (2) Carbon emission constraints (rigid constraints)

[0183] Total constraint: ∑C_ total ≤C_ Limit (C_ Limit (For the system's entire life cycle carbon emission limit);

[0184] Strength constraint: C_ total / E_ total ≤C_ Standard (E_ total For the total power generation, C_ Standard (As a provincial industry benchmark value);

[0185] Phased constraints: Annual carbon emissions ≤ annual carbon quota, to avoid the risk of carbon over-emission across years.

[0186] (3) Equipment capacity constraints (rigid constraints)

[0187] Power supply: 0≤P_ Gi (t)≤P_ Gi ,max(P_ Gi ,max is the rated capacity of power source i (renewable energy sources need to be multiplied by the resource utilization factor);

[0188] Power grid: P_ Linej (t)≤P_ Linej ,max(P_ Linej ,max is the rated current carrying capacity of line j, which is taken as 80% under the N-1 criterion;

[0189] Energy storage: 0≤P_ SD (t)≤P_ S max, 0≤P_ SC (t)≤P_ S ,max,SOC_ min ≤SOC(t)≤SOC_ max (SOC∈[20%,80%]).

[0190] (4) Load constraints

[0191] Rigid load: P_ Lrigid(t) Not adjustable, requires 100% power supply guarantee;

[0192] Flexible load: 0≤P_Ladj(t)≤P_L_adj,max (adjustment amount ≤ maximum potential), adjustment interval ≥15min (avoid frequent adjustments).

[0193] Among them, P _G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX (t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the grid loss power; C_total represents the total carbon emissions over the entire life cycle; C_ Limit For the system's entire life cycle carbon emission limit; E_ total For the total power generation, C_ Standard This is the provincial industry benchmark value; P_ Gi (t) represents the output of the i-th generator unit at time t; P_ Gi ,max is the rated capacity of power supply i; P_ Linej (t) represents the power transmitted by line j at time t; P_ Linej ,max is the rated current carrying capacity (thermal stability limit) of line j; P_ S ,max is the upper limit of the charging / discharging power of the energy storage system; SOC_ min and SOC_ max These represent the upper and lower safety limits of the energy storage SOC; P_ Lrigid P_Ladj(t) is a rigid, non-adjustable load that must be supplied with 100% power; P_Ladj(t) is the adjustable load reduction amount (responding to demand response); P_L_adj,max is the maximum adjustable load reduction value.

[0194] 2) Constraints of Carbon Market Mechanisms (Dynamic)

[0195] (1) The carbon cost coefficient is used as one of the constraints to characterize carbon price fluctuations. As an uncertain parameter, a range of carbon price fluctuations that can guarantee the economics and feasibility of the system in a medium- to long-term plan can be set, and the carbon cost coefficient can be determined by analyzing different configuration scenarios of source, grid, load and storage.

[0196] (2) Real-time tracking of the "remaining power" of energy storage to avoid the constraints of "blind charging and discharging":

[0197] SOC(t)=SOC(t-1)+P_ SC (t)×0.9-P_ SD (t) / Charge / discharge efficiency.

[0198] In step 104, the carbon source-grid-load-storage configuration is performed, and the configuration information is determined.

[0199] Preferably, the configuration of carbon storage based on grid load and source includes determining the configuration information, such as:

[0200] For the power supply side, with decarbonization as the core, priority should be given to allocating renewable energy, and the reserve capacity of thermal power should be determined in combination with carbon emission intensity.

[0201] For the power grid side, the grid structure is optimized based on the distribution of power sources and loads;

[0202] For the load-storage side, explore the potential of flexible load peak shaving and valley filling, and configure energy storage capacity to match the fluctuation of renewable energy. The energy storage capacity must meet the following requirements: rated energy storage power ≥ maximum output fluctuation of renewable energy × adjustment coefficient.

[0203] In the configuration scheme, all equipment data from the source, grid, load, and storage systems are combined with the full life cycle theory, covering all stages of equipment production, construction, operation, and decommissioning.

[0204] In this invention, the whole life cycle theory is applied throughout the entire process of energy source, grid, load and storage configuration, including: clarifying the quantitative method of carbon emissions during the energy source and grid construction phase, and the calculation model of the carbon footprint of energy storage equipment throughout its entire life cycle; by coupling the calculation of life cycle cost (LCC) and carbon cost, the error of carbon emission assessment is reduced, and the rationality of the low-carbon indicators in the planning scheme is improved.

[0205] Specifically, in this invention, the configuration of source-grid-load carbon storage includes:

[0206] 1) Power supply side: With “low carbonization” as the core, prioritize the allocation of renewable energy sources such as wind power and photovoltaic power, and determine the reserve capacity of thermal power (especially gas-fired thermal power) in combination with carbon emission intensity, calculated according to the formula “the proportion of renewable energy installed capacity ≥ (target carbon intensity reduction rate / benchmark carbon intensity) × 100%”.

[0207] 2) Grid side: Optimize the grid structure based on power supply and load distribution to reduce indirect carbon emissions caused by transmission losses, with a focus on optimizing the expansion of heavy-load lines and the access points of distributed power sources.

[0208] 3) Load and storage side: Explore the potential of flexible load peak shaving and valley filling, and configure energy storage capacity to match the fluctuation of renewable energy. The energy storage capacity must meet the following requirements: rated energy storage power ≥ maximum output fluctuation value of renewable energy × adjustment coefficient (usually taken as 0.3-0.5).

[0209] 4) In the configuration scheme, all equipment data of source, grid, load and storage are combined with the full life cycle theory to cover the entire stage of equipment production, construction, operation and decommissioning.

[0210] In step 105, the planning scheme is determined by solving the problem based on the power grid basic data, comprehensive optimization objectives, constraints, and configuration information.

[0211] Preferably, the planning scheme includes: a power generation capacity list, a load-storage regulation strategy, an annual carbon emission forecast curve, and a provincial power grid source-grid-load-storage configuration scheme for different stages.

[0212] In this invention, the output planning scheme is based on several parts: target layer quantification and weight setting, constraint layer dynamic construction, configuration of all elements of source, grid, load, storage, and carbon, model solution, and scheme output. The target layer solves the multi-objective normalization problem through comprehensive optimization formulas and weight settings; the constraint layer refines the quantitative constraints of dynamic variables such as power balance, power exchange between provincial grids, and adjustable load; the configuration layer adopts a progressive logic of "power source optimization → grid adaptation → load-storage regulation", which significantly improves operability.

[0213] Specifically, this invention employs a "genetic algorithm-particle swarm optimization hybrid algorithm" to solve the problem. The population size and number of iterations are set, and operators (such as crossover probability) are optimized based on the characteristics of provincial power grid data. The resulting solution outputs a planning scheme. This planning scheme includes: a power generation capacity list, load-storage regulation strategies, annual carbon emission forecast curves, and power generation-grid-load-storage configuration schemes for different stages of the provincial power grid.

[0214] This invention provides a method and system for co-location planning of carbon and electricity in provincial power grids. It embeds dynamic carbon cost constraints into the traditional calculation of power system source-grid-load-storage configuration, making the planning scheme more aligned with the needs of low-carbon transformation and avoiding the problem of neglecting environmental costs in traditional planning. The method employs a planning framework of "target quantification - dynamic constraints - full-element coordination - efficient solution," considering dynamic cost changes caused by the carbon market. It guides the optimization direction through a carbon cost function and incorporates CCER trading revenue into the calculation, forming a virtuous cycle incentive mechanism of "emission reduction - revenue - reinvestment." This solves the problems of carbon cost decoupling from LCC (Limited Capacity) in existing technologies, static constraints, and dispersed configuration, achieving coordinated optimization of provincial power grids in medium- and long-term power balance planning and carbon cost for "low-carbon, economical, and reliable" performance.

[0215] The method of this invention can also be applied to scenarios such as the annual rolling adjustment of provincial power grid planning and the planning of supporting power grids for new energy bases, thereby achieving the expected goals of carbon emission reduction and economic efficiency.

[0216] The following specific examples illustrate the embodiments of the present invention.

[0217] Taking a provincial power grid (planned for 2025-2040) as an example, the steps of the electricity-carbon coupling planning method for a provincial power grid are as follows:

[0218] 1. Data Acquisition: Collect all types of installed power output (minutes / hours and more detailed resolution), generator set technical parameters and fuel type, transmission line and substation equipment losses, node load (classified by user type and industry), distributed generation output, energy storage charging and discharging records and constraints, historical carbon emission factors and monitoring data, and electricity market clearing prices and compensation mechanisms in the province.

[0219] 2. Target Quantification: Set the discount rate to 7%, with carbon peak stage weights ω1 = 0.35, ω2 = 0.35, and ω3 = 0.3. LCC accounting covers the entire life cycle cost of equipment, including photovoltaic investment of 7.75 billion yuan and wind power investment of 10.8 billion yuan.

[0220] 3. Constraints: 100 million tCO2 carbon quota in 2025, carbon intensity ≤300gCO2 / kWh, inter-grid exchange power ±5000MW, carbon price fluctuation range [60,100] yuan / tCO2;

[0221] 4. Coordinated configuration: wind and solar power account for 52% (43GW), gas-fired power accounts for 5GW, energy storage accounts for 3.2GW, and flexible load regulation accounts for 3GW;

[0222] 5. Solution and Verification: The output scheme has an LCC of 89 billion yuan and carbon emissions of 0.92 billion tCO2 in 2025; the verification shows that ASAI = 99.94% under high, medium and low scenarios, which meets the target requirements.

[0223] Figure 3 This is a schematic diagram of the structure of a provincial power grid electricity-carbon coupling planning system 300 according to an embodiment of the present invention. Figure 3 As shown, the provincial power grid carbon coupling planning system 300 provided in this embodiment of the invention includes: a data acquisition unit 301, an optimization target determination unit 302, a constraint condition determination unit 303, a configuration unit 304, and a planning scheme determination unit 305.

[0224] Preferably, the data acquisition unit 301 is used to determine the planning boundary and collect basic data of the provincial power grid based on the planning boundary.

[0225] Preferably, the basic data includes: wind and solar resource planning data, load data, equipment parameters, carbon market data, and policy data.

[0226] Preferably, the comprehensive optimization objective includes:

[0227] minF=ω1×F1+ω2×F2+ω3×(1-F3),

[0228] Where F is the comprehensive optimization objective; F1 is the minimized total life cycle cost; F2 is the minimized total life cycle carbon emissions; F3 is the maximized power supply reliability; ω1, ω2, and ω3 are all weighting coefficients, and ω1+ω2+ω3=1.

[0229] Preferably, the optimization target determination unit 302 is used to quantify the target layer and determine the comprehensive optimization target.

[0230] Preferably, the optimization target determination unit further includes:

[0231] The lifecycle cost is determined using the following methods, including:

[0232] LCC = ∑(Investment cost of each piece of equipment × Capital recovery factor) + ∑(Annual operation and maintenance cost + Fuel cost + Carbon cost) × Present value factor - Residual value × Present value factor

[0233] Capital recovery coefficient = [i(1+i)n] / [(1+i)n-1],

[0234] Carbon cost = Carbon allowance unit price × (Actual carbon emissions - Free allowances) - CCER unit price × Certified emission reductions

[0235] Residual value = Initial investment × Residual value rate (5% - 10%)

[0236] The total carbon emissions over the entire life cycle are determined using the following methods, including:

[0237] C_total=C_source+C_network+C_storage+C_l load,

[0238] C_source = ∑(Annual power generation × Unit carbon emission intensity × Operating life),

[0239] C_network = Carbon emissions during the construction phase (steel / cement consumption × corresponding carbon emission factor)

[0240] + Carbon emissions during operation (grid loss electricity × average carbon intensity of power source),

[0241] C_storage = Life-cycle carbon emission intensity × Energy storage capacity × Operating years

[0242] C_load = ∑(Electricity consumption of different load categories × Corresponding power supply carbon intensity),

[0243] The power supply reliability rate is determined using the following methods, including:

[0244] ASAI = (Total power supply time - Power outage time) / Total power supply time × 100%

[0245] Where LCC is the total life cycle cost; i is the discount rate; n is the design life; C_total is the total carbon emissions over the entire life cycle; C_source is the carbon emissions from the power source; C_network is the carbon emissions from the power grid; C_storage is the carbon emissions from energy storage; and C_load is the carbon emissions from the load.

[0246] Preferably, the constraint determination unit 303 is used to construct a dynamic constraint system and determine the constraint conditions.

[0247] Preferably, the constraints include:

[0248] Power balance constraints, including: P _G (t)+P _SD (t)+P _IX (t)=P _L (t)-P _Ladj (t)+P _SC (t)+P _Loss (t),

[0249] Carbon emission constraints include:

[0250] ∑C_ total ≤C_ Limit ,

[0251] C_ total / E_ total ≤C_ Standard ,

[0252] Annual carbon emissions ≤ annual carbon allowance

[0253] Equipment capacity constraints include:

[0254] 0≤P_ Gi (t)≤P_ Gi ,max,

[0255] P_ Linej (t)≤P_ Linej ,max,

[0256] Load constraints, including:

[0257] 0≤P_ SD (t)≤P_ S max, 0≤P_ SC (t)≤P_ S ,max,SOC_ min ≤SOC(t)

[0258] ≤SOC_ max ,

[0259] 0≤P_Ladj(t)≤P_L_adj, max(adjustment amount ≤ maximum potential), adjustment interval ≥15min,

[0260] Constraints of the carbon market mechanism include:

[0261] Setting a carbon price fluctuation range, determining the carbon cost coefficient through analysis of different configuration scenarios of source, grid, load, and storage; and based on SOC(t)=SOC(t-1)+P_ SC (t)×0.9-P_ SD (t) / Real-time tracking of energy storage charge and discharge efficiency;

[0262] Among them, P _G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX (t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the grid loss power; C_total represents the total carbon emissions over the entire life cycle; C_ Limit For the system's entire life cycle carbon emission limit; E_ total For the total power generation, C_ Standard This is the provincial industry benchmark value; P_ Gi (t) represents the output of the i-th generator unit at time t; P_ Gi ,max is the rated capacity of power supply i; P_ Linej (t) represents the power transmitted by line j at time t; P_ Linej ,max is the rated current carrying capacity of line j; P_ S ,max is the upper limit of the charging / discharging power of the energy storage system; SOC_ min and SOC_ max These represent the upper and lower safety limits of the energy storage SOC; P_ Lrigid P_Ladj(t) represents the rigid, non-adjustable load; P_Ladj(t) represents the adjustable load reduction amount; and P_L_adj,max represents the maximum adjustable load reduction value.

[0263] Preferably, the configuration unit 304 is used to configure the source-grid-load-storage carbon system and determine the configuration information.

[0264] Preferably, the configuration unit 304 configures the source-grid-load carbon storage system and determines the configuration information, including:

[0265] For the power supply side, with decarbonization as the core, priority should be given to allocating renewable energy, and the reserve capacity of thermal power should be determined in combination with carbon emission intensity.

[0266] For the power grid side, the grid structure is optimized based on the distribution of power sources and loads;

[0267] For the load-storage side, explore the potential of flexible load peak shaving and valley filling, and configure energy storage capacity to match the fluctuation of renewable energy. The energy storage capacity must meet the following requirements: rated energy storage power ≥ maximum output fluctuation of renewable energy × adjustment coefficient.

[0268] In the configuration scheme, all equipment data from the source, grid, load, and storage systems are combined with the full life cycle theory, covering all stages of equipment production, construction, operation, and decommissioning.

[0269] Preferably, the planning scheme determination unit 305 is used to solve the problem based on the power grid basic data, comprehensive optimization objectives, constraints and configuration information to determine the planning scheme.

[0270] Preferably, the planning scheme includes: a power generation capacity list, a load-storage regulation strategy, an annual carbon emission forecast curve, and a provincial power grid source-grid-load-storage configuration scheme for different stages.

[0271] The provincial power grid electric-carbon coupling planning system 300 of this invention corresponds to the provincial power grid electric-carbon coupling planning method 100 of another embodiment of this invention, and will not be described again here.

[0272] According to another aspect of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the methods for a provincial power grid's electric-carbon coupling planning.

[0273] According to another aspect of the present invention, the present invention provides an electronic device, comprising:

[0274] The aforementioned computer-readable storage medium; and

[0275] One or more processors for executing a program in the computer-readable storage medium.

[0276] The present invention has been described with reference to a few embodiments. However, it will be apparent to those skilled in the art that other embodiments besides those disclosed above fall equivalently within the scope of the present invention.

[0277] Generally, all terms used in this invention are interpreted according to their ordinary meaning in the art, unless otherwise expressly defined herein. All references to “a / the / the [device, component, etc.]” ​​are openly interpreted as at least one instance of said device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein need not be performed in the exact order disclosed unless explicitly stated otherwise.

[0278] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0279] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0280] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0281] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0282] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for electricity-carbon coupling planning of a provincial power grid, characterized in that, The method includes: Determine the planning boundaries and collect basic data of the provincial power grid based on the planning boundaries; Quantify the target layer to determine the comprehensive optimization objective; Construct a dynamic constraint system and determine the constraint conditions; Configure the carbon source-grid-load-storage system and determine the configuration information; The planning scheme is determined by solving the problem based on the power grid basic data, comprehensive optimization objectives, constraints, and configuration information.

2. The method according to claim 1, characterized in that, The basic data includes: wind and solar resource planning data, load data, equipment parameters, carbon market data, and policy data.

3. The method according to claim 1, characterized in that, The comprehensive optimization objectives include: minF=ω1×F1+ω2×F2+ω3×(1-F3), Where F is the comprehensive optimization objective; F1 is the minimized total life cycle cost; F2 is the minimized total life cycle carbon emissions; F3 is the maximized power supply reliability; ω1, ω2, and ω3 are all weighting coefficients, and ω1+ω2+ω3=1.

4. The method according to claim 3, characterized in that, The method further includes: The lifecycle cost is determined using the following methods, including: LCC = ∑(Investment cost of each piece of equipment × Capital recovery factor) + ∑(Annual operation and maintenance cost + Fuel cost + Carbon cost) × Present value factor - Residual value × Present value factor Capital recovery coefficient = [i(1+i)n] / [(1+i)n-1], Carbon cost = Carbon allowance unit price × (Actual carbon emissions - Free allowances) - CCER unit price × Certified emission reductions Residual value = Initial investment × Residual value rate (5% - 10%) The total carbon emissions over the entire life cycle are determined using the following methods, including: C_tota l=C_source+C_network+C_storage+C_l oad, C_source = ∑(Annual power generation × Unit carbon emission intensity × Operating life), C_network = Carbon emissions during construction (steel / cement consumption × corresponding carbon emission factor) + Carbon emissions during operation (grid loss × average carbon intensity of power source), C_storage = Life-cycle carbon emission intensity × Energy storage capacity × Operating years C_load = ∑(Electricity consumption of different load categories × Corresponding power supply carbon intensity), The power supply reliability rate is determined using the following methods, including: ASAI = (Total power supply time - Power outage time) / Total power supply time × 100% Where LCC is the total life cycle cost; i is the discount rate; n is the design life; C_total is the total carbon emissions over the entire life cycle; C_source is the carbon emissions from the power source; C_network is the carbon emissions from the power grid; C_storage is the carbon emissions from energy storage; and C_load is the carbon emissions from the load.

5. The method according to claim 1, characterized in that, The constraints include: Power balance constraints, including: P _G (t)+P _SD (t)+P _IX (t)=P _L (t)-P _Ladj (t)+P _SC (t)+P _Loss (t), Carbon emission constraints include: ∑C_ total ≤C_ Limit , C_ total / AND_ total ≤C_ Standard , Annual carbon emissions ≤ annual carbon allowance Equipment capacity constraints include: 0≤P_ Gi (t)≤P_ Gi ,max, P_ Linej (t)≤P_ Linej ,max, Load constraints, including: 0≤P_ SD (t)≤P_ S ,max,0≤P_ SC (t)≤P_ S ,max,SOC_ min ≤SOC(t) ≤SOC_ max , 0≤P_Ladj(t)≤P_L_adj, max(adjustment amount ≤ maximum potential), adjustment interval ≥15min, Constraints of the carbon market mechanism include: Setting a carbon price fluctuation range, determining the carbon cost coefficient through analysis of different configuration scenarios of source, grid, load, and storage; and based on SOC(t)=SOC(t-1)+P_ SC (t)×0.9-P_ SD (t) / Real-time tracking of energy storage charge and discharge efficiency; Among them, P _G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX (t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the grid loss power; C_total represents the total carbon emissions over the entire life cycle; C_ Limit For the system's entire life cycle carbon emission limit; E_ total For the total power generation, C_ Standard This is the provincial industry benchmark value; P_ Gi (t) represents the output of the i-th generator unit at time t; P_ Gi ,max is the rated capacity of power supply i; P_ Linej (t) represents the power transmitted by line j at time t; P_ Linej ,max is the rated current carrying capacity of line j; P_ S ,max is the upper limit of the charging / discharging power of the energy storage system; SOC_ min and SOC_ max These represent the upper and lower safety limits of the energy storage SOC; P_ Lrigid P_Ladj(t) represents the rigid, non-adjustable load; P_Ladj(t) represents the adjustable load reduction amount; and P_L_adj,max represents the maximum adjustable load reduction value.

6. The method according to claim 1, characterized in that, Configure the carbon source-grid-load-storage system and determine the configuration information, including: For the power supply side, with decarbonization as the core, priority should be given to allocating renewable energy, and the reserve capacity of thermal power should be determined in combination with carbon emission intensity. For the power grid side, the grid structure is optimized based on the distribution of power sources and loads; For the load-storage side, explore the potential of flexible load peak shaving and valley filling, and configure energy storage capacity to match the fluctuation of renewable energy. The energy storage capacity must meet the following requirements: rated energy storage power ≥ maximum output fluctuation value of renewable energy × adjustment coefficient; In the configuration scheme, all equipment data from the source, grid, load, and storage systems are combined with the full life cycle theory, covering all stages of equipment production, construction, operation, and decommissioning.

7. The method according to claim 1, characterized in that, The planning scheme includes: a power generation capacity list, a load-storage regulation strategy, an annual carbon emission forecast curve, and a provincial power grid source-grid-load-storage configuration scheme for different stages.

8. A provincial power grid's electricity-carbon coupling planning system, characterized in that, The system includes: The data acquisition unit is used to determine the planning boundaries and collect basic data of the provincial power grid based on the planning boundaries; The optimization target determination unit is used to quantify the target layer and determine the comprehensive optimization target. The constraint determination unit is used to construct a dynamic constraint system and determine the constraint conditions. The configuration unit is used to configure the carbon source, grid, load, and storage, and to determine the configuration information. The planning scheme determination unit is used to solve the problem based on the power grid basic data, comprehensive optimization objectives, constraints and configuration information to determine the planning scheme.

9. The system according to claim 8, characterized in that, The basic data includes: wind and solar resource planning data, load data, equipment parameters, carbon market data, and policy data.

10. The system according to claim 8, characterized in that, The comprehensive optimization objectives include: minF=ω1×F1+ω2×F2+ω3×(1-F3), Where F is the comprehensive optimization objective; F1 is the minimized total life cycle cost; F2 is the minimized total life cycle carbon emissions; F3 is the maximized power supply reliability; ω1, ω2, and ω3 are all weighting coefficients, and ω1+ω2+ω3=1.

11. The system according to claim 10, characterized in that, The optimization target determination unit further includes: The lifecycle cost is determined using the following methods, including: LCC = ∑(Investment cost of each piece of equipment × Capital recovery factor) + ∑(Annual operation and maintenance cost + Fuel cost + Carbon cost) × Present value factor - Residual value × Present value factor Capital recovery coefficient = [i(1+i)n] / [(1+i)n-1], Carbon cost = Carbon allowance unit price × (Actual carbon emissions - Free allowances) - CCER unit price × Certified emission reductions Residual value = Initial investment × Residual value rate (5% - 10%) The total carbon emissions over the entire life cycle are determined using the following methods, including: C_tota l=C_source+C_network+C_storage+C_l oad, C_source = ∑(Annual power generation × Unit carbon emission intensity × Operating life), C_network = Carbon emissions during construction (steel / cement consumption × corresponding carbon emission factor) + Carbon emissions during operation (grid loss × average carbon intensity of power source), C_storage = Life-cycle carbon emission intensity × Energy storage capacity × Operating years C_l oad = ∑(Electricity consumption of classified loads × Corresponding power supply carbon intensity), The power supply reliability rate is determined using the following methods, including: ASAI = (Total power supply time - Power outage time) / Total power supply time × 100% Where LCC is the total life cycle cost; i is the discount rate; n is the design life; C_total is the total carbon emissions over the entire life cycle; C_source is the carbon emissions from the power source; C_network is the carbon emissions from the power grid; C_storage is the carbon emissions from energy storage; and C_load is the carbon emissions from the load.

12. The system according to claim 8, characterized in that, The constraints include: Power balance constraints, including: P _G (t)+P _SD (t)+P _IX (t)=P _L (t)-P _Ladj (t)+P _SC (t)+P _Loss (t), Carbon emission constraints include: ∑C_ total ≤C_ Limit , C_ total / AND_ total ≤C_ Standard , Annual carbon emissions ≤ annual carbon allowance Equipment capacity constraints include: 0≤P_ Gi (t)≤P_ Gi ,max, P_ Linej (t)≤P_ Linej ,max, Load constraints, including: 0≤P_ SD (t)≤P_ S ,max,0≤P_ SC (t)≤P_ S ,max,SOC_ min ≤SOC(t)≤SOC_ max , 0≤P_Ladj(t)≤P_L_adj, max(adjustment amount ≤ maximum potential), adjustment interval ≥15min, Constraints of the carbon market mechanism include: Setting a carbon price fluctuation range, determining the carbon cost coefficient through analysis of different configuration scenarios of source, grid, load, and storage; and based on SOC(t)=SOC(t-1)+P_ SC (t)×0.9-P_ SD (t) / Real-time tracking of energy storage charge and discharge efficiency; Among them, P _G (t) represents the total power output of the power source at time t; P _SD (t), P _SC (t) represents the energy storage charging / discharging power; P _IX (t) represents the inter-network switching power; P _L (t) represents the initial load power; P _Ladj (t) represents the adjustable load reduction amount; P _Loss (t) represents the grid loss power; C_total represents the total carbon emissions over the entire life cycle; C_ Limit For the system's entire life cycle carbon emission limit; E_ total For the total power generation, C_ Standard This is the provincial industry benchmark value; P_ Gi (t) represents the output of the i-th generator unit at time t; P_ Gi ,max is the rated capacity of power supply i; P_ Linej (t) represents the power transmitted by line j at time t; P_ Linej ,max is the rated current carrying capacity of line j; P_ S ,max is the upper limit of the charging / discharging power of the energy storage system; SOC_ min and SOC_ max These represent the upper and lower safety limits of the energy storage SOC; P_ Lrigid P_Ladj(t) represents the rigid, non-adjustable load; P_Ladj(t) represents the adjustable load reduction amount; and P_L_adj,max represents the maximum adjustable load reduction value.

13. The system according to claim 8, characterized in that, The configuration unit configures the carbon source, grid, load, and storage, and determines the configuration information, including: For the power supply side, with decarbonization as the core, priority should be given to allocating renewable energy, and the reserve capacity of thermal power should be determined in combination with carbon emission intensity. For the power grid side, the grid structure is optimized based on the distribution of power sources and loads; For the load-storage side, explore the potential of flexible load peak shaving and valley filling, and configure energy storage capacity to match the fluctuation of renewable energy. The energy storage capacity must meet the following requirements: rated energy storage power ≥ maximum output fluctuation value of renewable energy × adjustment coefficient; In the configuration scheme, all equipment data from the source, grid, load, and storage systems are combined with the full life cycle theory, covering all stages of equipment production, construction, operation, and decommissioning.

14. The system according to claim 8, characterized in that, The planning scheme includes: a power generation capacity list, a load-storage regulation strategy, an annual carbon emission forecast curve, and a provincial power grid source-grid-load-storage configuration scheme for different stages.

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