Power generation and transmission cooperative capacity expansion method considering renewable energy quota and carbon emission

Abstract

The invention discloses a power generation and transmission cooperative capacity expansion method considering renewable energy quota and carbon emission. The method comprises the following steps: establishing a power generation and transmission cooperative capacity expansion model based on a carbon quota limitation constraint and a capacity utilization rate constraint of a power system containing a renewable energy unit in a region, and outputting renewable energy and carbon emission quota preset input quantity input model after processing, and the renewable energy and the power generation and transmission capacity of the power system are cooperatively expanded. According to the method, a multi-region cooperation mechanism of renewable energy sources, carbon emission quotas, region characteristics and power transmission constraints is considered, and a multi-region cooperation planning structure is constructed; the optimal power capacity and transmission capacity are determined through staged and annual scheduling, and the optimal configuration of power production and transmission is realized; an energy storage system is reasonably arranged, a transmission line is built, and effective distribution of electric power among different areas is ensured; the renewable energy source proportion is determined, and under the condition that the requirement of the renewable energy source quota is met, renewable energy source consumption is improved, and carbon emission is reduced.

Description

Technical Field

[0001] This invention relates to a method for coordinated expansion of power generation and transmission capacity, specifically a method for coordinated expansion of power generation and transmission capacity that takes into account renewable energy quotas and carbon emissions. Background Technology

[0002] Currently, when considering transmission network planning, some literature proposes robust planning models that coordinate energy storage and transmission networks. To fully consider the synergistic effects of dynamic thermal setpoint technology for transmission lines and energy storage, the planning model incorporates operational simulations based on typical days. However, these models only consider the single objective of economic efficiency. For transmission network planning, multiple objectives such as cross-sectional transmission capacity and system voltage quality usually need to be taken into account. Other literature considers the uncertainty and time-series correlation of wind and solar power output, establishing a robust optimization collaborative planning model for transmission network transmission channels and energy storage. The collaborative planning of transmission network transmission channels and energy storage can have a complementary effect, helping to reduce wind and solar curtailment capacity and lower the total annual investment. While the existing model addresses operating costs, its scenario considerations are relatively limited and lack multi-scenario transmission expansion. To address this, some literature proposes a comprehensive transmission network planning method based on multi-scenario joint optimization. This method effectively transforms the original transmission network planning model into a more solution-friendly line interruption problem. By limiting the number of short-circuit current exceeding the standard and the number of candidate interrupted branches, the solution speed is accelerated while maintaining accuracy. However, the investment cost is difficult to balance with the absorption of renewable energy. Furthermore, transmission network load is affected by factors such as weather, exhibiting a degree of uncertainty and volatility, and its value is usually not a fixed constant. Damage and aging of transmission equipment are also probabilistic events. Additionally, renewable energy output exhibits spatiotemporal correlations, requiring further in-depth research to reduce the dimensionality of uncertain parameters and thus accelerate the solution process. Therefore, the planning of the power grid also needs to consider the multi-objective planning problem of the power grid with a high proportion of renewable energy access, as well as the uncertainties of load and transmission equipment, improve the uncertainty modeling of load side and transmission equipment, and further consider how to coordinate the expansion of the power grid and the capacity of generator units to obtain the optimal results in several planning years, so as to give a more targeted power system planning scheme. Summary of the Invention

[0003] To address the problems existing in the background art, the present invention provides a method for coordinated expansion of power generation and transmission capacity that takes into account renewable energy quotas and carbon emissions.

[0004] The technical solution adopted in this invention is:

[0005] The present invention provides a method for coordinated capacity expansion of power generation and transmission that considers renewable energy quotas and carbon emissions, comprising:

[0006] A power generation and transmission capacity expansion model based on carbon quota constraints and capacity utilization constraints is established for power systems in regions containing renewable energy units. The model inputs the current preset input of renewable energy and carbon emission quota into the power generation and transmission capacity expansion model. After processing, the optimal power generation and transmission capacity layout and the proportion of renewable energy in the power system are output to coordinate the expansion of renewable energy and power generation and transmission capacity in the power system.

[0007] The power generation and transmission coordinated capacity expansion model is as follows:

[0008]

[0009] Where TC is the total operating cost of the power system; T is the total annual cost; PG t IN represents the total annual power generation cost of the power system in year t. t The total cost of the power system in year t; TR t The annual transmission cost of the power system; ESC t The total cost of energy storage for the power system in year t; DRC t The annual load response cost of the power system; RPS t The cost of renewable energy input to the power system in year t; ETS t The cost of the annual carbon emission allowance for the power system; LC t The cost of load shedding in the power system in year t; RC t The cost of curtailing renewable energy in the power system in year t. This cost can be specifically measured in terms of the amount of electricity transmitted.

[0010] The total annual investment cost IN of the power system mentioned above. t Specifically as follows:

[0011]

[0012] Where M is the total number of regions; K is the set of transmission lines; IC e The cost of power generation capacity input for generator set e, which includes both non-renewable energy units and renewable energy units; EC e,m,t fc represents the newly added generating capacity of generator unit e in region m during year t, in MW; k The fixed cost of power transmission technology for transmission line k; vc k The fixed cost of power transmission technology for transmission line k; d mm′ c is the distance between region m and region m', in km; k N represents the transmission capacity of transmission line k, in MW; m,m′,k,t Let k be the number of power transmission lines using transmission technology between region m and region m' in year t.

[0013] Based on the newly added generating capacity EC of generator set e in region m during year t. e,m,t Determine the optimal power generation capacity layout for the power system.

[0014] The annual renewable energy portfolio input cost (RPS) of the power system is t years. t Specifically as follows:

[0015]

[0016] Where M is the total number of regions; QRb m,t and QRs m,t RP represents the renewable energy input and output of region m in year t, respectively, in MWh; t QRp is the renewable energy cost parameter for year t. m,t This represents the difference between the pre-set and actual renewable energy input for region m in year t, expressed in MWh.

[0017] The cost of curtailing renewable energy in the power system in year t (RC) t Specifically as follows:

[0018]

[0019] Where γ2 is the abandonment and regeneration penalty factor; PG f,j,m,t and PG a,j,m,t These represent the predicted and actual power generation of renewable energy unit j in region m during year t, respectively, in MWh.

[0020] The annual carbon emission allowance cost (ETS) of the power system mentioned above. t Specifically as follows:

[0021]

[0022] Where M is the total number of regions; QCb m,t and QCs m,t , representing the carbon emission quota input and output of region m in year t, respectively, in tCO2; CP t QCp is the carbon emission allowance cost parameter for year t. m,t This represents the difference between the preset input and the actual input of carbon emission quotas for region m in year t, expressed in tCO2.

[0023] The specific carbon quota restrictions are as follows:

[0024]

[0025] Among them, RT m,tLet h be the renewable energy quota ratio for region m in year t; I and J be the sets of non-renewable energy units and renewable energy units, respectively; i,m,t and h j,m,t These represent the annual operating hours of non-renewable energy unit i and renewable energy unit j in region m during year t; Eff i and Eff j The energy generation efficiency of non-renewable energy unit i and renewable energy unit j, respectively; MC i,m,t-1 M represents the cumulative installed capacity of non-renewable energy unit i in region m during year t-1; j,m,t W represents the installed capacity of renewable energy unit j in region m during year t; j QRb is the power generation weight of renewable energy unit j, used to measure the proportion of renewable energy power generation in total power generation; m,t and QRs m,t These represent the renewable energy input and output of region m in year t, respectively; QRp m,t EQ represents the difference between the preset and actual renewable energy input for region m in year t; RL represents the preset renewable energy input limit in MWh; m,t QCp represents the carbon emission allowance for region m in year t, expressed in tCO2. m,t QCb represents the difference between the preset input and actual input of carbon emission allowances for region m in year t. m,t and QCs m,t , respectively, represent the carbon emission quota input and output of region m in year t, in tCO2; E represents the set of generating units in the power system; h e,m,t Eff represents the annual operating hours of generator unit e in region m during year t; e The energy generation efficiency of generator set e; MC e,m,t CM represents the cumulative installed capacity of generator unit e in region m during year t; e is the carbon dioxide emission coefficient of generator set e, in tCO2 / MWh; CL is the preset carbon emission quota input, in tCO2.

[0026] According to the power generation weight W of renewable energy unit j j The percentage of renewable energy sources in the electricity system.

[0027] The capacity utilization constraints are as follows:

[0028]

[0029] Where β is the minimum utilization rate of the transmission line, in percentage; C m,m′,k,tN represents the newly added transmission capacity (in MW) between region m and region m' using transmission line k in year t; m,m′,k,t c is the number of transmission lines k using transmission technology between region m and region m' in year t; l l represents the original capacity of the transmission line; M represents the total number of areas.

[0030] Based on the newly added transmission capacity C of transmission line k between region m and region m' in year t. m,m′,k,t Determine the optimal transmission capacity layout for the power system.

[0031] The present invention provides a power generation and transmission coordinated capacity expansion system that considers renewable energy quotas and carbon emissions, comprising:

[0032] The model building module establishes a power generation and transmission coordinated capacity expansion model for a power system in a region that includes renewable energy units, based on carbon quota constraints and capacity utilization constraints.

[0033] The collaborative expansion module inputs the preset input of renewable energy and carbon emission quota in the current region into the power generation and transmission collaborative expansion model. After processing, it outputs the optimal power generation and transmission capacity layout and the proportion of renewable energy in the power system, so as to collaboratively expand the renewable energy and power generation and transmission capacity of the power system.

[0034] The electronic device of the present invention includes: a memory and a processor coupled to each other, wherein the memory stores program data, and the processor invokes the program data to execute the method described above.

[0035] The present invention provides a computer-readable storage medium having program data stored thereon, which, when executed by a processor, implements the method described above.

[0036] This invention addresses the complex challenges of power capacity and generation / transmission planning, introducing an optimization model designed to minimize upfront equipment investment while providing optimal solutions for generation capacity, transmission capacity, and energy distribution. The invention details the potential to improve renewable energy utilization and reduce greenhouse gas emissions within a dual system and environment framework, as well as pathways to optimize power generation planning. By addressing these issues, it helps to understand how to effectively balance energy planning and environmental governance objectives.

[0037] The beneficial effects of this invention are:

[0038] 1. Most power generation or transmission planning models only consider the proportion of renewable energy or carbon emission constraints, ignoring the synergistic or conflicting effects of the two. This invention proposes for the first time a synergistic model for power system generation and transmission capacity expansion under the constraints of renewable energy and carbon emission quotas. Under the premise of meeting regional electricity demand and carbon emission quotas, it minimizes the global cost of power generation and transmission capacity expansion, significantly improves the system's adaptability to complex policy environments, balances renewable energy development and carbon emission reduction targets, avoids local optima, policy conflicts, or investment waste, and introduces power storage and demand response to enhance system flexibility and economy.

[0039] 2. This invention addresses the feasibility-enhanced genetic algorithm optimization mechanism for large-scale model design. Traditional heuristic algorithms or mathematical programming tools are prone to getting trapped outside the feasible region or experiencing slow convergence when dealing with large-scale multivariate mixed integer models. This invention applies genetic algorithms to the modeling problem of joint capacity expansion in power generation and transmission, innovatively introducing a "feasibility check" mechanism to eliminate chromosomes that do not meet power balance and capacity constraints; employing two-point crossover, multi-gene chromosome encoding, and an elite retention mechanism to improve the quality and stability of the algorithm's solution. This ensures efficient search for "economically feasible" solutions, balancing optimization efficiency and physical feasibility.

[0040] 3. This invention combines regionalized fine-grained modeling with dynamic transmission line planning, and considers a multi-regional collaborative planning mechanism that takes into account regional characteristics and transmission constraints. Most existing models adopt centralized or static planning methods, which do not fully consider the power transmission capacity and geographical factors between regions. In the model of this invention, each region can both generate electricity and import / export electricity. Combining the distance between regions, grid technical parameters (such as loss rate and distance constraints), and interconnection limitations, a multi-regional collaborative planning structure is constructed. A "priority early construction" transmission strategy is designed to maximize the role of newly added transmission lines in the long term, support refined regional grid investment decisions, improve transmission efficiency and system flexibility, avoid regional power supply bottlenecks, and achieve optimal configuration of power production and transmission by rationally deploying energy storage systems and constructing transmission lines through phased and annual scheduling, thereby meeting the ever-growing energy demand. Attached Figure Description

[0041] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0042] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] like Figure 1 As shown, the power generation and transmission capacity expansion method of the present invention, which considers renewable energy quotas and carbon emissions, is as follows:

[0044] A coordinated generation and transmission capacity expansion model is established for power systems in a region that include renewable energy units, based on carbon quota constraints and capacity utilization constraints. The model inputs the current preset input amounts of renewable energy and carbon emission quotas to the model, processes them, and outputs the optimal generation and transmission capacity layout and the proportion of renewable energy in the power system, thereby synergistically expanding the renewable energy and generation and transmission capacity of the power system. The specific details of the coordinated generation and transmission capacity expansion model are as follows:

[0045]

[0046] Where TC is the total operating cost of the power system; T is the total annual cost; PG t IN represents the total annual power generation cost of the power system in year t. t The total cost of the power system in year t; TR t The annual transmission cost of the power system; ESC t The total cost of energy storage for the power system in year t; DRC t The annual load response cost of the power system; RPS t The cost of renewable energy input to the power system in year t; ETS t The cost of the annual carbon emission allowance for the power system; LC t The cost of load shedding in the power system in year t; RC t The cost of curtailing renewable energy in the power system in year t. This cost can be specifically measured in terms of electricity transmission volume.

[0047] This invention presents a hybrid integer linear programming model for coordinated expansion of generation and transmission capacity, considering renewable energy mix and carbon emission quotas. It takes into account the complexity of region-driven generation and regulated transmission. In this model, each region can independently generate, input, and output electricity, expanding generation and transmission capacity to meet electricity demand based on load growth. Furthermore, each region has generation and transmission targets, a renewable energy ratio, and maximum carbon dioxide emission quotas. The coordinated expansion model presents a nondeterministic polynomial NP-hard problem. Metaheuristic methods can typically solve computations related to the problem size of this invention while saving computation time. Therefore, this invention applies a Genetic Algorithm (GA) to find the optimal solution within a reasonable timeframe.

[0048] Total annual power generation cost PG of the power system t Specifically as follows:

[0049]

[0050] Where e is the generator set indicator (k = 1, 2, 3, ..., 11); h e,m,t Eff represents the annual operating hours of generator unit e in region m during year t, in hours. e The energy generation efficiency of generator set e is expressed as a percentage (%). e,m,t Gen represents the cumulative installed capacity of generator units e in region m during year t, in MW. e,t The cost of generating electricity for generator set e.

[0051] The annual transmission cost (TR) of the power system t Specifically as follows:

[0052]

[0053] Where λ is the transmission cost; PT m,m′,k,t α represents the transmission power of transmission line k between region m and region m' in year t, expressed in MWh; k The loss of transmission line k is expressed in percent.

[0054] Total annual energy storage cost of the power system (ESC) t Specifically as follows:

[0055]

[0056] Where π represents the cost per unit of energy storage; ES m,t EH represents the energy storage capacity of region m in year t, in MW; EH represents the annual operating hours of energy storage, in hours.

[0057] Annual Load Response Cost (DRC) of Power Systems t Specifically as follows:

[0058]

[0059] Among them, DR m,t Let τ be the demand response capacity of region m in year t, in MW; τ be the demand response capacity cost; δ be the electricity demand response cost; and DH be the annual operating time of the demand response, in hours.

[0060] The annual load loss cost LC of the power system t Specifically as follows:

[0061]

[0062] Where γ1 is the unload penalty factor; ed m,t Let CS represent the electricity demand of region m in year t, expressed in MWh. m,tPG represents the inter-regional power transmission support amount for region m in year t, in MWh. m,t This represents the total power generation of all types of generating units in region m during year t, expressed in MWh.

[0063] Total annual investment cost of the power system IN t Specifically as follows:

[0064]

[0065] Where M is the total number of regions; k is the transmission line indicator (k = 1, 2, 3, ..., 7), and K is the set of transmission lines; IC e The cost of power generation capacity input for generator set e, which includes both non-renewable energy units and renewable energy units; EC e,m,t fc represents the newly added generating capacity of generator unit e in region m during year t, in MW; k The fixed cost of power transmission technology for transmission line k; vc k The fixed cost of power transmission technology for transmission line k; d mm′ c is the distance between region m and region m', in km; k N represents the transmission capacity of transmission line k, in MW; m,m′,k,t Let k be the number of power transmission lines using transmission technology between region m and region m' in year t.

[0066] Based on the newly added generating capacity EC of generator set e in region m during year t. e,m,t Determine the optimal power generation capacity layout for the power system.

[0067] The annual renewable energy portfolio input cost (RPS) of the power system t Specifically as follows:

[0068]

[0069] Where M is the total number of regions; QRb m,t and QRs m,t RP represents the renewable energy input and output of region m in year t, respectively, in MWh; t QRp is the renewable energy cost parameter for year t. m,t This represents the difference between the pre-set and actual renewable energy input for region m in year t, expressed in MWh.

[0070] The cost of curtailing renewable energy in the power system in year t (RC) t Specifically as follows:

[0071]

[0072] Where γ2 is the abandoned regenerative penalty factor; PG f,j,m,t and PG a,j,m,t These represent the predicted and actual power generation of renewable energy unit j in region m during year t, respectively, in MWh.

[0073] The cost of annual carbon emission allowances for the power system (ETS) t Specifically as follows:

[0074]

[0075] Where M is the total number of regions; QCb m,t and QCs m,t , representing the carbon emission quota input and output of region m in year t, respectively, in tCO2; CP t QCp is the carbon emission allowance cost parameter for year t. m,t This represents the difference between the preset input and the actual input of carbon emission quotas for region m in year t, expressed in tCO2.

[0076] The specific carbon quota restrictions are as follows:

[0077]

[0078] Among them, RT m,t Let h be the renewable energy quota ratio for region m in year t; I and J be the sets of non-renewable energy units and renewable energy units, respectively; i,m,t and h j,m,t These represent the annual operating hours of non-renewable energy unit i and renewable energy unit j in region m during year t; Eff i and Eff j The energy generation efficiency of non-renewable energy unit i and renewable energy unit j are respectively; MC i,m,t-1 M represents the cumulative installed capacity of non-renewable energy unit i in region m during year t-1; j,m,t W represents the installed capacity of renewable energy unit j in region m during year t; j QRb is the power generation weight of renewable energy unit j, used to measure the proportion of renewable energy power generation in total power generation; m,t and QRs m,t These represent the renewable energy input and output of region m in year t, respectively; QRp m,t EQ represents the difference between the preset and actual renewable energy input for region m in year t; RL represents the preset renewable energy input limit in MWh; m,t QCp represents the carbon emission allowance for region m in year t, expressed in tCO2. m,tQCb represents the difference between the preset input and actual input of carbon emission allowances for region m in year t. m,t and QCs m,t , respectively, represent the carbon emission quota input and output of region m in year t, in tCO2; E represents the set of generating units in the power system; h e,m,t Eff represents the annual operating hours of generator unit e in region m during year t; e The energy generation efficiency of generator set e; MC e,m,t CM represents the cumulative installed capacity of generator unit e in region m during year t; e is the carbon dioxide emission coefficient of generator set e, in tCO2 / MWh; CL is the preset carbon emission quota input, in tCO2.

[0079] According to the power generation weight W of renewable energy unit j j The percentage of renewable energy sources in the electricity system.

[0080] The specific capacity utilization constraints are as follows:

[0081]

[0082] Where β is the minimum utilization rate of the transmission line, in percentage; C m,m′,k,t N represents the newly added transmission capacity (in MW) between region m and region m' using transmission line k in year t; m,m′,k,t c is the number of transmission lines k using transmission technology between region m and region m' in year t; l l represents the original capacity of the transmission line; M represents the total number of areas.

[0083] Based on the newly added transmission capacity C of transmission line k between region m and region m' in year t. m,m′,k,t Determine the optimal transmission capacity layout for the power system.

[0084] The structure of this invention ensures that the model takes into account the physical constraints of the power system, represented by capacity, loss, and loss rate parameters. The transmitted power and the number of lines provide a comprehensive view of how energy flows between regions. The constraints of the power generation and transmission coordinated capacity expansion model also include the following:

[0085] Power balance constraints:

[0086]

[0087] Among them, ed m,t Let be the electricity demand of region m in year t, in MWh; φ be the energy storage loss rate, in %.

[0088] Peak load constraints:

[0089]

[0090] Among them, CT m′,m,k,t σ represents the transmission capacity of transmission line k used between region m and region m' in year t, in MW; σ is the peak load reserve factor, in %; PL m,t The peak load of region m in year t is expressed in MW.

[0091] Transmission distance constraints:

[0092]

[0093] in, and These represent the maximum and minimum transmission distances of transmission line k, respectively, in km.

[0094] Power transfer constraints:

[0095]

[0096] Where ρ is the input power share, in %; the above formula represents the minimum power transmission input constraint, and the below formula represents the power transmission constraint.

[0097] Energy storage and demand response constraints:

[0098]

[0099] in, Maximum energy storage capacity, in MW; ε U and ε L These represent the upper and lower limits of the regional peak load demand response capacity, in percentage; the upper formula represents the energy storage constraint, and the lower formula represents the demand response constraint.

[0100] Maximum available generating capacity constraint:

[0101]

[0102] Where, η e This represents the maximum additional power generation of unit e, expressed in MW / year.

[0103] Waste power constraints:

[0104]

[0105] Where ω represents the minimum waste power ratio, expressed as a percentage.

[0106] Regional energy availability constraints:

[0107]

[0108] Nonnegativity constraint:

[0109]

[0110] This invention also designs a power generation and transmission capacity expansion system that considers renewable energy quotas and carbon emissions, including a model building module and a collaborative expansion module. The model building module is used to establish a power system with renewable energy units in the region based on carbon quota constraints and capacity utilization constraints for power generation and transmission capacity expansion. The collaborative expansion module is used to input the preset input of renewable energy and carbon emission quota in the current region into the power generation and transmission capacity expansion model, and output the optimal power generation and transmission capacity layout and renewable energy ratio of the power system after processing, so as to collaboratively expand the renewable energy and power generation and transmission capacity of the power system.

[0111] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented using various computer languages. This application is described with flowcharts of methods, systems, and computer program products according to embodiments of this application.

[0112] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, this invention is intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0113] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations of this application fall within the scope of the equivalent technology of this invention, this application also intends to include these modifications and variations.

[0114] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for coordinated power generation and transmission capacity expansion considering renewable energy quotas and carbon emissions, characterized in that, include: A power generation and transmission capacity expansion model based on carbon quota constraints and capacity utilization constraints is established for power systems in regions containing renewable energy units. The model inputs the current preset input of renewable energy and carbon emission quota into the power generation and transmission capacity expansion model. After processing, the optimal power generation and transmission capacity layout and the proportion of renewable energy in the power system are output to coordinate the expansion of renewable energy and power generation and transmission capacity in the power system.

2. The method for coordinated power generation and transmission capacity expansion considering renewable energy and carbon emissions according to claim 1, characterized in that: The power generation and transmission coordinated capacity expansion model is as follows: Where TC is the total operating cost of the power system; T is the total annual cost; PG t IN represents the total annual power generation cost of the power system in year t. t The total cost of the power system in year t; TR t The annual transmission cost of the power system; ESC t The total cost of energy storage for the power system in year t; DRC t The annual load response cost of the power system; RPS t The cost of renewable energy input to the power system in year t; ETS t The cost of the annual carbon emission allowance for the power system; LC t The cost of load shedding in the power system in year t; RC t The cost of abandoning renewable energy in the power system in year t.

3. The method for coordinated power generation and transmission capacity expansion considering renewable energy and carbon emissions according to claim 2, characterized in that: The total annual investment cost IN of the power system mentioned above. t Specifically as follows: Where M is the total number of regions; K is the set of transmission lines; IC e The cost of power generation capacity input for generator set e, which includes both non-renewable energy units and renewable energy units; EC e,m,t fc represents the newly added generating capacity of generator unit e in region m during year t, in MW; k The fixed cost of power transmission technology for transmission line k; vc k The fixed cost of power transmission technology for transmission line k; d mm′ c is the distance between region m and region m', in km; k N represents the transmission capacity of transmission line k; m,m′,k,t Let k be the number of power transmission lines using transmission technology between region m and region m' in year t; Based on the newly added generating capacity EC of generator set e in region m during year t. e,m,t Determine the optimal power generation capacity layout for the power system.

4. The method for coordinated power generation and transmission capacity expansion considering renewable energy and carbon emissions according to claim 2, characterized in that: The annual renewable energy portfolio input cost (RPS) of the power system is t years. t Specifically as follows: Where M is the total number of regions; QRb m,t and QRs m,t These represent the renewable energy input and output of region m in year t, respectively; RP t QRp is the renewable energy cost parameter for year t. m,t The difference between the preset and actual renewable energy input for region m in year t; The cost of curtailing renewable energy in the power system in year t (RC) t Specifically as follows: Where γ2 is the abandonment and regeneration penalty factor; PG f,j,m,t and PG a,j,m,t These represent the predicted and actual power generation of renewable energy unit j in region m during year t.

5. The method for coordinated power generation and transmission capacity expansion considering renewable energy and carbon emissions according to claim 2, characterized in that: The annual carbon emission allowance cost (ETS) of the power system mentioned above. t Specifically as follows: Where M is the total number of regions; QCb m,t and QCs m,t These represent the carbon emission quota input and output for region m in year t, respectively; CP t QCp is the carbon emission allowance cost parameter for year t. m,t This represents the difference between the preset input and the actual input of carbon emission quotas for region m in year t.

6. The method for coordinated power generation and transmission capacity expansion considering renewable energy and carbon emissions according to claim 1, characterized in that: The specific carbon quota restrictions are as follows: Among them, RT m,t Let h be the renewable energy quota ratio for region m in year t; I and J be the sets of non-renewable energy units and renewable energy units, respectively; i,m,t and h j,m,t These represent the annual operating hours of non-renewable energy unit i and renewable energy unit j in region m during year t; Eff i and Eff j The energy generation efficiency of non-renewable energy unit i and renewable energy unit j, respectively; MC i,m,t-1 M represents the cumulative installed capacity of non-renewable energy unit i in region m during year t-1; j,m,t W represents the installed capacity of renewable energy unit j in region m during year t; j The power generation weight of renewable energy unit j; QRb m,t and QRs m,t These represent the renewable energy input and output of region m in year t, respectively; QRp m,t EQ represents the difference between the preset and actual renewable energy input for region m in year t; RL represents the preset renewable energy input limit; m,t QCp represents the carbon emission allowance for region m in year t. m,t QCb represents the difference between the preset input and actual input of carbon emission allowances for region m in year t. m,t and QCs m,t Let be the carbon emission quota input and output for region m in year t, respectively; E be the set of generating units in the power system; h be the carbon emission quota input and output for region m in year t. e,m,t Eff represents the annual operating hours of generator unit e in region m during year t; e The energy generation efficiency of generator set e; MC e,m,t CM represents the cumulative installed capacity of generator unit e in region m during year t; e CL represents the carbon dioxide emission coefficient of generator set e; CL represents the preset carbon emission quota input. According to the power generation weight W of renewable energy unit j j The percentage of renewable energy sources in the electricity system.

7. The method for coordinated power generation and transmission capacity expansion considering renewable energy and carbon emissions according to claim 1, characterized in that: The capacity utilization constraints are as follows: Where β is the minimum utilization rate of the transmission line; C m,m′,k,t N represents the new transmission capacity of transmission line k used between region m and region m' in year t; m,m′,k,t c is the number of transmission lines k using transmission technology between region m and region m' in year t; l l represents the original capacity of the transmission line; M represents the total number of areas. Based on the newly added transmission capacity C of transmission line k between region m and region m' in year t. m,m′,k,t Determine the optimal transmission capacity layout for the power system.

8. A power generation and transmission capacity expansion system that considers renewable energy quotas and carbon emissions, characterized in that, include: The model building module establishes a power system in a region that includes renewable energy units, based on carbon quota constraints and capacity utilization constraints, to create a coordinated power generation and transmission capacity expansion model. The collaborative expansion module inputs the preset input of renewable energy and carbon emission quota in the current region into the power generation and transmission collaborative expansion model. After processing, it outputs the optimal power generation and transmission capacity layout and the proportion of renewable energy in the power system, so as to collaboratively expand the renewable energy and power generation and transmission capacity of the power system.

9. An electronic device, characterized in that, include: A memory and a processor are coupled to each other, wherein the memory stores program data, and the processor invokes the program data to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing program data thereon, characterized in that, When the program data is executed by the processor, the method as described in any one of claims 1-7 is implemented.

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