A power structure evolution method for energy-economy-environment system

Abstract

The invention discloses a power structure evolution method for an energy-economy-environment system, comprising the following steps: 1) establishing a multi-sector dynamic economic growth model including a production sector, an environmental sector, a household and a government to describe the economic growth process and its impact on the environment, and obtain government environmental expenditure; 2) establishing a lumped power planning model, and then incorporating the lumped power planning model as a submodule of energy into the energy-economy-environment system, and using this to calculate the power environmental efficiency; 3) based on a relaxation algorithm, using power environmental efficiency and government environmental expenditure as interactive variables, realizing the coupling of the multi-sector dynamic economic growth model and the lumped power planning model, and ensuring the convergence of the multi-sector dynamic economic growth model and the lumped power planning model, the method realizes the coupling of various elements in the 3E system, effectively improves the comprehensiveness of the long-term power planning scheme, and has high feasibility.

Description

Technical Field

[0001] The present invention belongs to the intersection of power system and economics, and relates to a power structure evolution method for energy-economy-environment system. Background Art

[0002] As the country with the largest energy consumption and carbon emissions in the world, my country is facing a particularly urgent and arduous task of promoting energy revolution. This not only involves a solemn commitment to the international community, but also concerns whether my country can occupy a favorable position in the new round of technological revolution and achieve a successful transformation of economic structure and energy structure. Therefore, it is urgent to study the power structure adjustment method. In the process of realizing the present invention, the inventor found that the prior art has at least the following shortcomings and deficiencies:

[0003] (1) The elements of the 3E system are coupled and coordinated with each other. It is one-sided to ignore economic and environmental factors and discuss the development of the energy system in isolation.

[0004] (2) The power structure planning model starts with specific technologies and takes economic and environmental factors as boundary conditions to simplify the description of the economy and environment. The comprehensiveness and economy of the planning scheme are poor, and sustainable development has long remained at the conceptual level.

[0005] (3) Macroeconomic models focus on the relationship between energy consumption, economy and environment, but cannot describe the specific details of power supply planning and cannot guarantee the feasibility of the plan. Summary of the invention

[0006] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a power structure evolution method for the energy-economy-environment system, which realizes the coupling of various elements in the 3E system and effectively improves the comprehensiveness and technical feasibility of long-term power planning solutions.

[0007] To achieve the above-mentioned purpose, the power structure evolution method for the energy-economy-environment system described in the present invention comprises the following steps:

[0008] 1) Based on the theory of infinite dynamic economic growth, a multi-sector dynamic economic growth model including production sector, environmental sector, household and government is established to describe the economic growth process and its impact on the environment, and to obtain government environmental expenditure;

[0009] 2) Construct the internal and external constraints of the power system, establish a lumped power planning model with the goal of minimizing the total investment and operation costs, and then incorporate the lumped power planning model into the energy-economy-environment system as a sub-module of energy, and use it to calculate the power environmental efficiency;

[0010] 3) Based on the relaxation algorithm, with power environmental efficiency and government environmental expenditure as interactive variables, the coupling of the multi-sector dynamic economic growth model and the lumped power planning model is realized, and the convergence of the multi-sector dynamic economic growth model and the lumped power planning model is ensured.

[0011] The specific operations of step 1) are:

[0012] 11) Build a multi-sector dynamic economic growth model of production sector, environmental sector, household and government, and then verify the parameters of the multi-sector dynamic economic growth model based on maximum likelihood estimation;

[0013] 12) Taking infinite social utility maximization as the objective function, environmental quality is included in the utility function as a commodity, and personal utility is maximized by choosing to improve consumption level or environmental quality, thus achieving the coupling between economy and environment in the multi-sector dynamic economic growth model;

[0014] 13) Through the indefinite economic growth model, the state of balanced growth of society, economy, energy and environment in the infinite future can be quantitatively described, combined with indefinite planning, to quantitatively reflect the inherent needs of sustainable development;

[0015] 14) Calculate the equilibrium solution for each period on the saddle point path of economic growth, analyze the impact of the macro-economy on the power planning scheme period by period, achieve a balance between environmental quality demand and sustained economic growth during the dynamic growth process, and obtain government environmental expenditure.

[0016] The specific operations of step 2) are:

[0017] 21) Use power demand data as boundary conditions to achieve the coupling of energy and economy;

[0018] 22) Construct external primary energy output and government environmental expenditure constraints, internal power balance and peak and frequency regulation reserve constraints, and establish a lumped power planning model with the goal of minimizing the annual value of investment costs and operating costs;

[0019] 23) The lumped power planning model is incorporated into the energy-economy-environment system as a sub-module of energy, and the environmental efficiency of power supply is calculated based on it.

[0020] The specific operations of step 3) are:

[0021] 31) The environmental efficiency of power supply and government environmental expenditure are used as interactive variables of the energy-environment system. The environmental efficiency of power supply directly reflects the amount of carbon dioxide emissions that can be reduced by the power system under unit environmental expenditure, and the government environmental expenditure represents the optimal solution of the multi-sector dynamic economic growth model under the set environmental efficiency.

[0022] 32) The government environmental expenditure is transferred to the aggregate power planning model as a clean energy subsidy in exchange for environmental emission reduction. Under the constraint of government environmental expenditure, the aggregate power planning model invests in new energy and simulates the operation of the power system. At the same time, it calculates the solution with the maximum power environmental efficiency and returns it to the multi-sector dynamic economic growth model, thus realizing the coupling of the aggregate power planning model and the multi-sector dynamic economic growth model.

[0023] The present invention has the following beneficial effects:

[0024] The power structure evolution method for the energy-economy-environment system described in the present invention, in specific operation, establishes a multi-sector dynamic economic growth model including the production sector, the environmental sector, households and the government to describe the economic growth process and its impact on the environment, so as to avoid discussing the development of the energy system in isolation. In addition, a lumped power planning model is established, and then the lumped power planning model is incorporated into the energy-economy-environment system as a sub-module of energy, and the power environmental efficiency and government environmental expenditure are used as interactive variables to achieve the coupling of the multi-sector dynamic economic growth model and the lumped power planning model, thereby realizing the construction of the 3E system, effectively improving the comprehensiveness of the long-term power planning solution, and having high feasibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a planning flow chart of the power supply structure for the 3E system in the present invention;

[0026] Figure 2 It is the optimal economic growth trajectory and its transfer process diagram in the present invention;

[0027] Figure 3 It is a power supply structure diagram in the present invention;

[0028] Figure 4 It is a carbon dioxide emission trajectory diagram of the power industry in the present invention;

[0029] Figure 5 This is the impact diagram of government environmental expenditure on GDP in the present invention;

[0030] Figure 6 It is the iterative convergence diagram in the present invention. DETAILED DESCRIPTION

[0031] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0032] like Figure 1 As shown, the power structure evolution method for the energy-economy-environment system of the present invention is divided into three parts in specific operation, namely, an upper-level dynamic economic model, a lower-level lumped power structure planning model and a coordination layer for model iterative convergence.

[0033] A: Upper level dynamic economic model

[0034] (1) Establish a multi-sector dynamic economic growth model that includes the production sector, environmental sector, households and government.

[0035] 1. Production department: The Cobb-Douglas function is used to describe the output process of the manufacturer, and its equation is expressed as:

[0036]

[0037] Among them, Y t is the manufacturer’s output, K t is the capital stock, K t >0,A t Represents the technical level, L t Represents the labor force, A t L t represents effective labor force, α is the production elasticity coefficient, 0<α<1, y t represents per capita output, k t represents the capital stock per capita, y t and k t The dynamic equation is:

[0038]

[0039] Divide both sides of equation (2) by L t ,have to

[0040] k′ t =y t -c t -gov t -(n+δ)k t (3)

[0041] Among them, n is the population growth rate, g is the rate of technological progress, δ is the asset depreciation rate, and Gov t is the percentage of output, Gov t for:

[0042]

[0043] Where φ is the ratio of environmental expenditure to GDP, 0≤φ≤R env , 0 <c t <y t ,y t >0,c t >0, R env is the ratio of maximum environmental expenditure to GDP, and δ is the depreciation rate.

[0044] 2. Environmental sector: If pollution is regarded as a by-product of the production process, the pollution stock is proportional to GDP and inversely proportional to environmental expenditure. The environmental sector can be expressed as:

[0045]

[0046] Formula (5) is the environment-economy coupling equation. Formula (5) represents the pollution y generated in the production process. t ·z t and government environmental governance efficiency t σ t and environmental self-purification capacity ηp t The difference between t represents carbon emission intensity, gov t Government environmental spending, gov t It is obtained through lower-level power supply planning and production simulation, η is the environmental self-purification rate, P t represents the pollutant stock, P t >0,σ t represents the environmental efficiency of the power supply, σ t From the simulation of the lower model, σ t represents the amount of carbon dioxide emissions that can be reduced by unit environmental expenditure in the power industry, σ t Determined by the development level of underlying electrical related technologies.

[0047] 3. Representative households: Using a constant relative risk aversion function, environmental quality is included as a commodity in the utility function, that is,

[0048]

[0049] Among them, u(c,p) is the instantaneous utility function, θ and ω represent the cross-regional elasticity coefficients of consumption and pollution, L is the labor force population, and w t is the labor income of the household unit, ρ is the subjective discount rate, the more serious the pollution, the higher the t The larger the value, the worse the environmental quality, and residents can achieve the coupling of economy and environment by maximizing their personal utility.

[0050] (2) Taking the maximization of indefinite social utility as the objective function, considering per capita consumption and environmental quality, and combining indefinite planning to reflect the inherent needs of sustainable development;

[0051] (3) The constraints are written into the above objective function in the form of multipliers, and the dynamic economic model is solved by the Lagrangian function. The Lagrangian function is:

[0052]

[0053] in, and are Hamilton multipliers and Lagrange multipliers respectively. They need to be converted into present values ​​in the solution process. Let λ i,t is the present value Hamilton multiplier μ i,t The present value Lagrange multiplier, B is equal to the initial value of labor force L0, β = ρ-n. According to the theory of dynamic economics, the optimality condition of the dynamic economics model is:

[0054]

[0055]

[0056]

[0057]

[0058]

[0059] According to the boundary value condition, since k t is not equal to 0, then μ 6,t =0,μ 4,t =0; when c t =0, as long as c t If we increase it a little, we can improve the efficiency, then μ 5,t = 0, i.e. paddy field condition; due to the pollution stock p t >0, then μ 1,t =0, during the calculation process, when c t =0, k t =0, p t = 0, these situations will be naturally avoided when solving boundary value problems of differential equations by shooting method, so μ 1,t =0,μ 4,t =0,μ5=0,μ 6,t =0 is established;

[0060] (4) Using China’s actual economic data to calibrate the parameters of the dynamic economics model;

[0061] (5) Solve the equilibrium state of the above equation by optimizing the conditions and the maximum principle, and prove the stability of the transition process;

[0062] (6) Taking China's actual capital stock k0 as a reference, select the initial consumption c0 and bring it into the differential equation. Use the shooting method to solve the optimal consumption and capital path and determine whether the boundary value condition is met. If not, select other values ​​and assign them to c0. Start the next cycle until the boundary value condition is met.

[0063] (7) Output the dynamic trajectory of economic growth and pass the government environmental expenditure to the lower-level model.

[0064] Figure 2 The saddle point path and its transfer process are calculated after calibration with China’s actual parameters. Assume that the maximum environmental expenditure for electricity accounts for the proportion of GDP as R env , when φ=0 and φ=R env When , the model has two different stable states, and the optimal trajectory changes between the saddle point paths of the two stable states. Figure 2 The circle in the middle is the saddle point trajectory of economic operation, and the dotted line is the linearized path around the equilibrium point.

[0065] B: Lower-level centralized voltage planning model

[0066] (1) The lumped power planning model considers each type of power source as a whole, with the goal of minimizing the investment and operation costs. Its objective function is:

[0067]

[0068]

[0069]

[0070]

[0071] v g,t =x g,t+1 -x g,t (17)

[0072] Among them, G is the type set of the unit, F ID is the total cost of investment, construction and operation, F Inv 、F Op and F Mai They represent investment and construction costs, operating costs, and maintenance costs, respectively. Inv represents the unit capacity investment cost, C Mai is the sum of fixed operation and maintenance costs per unit capacity, C Op is the variable operating cost, T Life g Indicates the life cycle of the g-type power supply, TH Inv is the planning level year, v g,t is the number of type g power sources invested and constructed in period t, o g,t is the average number of power sources of category g operating in period t, x g,t is the number of g-type power sources built in the t-th period, h g,t is the annual utilization hours of the g-type power source, P Max g is the capacity of the g-th type unit, CRF is the capital recovery factor, and ρ is the discount rate.

[0073] (2) Establish constraints on maintenance, investment and construction capacity, reliability, primary energy, peak load regulation and standby, average unit output level, and environmental expenditure, expressed as:

[0074] 0≤o g,t ≤R g,t x g,t (18)

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083] (3) Solve the power planning procedure without environmental expenditure and obtain the power structure plan under the baseline state;

[0084] (4) Add environmental expenditure constraints, output the power structure plan, and calculate the power environmental efficiency and pass it to the coordination layer.

[0085] Figure 3 This is the power structure plan when the proportion of environmental expenditure accounts for 0.5% of GDP. Among them, the proportion of thermal power will gradually decrease from 68.1% to 55.6% from 1990 to 2040. In the early stage of power planning, the cost of other power sources is relatively high, and thermal power and hydropower are almost the only options for power planning. After 2000, the competitiveness of nuclear power has gradually increased and maintained a relatively stable growth rate. Eventually, its share will stabilize between 7% and 10%.

[0086] Figure 4 The carbon dioxide emission trajectory of the power industry under different government environmental expenditure ratios. In its "Nationally Determined Contribution" to the Paris Agreement, China proposed to peak carbon dioxide emissions around 2030. In order to meet this goal, the proportion of environmental expenditure to GDP remains at around 0.67%.

[0087] from Figure 5 It can be seen that environmental expenditure has a more obvious impact on the macro-economy in the early stage, but gradually decreases in the later stage. Overall, the expenditure of the power industry has a smaller impact on the economy, with the maximum impact on GDP being about 0.3%.

[0088] C: Coordination Layer

[0089] (1) Relax the peak and frequency regulation constraints of renewable energy in the power planning model, that is, Equation (23) and Equation (24), and obtain the upper bound σ of the power environmental efficiency from the lower problem: sup t .

[0090] (2) Relax the environmental sector-related constraints in the economic growth model, that is, equation (5). Since there is no environmental expenditure, its output will be greater than that with environmental expenditure, and φ t With y t Multiply them together to get the upper bound of government investment Gov sup t .

[0091] (3) The upper bound of the power environment efficiency is calculated by relaxing the problem, so that the actual power environment efficiency σ D t Try to get as close to the upper bound σ sup t , where the relaxed problem is:

[0092]

[0093]

[0094]

[0095]

[0096]

[0097] in, and are the surplus and deficit variables, σ D t represents the power environment efficiency transmitted from the bottom layer to the coordination layer, σ D t According to the power planning model, Gov D t represents the government environmental expenditure transmitted from the bottom layer to the coordination layer, Gov D t Equal to Gov t ,set up is the dual variable of formula (28), It indicates the change in actual power environmental efficiency and its upper limit difference caused by a change of 1 in government environmental expenditure.

[0098] (4) Let Gov U tThe government environmental expenditure after the coordination layer correction, Gov U t In order to make the environmental efficiency of the power supply equal to the given upper bound, the value of government environmental expenditure is:

[0099]

[0100] Because the upper Gov t Limited, φ t From 0 to R env Therefore, Gov t It is not completely equal to Gov U t , we can only decide the investment and construction time and make the two as close as possible.

[0101] (5) Under the same environmental investment schedule, find the environmental efficiency σ that is closest to the actual power supply D t σ U t The solution returns to the upper layer, that is

[0102] min|σ U t -σ D t | (33)

[0103]

[0104]

[0105]

[0106] Aux U gov,τ =Aux id,τ (37)

[0107] τ∈{t|Aux id,t +Aux D gov,t =1} (38)

[0108] Among them, Aux id,t represents the revised environmental expenditure table, Aux D gov,t Represented by σ D t The environmental expenditure table calculated according to the maximum principle, λ 1,t and 2,t is the present value Hamilton multiplier in formula (13), and τ represents the revised environmental expenditure table relative to Aux D gov,t The time point when the status is inconsistent;

[0109] (6) According to the maximum principle, the σ transmitted to the upper layer U t and the σ calculated at the bottom layer D t The power supply environmental efficiency is calculated with the minimum difference as the goal, and the power supply environmental efficiency σ that is closest to the actual power supply environmental efficiency is selected. D t The solution is returned to the upper layer;

[0110] (7) U τ After being passed to the upper-level dynamic growth model, the next round of iteration is started. When the power environment efficiency σ D t After stabilization, determine whether the convergence condition (39) is met;

[0111] |σ sup t -σ D t |≤ζ (39)

[0112] σ sup t =σ sup t -sign(σ sup t -σ D t )·Δσ (40)

[0113] Among them, ζ is the preset value, and σ sup t -σ D t Is it less than the preset value ζ? When the convergence condition is met, the iteration is stopped. When it is not met, the upper bound is corrected according to formula (40), and then the iteration is continued until the convergence condition is met.

[0114] The coordination layer changes Gov t The value of σ D t Try to get as close as possible to the given upper bound σ sup t , and then modify the upper bound through the gradient method, and finally make the upper and lower bounds equal and the model converges.

[0115] Figure 6 It is an iterative convergence process, which is reflected in the power environment efficiency. As the number of iterations increases, the power environment efficiency gradually converges to the true value from the given upper bound.

Claims

1. A power structure evolution method for energy-economy-environment system, characterized in that: The following steps are involved: 1) Based on the theory of infinite dynamic economic growth, a multi-sector dynamic economic growth model including production sector, environmental sector, household and government is established to describe the economic growth process and its impact on the environment, and to obtain government environmental expenditure; 2) Construct the internal and external constraints of the power system, establish a lumped power planning model with the goal of minimizing the total investment and operation costs, and then incorporate the lumped power planning model into the energy-economy-environment system as a sub-module of energy, and use it to calculate the power environmental efficiency; 3) Based on the relaxation algorithm, with power environmental efficiency and government environmental expenditure as interactive variables, the coupling of the multi-sector dynamic economic growth model and the lumped power planning model is realized, and the convergence of the multi-sector dynamic economic growth model and the lumped power planning model is ensured; The specific operations of step 1) are: 11) Build a multi-sector dynamic economic growth model of production sector, environmental sector, household and government, and then verify the parameters of the multi-sector dynamic economic growth model based on maximum likelihood estimation; 12) Taking infinite social utility maximization as the objective function, environmental quality is included in the utility function as a commodity, and personal utility is maximized by choosing to improve consumption level or environmental quality, thus achieving the coupling between economy and environment in the multi-sector dynamic economic growth model; 13) Through the indefinite economic growth model, the state of balanced growth of society, economy, energy and environment in the infinite future can be quantitatively described, combined with indefinite planning, to quantitatively reflect the inherent needs of sustainable development; 14) Calculate the equilibrium solution of each period on the saddle point path of economic growth, analyze the impact of macroeconomics on power planning schemes period by period, achieve the balance between environmental quality demand and sustained economic growth in the dynamic growth process, and obtain government environmental expenditure; Establish a multi-sector dynamic economic growth model that includes production sectors, environmental sectors, households and the government; Production department: Cobb-Douglas function is used to describe the output process of the manufacturer, and its equation is expressed as: Among them, Y t is the output of the manufacturer, K t is the capital stock, K t >0,A t Represents the technical level, L t Represents the labor force, A t L t represents effective labor force, α is the production elasticity coefficient, 0<α<1, y t represents per capita output, k t represents the capital stock per capita, y t and k t The dynamic equation is: Divide both sides of the first formula in equation (2) by L t ,have to k t ′=y t -c t -gov t -(n+δ)k t (3) Among them, n is the population growth rate, g is the rate of technological progress, δ is the asset depreciation rate, and Gov t is the percentage of output, Gov t for: Where φ is the ratio of environmental expenditure to GDP, 0≤φ≤R env , 0 <c t <y t ,y t >0,c t >0, R env is the maximum environmental expenditure as a percentage of GDP; Environmental sector: If pollution is regarded as a by-product of the production process, the pollution stock is directly proportional to GDP, and the pollution stock is inversely proportional to environmental expenditure, expressed as: Formula (5) is the environment-economy coupling equation. Formula (5) represents the pollution y generated in the production process. t ·z t and government environmental governance efficiency t σ t and environmental self-purification capacity ηp t The difference between t represents carbon emission intensity, gov t Government environmental spending, gov t It is obtained through lower-level power supply planning and production simulation, η is the environmental self-purification rate, P t represents the pollutant stock, P t >0,σ t represents the environmental efficiency of the power supply, σ t It is simulated by the lower model; Representative households: Using a constant relative risk aversion function, environmental quality is included as a commodity in the utility function, that is, Among them, u(c,p) is the instantaneous utility function, θ and ω represent the cross-regional elasticity coefficients of consumption and pollution, respectively, and ρ is the subjective discount rate. The more serious the pollution, the lower the cost of pollution. t The larger the value, the worse the environmental quality, and residents can achieve the coupling of economy and environment by maximizing their personal utility; The specific operations of step 2) are: 21) Use power demand data as boundary conditions to achieve the coupling of energy and economy; 22) Construct external primary energy output and government environmental expenditure constraints, internal power balance and peak and frequency regulation reserve constraints, and establish a lumped power planning model with the goal of minimizing the annual value of investment costs and operating costs; 23) Incorporate the lumped power planning model as a submodule of energy into the energy-economy-environment system and use it to calculate the environmental efficiency of power supply; The lumped power planning model considers each type of power as a whole, with the goal of minimizing the investment and operation costs. Its objective function is: v g,t =x g,t+1 -x g,t (17) Among them, G is the type set of the unit, F ID is the total cost of investment, construction and operation, F Inv 、F Op and F Mai They represent investment and construction costs, operating costs, and maintenance costs, respectively. Inv represents the unit capacity investment cost, C Mai is the sum of fixed operation and maintenance costs per unit capacity, C Op is the variable operating cost, T Life g Indicates the life cycle of the g-type power supply, TH Inv is the planning level year, v g,t is the number of type g power sources invested and constructed in period t, o g,t is the average number of power sources of category g operating in period t, x g,t is the number of g-type power sources built in the t-th period, h g,t is the number of hours of use of the g-type power source in the t-th period, P Max g is the capacity of the g-th type unit, CRF is the capital recovery factor; The specific operations of step 3) are: 31) The environmental efficiency of power supply and government environmental expenditure are used as interactive variables of the energy-environment system. The environmental efficiency of power supply directly reflects the amount of carbon dioxide emissions that can be reduced by the power system under unit environmental expenditure, and the government environmental expenditure represents the optimal solution of the multi-sector dynamic economic growth model under the set environmental efficiency. 32) The government environmental expenditure is transferred to the aggregate power planning model as a clean energy subsidy in exchange for environmental emission reduction. Under the constraint of government environmental expenditure, the aggregate power planning model invests in new energy and simulates the operation of the power system. At the same time, the solution with the maximum power environmental efficiency is calculated and returned to the multi-sector dynamic economic growth model, realizing the coupling of the aggregate power planning model and the multi-sector dynamic economic growth model. The relaxation problem in the relaxation algorithm is: in, and are the surplus and deficit variables, σ D t represents the power environment efficiency transmitted from the bottom layer to the coordination layer, σ D t According to the power planning model, Gov D t represents the government environmental expenditure transmitted from the bottom layer to the coordination layer, Gov D t Equal to Gov t ,set up is the dual variable of formula (28), It indicates the change in actual power environmental efficiency and its upper limit difference caused by a change of 1 in government environmental expenditure.

Images