A dispatching method and system for PIES to participate in the electricity-carbon-green certificate market

Abstract

The present invention proposes a scheduling method and system for PIES to participate in the electricity-carbon-green certificate market, which belongs to the field of integrated energy technology. The method includes: obtaining the carbon tariff amount of the integrated energy system of the park, based on the user-side green certificate hourly allocation strategy of carbon potential response, and allocating the green certificate corresponding to the electricity quantity hourly on demand according to the carbon potential in each time period; discretizing the time scale of the continuous carbon market and the green certificate market to the same scheduling time scale of the electricity market, establishing a connection trading strategy for the electricity-carbon-green certificate market, determining the green certificate trading volume and the deductible carbon emission reduction, and realizing the dynamic transmission of the three market key variables; based on the green certificate trading volume and the deductible carbon emission reduction, constructing a PIES multi-agent double-layer game optimization scheduling model to realize the scheduling of the integrated energy system of the park. It can effectively reduce the carbon tariff cost, retain the initial energy demand of the load, meet the energy consumption willingness of the enterprise, and compared with the two-to-two market connection trading strategy, it reflects obvious economy and low carbon.

Description

Technical Field

[0001] The present invention belongs to the technical field of integrated energy, and in particular relates to a scheduling method and system for PIES to participate in the electricity-carbon-green certificate market. Background Art

[0002] The statements in this part only provide background technical information related to the present invention, and do not necessarily constitute prior art.

[0003] The introduction and implementation of carbon tariffs have impacted the export trade of high-carbon products in the park-level integrated energy system (PIES), and to a certain extent, affected the international competitiveness of export enterprises. Since the electricity market, carbon market, and green certificate market interact with each other, directly or indirectly affecting the actual carbon emissions and operating costs of market participants, making full use of the interaction effects between different markets is conducive to forming a joint force to cope with the adverse effects of carbon tariffs. In the initial implementation stage of carbon tariffs, taxes are levied on the direct carbon emissions of some high-carbon emission products, including the CO2 generated by the products themselves and the CO2 generated during fossil fuel energy supply, and the indirect carbon emissions generated during the electricity consumption process are gradually included in the scope of levy.

[0004] Currently, in response to the adverse effects brought about by the implementation of carbon tariffs, scholars in multiple fields have proposed different coping strategies. For example: by constructing a price variable resource allocation model, studying the quota allocation strategy from the perspective of the carbon market to mitigate the impact of carbon tariffs; verifying the feasibility of green certificates offsetting carbon tariffs through economic modeling. However, the above studies take specific industries as examples, analyze the overall impact of carbon tariffs on the industry, calculate direct and indirect carbon emissions, and propose different carbon emission reduction and carbon tariff coping measures, but none of them deeply analyze the impact of carbon tariffs on the power industry. In addition, by constructing a multi-scenario analysis framework, the influence mechanism of factors such as carbon price level, carbon tariff pricing, and levy ratio on the decision-making of market participants is explored, and suggestions for coping with carbon tariffs are put forward from the price perspective, without studying from the aspect of reducing carbon emissions related to taxation, and the current research on the mechanism of the green certificate trading market in coping with carbon tariffs is still insufficient. At the same time, some researchers have constructed a joint trading mechanism considering the mutual recognition of carbon quotas and green certificates, and simulated and verified the complementary characteristics and synergy effects of the joint trading mechanism. However, the above green certificate trading model only studies and analyzes the trading price or trading mode, and fails to clarify the corresponding quantity of green certificates in each period during the verification process, so enterprises cannot reasonably allocate green certificate resources according to the production energy consumption characteristics. Summary of the Invention

[0005] To overcome the deficiencies of the above-mentioned existing technologies, the present invention provides a scheduling method and system for PIES to participate in the electricity-carbon-green certificate market. By designing the trading strategies of entities participating in the electricity-carbon-green certificate market and utilizing market resources to address the adverse impacts caused by carbon tariffs, the pressure of a sharp increase in the costs of export enterprises resulting from the implementation of carbon tariffs is alleviated.

[0006] To achieve the above objective, one or more embodiments of the present invention provide the following technical solutions:

[0007] The first aspect of the present invention provides a scheduling method for PIES to participate in the electricity-carbon-green certificate market;

[0008] A scheduling method for PIES to participate in the electricity-carbon-green certificate market includes:

[0009] Obtain the carbon tariff amount of the park integrated energy system, and adopt a user-side green certificate hourly allocation strategy based on carbon potential response to allocate the electricity corresponding to the green certificates hourly according to demand based on the carbon potential levels in each period;

[0010] Discretize the time scales of the continuous carbon market and green certificate market to the same scheduling time scale of the electricity market, establish a connection trading strategy for the electricity-carbon-green certificate market, determine the green certificate trading volume and the deductible carbon emission reduction volume, and realize the dynamic transmission of the key variables in the three markets;

[0011] Based on the green certificate trading volume and the deductible carbon emission reduction volume, construct a multi-agent two-layer game optimization scheduling model for PIES. The upper layer focuses on the overall optimization objective of the park integrated energy system, and the lower layer considers the individual interests of each entity, and outputs the total operating cost and carbon emissions to achieve the low-carbon economic scheduling of the park integrated energy system.

[0012] As a further technical solution, the user-side green certificate hourly allocation strategy based on carbon potential response is:

[0013]

[0014]

[0015]

[0016] In the formula: is the number of green certificates allocated in period t; is the proportionality coefficient for obtaining green certificates based on carbon potential in period t; is the carbon potential calculated based on the carbon emission flow model in period t; is the amount of carbon dioxide deducted in period t.

[0017] As a further technical solution, the process of discretizing the time scales of the continuous carbon market and green certificate market to the same scheduling time scale of the electricity market is:

[0018] Unify the time scale, discretize the trading time of the carbon market, and make the trading time scale consistent with that of the electricity market;

[0019] The integrated energy system of the park makes decisions on the electricity market and the carbon market within a single time period simultaneously, realizing the coordination of electricity-carbon trading decisions on the same time scale;

[0020] Retain the characteristic that the carbon emission over-punishment cost is calculated at the end of the dispatching cycle. The changes in carbon quotas caused by previous transactions continuously accumulate to affect the decision-making results of the current time period, maintaining the information continuity of the carbon market participants in each trading time period.

[0021] As a further technical solution, the process of establishing the connection trading strategy for the electricity-carbon-green certificate market and determining the green certificate trading volume and the carbon emission reduction volume offset is as follows:

[0022] Obtain the initial carbon quota of the PIES entity;

[0023] Determine the trading volumes and trading prices of electric energy, carbon quotas, and green certificates;

[0024] Determine the green certificate trading volume and the carbon emission reduction volume offset.

[0025] As a further technical solution, the multi-agent two-layer game optimization dispatching model of the PIES includes a PIES low-carbon economic dispatching model based on the master-slave game and a multi-PIES low-carbon economic dispatching model based on the cooperative game.

[0026] As a further technical solution, the PIES low-carbon economic dispatching model based on the master-slave game takes the minimum comprehensive cost as the objective function:

[0027]

[0028]

[0029]

[0030] In the formula: is the comprehensive cost of entity i; and are the energy purchase cost and energy sales revenue of entity i respectively; is the penalty cost paid for the part where the actual carbon emissions of entity i exceed the carbon quota; 、 and are the carbon trading cost, electricity trading cost, and electricity network passing cost between entity i and entity j respectively; and are the electricity purchase volume and gas purchase volume purchased by entity i from the power grid and the gas source in time period t respectively; and are the electricity price and gas price for the upper - layer power grid to purchase energy in period t, respectively; is the electric energy sold by entity i to the upper - layer power grid in period t; is the price of entity i selling electricity to the upper - layer power grid in period t; and are the free carbon quota and actual carbon emissions allocated to entity i, respectively; is the total carbon quota trading volume between entity i and entity j; is the penalty coefficient when the carbon emissions exceed the limit; and are the green certificate trading volume and green certificate trading price between entity i and entity j; and are the carbon quota trading volume and carbon quota trading price between entity i and entity j in period t, respectively; and are the electric energy trading volume and electric energy trading price in period t, respectively; is the per - unit electric energy passing - through network cost.

[0031] As a further technical solution, the multi - PIES low - carbon economic dispatch model based on cooperative game adopts a decomposition strategy, splitting the non - linear optimization problem into two sub - problems: one is to maximize the cooperative benefit, and the other is the energy trading allocation scheme;

[0032] For entity i, the augmented Lagrangian function of its cooperative benefit maximization sub - problem is:

[0033]

[0034] In the formula: is the total cost of entity i without transaction costs; and are the generalized expressions of entity i trading electric energy, trading thermal energy and trading carbon quota with entity j; is the Lagrange multiplier of the energy coupling constraint; is the penalty parameter of the cooperative benefit maximization sub - problem; is the 2 - norm;

[0035] For entity i, the augmented Lagrangian function of its energy trading payment sub - problem The expression is:

[0036]

[0037] In the formula: is the optimal solution obtained from sub - problem 1; and It is a generalized expression of the trading prices for the electricity, heat, and carbon quota trading between entity i and entity j. It is the Lagrange multiplier for the sub-problem of energy trading payment. It is the penalty parameter for the sub-problem of energy trading payment. Among them, the initial values of the trading prices for electricity, heat, and carbon quota are all 0.

[0038] The second aspect of the present invention provides a dispatching system for PIES participating in the electricity-carbon-green certificate market.

[0039] A dispatching system for PIES participating in the electricity-carbon-green certificate market includes:

[0040] A green certificate allocation module, configured to: obtain the carbon tariff amount of the park integrated energy system, and adopt a user-side green certificate hourly allocation strategy based on carbon potential response to allocate the electricity corresponding to the green certificate hourly according to demand based on the carbon potential level in each period.

[0041] An interface trading strategy determination module, configured to: discretize the time scales of the continuous carbon market and green certificate market to the same dispatching time scale of the electricity market, establish an interface trading strategy for the electricity-carbon-green certificate market, and determine the green certificate trading volume and the carbon emission reduction volume offset.

[0042] An integrated energy system dispatching module, configured to: based on the green certificate trading volume and the carbon emission reduction volume offset, construct a PIES multi-agent two-layer game optimization dispatching model to realize the dispatching of the park integrated energy system.

[0043] The third aspect of the present invention provides a computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, it realizes the steps in a dispatching method for PIES participating in the electricity-carbon-green certificate market as described in the first aspect of the present invention.

[0044] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored on the memory and executable on the processor. When the processor executes the program, it realizes the steps in a dispatching method for PIES participating in the electricity-carbon-green certificate market as described in the first aspect of the present invention.

[0045] The above one or more technical solutions have the following beneficial effects:

[0046] Aiming at the problem that the green certificate market can effectively relieve the pressure on export and foreign trade enterprises to cope with carbon tariff collection, the present invention proposes an interface trading strategy considering the electricity-carbon-green certificate market among PIES, and at the same time proposes a user-side green certificate hourly allocation strategy based on carbon potential response for enterprise users in PIES. It can promote the overall new energy consumption and carbon emission reduction, and effectively utilize the market to cope with international carbon tariffs.

[0047] (1) The user-side green certificate hourly allocation strategy based on carbon potential response proposed in the present invention can reasonably allocate large green certificate resources according to the carbon potential level in each time period. It can effectively reduce the carbon tariff cost in different types of PIES and different types of loads, and at the same time, it can retain the initial energy demand of the load to a certain extent, which is in line with the energy consumption willingness of enterprises.

[0048] (2) The electricity-carbon-green certificate market connection trading strategy proposed in the present invention achieves the effect of complementary resource advantages among the three markets by comprehensively analyzing various market variables within the same time section. Compared with the two-market connection trading strategy, it embodies obvious economic and low-carbon characteristics.

[0049] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0051] Figure 1 This is a flow chart of the method of the first embodiment.

[0052] Figure 2 This is a schematic diagram of the electricity-carbon-green certificate market connection trading strategy mechanism of the first embodiment.

[0053] Figure 3 It is a system structure diagram of the second embodiment. DETAILED DESCRIPTION

[0054] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0055] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0056] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0057] The present invention proposes a dispatching method and system for PIES to participate in the electricity-carbon-green certificate market. First, clarify the carbon tariff and its tax calculation principle, and propose a carbon tariff tax calculation method considering the mutual recognition of green certificates and carbon tariffs. Then, to reasonably allocate the green certificate cost purchased by the tax-paying entity and effectively adjust the energy demand in each period to cope with the carbon tariff levy pressure, a user-side green certificate hourly allocation strategy based on carbon potential response is proposed. The electricity corresponding to the green certificate is allocated hourly according to demand based on the carbon potential in each period, and small-scale loads use the obtained green certificates to offset the carbon emissions corresponding to the carbon tariff tax amount. After that, analyze the operation mechanism of the price connection in the electricity, carbon, and green certificate markets, propose a connection trading strategy for market entities to participate in the electricity-carbon-green certificate market, and establish a multi-agent two-layer game optimization dispatching model for PIES to give full play to the resource complementarity in each market and each entity to promote cost reduction and emission reduction. Finally, use the improved alternating direction multiplier method for distributed solution, and verify through typical examples that the proposed strategy can promote overall consumption and emission reduction and relieve the carbon tariff levy pressure on enterprises.

[0058] Embodiment 1

[0059] This embodiment discloses a dispatching method for PIES to participate in the electricity-carbon-green certificate market;

[0060] As Figure 1 shown, a dispatching method for PIES to participate in the electricity-carbon-green certificate market includes:

[0061] Step S1, obtain the carbon tariff tax amount of the park integrated energy system, and adopt a user-side green certificate hourly allocation strategy based on carbon potential response to allocate the electricity corresponding to the green certificate hourly according to demand based on the carbon potential in each period;

[0062] In step S1, the carbon tariff tax amount is levied on the difference after deducting the carbon cost already paid by the exporting enterprise in the producing country, that is:

[0063]

[0064] In the formula: is the carbon tariff cost of the export trading enterprise; is the total carbon emissions brought by the production of export products; and are the carbon market price and the domestic carbon price already paid in the producing country, respectively.

[0065] The foreign trade enterprise can obtain free emission allowances by purchasing green certificates, and its carbon tariff cost is correspondingly converted to:

[0066]

[0067] In the formula: is the number of green certificates obtained by the foreign trade enterprise; The carbon dioxide coefficient that each green certificate can offset is 0.8042. It can be seen from the above formula that purchasing green certificates can effectively reduce the carbon tariff costs of export trading enterprises.

[0068] Therefore, as end-users, energy-consuming enterprises can purchase green certificates to offset the carbon emissions during the production process. Due to the influence of the production energy consumption characteristics of each export enterprise, the shapes of the carbon potential curves are very different. From the perspective of their own economic interests, after each enterprise purchases green certificates, it divides the green certificate allocation ratio according to the level of carbon potential during each period. According to the principle that more green certificate electricity is allocated during the period with high carbon potential and less green certificate electricity is allocated during the period with low carbon potential, when green certificates are allocated to the period with high carbon potential, it provides more carbon cost buffers for the enterprise's production during these periods, which is conducive to the enterprise maintaining an efficient production mode. In this embodiment, a user-side green certificate hourly allocation strategy based on carbon potential response is established to guide the enterprise to adjust the energy consumption plan through demand response and adopt an energy consumption method to cope with carbon tariffs. The formula is as follows:

[0069]

[0070]

[0071]

[0072] In the formula: is the number of green certificates allocated during period t; is the proportional coefficient of green certificates that can be obtained according to the carbon potential during period t; is the carbon potential during period t; is the amount of carbon dioxide offset during period t.

[0073] Step S2: Discretize the time scales of the continuous carbon market and green certificate market to the same scheduling time scale of the power market, establish a connection trading strategy for the power-carbon-green certificate market, and determine the green certificate trading volume and the carbon emission reduction volume offset.

[0074] The power-carbon-green certificate market system consists of the power market, the carbon emission quota market, and the green power certificate trading market. Its interaction and conduction mechanism is as Figure 2 shown. In this multi-level market system, key market variables such as power prices, carbon quota trading prices, carbon quota supply and demand conditions, and green certificate trading scales constitute the core elements of the cross-market conduction mechanism. The dynamic changes of these variables will further affect the decision-making behaviors and optimization strategies of market participants. In step S2, the time scales of the continuous carbon market and green certificate market are discretized to the same scheduling time scale of the power market for research, and a connection trading strategy for the power-carbon-green certificate market is established.

[0075] Each PIES adopts the connection trading strategy of the power-carbon-green certificate market, and the specific implementation steps are as follows:

[0076] (1) Calculate the initial carbon quota of the PIES entity

[0077] Calculate the carbon quota allocated to each entity using the predicted values of various types of loads:

[0078]

[0079] In the formula: is the free carbon quota obtained by entity i; is the total carbon emission limit of the overall region; is the total equivalent electrical load of entity i; 、 and are the predicted electrical, thermal, and gas load values of entity i at time period t, respectively; and are the equivalent ratios of electrical and thermal loads to electrical and gas loads, respectively.

[0080] (2)Determine the trading volume and trading price of electric energy, carbon quota, and green certificates

[0081] Based on the cooperative game model of the Nash bargaining theory, determine the trading volume and trading price of electric energy and carbon quota among PIESs.

[0082] The price of green certificates is affected by market supply and demand. The more green certificates purchased from the green certificate market, the higher the price; conversely, the more green certificates sold to the green certificate market, the lower the price. The green certificate trading cost considering market supply and demand is:

[0083]

[0084] In the formula: is the green certificate trading cost at time period t; 、 、 、 and are the green certificate prices under different supply and demand, respectively; and are both constants.

[0085] (3)Determine the trading volume of green certificates and the carbon emission reduction amount offset

[0086]

[0087] In the formula: is the number of green certificates used to offset carbon dioxide at time period t; is the number of green certificates required for assessment at time period t.

[0088] Step S3: Based on the green certificate trading volume and the carbon emission reduction volume offset, construct a PIES multi-agent two-layer game optimization scheduling model. The inner layer focuses on the internal optimization of the park integrated energy system, and the outer layer considers the individual interests of each agent to achieve the coordinated scheduling of the regional integrated energy system.

[0089] Among them, the PIES multi-agent two-layer game optimization scheduling model includes a PIES low-carbon economy scheduling model based on the master-slave game and a multi-PIES low-carbon economy scheduling model based on the cooperative game. In the PIES low-carbon economy scheduling model based on the master-slave game,

[0090] Taking the minimum comprehensive cost as the objective function, that is:

[0091]

[0092]

[0093]

[0094] In the formula: is the comprehensive cost of agent i; and are the energy purchase cost and energy sales revenue of agent i respectively; is the penalty cost paid for the part where the actual carbon emissions of agent i exceed the carbon quota; 、 and are the carbon trading cost, electricity trading cost and electricity network passing fee between agent i and agent j respectively; and are the electricity purchase volume from the power grid and the gas purchase volume from the gas source by agent i at time t respectively; and are the electricity price and gas price for energy purchase by the upper-layer power grid at time t respectively; is the electricity sold by agent i to the upper-layer power grid at time t; is the electricity selling price of the agent to the upper-layer power grid at time t; and are the free carbon quota and the actual carbon emissions allocated to agent i respectively; is the total carbon quota trading volume between agent i and agent j; is the penalty coefficient when the carbon emissions exceed the limit; and are the green certificate trading quantity and green certificate trading price between agent i and agent j respectively; and are the carbon quota trading volume and carbon quota trading price between agent i and agent j at time t respectively; and are the electricity trading volume and electricity trading price at time t respectively; is the network cost per unit of electric energy.

[0095] The PIES source side needs to set the carbon price for selling energy according to the carbon emission responsibilities borne by users for their energy consumption, and guide users to adopt cleaner and more environmentally friendly energy consumption methods. In order to more precisely quantify the carbon emissions of each user, in the previous research work, carbon emission flow models of electric, gas, and heat energy subsystems and energy coupling devices were established respectively. Taking the power system as an example, the node carbon intensity (NCI) is:

[0096]

[0097] In the formula: is the NCI of node n at time t; is the set of power lines with node n as the end node; is the set of units g located at node n; is the line power flowing from node k to node n at time t; is the NCI of node k at time t; is the generation carbon intensity (GCI) of unit g at time t. The calculation methods of the node carbon potential of the gas and heat energy subsystems are similar to those of the power system and will not be elaborated here.

[0098] The level of the carbon potential of the node where the user is located directly reflects the cleanliness of the user's energy consumption. The carbon price that the user needs to pay is positively correlated with the carbon potential of the location, which is expressed as:

[0099]

[0100] In the formula: is the carbon price that user i needs to pay for energy consumption; is the carbon cost coefficient; is the carbon potential of the user located at node n at time t.

[0101] The user side receives the energy selling price and carbon price issued by the energy supply side, and optimizes its own energy consumption behavior according to different energy consumption restrictions. Considering the product order constraints of export trading enterprises, their demand response methods mainly include shiftable load and curtailable load, with the goal of minimizing the comprehensive cost, that is:

[0102]

[0103] In the formula: is the comprehensive cost of export trading enterprise i; is the carbon tariff cost of export trading enterprise i; , and are the unit prices of electric energy, natural gas, and heat energy at time period t, respectively; , and are the initial electric load, gas load, and heat load, respectively; , and are the changes in the electric load, gas load, and heat load of user i within time period t after price-based low-carbon DR, respectively.

[0104]

[0105] In the formula: are the actual transferred electric, gas, and heat load quantities of entity i within time period t, respectively; are the reduced electric, gas, and heat load quantities of entity i within time period t, respectively.

[0106] The total load quantity transferred in and out during the dispatching period should be equal, expressed as:

[0107]

[0108]

[0109]

[0110] In the formula: , , , and , are the transferred-in, transferred-out electric load quantity, gas load quantity, and heat load quantity of load i at time period t, respectively; , and are the proportions of the electric load, gas load, and heat load that load i can participate in transferring, respectively.

[0111] To ensure that the energy supply quality and system security are not affected after DR, the reduced load quantity needs to satisfy:

[0112]

[0113] In the formula: , and are the proportions of the electric load, gas load, and heat load that load i can participate in reducing, respectively.

[0114] In the multi-PIES low-carbon economic dispatching model based on cooperative game, the Nash bargaining theory is used to construct a cooperative game decision model with multiple parties participating. For this non-linear optimization problem, the research adopts a decomposition strategy and splits it into two sub-problems: one is to maximize the cooperative benefit, and the other is the energy trading price payment plan

[0115] For entity \(i\), the augmented Lagrangian function of its sub-problem of maximizing cooperation benefit is:

[0116]

[0117] In the formula: is the total cost of entity \(i\) excluding transaction costs; and are the generalized expressions for entity \(i\) to trade electric energy, thermal energy, and carbon quotas with entity \(j\); is the Lagrange multiplier for the energy coupling constraint; is the penalty parameter for the sub-problem of maximizing cooperation benefit; is the 2-norm;

[0118] For entity \(i\), the augmented Lagrangian function of its sub-problem of energy trading payment The expression is:

[0119]

[0120] In the formula: is the optimal solution obtained from sub-problem 1; and are the generalized expressions for the trading prices of entity \(i\) to trade electric energy, thermal energy, and carbon quotas with entity \(j\); is the Lagrange multiplier for the sub-problem of energy trading payment; is the penalty parameter for the sub-problem of energy trading payment; among them, the initial values of the trading prices of electricity, heat, and carbon quotas are all 0.

[0121] Furthermore, in this embodiment, the improved PR-ADMM algorithm is used to solve the two-layer game optimization decision model. By introducing the 1 / 2 power multiplier , the Lagrange multiplier is iterated twice, reducing the number of algorithm solution iterations to improve the solution efficiency.

[0122] The convergence criterion for the master-slave game optimization decision problem inside PIES is that the change in the carbon price of users in each time period is less than or equal to the given convergence accuracy, that is:

[0123]

[0124] In the formula: is the carbon price of user \(i\) in time period \(t\) during the th iteration process; and are the iteration number and convergence accuracy of the master-slave game optimization problem respectively.

[0125] The multi-PIES cooperative game optimization decision problem determines whether to end the iteration by whether the primal residual and dual residual of the PR-ADMM algorithm reach the convergence accuracy, that is:

[0126]

[0127] In the formula: is the number of iterations of the improved PR-ADMM; and are the generalized expressions of the electricity, heat, and carbon quota transactions between the main body i and the main body j during the th iteration; is the penalty parameter of the sub-problem of maximizing the cooperation benefit during the th iteration; is the primal residual obtained in the th iteration; is the dual residual obtained in the th iteration; and are the convergence accuracies of the primal residual and the dual residual respectively.

[0128] Experimental verification

[0129] To verify the optimization effect of the proposed electricity-carbon-green certificate market connection trading strategy on the total cost, new energy consumption, and carbon emissions, the following 4 comparison scenarios are constructed, and the comparison results are shown in Table 1.

[0130] Scenario 1: Electricity-carbon market connection trading strategy, that is, each PIES only participates in the electricity market and the carbon market;

[0131] Scenario 2: Electricity-green certificate market connection trading strategy, that is, each PIES only participates in the electricity market and the green certificate market;

[0132] Scenario 3: Carbon-green certificate market connection trading strategy, that is, each PIES only participates in the carbon market and the green certificate market;

[0133] Scenario 4: The proposed electricity-carbon-green certificate market connection trading strategy in this paper, that is, each PIES participates in the electricity market, the carbon market, and the green certificate market at the same time.

[0134] Table 1 Regional PIES decision results under four scenarios

[0135]

[0136] As can be seen from Table 1, under the electricity-carbon-green certificate market connection trading strategy proposed in the present invention, the total cost of each PIES and the whole is the smallest, the new energy consumption is the largest, and the amount of carbon dioxide participating in the accounting is the smallest.

[0137] By comparing the data in Scenario 1 and Scenario 4, it can be seen that compared with the electricity-carbon market connection trading strategy, under the electricity-carbon-green certificate market connection trading strategy, the overall regional cost is reduced by 1.5%, the new energy consumption is increased by 12.48%, and the carbon dioxide emissions are reduced by 3.02%. This is because after considering the connection of the green certificate market, each PIES can give full play to the role of green certificate resources in certifying new energy consumption and offsetting carbon emissions. While offsetting carbon emissions to reduce the carbon emission penalty cost, the number of green power certifications of PIES is increased, promoting PIES to fulfill its new energy consumption responsibility.

[0138] By comparing the data in Scenario 2 and Scenario 4, it can be seen that after considering participating in the carbon market at the same time, the total cost in Scenario 4 is 2.22% lower than that in Scenario 2, the carbon emissions are reduced by 0.73%, and the new energy consumption is increased by 2.3%. The reason for the relatively small reduction in carbon emissions is that the carbon market only trades carbon quotas and does not directly affect the actual carbon emissions generated. All three markets can directly or indirectly affect the carbon emissions of each PIES through costs. Therefore, PIES will rationally utilize the market advantages and adopt the lowest-carbon economic dispatching strategy.

[0139] Compared with Scenario 3, the overall regional cost and carbon emissions of the electricity-carbon-green certificate market connection trading strategy in Scenario 4 are reduced by 5.67% and 3.77% respectively, and the new energy consumption increases by 4.98%. Among them, the carbon emissions of PIES1 and PIES2 are significantly reduced, and the carbon emissions of PIES3 increase. This is because after considering the connection of the electricity market, PIES1 and PIES2 purchase electricity with lower prices from PIES3, and at the same time, the carbon emissions associated with this part of the electricity are included in PIES3. Therefore, the total costs and carbon emissions of PIES1 and PIES2 are both reduced. PIES3 makes a profit by selling a part of the electricity, resulting in a further reduction in its operating cost and an increase in carbon emissions, but it will not exceed the limit of its own free carbon quota.

[0140] It can be seen that compared with the trading strategies of pairwise market connections, the electricity-carbon-green certificate market connection trading strategy proposed in the present invention can timely mobilize market interaction information and achieve the Pareto optimality of low carbon and economy among PIES in the region.

[0141] Embodiment 2

[0142] This embodiment discloses a dispatching system for PIES to participate in the electricity-carbon-green certificate market;

[0143] As Figure 2 shown, a dispatching system for PIES to participate in the electricity-carbon-green certificate market includes:

[0144] The green certificate allocation module is configured to: obtain the carbon tariff amount of the park's integrated energy system, adopt a user-side green certificate hourly allocation strategy based on carbon potential response, and allocate the electricity corresponding to the green certificate hourly on demand according to the carbon potential level in each time period;

[0145] The connection trading strategy determination module is configured to: discretize the time scales of the continuous carbon market and green certificate market to the same dispatch time scale of the electricity market, establish a connection trading strategy for the electricity-carbon-green certificate market, and determine the green certificate trading volume and the carbon emission reduction to be offset;

[0146] The integrated energy system scheduling module is configured as follows: Based on the green certificate trading volume and the offset carbon emission reduction, a PIES multi-agent two-layer game optimization scheduling model is constructed to realize the scheduling of the park's integrated energy system.

[0147] Embodiment 3

[0148] The purpose of this embodiment is to provide a computer-readable storage medium.

[0149] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in a scheduling method for a PIES to participate in an electricity-carbon-green certificate market as described in Example 1.

[0150] Embodiment 4

[0151] The purpose of this embodiment is to provide an electronic device.

[0152] An electronic device comprises a memory, a processor and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in a method for scheduling a PIES to participate in an electricity-carbon-green certificate market as described in Example 1 are implemented.

[0153] The steps involved in the apparatuses of the above embodiments 2, 3 and 4 correspond to the method embodiment 1, and the specific implementation methods can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0154] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0155] Although the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications or deformations that can be made without creative efforts on the basis of the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A dispatching method for PIES to participate in the electricity-carbon-green certificate market, characterized in that Including: Obtain the carbon tariff amount of the park integrated energy system, and adopt a user-side green certificate hourly allocation strategy based on carbon potential response to allocate the electricity corresponding to the green certificate hourly according to the carbon potential level in each period; among them, the user-side green certificate hourly allocation strategy based on carbon potential response is: Wherein: is the number of green certificates allocated within time period t; is the carbon potential calculated according to the carbon emission flow model within time period t; is the amount of carbon dioxide deducted within time period t; is the carbon dioxide coefficient that each green certificate can deduct; Discretize the time scales of the continuous carbon market and green certificate market to the same scheduling time scale of the electricity market, establish a connection trading strategy for the electricity-carbon-green certificate market, determine the green certificate trading volume and the deductible carbon emission reduction amount, and realize the dynamic conduction of the key variables in the three markets; among them, the process of establishing a connection trading strategy for the electricity-carbon-green certificate market and determining the green certificate trading volume and the deductible carbon emission reduction amount is: Obtain the initial carbon quota of the PIES entity; Determine the trading volume and trading price of electric energy, carbon quota and green certificate; Determine the green certificate trading volume and the deductible carbon emission reduction amount; Based on the green certificate trading volume and the deductible carbon emission reduction amount, construct a two-layer game optimization scheduling model for multiple PIES entities. The upper layer focuses on the overall optimization goal of the park integrated energy system, and the lower layer considers the individual interests of each entity, and outputs the total operating cost and carbon emissions to realize the low-carbon economic scheduling of the park integrated energy system; among them, the two-layer game optimization scheduling model for multiple PIES entities includes a PIES low-carbon economic scheduling model based on master-slave game and a multi-PIES low-carbon economic scheduling model based on cooperative game.

2. The dispatching method for PIES to participate in the electricity-carbon-green certificate market according to claim 1, characterized in that The process of discretizing the time scales of the continuous carbon market and green certificate market to the same scheduling time scale of the electricity market is: Unify the time scale, discretize the trading time of the carbon market, and make the trading time scale consistent with the electricity market time scale; The park integrated energy system makes decisions on the electricity market and carbon market within a single period at the same time, realizing the coordination of electricity-carbon trading decisions on the same time scale; Retain the characteristic that the carbon emission excess penalty cost is calculated at the end of the scheduling period, and the carbon quota changes caused by previous transactions affect the decision-making results of the current period through continuous accumulation, maintaining the information continuity of the carbon market participants in each trading period.

3. The dispatching method for PIES to participate in the electricity-carbon-green certificate market according to claim 1, characterized in that The PIES low-carbon economic scheduling model based on master-slave game takes the minimum comprehensive cost as the objective function: Wherein: is the comprehensive cost of entity i; and are the energy purchase cost and energy sales revenue of entity i respectively; is the penalty cost paid for the part where the actual carbon emissions of entity i exceed the carbon quota; 、 and are the carbon trading cost, electricity trading cost and electricity network passing cost between entity i and entity j respectively; and are the electricity purchase quantity and gas purchase quantity purchased by entity i from the power grid and gas source at time t respectively; and are the electricity price and gas price for energy purchase by the upper-layer power grid at time t respectively; is the electric energy sold by entity i to the upper-layer power grid at time t; is the price of selling electricity by the entity to the upper-layer power grid at time t; and are the free carbon quota and actual carbon emissions allocated to entity i respectively; is the total carbon quota trading volume between entity i and entity j; is the penalty coefficient when the carbon emissions exceed the limit; and are the green certificate trading quantity and green certificate trading price between entity i and entity j respectively; and are the carbon quota trading volume and carbon quota trading price between entity i and entity j at time t respectively; and are the electricity trading volume and electricity trading price at time t respectively; is the unit electricity network passing cost.

4. The dispatching method for PIES to participate in the electricity-carbon-green certificate market according to claim 1, wherein The multi-PIES low-carbon economic scheduling model based on cooperative game adopts a decomposition strategy to split the non-linear optimization problem into two sub-problems: one is to maximize the cooperative benefit, and the other is the energy trading allocation scheme; For agent i, the augmented Lagrangian function of its subproblem of maximizing the cooperation benefit is as follows: In the formula: is the total cost of entity i without transaction costs; and are the generalized expressions for entity i to trade electric energy, thermal energy and carbon quota with entity j; is the Lagrange multiplier for the energy coupling constraint; is the penalty parameter for the sub-problem of maximizing the cooperation benefit; is the 2-norm; For the main body i, the augmented Lagrangian function of its energy trading payment sub-problem The expression is as follows: In the formula: The optimal solution obtained for sub-problem 1; and Are the generalized expressions of the trading prices for the main body i and the main body j to trade electric energy, trading heat energy, and trading carbon quotas; Is the Lagrange multiplier of the energy trading payment sub-problem; Is the penalty parameter of the energy trading payment sub-problem; among them, the initial values of the trading prices of electricity, heat, and carbon quotas are all 0.

5. A scheduling system for a PIES participating in the electricity-carbon-green certificate market, adopting a scheduling method for a PIES participating in the electricity-carbon-green certificate market according to any one of claims 1-4, characterized in that: A green certificate allocation module, configured to: obtain the carbon tariff amount of the park integrated energy system, adopt a user-side green certificate hourly allocation strategy based on carbon potential response, and allocate the electricity corresponding to the green certificate hourly according to the carbon potential level in each period; A connection trading strategy determination module, configured to: discretize the time scales of the continuous carbon market and green certificate market to the same scheduling time scale of the electricity market, establish a connection trading strategy for the electricity-carbon-green certificate market, and determine the green certificate trading volume and the deductible carbon emission reduction amount; The integrated energy system scheduling module is configured as follows: Based on the green certificate trading volume and the offset carbon emission reduction, a PIES multi-agent two-layer game optimization scheduling model is constructed to realize the scheduling of the park's integrated energy system.

6. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by a processor, the steps in the scheduling method of a PIES participating in the electricity-carbon-green certificate market as described in any one of claims 1 to 4 are implemented.

7. An electronic device, comprising a memory, a processor, and a program stored on the memory and executable on the processor, characterized in that When the processor executes the program, the steps in the scheduling method of PIES participating in the electricity-carbon-green certificate market as described in any one of claims 1 to 4 are implemented.

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