An electric-carbon collaborative trading system for building main bodies

Abstract

The present invention discloses a building main body electric-carbon collaborative trading system, which includes a building main body, a building virtual power plant, an external power market, a carbon emission compliance supervision agency, and an emission reduction volume certification agency; the building virtual power plant is a coalition composed of a number of building main bodies; the building virtual power plant is used to integrate the electricity demands reported by the building main bodies and the online electricity purchase and sale prices in the external power market, receive the grid demand response invitations, and obtain the carbon purchase and sale price information in the carbon market; the building virtual power plant is also used to issue instructions to enable electricity trading, demand response, and carbon trading among different building main bodies, seek internal trading equilibrium, and integrate the trading surplus volume; the building virtual power plant conducts information interaction with the power market and the carbon market to achieve the imbalance of the internal market in internal trading; the present invention solves the problem of trading redundancy brought about by individual buildings participating in the market, reduces the emission reduction costs of the construction industry, and solves the problem of electric-carbon linkage in building decision-making.

Description

Technical Field

[0001] The present invention relates to a trading system, and more particularly to an electric-carbon collaborative trading system for building entities. Background Art

[0002] At present, the standards and policies regarding carbon emissions in the construction field are still in their infancy, and a systematic carbon emission trading method for the construction field urgently needs to be filled. Secondly, according to the division of the whole life cycle of buildings, building carbon emissions can be divided into: 1) carbon emissions during the operation stage; 2) carbon emissions during the construction and demolition stages; 3) carbon emissions during the building material production and transportation stages. According to statistics, building operation carbon emissions account for 60%-80% of the carbon emissions in the whole life cycle of buildings, and among them, electricity carbon emissions account for about 50%. It can be seen that electricity carbon emissions play an important role in building carbon emissions, and electricity has the characteristic of being easy to measure. It is indeed feasible to study the optimal emission reduction path of buildings by taking the building electricity carbon emissions as the entry point. With the construction and development of the new power system, the installed capacity of renewable energy power generation is continuously increasing. The thermal power consumed on the user side corresponds to indirect carbon emissions, while the green power corresponds to emission reduction amounts. Therefore, if the building entity can couple the carbon emissions of electric energy during the electricity consumption decision-making process for collaborative decision-making, that is, while ensuring its own electricity consumption needs, taking into account the carbon emission compliance needs and realizing the linkage of electric-carbon decision-making, it can effectively improve its own compliance economy, reduce the emission control pressure, lower the emission reduction cost of the construction industry, and at the same time promote the green transformation of the power system. Summary of the Invention

[0003] The purpose of the present invention is to overcome the above-mentioned deficiencies of the prior art and provide an electric-carbon collaborative trading system for building entities to reduce the emission reduction cost of the construction industry and solve the problem of electric-carbon linkage in building decision-making.

[0004] To achieve the above purpose, the technical solution of the present invention is:

[0005] An electric-carbon collaborative trading system for building entities includes a building entity, a building-type virtual power plant, an external power market, a carbon emission compliance supervision agency, and an emission reduction amount certification agency; the building-type virtual power plant is a coalition composed of several building entities; the external power market includes a power market and a carbon market;

[0006] The building entity is used to integrate the power generation situation of each time period of its power generation equipment and its own load situation on the d-th day, as well as the carbon neutrality demand up to the (d - 1)-th day, and send the power demand to the building-type virtual power plant;

[0007] The described building-type virtual power plant is used to integrate the electricity demand reported by the building main body and the online electricity purchase and sale prices in the external electricity market, receive the grid demand response invitation, and obtain the carbon purchase and sale price information in the carbon market; the building-type virtual power plant is also used to issue instructions to enable electricity trading, demand response, and carbon trading among different building main bodies, seek internal trading balance, and integrate the trading surplus; the building-type virtual power plant conducts information interaction with the electricity market and the carbon market to achieve the imbalance of the internal market in internal trading.

[0008] The carbon emission compliance supervision agency is used to verify the carbon emission situation of the building main body.

[0009] The emission reduction quantity certification agency is used to certify the emission reduction quantity of the building main body.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0011] The present invention solves the problem of transaction redundancy brought by individual buildings participating in the market. Based on the principle of energy sharing, transactions are preferentially conducted within the building-type virtual power plant. The transaction imbalance is then traded with the external market, reducing the emission reduction cost of the construction industry and solving the problem of electric-carbon linkage in building decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 Schematic diagrams of different types of building characteristics;

[0013] Figure 2 Schematic diagram of the composition of the building main body electric-carbon collaborative trading system provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] Embodiment:

[0015] The technical solutions of the present invention will be further described below with reference to the drawings and embodiments.

[0016] The current domestic carbon markets that take into account buildings are mainly in Tianjin, Shanghai, and Shenzhen. Taking these as the prototype for classifying building main bodies, the building main bodies are divided into mandatory buildings, emission reduction buildings, and zero-carbon buildings. Among them, as Figure 1 shown, mandatory buildings are a type of building with a relatively large carbon emission base, located in the government control list, and hold a certain number of free quotas every year. The green electricity consumed by them is recognized as CCER to fill the quota shortage. At the same time, the surplus and deficit can be traded in the internal carbon market of the building-type virtual power plant; emission reduction buildings generally have their own small-scale power generation equipment, and the self-generated and self-used green electricity can be recognized as CCER and traded in the internal carbon market of the building-type virtual power plant; zero-carbon buildings are a special type of building. To fulfill the commitment of zero carbon emissions, the thermal power consumed by them needs to obtain an equal amount of CCER through trading in the internal carbon market of the building-type virtual power plant for filling.

[0017] Refer toFigure 2 As shown, the building entity electricity-carbon collaborative trading system provided in this embodiment mainly includes the building entity, a building-type virtual power plant, an external electricity market, a carbon emission compliance regulatory agency, and an emission reduction certification agency; the external electricity market includes an electricity market and a carbon market.

[0018] Since the volume of electricity-carbon trading by individual buildings is relatively small, the entry of individual buildings into the market will bring a large amount of trading demand to the market, and at the same time bring huge pressure to market management. In addition, transactions of individual buildings may have decision-making outliers. Frequent transactions caused by irrational trading behaviors are not only not conducive to maximizing the benefits of individual buildings, but also bring greater trading risks to the market. Therefore, the present invention proposes the concept of a building-type virtual power plant as an alliance composed of building entities.

[0019] The building is used to integrate the power generation of its own power generation equipment at each time period on day d, its own load, and the carbon neutrality demand until day d-1, and send the power demand to the building-type virtual power plant;

[0020] The building-type virtual power plant is used to integrate the power demand reported by the building entity and the online electricity price of the external power market, receive grid demand response invitations, and obtain carbon price information in the carbon market; the building-type virtual power plant is also used to issue instructions to enable different building entities to conduct power transactions, demand response and carbon transactions, seek internal transaction balance and integrate transaction surpluses; the building-type virtual power plant interacts with the power market and the carbon market to achieve internal transactions and internal market imbalances. In other words, an internal electricity-carbon market is constructed within the building-type virtual power plant based on the principle of energy sharing. The electricity-carbon transactions of the building entity are preferentially carried out within the building-type virtual power plant, giving priority to ensuring the internal balance of the alliance. The imbalance is then traded with the external electricity and carbon markets using the building-type virtual power plant as an agent, thereby reducing the emission reduction costs of the construction industry and solving the electricity-carbon linkage problem of building decision-making.

[0021] The carbon emission compliance regulatory agency is used to verify the carbon emission status of the building entity;

[0022] The emission reduction certification agency is used to certify the emission reduction of the building entity.

[0023] It can be seen that this system solves the problem of transaction redundancy caused by the participation of individual buildings in the market. It prioritizes transactions based on the principle of energy sharing within the building-type virtual system, and then trades unbalanced quantities with the external market, thereby reducing the emission reduction costs of the construction industry and solving the problem of electricity-carbon linkage in building decision-making.

[0024] In a specific embodiment, the building-type virtual power plant optimizes the internal electricity carbon market pricing with the goal of maximizing its own revenue, and the objective function is:

[0025]

[0026] In the formula, F BVPP is the revenue function of the building-type virtual power plant; R e,BVPP is the revenue of the internal power market of the building-type virtual power plant; R e,grid is the revenue from the transaction between the building-type virtual power plant and the external power grid; R c,BVPP is the revenue of the internal carbon market of the building-type virtual power plant; R c,ext is the revenue from the transaction between the building-type virtual power plant and the external carbon market; is the selling price of electricity in the internal power market of the building-type virtual power plant; is the purchase price of electricity in the internal power market of the building-type virtual power plant; is the selling price of electricity of the power grid; is the purchase price of electricity of the power grid; is the selling price of carbon in the internal carbon market of the building-type virtual power plant; is the purchase price of carbon in the internal carbon market of the building-type virtual power plant; is the selling price of carbon in the external carbon market; is the purchase price of carbon in the external carbon market; is the electricity quantity purchased by building entity i from the building-type virtual power plant; is the electricity quantity sold by building entity i to the building-type virtual power plant; is the carbon quantity purchased by building entity i from the building-type virtual power plant; is the carbon quantity sold by building entity i to the building-type virtual power plant; is the electricity quantity sold by the building-type virtual power plant to the external power grid; is the electricity quantity purchased by the building-type virtual power plant from the external power grid; is the carbon quantity sold by the building-type virtual power plant to the external carbon market; is the carbon quantity purchased by the building-type virtual power plant from the external carbon market.

[0027] The constraint conditions of this objective function are mainly price range constraints. To prevent problem degradation and avoid direct transactions between building entities and the external market, it should be ensured that the purchase price of the building-type virtual power plant is slightly higher than the external market price, and the selling price is slightly lower than the external market price. In addition, there are also the transaction capital flow constraint of the building-type virtual power plant and the coupling constraint of the surplus between external transactions and internal transactions:

[0028]

[0029] In the formula, fund e , fund c is the transaction capital flow constraint of the building-type virtual power plant with the external power and carbon markets; is the Boolean variable of electricity purchase and sale of the building-type virtual power plant with the external power grid; is the Boolean variable of carbon purchase and sale of the building-type virtual power plant with the external carbon market.

[0030] The building main bodies are grouped into I = {fb, lcb, zcb}, including three types of building main bodies: mandatory buildings, emission reduction buildings, and zero-carbon buildings. The objective functions of the building main bodies are all to maximize their own benefits, which consist of electricity consumption benefits, internal market trading revenues of building-type virtual power plants, demand response revenues, and costs. However, the carbon emission characteristics and market pursuits of various building main bodies are different. Mandatory buildings have a large carbon emission base, hold free carbon emission allowances issued by the government, and have an end-of-year compliance constraint: the carbon quotas / CCERs held at the end of the year must be equal to their own carbon emissions; Emission reduction buildings have no mandatory compliance requirements, have low carbon emissions, and are equipped with green power equipment, so they have emission reduction characteristics, and the mutually recognized CCERs can be freely sold in the carbon market; Zero-carbon buildings are restricted by their own zero-carbon goals and need to ensure that their carbon emissions during operation are 0. Since they need to purchase electricity from a building-type virtual power plant when their self-generated green power is insufficient, and the purchased electricity includes some thermal power, this part of the carbon emissions needs to be offset by purchasing CCERs in the market. Therefore, a decision-making model is built into the building main body as follows:

[0031]

[0032] In the formula, F B,i is the building objective function; f B,i is the building electricity consumption utility function, representing the satisfaction of users with the consumed electricity; R BVPP,i is the internal market trading revenue of the building in the building-type virtual power plant; R DR,i is the building demand response revenue; R cost,i is the building operation cost; α e,i is the preference coefficient of users for consuming electric energy, reflecting the demand preference of electricity users for energy and affecting the demand quantity; P i,d,t is the actual load of users; is the demand response cost; is the demand response electricity quantity; γ green is the cost per unit of green electricity; is the green power output; γ es is the cost per unit of energy storage; is the energy storage discharge electricity quantity; is the energy storage charging electricity quantity; γ dr is the cost per unit of demand response; δ green is the green power operation and maintenance cost; is the green power capacity; δ es is the energy storage operation and maintenance cost; is the energy storage capacity; σ dr is the demand response reserve cost; P i drmax is the demand response upper limit.

[0033] Due to different carbon emission characteristics, various types of buildings have different positions in achieving building carbon neutrality. In this embodiment, a decision-making model is built into the building main body to classify various types of buildings, which is conducive to the fair and reasonable promotion of low-carbon development in the building industry and stimulates the enthusiasm of various building entities for emission reduction and market transactions.

[0034] The constraint conditions of this decision-making model are as follows:

[0035] Generator set power generation constraint:

[0036]

[0037] Demand response constraint:

[0038]

[0039] Power trading constraint:

[0040]

[0041] Carbon trading constraint:

[0042]

[0043] In the formula, is the electricity storage capacity; is the discharge Boolean variable; is the charge Boolean variable; is the upper and lower limits of energy storage; is the upper and lower limits of charge and discharge; is the predicted value of green electricity; is the load; is the demand response load reduction; is the demand response load increase; Δ - i,max is the maximum load reduction; Δ + i,max is the maximum load increase; is the load reduction Boolean variable; is the load increase Boolean variable; t i,give is the load reduction period; t i,receive is the load increase period; is the electricity selling Boolean variable; is the electricity buying Boolean variable; is the power market fund flow constraint; is the carbon selling Boolean variable; is the carbon buying Boolean variable; is the carbon quota / CCER holding; is the carbon market fund flow constraint; ΔC i,d is the carbon emission compliance imbalance; Gi,d The number of mutually recognized CCERs for Building i; is the green power factor of the building-type virtual power plant's power flow; η cf is the carbon emission factor of thermal power; is the carbon quota purchased by Building Entity i from the building-type virtual power plant; is the carbon quota sold by Building Entity i to the building-type virtual power plant; P i free is the free quota quantity for mandatory buildings.

[0044] In a specific embodiment, the building-type virtual power plant is built-in with an improved shared price model algorithm that takes into account segmented coordination of supply and demand. To make the pricing of the virtual power plant more fair and reasonable and conform to the characteristics of market transactions, the concept of market supply and demand ratio is introduced. For example, the calculation of the power supply and demand ratio is as follows:

[0045]

[0046] In the formula, N e,s is the set of power selling entities, N e,b is the set of power purchasing entities.

[0047] According to the relevant theories of the power market, the market price is negatively correlated with the supply and demand ratio. The larger the supply and demand ratio, the lower the market price. Therefore, setting the electricity sharing price inside the building-type virtual power plant according to the supply and demand ratio can ensure the fairness and reasonableness of the price. The price is divided into K segments, and the method for segmenting the power purchase and sale prices of the building-type virtual power plant is as follows:

[0048]

[0049] In the formula, ξ k is the segmented Boolean variable. Then, a third variable is introduced to replace to replace Then:

[0050]

[0051] Finally, the internal market supply and demand ratio is associated with the segmentation of the power purchase and sale prices of the building-type virtual power plant:

[0052]

[0053] The segmented linear process of the power purchase and sale prices and the supply and demand ratio of the building-type virtual power plant shares the Boolean variable ξ k , which can realize the association between the power purchase and sale prices and the supply and demand ratio, and make the optimization results of the power purchase and sale prices of the building-type virtual power plant match the market supply and demand characteristics. Since in this segmentation method, the solution of the supply and demand ratio depends on the denominator value, if the denominator is 0, the market supply and demand ratio cannot be obtained. An infinitesimal ε is set such that to avoid the occurrence of a denominator of 0. At the same time, for Linearization using the Big M method:

[0054]

[0055] Furthermore, for Linearize the term:

[0056]

[0057] Carbon market is based on market supply and demand ratio The same is true for the piecewise linearization process. Through the above processing, the improved shared price model taking into account the piecewise coordination of supply and demand ratio can be converted into a convex optimization model, which can be solved by a solver. At the same time, the above model is a two-layer model and can be solved by combining analytical methods or iterative methods.

[0058] It can be seen that since the building-type virtual power plant has an improved shared price model algorithm that takes into account the segmented coordination of the supply and demand ratio, the setting of the shared price algorithm is in line with the market supply and demand ratio, that is, the pricing has market characteristics, which ensures the fairness and rationality of the shared price setting within the building-type virtual power plant. At the same time, the nonlinear problem of shared price setting is solved by combining the big M method and the binary expansion method, which ensures the solvability of the model while improving the efficiency of the model solution.

[0059] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable ordinary technicians in the field to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made based on the essence of the content of the present invention should be included in the protection scope of the present invention.

Claims

1. An electric-carbon collaborative trading system for a building main body, characterized in that It includes a building main body, a building-type virtual power plant, an external power market, a carbon emission compliance supervision agency, and an emission reduction amount certification agency; The building-type virtual power plant is a coalition composed of several building main bodies; The external power market includes a power market and a carbon market; The building main body is used to integrate the power generation situation of each time period of its own power generation equipment and its own load situation on the dth day, as well as the carbon neutrality demand up to the (d - 1)th day, and send the power demand to the building-type virtual power plant; The building-type virtual power plant is used to integrate the power demands reported by the building main bodies and the online power purchase and sale electricity prices in the external power market, receive the grid demand response invitation, and obtain the power purchase and sale carbon price information in the carbon market; The building-type virtual power plant is also used to issue instructions to enable power transactions, demand response, and carbon trading among different building main bodies, seek internal trading equilibrium, and integrate the trading surplus; the building-type virtual power plant conducts information interaction with the power market and the carbon market to achieve the imbalance of the internal market in the internal trading; The carbon emission compliance supervision agency is used to verify the carbon emission situation of the building main body; The emission reduction amount certification agency is used to certify the emission reduction amount of the building main body; The building-type virtual power plant optimizes the internal electricity-carbon market pricing with the goal of maximizing its own benefits, and the objective function is: where, F BVPP is the revenue function of the building-type virtual power plant; R e,BVPP is the revenue of the internal power market of the building-type virtual power plant; R e,grid is the revenue from the transaction between the building-type virtual power plant and the external power grid; R c,BVPP is the revenue of the internal carbon market of the building-type virtual power plant; R c,ext is the revenue from the transaction between the building-type virtual power plant and the external carbon market; is the electricity selling price in the internal power market of the building-type virtual power plant; is the electricity purchasing price in the internal power market of the building-type virtual power plant; is the electricity selling price of the power grid; is the electricity purchasing price of the power grid; is the carbon selling price in the internal carbon market of the building-type virtual power plant; is the carbon purchasing price in the internal carbon market of the building-type virtual power plant; is the carbon selling price of the external carbon market; is the carbon purchasing price of the external carbon market; is the electricity quantity purchased by building entity i from the building-type virtual power plant; is the electricity quantity sold by building entity i to the building-type virtual power plant; is the carbon quantity purchased by building entity i from the building-type virtual power plant; is the carbon quantity sold by building entity i to the building-type virtual power plant; is the electricity quantity sold by the building-type virtual power plant to the external power grid; is the electricity quantity purchased by the building-type virtual power plant from the external power grid; is the carbon quantity sold by the building-type virtual power plant to the external carbon market; is the carbon quantity purchased by the building-type virtual power plant from the external carbon market; The constraint conditions of the objective function include price range constraint, building-type virtual power plant trading capital flow constraint, and external trading and internal trading surplus coupling constraint; The building-type virtual power plant trading capital flow constraint and external trading and internal trading surplus coupling constraint are: where, fund e , fund c is the capital flow constraint for the building-type virtual power plant in the external electricity-carbon market transaction; is the Boolean variable for the building-type virtual power plant to buy and sell electricity from / to the external power grid; is the Boolean variable for the building-type virtual power plant to buy and sell carbon in the external carbon market; A decision-making model is built in the building main body as follows: where, F B,i is the building objective function; f B,i is the building electricity consumption utility function, representing the satisfaction of users' electricity consumption; R BVPP,i is the internal market trading revenue of the building in the building-type virtual power plant; R DR,i is the building's demand response revenue; R cost,i is the building operation cost; α e,i is the preference coefficient of users' electricity consumption, reflecting the demand preference of electricity users for energy and affecting the magnitude of demand; P i,d,t is the actual load of users; is the demand response cost; is the demand response electricity; γ green is the cost per unit of green electricity; is the green electricity output; γ es is the cost per unit of energy storage; is the energy storage discharge electricity; is the energy storage charge electricity; γ dr is the cost per unit of demand response; δ green is the green electricity operation and maintenance cost; is the green electricity capacity; δ es is the energy storage operation and maintenance cost; is the energy storage capacity; σ dr is the demand response reserve cost; P i drmax is the demand response upper limit; The constraint conditions of the decision-making model include unit power generation constraint, demand response constraint, power trading constraint, and carbon trading constraint; The unit power generation constraint is: The demand response constraint is: The power trading constraint is: The carbon trading constraint is: Wherein, is the electricity storage capacity of the energy storage; is the discharge Boolean variable; is the charge Boolean variable; is the upper and lower limits of the energy storage; is the upper and lower limits of charge and discharge; is the predicted value of green power; is the load; is the load reduced by demand response; is the load increased by demand response; Δ - i,max is the maximum load reduction; Δ + i,max is the maximum load increase; is the load reduction Boolean variable; is the load increase Boolean variable; t i,give is the load curtailment period; t i,receive is the load increase period; is the electricity selling Boolean variable; is the electricity purchasing Boolean variable; is the power market fund flow constraint; is the carbon selling Boolean variable; is the carbon purchasing Boolean variable; is the carbon quota / CCER holding quantity; is the carbon market fund flow constraint; ΔC i,d is the carbon emission compliance imbalance quantity; G i,d is the number of mutually recognized CCERs of building i; is the green power factor of the building-type virtual power plant power flow; η cf is the carbon emission factor for thermal power; is the carbon quota purchased by building entity i from the building-type virtual power plant; is the carbon quota sold by building entity i to the building-type virtual power plant; P i free is the free quota quantity for mandatory buildings; fb is a mandatory building; lcb is a carbon-reducing building; zcb is a zero-carbon building.

2. The building main body electric-carbon collaborative trading system according to claim 1, wherein, An improved shared price model algorithm considering segmented coordination of supply and demand ratio is built in the building-type virtual power plant, and the improved shared price model algorithm considering segmented coordination of supply and demand ratio includes: Where N e,s is the set of electricity selling entities, and N e,b is the set of electricity purchasing entities.

3. The building main body electric-carbon collaborative trading system according to claim 2, wherein, The improved shared price model algorithm considering segmented coordination of supply and demand ratio also includes: The price is divided into K segments, and the method for segmenting the power purchase and sale prices of the building-type virtual power plant is as follows: where ξ k is a piecewise Boolean variable.

4. The building main body electric-carbon collaborative trading system according to claim 3, characterized in that The improved shared price model algorithm considering segmented coordination of supply and demand ratio also includes: Introduce a third variable to the formula (9) Replace Replace Then: Associate the internal market supply and demand ratio with the segmented power purchase and sale electricity prices of the building-type virtual power plant: The common Boolean variable ξ for the segmented linear process of the purchase and sale electricity prices and the supply-demand ratio of the building-type virtual power plant k , to realize the correlation between the purchase and sale electricity prices and the supply-demand ratio, and make the optimization result of the purchase and sale electricity prices of the building-type virtual power plant match the market supply-demand characteristics; set the infinitesimal ε so that to avoid the denominator being zero; at the same time, for use the big M method for linearization: Linearize the terms in the form of :

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