Industrial park operation optimization scheduling method and system considering low-carbon response

Abstract

The invention discloses an industrial park operation optimization scheduling method and system considering low-carbon response, and the method comprises the steps: carrying out the classification modeling of industrial energy consumption, and constructing a system transferable load response model; based on carbon emission and carbon quota in industrial production, a stepped system carbon trading cost model comprehensively considering trading prices of a forced carbon market and a voluntary carbon market is constructed; establishing an industrial user system optimization scheduling model considering the transferable load and the low-carbon response; and carrying out optimization solution on the industrial user system optimization scheduling model considering the transferable load and the low-carbon response to obtain an optimal scheduling strategy in the production process of the industrial park. According to the invention, energy consumption and carbon emission can be balanced, and industrial users are promoted to develop towards the low-carbon production direction, so that the purposes of carbon reaching the peak and carbon neutralization can be assisted to be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial park operation optimization, and relates to an industrial park operation optimization scheduling method and system taking low-carbon response into account. Background Art

[0002] As the global climate change problem intensifies, reducing carbon emissions has become a focus of industrial enterprises. As the main source of energy consumption and carbon emissions, industrial users bear the important responsibility of achieving carbon reduction targets. In order to promote the optimization of energy structure and low-carbon development, low-carbon response mechanisms have gradually been introduced into the industrial production process. Low-carbon response is a means of optimizing energy use and reducing carbon emissions, which can reduce energy consumption and emissions while meeting production needs.

[0003] However, when industrial users conduct production scheduling, traditional scheduling methods often only consider economic costs or energy efficiency, ignoring carbon emission factors. Therefore, how to fully consider carbon emission factors while ensuring production efficiency and achieve coordinated optimization of energy and carbon emissions has become a research hotspot in the current industrial field. Summary of the invention

[0004] In order to solve the shortcomings existing in the prior art, the present invention provides an industrial park operation optimization scheduling method and system taking into account low-carbon response, which comprehensively considers the energy consumption and carbon emissions of each production link, encourages park users to actively make low-carbon response adjustments, and users change their own energy use behavior by participating in demand response, thereby reducing the operating cost of the system. The system production carbon emissions are taken into account in the response to form a low-carbon response mode. While achieving low-carbon goals, energy utilization efficiency is improved, thereby enhancing the overall environmental and economic benefits of industrial users, and can balance energy consumption and carbon emissions, and promote industrial users to develop in the direction of low-carbon production, thereby helping to achieve carbon peak and carbon neutrality goals.

[0005] The present invention adopts the following technical solution.

[0006] The first aspect of the present invention provides an industrial park operation optimization scheduling method taking into account low-carbon response, comprising:

[0007] Classify and model industrial energy consumption and build a system transferable load response model;

[0008] Based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model is constructed that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market;

[0009] Based on the system transferable load response model and the step-by-step system carbon trading cost model, an industrial user system optimization scheduling model taking into account transferable load and low-carbon response is established;

[0010] The optimal scheduling model of the industrial user system taking into account transferable loads and low-carbon response is optimized and solved to obtain the optimal scheduling strategy in the production process of the industrial park.

[0011] Preferably, the industrial energy consumption is divided into total power consumption and sub-process power consumption, wherein the total power consumption model is:

[0012]

[0013] Among them, P t is the total electricity consumption of the entire industrial production at time t, P t i is the electricity consumption of the ith production link at time t; I is the total number of links in industrial production;

[0014] The sub-process power consumption model is:

[0015]

[0016] in, Indicates the operating condition of each link, 0 means the condition is running, and 1 means the condition is not running; is the power consumed per unit output of the i-th production link at time t; is the output of the ith production link at time t.

[0017] Preferably, the system transferable load response model is:

[0018]

[0019] in, is the total transferable load at time t; N TL is the amount of load that can be transferred during industrial production; is the unit transferable load of transferable load j at time t.

[0020] Preferably, based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market is constructed as follows:

[0021]

[0022]

[0023] Among them, F CO2 It is expressed as carbon trading cost; λ is the transaction price of the mandatory carbon market; φ is the transaction price of the voluntary carbon market; ε is the ratio of the current mandatory carbon market transaction volume to the total carbon transaction volume, and l is the carbon emission range; is the price increase;

[0024] It is the total carbon emissions and total carbon quota in the industrial production of the system; Carbon emissions for participating in the carbon trading mechanism; To consider the carbon emission reduction of wind and solar renewable energy power generation;

[0025] T is the scheduling period; δ e represents the carbon emission coefficient of production output; ρ e represents the carbon quota coefficient of production output; ζ e Represents the carbon emission reduction coefficient of wind and solar power generation; P wp Indicates the power generation of wind and solar power generators; P t is the total electricity consumption of the entire industrial production at time t.

[0026] Preferably, the objective function of the industrial user system optimization scheduling model taking into account transferable load and low-carbon response is:

[0027]

[0028] Where F is the total cost of operating the industrial user system;

[0029] α dis , α cha , α dg , α wp They represent the energy storage charging and discharging operating costs, the power generation costs of conventional units, and the wind and solar power generation costs of the system at time t respectively; They represent the energy storage charging and discharging power, the power generation power of conventional units and the wind and solar power generation power of the system at time t respectively; Expressed as carbon trading cost; F DR is the compensation cost of the system for load transfer; T is the scheduling period.

[0030] Preferably, the calculation formula of the compensation cost of the system for load transfer is:

[0031]

[0032] in, is the unit electricity price of the system at time t; They represent the load power of the system before and after load transfer at time t respectively; is the unit load transfer price of each load in the system; is a 0-1 variable. When When , it means that the system does not transfer load; is the total transferable load at time t.

[0033] Preferably, the constraints of the industrial user system optimization scheduling model taking into account transferable load and low-carbon response include:

[0034] (1) System supply and demand balance constraints:

[0035]

[0036] in, They represent the energy storage charging and discharging power, the power generation power of conventional units and the wind and solar power generation power of the system at time t respectively; is the total transferable load at time t; P t is the total electricity consumption of the entire industrial production at time t;

[0037] (2) System operation constraints:

[0038]

[0039] Among them, P dg,min , P dg,max It is the lower and upper limits of the power generation capacity of conventional units;

[0040] P wp,min , P wp,max The lower and upper limits of wind and solar power generation;

[0041] γ down , γ up are the lower and upper limits of the power difference between the conventional generator set at time t and time t-1;

[0042] κ down , κ up The lower and upper limits of the power difference between the wind and solar generator sets at time t and time t-1;

[0043] They represent the load power of the system before and after load transfer at time t respectively;

[0044] P tl,max , P tl,max The lower and upper limits of load power for load transfer;

[0045] (3) Energy storage constraints:

[0046]

[0047] In the formula, is a 0-1 variable representing the battery discharge state; its value is 0 when the battery is charging and 1 when it is discharging; is a 0-1 variable representing the battery charging state, which is 1 when the battery is charging and 0 when it is discharging; P dis,max , Pcha,max It is the maximum charge and discharge power of the battery.

[0048] Preferably, the optimizing and solving the industrial user system optimization scheduling model taking into account the transferable load and low-carbon response to obtain the optimal scheduling strategy in the production process of the industrial park includes:

[0049] (1) Input the system time-of-use electricity price, transferable load, wind and solar units and related parameters of conventional units;

[0050] (2) Compare the peak-valley electricity price difference with the unit transfer cost of the transferable load. If the peak-valley electricity price difference is greater than the unit transfer cost of the transferable load, the transferable load participates in the demand response and enters (3). Otherwise, the transferable load does not participate in the demand response. After all the parameters related to the transferable load in the optimization scheduling model are set to 0, the optimization scheduling model is solved using the CPLEX solver based on the input of (1) to obtain the optimized energy storage charging and discharging power, the power generation power of the conventional units, and the wind and solar power generation power;

[0051] (3) The system load curve is modified according to the load transfer situation in each period of the transferable load, and then the step-by-step system carbon trading cost is calculated. The optimization scheduling model is input and solved by CPLEX solver based on the input of (1) to obtain the load power before and after the optimized load transfer, energy storage charging and discharging power, conventional unit power generation power and wind and solar power generation power.

[0052] The second aspect of the present invention provides an industrial park operation optimization scheduling system taking into account low-carbon response, comprising:

[0053] The model building module is used to classify and model industrial energy consumption and construct a system transferable load response model; based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model is constructed that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market; an industrial user system optimization scheduling model that takes into account transferable loads and low-carbon responses is established;

[0054] Run the optimization scheduling module to optimize and solve the optimization scheduling model of the industrial user system taking into account transferable loads and low-carbon response, and obtain the optimal scheduling strategy in the production process of the industrial park.

[0055] A third aspect of the present invention provides a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0056] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0057] Compared with the prior art, the beneficial effects of the present invention include at least:

[0058] The stepped system carbon trading cost model of the present invention comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market, enriching the market transaction varieties. The two influence each other in actual transactions. The mandatory carbon market price is affected by the supply and demand relationship of quotas, and the voluntary emission reduction carbon market price is affected by the cost and market supply and demand of emission reduction projects such as wind and solar power generation. The two form a complementary mechanism to more reasonably and accurately reflect the carbon trading cost, thereby highlighting the actual value brought by low-carbon response.

[0059] The present invention utilizes the transferable demand response model and the stepped system carbon trading cost model to explore the correlation between electricity and carbon emissions, make an estimate of the carbon emissions of the system production process, and based on the transferable demand response of industrial users, ultimately achieve low-carbon economic operation of the industrial park, which can solve the problem that the existing industrial park operation only considers the system economy.

[0060] The present invention solves the optimization scheduling model of the industrial user system taking into account transferable loads and low-carbon responses, and obtains the optimal operating state of the system and the power output of the equipment. During the scheduling process, the electric load is transferred to the user load according to the time-of-use price, so that the electricity, heat, gas and cooling power of each equipment can achieve supply and demand balance during the whole operation process, and reduce the system carbon emissions and improve the system economy during the response adjustment, thereby realizing the low-carbon economic development of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 is a flow chart of the method of the present invention;

[0062] Figure 2 It is a time-of-use electricity price map;

[0063] Figure 3 is the time-sharing adjustment amount of the transferable load;

[0064] Figure 4 Electric load before and after demand response adjustment for industrial park operation;

[0065] Figure 5 Balancing the supply and demand of electricity for the operation of industrial parks. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0067] like Figure 1 As shown, Embodiment 1 of the present invention provides an industrial user optimization scheduling method taking low-carbon response into account, comprising the following steps:

[0068] Step 1: Classify and model the industrial energy consumption types and build a system transferable load response model;

[0069] Further preferably, the industrial load types are classified and modeled, and a system transferable demand response model is constructed, specifically including:

[0070] Energy consumption in industrial production is classified, mainly including the total electricity consumption of the production process and the energy consumption between each process, that is, production electricity and basic electricity in industrial production. At the same time, a system transferable demand response model is established to ensure that the transferable load is adjusted in industrial production, and the transferable load remains at 0 during the entire scheduling cycle.

[0071] (1) Classification of industrial energy consumption:

[0072] 1)Total power consumption:

[0073]

[0074] Among them, P t is the electricity consumption of the entire industrial production at time t, P t i is the electricity consumption of the ith production link at time t.

[0075] 2) Sub-process power consumption:

[0076]

[0077] Among them, I represents the total number of links in industrial production; Indicates the operating condition of each link, 0 / 1 indicates the operating condition is running / not running respectively; is the power consumed per unit output of link i at time t; is the output of link i at time t.

[0078] (2) Transferable load:

[0079] The first constraint on the duration of the transferable workload ensures that once it starts operating, it must continue until the task is completed without any interruption:

[0080]

[0081] Among them, N TL is the amount of load that can be transferred during industrial production; is the unit transferable load at time t; is the total transferable load at time t.

[0082] Step 2: Based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model is constructed that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market;

[0083] Further preferably, the transaction prices of the mandatory carbon market and the voluntary carbon market are comprehensively considered to construct a carbon emission and carbon quota model in each production process of industrial users, and on this basis, a systematic carbon trading cost model is constructed, specifically including:

[0084] The model takes into account the carbon emissions in each process, either directly or indirectly. An electricity-carbon coupling model is constructed based on the energy consumption of each link, and a step-by-step carbon trading cost model is established under the condition of considering the system carbon quota to control the system carbon emissions.

[0085] The carbon emission and carbon quota model of industrial users in the production process is:

[0086]

[0087] The tiered carbon trading cost model is:

[0088]

[0089] Among them, F CO2 It is expressed as carbon trading cost; λ is the transaction price of the mandatory carbon market; φ is the transaction price of the voluntary carbon market; ε is the ratio of the current mandatory carbon market transaction volume to the total carbon transaction volume; E E,CO2 、E Q,CO2 is the total carbon emissions and total carbon quota of the system; E IES,CO2 is the carbon emissions participating in the carbon trading mechanism; T is the scheduling period; δ e represents the carbon emission coefficient of production output; ρ e represents the carbon quota coefficient of production output; λ is the carbon trading price; l is the carbon emission range; is the price increase rate.

[0090] To consider the carbon emission reduction of wind and solar renewable energy power generation; e Represents the carbon emission reduction coefficient of wind and solar power generation; P wp Indicates the power generation of wind and solar power generators.

[0091] Step 3: Based on the model constructed in Steps 1 and 2, an optimal dispatch model for the industrial user system taking into account transferable loads and low-carbon response is established;

[0092] Further preferably, based on the energy consumption model, transferable load model and carbon trading model constructed in step 1 and step 2, a low-carbon system optimization scheduling model taking into account transferable load response is constructed to minimize the system cost of the industrial park participating in demand response, which takes into account the energy storage operation cost, conventional unit power generation cost, wind and solar power generation cost, carbon trading cost and demand response compensation cost. The objective function of the system optimization scheduling model based on transferable load response and carbon trading market is:

[0093]

[0094] Where F is the total cost of industrial user system operation; F DR is the compensation cost of the system for load transfer; Expressed as carbon trading costs; is the unit electricity price of the system at time t; They represent the load power of the system before and after load transfer at time t respectively; is the unit load transfer price of each load in the system; is a 0-1 variable. When , it means that the system has transferred the load; the total amount that can be transferred within a scheduling cycle is 0; They represent the energy storage charging and discharging operating costs, the power generation costs of conventional units, and the wind and solar power generation costs of the system at time t respectively; They respectively represent the energy storage charging and discharging power, the power generation power of conventional units and the wind and solar power generation power of the system at time t.

[0095] During the operation of the system, the system meets the supply and demand balance constraints, operation constraints and energy storage constraints, which are expressed as follows:

[0096] (1) System supply and demand balance constraints:

[0097]

[0098] (2) System operation constraints:

[0099]

[0100] In the formula, γ down , γ up is the lower limit and upper limit of the power difference between the conventional generator set at time t and time t-1; κ down , κ up The lower and upper limits of the power difference between the wind and solar generator sets at time t and time t-1;

[0101] (3) Energy storage constraints:

[0102]

[0103] Where: is a 0-1 variable representing the battery discharge state; its value is 0 when the battery is charging and 1 when it is discharging; and is a 0-1 variable representing the battery charging state, which is 1 when the battery is charging and 0 when it is discharging; P dis,max , P cha,max It is the maximum charge and discharge power of the battery.

[0104] Step 4: Optimize and solve the optimal scheduling model of the industrial user system taking into account the transferable load and low-carbon response, and obtain the scheduling results of the optimal load transfer strategy and energy optimization in the production process of the industrial park.

[0105] Further preferably, in the industrial user system model considering transferable loads and carbon trading, the CPLEX solver in MATLAB is used to optimize the integrated energy system based on objectives and constraints, and the low-carbon scheduling results of the integrated energy system with the best transfer mode and energy optimization in the industrial production process are obtained, specifically including:

[0106] (1) System optimization mainly involves inputting system time-of-use electricity prices, transferable loads, and relevant parameters of wind and solar units and conventional units;

[0107] (2) Then, the peak-valley electricity price difference is compared with the unit transfer cost of the transferable load to determine whether the system transferable load participates in the demand response. If the peak-valley electricity price difference is greater than the unit transfer cost of the transferable load, the transferable load participates in the demand response and enters (3). Otherwise, the transferable load does not participate in the demand response. After all the parameters related to the transferable load in the optimization scheduling model are set to 0, based on the input of (1), the CPLEX solver in MATLAB is used to solve the industrial user system optimization scheduling model of the transferable load and carbon trading to obtain the final load curve and the low-carbon economic operation results of the industrial park system, including the optimized energy storage charging and discharging power, the power generation power of conventional units and the wind and solar power generation power. That is, when the transferable load does not participate in the demand response, when solving the optimization scheduling model, all the parameters related to the transferable load in the model formulas (9)-(13) are set to 0.

[0108] (3) Modify the system load curve (P) according to the load transfer situation of each period of the transferable load t ); then calculate the carbon trading cost of the tiered system based on carbon emissions and carbon quotas in industrial production, input it into the optimization scheduling model, and solve the optimal solution of the optimization scheduling model based on the low-carbon economic optimization scheduling objective function that introduces the tiered carbon trading mechanism and the transferable demand response mechanism as well as various constraints, including the load power before and after the optimized load transfer, the energy storage charging and discharging power, the power generation power of conventional units, and the wind and solar power generation power.

[0109] When the above scheme is implemented, firstly, industrial energy consumption is classified and modeled, and a transferable load response model of the system is constructed; then, the carbon emissions of each link are calculated from various production process flows of industrial users. Finally, a low-carbon system optimization scheduling model taking into account the transferable load response is constructed, with the goal of maximizing the market benefits of participating in demand response. Users change their energy consumption behavior by participating in demand response, reduce the operating cost of the system, and take into account the carbon emissions of system production in the response to form a low-carbon response method. It comprehensively considers the energy consumption and carbon emissions of each link of production, and encourages park users to actively make low-carbon response adjustments. While achieving the low-carbon goal, it improves energy utilization efficiency, thereby enhancing the overall environmental protection and economic benefits of industrial users. The carbon trading cost of the stepped system is associated with the carbon emissions generated by the total electricity consumption, and the transferable load participates in the demand response, which affects the energy storage charging and discharging power, the power generation power of conventional units and the wind and solar power generation power, and the total electricity consumption changes. After considering the transfer load to participate in demand response, this part of the cost is considered in the optimization scheduling model, and then the scheduling model is solved according to the constraint function. Finally, the load power after the response after the model is solved can be obtained, that is, the total transferable load at time t in the system balance constraint in the constraint function and the system operation constraint Load power before and after load transfer at time t Solve according to the optimal scheduling model.

[0110] This embodiment selects the comprehensive daily load data of a certain industrial park as the research object, takes 24 hours as a scheduling cycle, and performs optimization scheduling analysis with each scheduling interval of 1 hour. Figure 2 It is the time-of-use electricity price and initial price within the dispatch cycle of the integrated energy system.

[0111] The operation of industrial parks under different scenarios is optimized, and the relevant evaluation index costs are shown in Table 1. Scenario 1 adopts industrial users without considering the demand response mechanism and carbon trading mechanism; Scenario 2 adopts industrial users only considering the carbon trading mechanism; Scenario 3 adopts industrial users considering the demand response mechanism and carbon trading mechanism.

[0112] Table 1 System operation scheduling results under each scenario

[0113] Scenario Total Cost Energy purchase cost Carbon emissions 1 13859.98 7072.35 13575.26 2 10011.30 6734.75 12790.14 3 9619.57 6342.40 12714.77

[0114] From the operation and dispatch results of industrial parks under different scenarios shown in Table 1, it can be seen that in the comparison of the results of scenario 1 where industrial users do not consider the demand response mechanism and carbon trading mechanism and scenario 3 where only the carbon trading mechanism is considered, the total cost is reduced by 27.77%, the energy purchase cost is reduced by 4.77%, and the carbon emissions are reduced by 5.78%. In the comparison between scenario 2 and scenario 3, the introduction of the demand response mechanism in the system reduces the total cost, energy purchase cost and carbon emissions of the system, and the result is that the total cost is reduced by 3.91% and the carbon emissions are reduced by 0.6%. Therefore, it is necessary to introduce the step-by-step carbon trading mechanism and demand response mechanism in the system operation and dispatch strategy for the development of the system's low-carbon economy.

[0115] According to the total operating cost target and constraints, CPLEX is used to solve the optimal operating state of the system and the power output of the equipment. During the dispatching process, the electric load is transferred to the user load according to the time-of-use price, such as Figure 3 The load curve of the electric load after considering the demand response mechanism is shown in Figure 2. The electric load of the industrial park before and after the adjustment according to the demand response is shown in Figure 2. Figure 4 As shown, according to the influence of time-of-use electricity prices, the system reduces the electricity load during peak electricity consumption periods (9-11, 20-22 periods), transfers, reduces and replaces the electricity load, and increases the output of wind and solar power generators when electricity prices are high. After responding, the system reduces the power of purchased electricity to achieve a low-carbon economy. The thermal load responds to the load adjustment at the peak of heat consumption to reduce the heat load. During the response stage, the output power of the gas boiler is reduced to achieve the low-carbon nature of the system. The gas load increases after the load response during the entire period, but the gas consumption of the gas boiler is significantly reduced, and the gas purchase power is also continuously reduced, which reduces the carbon emissions of the system and improves the low-carbon nature of the system. During the entire operation process, the electricity, heat, gas and cooling power of each equipment have reached a balance between supply and demand, and the carbon emissions of the system are reduced and the economy of the system is improved during the response adjustment to achieve the low-carbon economic development of the system. The balance of electricity supply and demand in the operation of the industrial park is shown in the figure. Figure 5 shown.

[0116] Embodiment 2 of the present invention provides an industrial park operation optimization scheduling system taking low-carbon response into account, including:

[0117] The model building module is used to classify and model industrial energy consumption and construct a system transferable load response model; based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model is constructed that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market; an industrial user system optimization scheduling model that takes into account transferable loads and low-carbon responses is established;

[0118] Run the optimization scheduling module to optimize and solve the optimization scheduling model of the industrial user system taking into account transferable loads and low-carbon response, and obtain the optimal scheduling strategy in the production process of the industrial park.

[0119] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0120] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0121] Compared with the prior art, the beneficial effects of the present invention include at least:

[0122] The stepped system carbon trading cost model of the present invention comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market, enriching the market transaction varieties. The two influence each other in actual transactions. The mandatory carbon market price is affected by the supply and demand relationship of quotas, and the voluntary emission reduction carbon market price is affected by the cost and market supply and demand of emission reduction projects such as wind and solar power generation. The two form a complementary mechanism to more reasonably and accurately reflect the carbon trading cost, thereby highlighting the actual value brought by low-carbon response.

[0123] The present invention utilizes the transferable demand response model and the stepped system carbon trading cost model to explore the correlation between electricity and carbon emissions, make an estimate of the carbon emissions of the system production process, and based on the transferable demand response of industrial users, ultimately achieve low-carbon economic operation of the industrial park, which can solve the problem that the existing industrial park operation only considers the system economy.

[0124] The present invention solves the optimization scheduling model of the industrial user system taking into account transferable loads and low-carbon responses, and obtains the optimal operating state of the system and the power output of the equipment. During the scheduling process, the electric load is transferred to the user load according to the time-of-use price, so that the electricity, heat, gas and cooling power of each equipment can achieve supply and demand balance during the whole operation process, and reduce the system carbon emissions and improve the system economy during the response adjustment, thereby realizing the low-carbon economic development of the system.

[0125] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0126] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0127] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0128] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An industrial park operation optimization scheduling method taking into account low-carbon response, characterized in that: include: Classify and model industrial energy consumption and build a system transferable load response model; Based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model is constructed that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market; Based on the system transferable load response model and the step-by-step system carbon trading cost model, an industrial user system optimization scheduling model taking into account transferable load and low-carbon response is established; The optimal scheduling model of the industrial user system taking into account transferable loads and low-carbon response is optimized and solved to obtain the optimal scheduling strategy in the production process of the industrial park.

2. The method for optimizing the operation of an industrial park taking into account low-carbon response according to claim 1 is characterized in that: The industrial energy consumption is divided into total power consumption and sub-process power consumption, where the total power consumption model is: Among them, P t is the total electricity consumption of the entire industrial production at time t, P t i is the electricity consumption of the ith production link at time t; I is the total number of links in industrial production; The sub-process power consumption model is: in, Indicates the operating condition of each link, 0 means the condition is running, and 1 means the condition is not running; is the power consumed per unit output of the i-th production link at time t; is the output of the i-th production link at time t.

3. The method for optimizing the operation of an industrial park taking into account low-carbon response according to claim 1 is characterized in that: The system transferable load response model is: Among them, P t TL is the total transferable load at time t; N TL is the amount of load that can be transferred during industrial production; is the unit transferable load of transferable load j at time t.

4. The method for optimizing the operation of an industrial park taking into account low-carbon response according to claim 1 is characterized in that: Based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market is constructed as follows: in, It is expressed as carbon trading cost; λ is the transaction price of the mandatory carbon market; φ is the transaction price of the voluntary carbon market; ε is the ratio of the current mandatory carbon market transaction volume to the total carbon transaction volume, and l is the carbon emission range; is the price increase; It is the total carbon emissions and total carbon quota in the industrial production of the system; Carbon emissions for participating in the carbon trading mechanism; To consider the carbon emission reduction of wind and solar renewable energy power generation; T is the scheduling period; δ e represents the carbon emission coefficient of production output; ρ e represents the carbon quota coefficient of production output; ζ e P represents the carbon emission reduction coefficient of wind and solar power generation; wp Indicates the power generation of wind and solar power generators; P t is the total electricity consumption of the entire industrial production at time t.

5. The method for optimizing the operation of an industrial park taking into account low-carbon response according to claim 1 is characterized in that: The objective function of the industrial user system optimization scheduling model considering transferable load and low-carbon response is: Where F is the total cost of operating the industrial user system; α dis , α cha , α dg , α wp They represent the energy storage charging and discharging operation costs, the power generation costs of conventional units and the wind and solar power generation costs of the system at time t respectively; P t dis , P t cha , P t dg , P t wp They represent the energy storage charging and discharging power, the power generation power of conventional units and the wind and solar power generation power of the system at time t respectively; Expressed as carbon trading cost; F DR is the compensation cost of the system for load transfer; T is the scheduling period.

6. The method for optimizing the operation of an industrial park taking into account low-carbon response according to claim 5 is characterized in that: The calculation formula for the system's compensation cost for load transfer is: in, is the unit electricity price of the system at time t; P t tl , P t tl ′ respectively represent the load power before and after the load transfer of the system at time t; is the unit load transfer price of each load in the system; is a 0-1 variable. When When P t TL is the total transferable load at time t.

7. The method for optimizing the operation of an industrial park taking into account low-carbon response according to claim 1 is characterized in that: The constraints of the industrial user system optimization scheduling model considering transferable load and low-carbon response include: (1) System supply and demand balance constraints: P t dis +P t dg +P t wp =P t cha +P t +P t TL (11) Among them, P t dis , P t cha , P t dg , P t wp They represent the energy storage charging and discharging power, the power generation power of conventional units and the wind and solar power generation power of the system at time t respectively; P t TL is the total transferable load at time t; P t is the total electricity consumption of the entire industrial production at time t; (2) System operation constraints: Among them, P dg,min , P dg,max It is the lower and upper limits of the power generation capacity of conventional units; P wp,min , P wp,max The lower and upper limits of wind and solar power generation; γ down , γ up are the lower and upper limits of the power difference between the conventional generator set at time t and time t-1; κ down , κ up The lower and upper limits of the power difference between the wind and solar generator sets at time t and time t-1; P t tl , P t tl′ They represent the load power of the system before and after load transfer at time t respectively; P tl,max , P tl,max The lower and upper limits of load power for load transfer; (3) Energy storage constraints: In the formula, is a 0-1 variable representing the battery discharge state; its value is 0 when the battery is charging and 1 when it is discharging; is a 0-1 variable representing the battery charging state, which is 1 when the battery is charging and 0 when it is discharging; P dis,max , P cha ,max It is the maximum charge and discharge power of the battery.

8. The method for optimizing the operation of an industrial park taking into account low-carbon response according to claim 1 is characterized in that: The optimal scheduling model of the industrial user system taking into account the transferable load and low-carbon response is optimized and solved to obtain the optimal scheduling strategy in the production process of the industrial park, including: (1) Input the system time-of-use electricity price, transferable load, wind and solar units and related parameters of conventional units; (2) Compare the peak-valley electricity price difference with the unit transfer cost of the transferable load. If the peak-valley electricity price difference is greater than the unit transfer cost of the transferable load, the transferable load participates in the demand response and enters (3). Otherwise, the transferable load does not participate in the demand response. After all the parameters related to the transferable load in the optimization scheduling model are set to 0, the optimization scheduling model is solved using the CPLEX solver based on the input of (1) to obtain the optimized energy storage charging and discharging power, the power generation power of the conventional units, and the wind and solar power generation power; (3) The system load curve is modified according to the load transfer situation in each period of the transferable load, and then the step-by-step system carbon trading cost is calculated. The optimization scheduling model is input and solved by CPLEX solver based on the input of (1) to obtain the load power before and after the optimized load transfer, energy storage charging and discharging power, conventional unit power generation power and wind and solar power generation power.

9. An industrial park operation optimization scheduling system taking low-carbon response into account, using the method described in any one of claims 1 to 8, characterized in that: The operation optimization scheduling system comprises: The model building module is used to classify and model industrial energy consumption and construct a system transferable load response model; based on carbon emissions and carbon quotas in industrial production, a step-by-step system carbon trading cost model is constructed that comprehensively considers the transaction prices of the mandatory carbon market and the voluntary carbon market; an industrial user system optimization scheduling model that takes into account transferable loads and low-carbon responses is established; Run the optimization scheduling module to optimize and solve the optimization scheduling model of the industrial user system taking into account transferable loads and low-carbon response, and obtain the optimal scheduling strategy in the production process of the industrial park.

10. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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