Method for determining multi-energy complementary energy matching scheme applied to low-carbon park construction

Abstract

The application provides a multi-energy complementary energy matching scheme determination method applied to low zero-carbon park construction, and the total energy consumption is calculated according to first parameter data related to an energy consumption index for each alternative energy matching scheme; if a preset energy consumption requirement is met, carbon emissions are calculated according to second parameter data related to a carbon emission index; if a preset carbon emission requirement is met, a full life cycle cost is calculated according to third parameter data related to an economic index; and a target energy matching scheme is determined based on the calculation results corresponding to each alternative energy matching scheme. The method calculates the total energy consumption, carbon emissions and full life cycle cost corresponding to each alternative energy matching scheme, that is, when the target energy matching scheme is determined, the energy consumption index, economic index and carbon emission index are comprehensively considered, and through the multi-objective optimization method, the optimal energy matching scheme meeting the low zero-carbon park construction requirement can be automatically and quickly screened for the target park.

Description

Technical Field

[0001] This invention relates to the field of park planning and management technology, and in particular to a method for determining a multi-energy complementary energy support scheme for the construction of low-zero carbon parks. Background Technology

[0002] Currently, industrial parks are gradually developing from a single energy supply to a multi-source collaborative energy supply system. In addition, the construction of low-zero carbon parks has put forward requirements for energy and carbon emission indicators such as carbon emissions per unit of energy and the proportion of direct green electricity supply, which will directly affect the energy supporting schemes of the parks. However, existing technologies mostly adopt single-objective optimization (such as the lowest system cost or the lowest carbon emissions), failing to comprehensively consider multiple mutually restrictive indicators such as total energy consumption, carbon emissions, and life cycle costs. Furthermore, there is a lack of automated scheme selection and optimization methods that can simultaneously meet the relevant energy consumption and carbon emission requirements for the construction of low-zero carbon parks.

[0003] In summary, existing technologies lack a systematic technical solution that can automatically verify the energy balance of multi-energy systems and simultaneously optimize energy consumption, carbon emissions, and economic efficiency. This results in low efficiency and high subjectivity in the determination of energy support schemes for industrial parks, making it difficult to quickly obtain globally optimal configuration parameters that meet the requirements for building low- to zero-carbon industrial parks. Summary of the Invention

[0004] The purpose of this invention is to provide a method for determining a multi-energy complementary energy support scheme for the construction of low-zero carbon industrial parks, so as to select the optimal energy support scheme that can meet the requirements of low-zero carbon industrial park construction.

[0005] This invention provides a method for determining a multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks. The method is executed by a computer and includes the following steps: acquiring multiple alternative energy schemes for the target industrial park, and basic parameter data associated with multiple specified indicators for each alternative energy scheme; wherein the multiple specified indicators include: energy consumption indicators, economic indicators, and carbon emission indicators; for each alternative energy scheme, calculating the total energy consumption of the target industrial park based on the first parameter data associated with the energy consumption indicator in the basic parameter data corresponding to the alternative energy scheme; if the total energy consumption meets the preset energy consumption requirements, then... The carbon emissions of the target park are calculated based on the second parameter data related to carbon emission indicators in the basic parameter data corresponding to the supporting scheme. If the carbon emissions meet the preset carbon emission requirements, the total life cycle cost of the target park during the preset planning period is calculated based on the third parameter data related to economic indicators in the basic parameter data corresponding to the alternative energy supporting scheme. Based on the total energy consumption, carbon emissions, and total life cycle cost corresponding to each alternative energy supporting scheme, a weighted comprehensive evaluation is performed according to the preset multi-objective optimization rules. The target energy supporting scheme that matches the target park is determined based on the configuration parameters of the alternative energy supporting scheme with the best evaluation value.

[0006] Furthermore, each alternative energy supply scheme is determined based on a preset energy system; the preset energy system includes: source side, grid side, load side, and storage side; wherein, the source side includes: wind power, photovoltaic, coal-fired cogeneration, gas-fired cogeneration, biomass cogeneration, external power grid, and heat pump; the grid side includes: power grid, heating network, cooling network, and compressed air network; the load side includes: electrical load, heat load, cooling load, compressed air load, and adjustable load; the storage side includes: energy storage equipment and thermal storage equipment; the step of calculating the total energy consumption of the target park based on the first parameter data related to the energy consumption index in the basic parameter data corresponding to the alternative energy supply scheme includes: determining whether multiple energy sources satisfy their respective energy balance formulas based on the first parameter data related to the energy consumption index in the basic parameter data corresponding to the alternative energy supply scheme; wherein, multiple energy sources include: electrical energy, heat energy, cooling energy, and compressed air; if each energy source satisfies its respective energy balance formula, it is determined that each energy source satisfies energy conservation, and the total energy consumption of the target park is calculated.

[0007] Furthermore, the energy balance formula for electrical energy is:

[0008]

[0009] in, Contribute to photovoltaic power; Powering wind turbines; It provides power to coal-fired power plants, gas-fired power plants, and biomass cogeneration units; The power purchased by the target industrial park from the external power grid; The discharge power of the energy storage device; The electricity sold by the target industrial park to the external power grid; Within the target park The sum of the electricity loads of all users in the park; For the electrical load of refrigeration equipment; This refers to the electrical power required for the heat pump. The charging power for energy storage devices.

[0010] Furthermore, the energy balance formula corresponding to thermal energy is:

[0011] in, It outputs thermal power to coal-fired cogeneration, gas-fired cogeneration, and biomass combined heat and power units; The heat pump outputs heat power; Purchase heat from external sources for the target industrial park; The heat release power of the thermal storage device; Within the target park The sum of the heat loads of users in each park; To sell heat to external entities within the target industrial park; This refers to the heat storage capacity of the thermal storage equipment.

[0012] Furthermore, the energy balance formula corresponding to cold energy is:

[0013] in, To output cooling power to refrigeration equipment; Purchase cooling capacity from external sources for the target industrial park; Within the target park The sum of cooling loads of users in each park; The target area sells cooling capacity to external parties; The energy balance formula for compressed air is:

[0014] in, The equipment outputs compressed air power. Within the target park The sum of compressed air loads of users in each park.

[0015] Furthermore, the carbon emissions of the target park are calculated using the following formula:

[0016] in, The carbon emissions of the target industrial park; Carbon emissions generated from the use of fossil fuels as fuel within the target industrial park; In the process of energy processing and conversion, the input energy is processed or converted into other carbon-containing secondary energy through a certain technological process; Indirect carbon emissions from net electricity and heat intake within the target industrial park; Carbon emissions generated during the production process of industrial products.

[0017] Furthermore, the total life-cycle cost of the target park during the pre-planning period is calculated using the following formula:

[0018]

[0019] Where LCC is the total lifecycle cost of the target park over n years; The initial construction cost of the target park; Let be the operating cost of the target park in year t; a is the preset discount rate (%). The target park's subsidy income over n years; The material and fuel costs of the park in year t; The target park's operation and maintenance cost in year t; The cost of treating waste gas, wastewater, and solid waste in the target industrial park in year t; The green certificate transaction cost for the target park in year t; Let be the carbon trading cost for the target park in year t.

[0020] Furthermore, based on the total energy consumption, carbon emissions, and life-cycle cost corresponding to each alternative energy supply scheme, a weighted comprehensive evaluation is performed according to a preset multi-objective optimization rule. The steps for determining the target energy supply scheme that matches the target industrial park based on the configuration parameters of the alternative energy supply scheme with the best evaluation value include: constructing a multi-objective evaluation matrix based on the total energy consumption, carbon emissions, and life-cycle cost corresponding to each alternative energy supply scheme; performing weighted normalization on the multi-objective evaluation matrix according to pre-stored weight parameters corresponding to energy consumption indicators, carbon emission indicators, and economic indicators to obtain the comprehensive evaluation value of each alternative energy supply scheme; and determining the alternative energy supply scheme with the highest comprehensive evaluation value as the target energy supply scheme that matches the target industrial park.

[0021] This invention provides a device for determining a multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks. The device includes: an acquisition module for acquiring multiple alternative energy schemes for a target industrial park, and basic parameter data associated with multiple specified indicators for each alternative energy scheme; wherein the multiple specified indicators include: energy consumption indicators, economic indicators, and carbon emission indicators; a first calculation module for calculating the total energy consumption of the target industrial park for each alternative energy scheme based on the first parameter data associated with the energy consumption indicator in the basic parameter data corresponding to the alternative energy scheme; and a second calculation module for determining the total energy consumption of the target industrial park if the total energy consumption meets the preset energy consumption requirements, based on the alternative energy scheme. The system uses the following modules: First, it calculates the carbon emissions of the target park based on the second parameter data related to carbon emission indicators in the basic parameter data corresponding to the alternative energy supply scheme. Second, it calculates the total life cycle cost of the target park within the preset planning period, based on the third parameter data related to economic indicators in the basic parameter data corresponding to the alternative energy supply scheme, if the carbon emissions meet the preset carbon emission requirements. Third, it determines the target energy supply scheme that matches the target park based on the total energy consumption, carbon emissions, and total life cycle cost corresponding to each alternative energy supply scheme according to preset multi-objective optimization rules.

[0022] This invention provides a method for determining a multi-energy complementary energy supply scheme for the construction of low-zero carbon industrial parks. The method is executed by a computer, acquiring multiple alternative energy supply schemes for the target industrial park, and basic parameter data associated with multiple specified indicators for each alternative scheme. These specified indicators include energy consumption indicators, economic indicators, and carbon emission indicators. For each alternative energy supply scheme, the total energy consumption of the target industrial park is calculated based on the first parameter data associated with the energy consumption indicator from the basic parameter data corresponding to that scheme. If the total energy consumption meets the preset energy consumption requirements, the method proceeds according to the alternative energy supply scheme. The system calculates the carbon emissions of the target park based on the second parameter data associated with carbon emission indicators from the corresponding basic parameter data. If the carbon emissions meet the preset carbon emission requirements, the system calculates the full life cycle cost of the target park within the preset planning period based on the third parameter data associated with economic indicators from the basic parameter data corresponding to the alternative energy supply scheme. Based on the total energy consumption, carbon emissions, and full life cycle cost corresponding to each alternative energy supply scheme, a weighted comprehensive evaluation is performed according to preset multi-objective optimization rules. The target energy supply scheme that matches the target park is determined based on the configuration parameters of the alternative energy supply scheme with the best evaluation value. This method calculates the total energy consumption, carbon emissions, and full life cycle cost corresponding to each alternative energy supply scheme. That is, when determining the target energy supply scheme, energy consumption indicators, economic indicators, and carbon emission indicators are comprehensively considered. By adopting a multi-objective optimization approach, the optimal energy supply scheme that meets the requirements for building a low-zero carbon park can be automatically and quickly selected for the target park. Attached Figure Description

[0023] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 A flowchart illustrating a method for determining a multi-energy complementary energy support scheme for the construction of a low-zero carbon industrial park, provided by an embodiment of the present invention; Figure 2 A schematic diagram of the architecture of a preset energy system provided in an embodiment of the present invention; Figure 3 A flowchart illustrating another method for determining a multi-energy complementary energy support scheme for the construction of low-zero carbon industrial parks, provided by an embodiment of the present invention; Figure 4 A schematic diagram of a system analysis module provided in an embodiment of the present invention; Figure 5 A schematic diagram of a system optimization module provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a device for determining a multi-energy complementary energy support scheme for the construction of a low-zero carbon industrial park, provided by an embodiment of the present invention. Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0025] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Currently, industrial parks are gradually evolving from single-energy supply to a multi-source collaborative energy supply system. Zero-carbon energy sources such as wind power, photovoltaics, and biomass are rapidly developing, and technologies like heat pumps, district heating, and centralized compressed air supply are maturing. New business models and formats such as demand-side response, microgrids, DC distribution networks, and direct green electricity supply are emerging at an accelerated pace, providing multiple technological pathways for the construction of low-zero-carbon parks. However, this also increases the economic costs of these parks. In the multi-dimensional objective system of traditional project investment decisions, economic efficiency is the most crucial decision-making dimension and a fundamental pillar of sustainable development. However, for low-zero-carbon parks, energy consumption and carbon emissions will also become fundamental constraints on the decision-making process. Furthermore, the gradual maturation of market mechanisms such as the electricity market, carbon market, and green certificate trading means that building low-zero-carbon parks requires considering both internal and external economic factors, further increasing the complexity of creating economically viable low-zero-carbon parks.

[0027] The current energy system of the park mainly exhibits the following characteristics: In terms of energy management, the operation of electricity, heat or natural gas systems is relatively independent, or only simple multi-energy flow control methods are adopted, making it difficult to achieve optimal complementarity between various energy subsystems, and new supply and demand models such as integrated functional service stations and demand-side response are not fully incorporated. In terms of target optimization, many projects adopt single or a few target optimization methods, such as minimizing system cost or minimizing carbon emissions, failing to comprehensively consider the multi-objective requirements of energy supply and demand balance, energy consumption, economic efficiency, and carbon emissions within the industrial park. Furthermore, there is insufficient adaptability to new markets and current situations, failing to fully consider the impact of electricity market trading, carbon market trading, and green certificate trading on costs, as well as the impact of low-zero carbon industrial parks on carbon emission constraints.

[0028] In summary, existing technologies lack a systematic technical solution that meets the requirements for low-zero carbon park construction, is scale-oriented, covers multiple energy forms such as electricity, heat, cooling, and compressed air, and can be uniformly modeled and optimized under multiple objective constraints. Specifically, the construction of low-zero carbon parks imposes requirements on energy and carbon emission indicators such as carbon emissions per unit of energy and the proportion of direct green electricity supply, which directly affect the park's energy infrastructure. However, existing technologies do not take these constraints into account in the design of energy infrastructure; multiple energy systems are isolated from each other, making it difficult to reflect the synergistic effect of source, grid, load, and storage; they do not consider new supply and demand models such as integrated functional service stations and demand-side response; they do not systematically incorporate external mechanisms such as the electricity market, carbon market, and green certificate trading into the model; and they fail to reflect the weighting considerations of different stakeholders, such as investors, for multiple objectives such as economy and low carbon. Based on this, this invention provides a method for determining a multi-energy complementary energy infrastructure solution for the construction of low-zero carbon parks. This technology can be applied to scenarios where it is necessary to select the optimal energy infrastructure solution for a park.

[0029] To facilitate understanding of this embodiment, a method for determining a multi-energy complementary energy support scheme for the construction of low-zero carbon industrial parks, as disclosed in this embodiment of the invention, will first be introduced. This method is executed by a computer, such as... Figure 1 As shown, the method includes the following steps: Step S102: Obtain multiple alternative energy supply solutions for the target park, as well as basic parameter data for each alternative energy supply solution that are associated with multiple specified indicators; wherein, the multiple specified indicators include: energy consumption indicators, economic indicators and carbon emission indicators. Each of the above alternative energy supply options typically involves the coordinated supply of multiple energy sources such as electricity, heat, cooling, and compressed air. The basic parameter data mentioned above may include the installed capacity, utilization hours, and energy conversion efficiency of various energy facilities. In practice, when it is necessary to select the optimal energy supply option for a low-zero carbon park, multiple alternative energy supply options can be obtained in advance to select the optimal one from among them.

[0030] Step S104: For each alternative energy supply plan, calculate the total energy consumption of the target park based on the first parameter data related to the energy consumption index in the basic parameter data corresponding to the alternative energy supply plan. The aforementioned first parameter data may include: the installed capacity, utilization hours, energy conversion efficiency, fuel consumption, power generation, steam output, compressed air output of various energy facilities, and the electricity, heat, cooling, and compressed air load demands and adjustable load capacity of users in the park. In actual implementation, for each alternative energy support scheme, the first parameter data related to energy consumption indicators can be selected from the basic parameter data corresponding to the alternative energy support scheme, so as to calculate the total energy consumption of the target park based on the first parameter data.

[0031] Step S106: If the total energy consumption meets the preset energy consumption requirements, calculate the carbon emissions of the target park based on the second parameter data related to the carbon emission index in the basic parameter data corresponding to the alternative energy support scheme. The aforementioned preset energy consumption requirements may include: a pre-set threshold for total energy consumption of the park and a threshold for energy consumption per unit of GDP (Gross Domestic Product); the aforementioned second parameter data may include: emission factors for each type of fossil energy, emission factors for each type of electricity, emission factors for each type of heat, and relevant assessment indicators such as low-zero carbon parks; in actual implementation, after calculating the total energy consumption of the target park, it can be verified whether the total energy consumption meets the preset energy consumption requirements. If it does, the second parameter data related to carbon emission indicators can be selected from the basic parameter data corresponding to the alternative energy support scheme, and the carbon emissions of the target park can be calculated based on the second parameter data.

[0032] Step S108: If the carbon emissions meet the preset carbon emission requirements, calculate the full life cycle cost of the target park during the preset planning period based on the third parameter data related to the economic indicators in the basic parameter data corresponding to the alternative energy support scheme. The aforementioned preset carbon emission requirements typically include standard constraints related to the construction of low-zero carbon industrial parks, such as carbon emission requirements per unit of energy consumption and the proportion of direct green electricity supply. The aforementioned third parameter data may include: the cost per kilowatt-hour of each power source (considering construction and operation costs), fuel (coal, natural gas, biomass) costs, costs of supporting facilities such as substations (considering construction and operation costs), electricity market trading, carbon market trading, green certificate trading, and revenue from the supply of heat, cooling, and compressed air to the park. The aforementioned preset planning period can be a set future timeframe, such as 3 years or 5 years. The aforementioned total life cycle cost can be understood as all costs related to construction and operation incurred during the entire preset planning period. In actual implementation, after calculating the carbon emissions of the target park, it can be verified whether the carbon emissions meet the preset carbon emission requirements. If they do, the third parameter data related to economic indicators can be selected from the basic parameter data corresponding to the alternative energy supporting scheme. Based on this third parameter data, the total life cycle cost of the target park during the preset planning period can be calculated.

[0033] Step S110: Based on the total energy consumption, carbon emissions and life cycle cost corresponding to each alternative energy supply scheme, a weighted comprehensive evaluation is performed according to the preset multi-objective optimization rules, and the target energy supply scheme that matches the target park is determined based on the configuration parameters of the alternative energy supply scheme with the best evaluation value.

[0034] After calculating the total energy consumption, carbon emissions, and life-cycle cost for each alternative energy solution according to the above steps, this step further uses energy consumption indicators, carbon emission indicators, and economic indicators as evaluation dimensions, and the calculated values ​​of these three indicators for each solution as the evaluation basis for each dimension, thus constructing a unified evaluation foundation. Based on this, corresponding weight parameters are assigned to each evaluation dimension. These weight parameters can be pre-set according to the actual application scenario, or determined comprehensively by combining the decision-maker's subjective preferences with the objective differences in the indicator data of each solution. Then, the evaluation basis of each solution in each dimension is weighted and comprehensively processed using the determined weight parameters to calculate a comprehensive evaluation value that quantitatively reflects the overall superiority or inferiority of each solution. Finally, the alternative energy solutions are ranked in descending order of comprehensive evaluation value, and the solution with the highest comprehensive evaluation value is determined as the target energy solution. The configuration parameters of this solution are the optimal configuration result recommended for the target industrial park. In actual operation, corresponding equipment operation control parameters can also be generated based on the configuration parameters of the target energy solution to control the operating status of the source-side power generation equipment, energy storage equipment, and grid-side transmission equipment within the target industrial park.

[0035] The aforementioned method for determining multi-energy complementary energy support schemes for the construction of low-zero carbon industrial parks is executed by a computer. The method acquires multiple alternative energy support schemes for the target industrial park, as well as basic parameter data associated with multiple specified indicators for each alternative scheme. These specified indicators include energy consumption indicators, economic indicators, and carbon emission indicators. For each alternative energy support scheme, the total energy consumption of the target industrial park is calculated based on the first parameter data associated with the energy consumption indicator from the basic parameter data corresponding to that scheme. If the total energy consumption meets the preset energy consumption requirements, the energy consumption is further determined based on the corresponding energy consumption indicator of the alternative energy support scheme. The method calculates the carbon emissions of the target park based on the second parameter data associated with carbon emission indicators from the basic parameter data. If the carbon emissions meet the preset carbon emission requirements, the method calculates the full life cycle cost of the target park within the preset planning period based on the third parameter data associated with economic indicators from the basic parameter data corresponding to the alternative energy supporting scheme. Based on the total energy consumption, carbon emissions, and full life cycle cost corresponding to each alternative energy supporting scheme, a weighted comprehensive evaluation is performed according to preset multi-objective optimization rules. The target energy supporting scheme that matches the target park is determined based on the configuration parameters of the alternative energy supporting scheme with the best evaluation value. This method calculates the total energy consumption, carbon emissions, and full life cycle cost corresponding to each alternative energy supporting scheme. That is, when determining the target energy supporting scheme, energy consumption indicators, economic indicators, and carbon emission indicators are comprehensively considered. By adopting a multi-objective optimization approach, the optimal energy supporting scheme that meets the requirements for building a low-zero carbon park can be automatically and quickly selected for the target park.

[0036] This invention also provides another method for determining a multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks. This method is based on the method described in the above embodiments and includes the following steps: Step 1: Obtain multiple alternative energy supply solutions for the target park, as well as basic parameter data for each alternative energy supply solution that are associated with multiple specified indicators; among which, the multiple specified indicators include: energy consumption indicators, economic indicators, and carbon emission indicators. Each alternative energy solution is determined based on a pre-designed energy system. This pre-designated energy system can be understood as a model constructed with the target industrial park as the boundary and an integrated energy source-grid-load-storage system as the basic framework, covering electricity, heat, cold energy, compressed air, material flow, and capital flow; such as Figure 2The diagram illustrates a pre-designed energy system architecture, including an integrated energy system structure and its interactive relationships that combines energy generation, grid, load, and storage, with multi-energy complementarity and supply-demand interaction. Specifically, the pre-designed energy system includes: source side, grid side, load side, and storage side; where the source side includes: wind power, photovoltaic power, coal-fired power generation, gas-fired power generation, biomass power generation, external power grid, and heat pumps; the grid side includes: power grid, heating network, cooling network, and compressed air network; and the load side includes: electrical load, heat load, and cooling load (corresponding to...). Figure 2 The storage side includes lithium bromide refrigeration, compressed air load, and adjustable load; the storage side includes: energy storage equipment and thermal storage equipment.

[0037] Step 2: For each alternative energy source, based on the first parameter data related to the energy consumption index in the basic parameter data corresponding to the alternative energy source, determine whether the various energy sources meet their respective energy balance formulas; where the various energy sources include: electricity, heat, cold energy and compressed air; In practical applications, the park's integrated energy and power system consists of photovoltaic generators, wind turbines, combined heat and power (CHP) units, and energy storage devices. These components collectively handle the park's electricity load demand; any shortfall is supplied by the external power grid, and any excess is sold to the external grid. The corresponding energy balance formula for electricity is:

[0038]

[0039] in, Contribute to photovoltaic power; Powering wind turbines; It provides power to coal-fired power plants, gas-fired power plants, and biomass cogeneration units; The power purchased by the target industrial park from the external power grid; The discharge power of the energy storage device; The electricity sold by the target industrial park to the external power grid; Within the target park The sum of the electricity loads of all users in the park; For the electrical load of refrigeration equipment; This refers to the electrical power required for the heat pump. The charging power of the energy storage device; the units of the parameters in the above formula can be kilowatts, etc.

[0040] The park's integrated energy and heating system consists of combined heat and power (CHP) units, heat pumps, and thermal storage equipment. Together, they meet the park's heat load demand; any shortfall is supplied from the external grid, and any excess is sold to the grid. The energy balance formula for heat energy is:

[0041] in, It outputs thermal power to coal-fired cogeneration, gas-fired cogeneration, and biomass combined heat and power units; The heat pump outputs heat power; Purchase heat from external sources for the target industrial park; The heat release power of the thermal storage device; Within the target park The sum of the heat loads of users in each park; To sell heat to external entities within the target industrial park; The thermal storage capacity of the thermal storage equipment; the units of the parameters in the above formulas can be kilowatts, etc.

[0042] The park's integrated energy cooling system uses refrigeration equipment to meet the park's cooling load requirements. Any shortfall is supplied from the external grid, and any excess is sold to the external grid. The corresponding energy balance formula for cooling energy is:

[0043] in, To output cooling power to refrigeration equipment; Purchase cooling capacity from external sources for the target industrial park; Within the target park The sum of cooling loads of users in each park; The target park's external cooling capacity; the units of the parameters in the above formula can be kilowatts, etc.

[0044] The park's integrated energy compressed air system is responsible for meeting the park's compressed air needs through its production equipment. The energy balance formula for compressed air is:

[0045] in, The equipment outputs compressed air power. Within the target park The sum of compressed air loads of users in each park.

[0046] Step 3: If each energy source satisfies its corresponding energy balance formula, determine that each energy source satisfies energy conservation, and calculate the total energy consumption of the target park. In practice, the following formula can be used to calculate total energy consumption:

[0047] in, The total energy consumption of the target industrial park (tons of standard coal). This represents the sum of energy consumption (tons of standard coal) of i users within the target park, including electricity, heat, cooling, compressed air, and fossil fuel (coal, oil, and natural gas) consumption.

[0048] Step 4: If the total energy consumption meets the preset energy consumption requirements, calculate the carbon emissions of the target park based on the second parameter data related to the carbon emission index in the basic parameter data corresponding to the alternative energy support scheme. The carbon emissions of the industrial park are the sum of carbon emissions from the use of fossil fuels as fuel, carbon emissions from energy processing and conversion, indirect carbon emissions from net electricity and heat inputs into the park, and carbon emissions from industrial production processes. The carbon emissions of the target industrial park can be calculated using the following formula:

[0049] in, Carbon emissions (tons of CO2) for the target industrial park; Carbon emissions (tons of CO2) generated by using fossil energy (such as coal, oil, natural gas, etc.) as fuel within the target industrial park. In energy processing and conversion, input energy undergoes specific technological processes to be processed or converted into other carbon-containing secondary energy sources. For example, in oil refining and coal-to-oil / gas production processes, input energy is processed or converted into other carbon-containing secondary energy sources, such as blast furnace gas, converter gas, other gases, gasoline, kerosene, diesel, and fuel oil. These processes calculate carbon loss emissions (tons of CO2) based on the carbon balance principle. The indirect carbon emissions contained in the net electricity and heat intake within the target park, including electricity received and transmitted from the park, such as electricity from the public grid, electricity from directly supplied non-fossil energy sources, and renewable energy obtained through green certificate and green electricity trading (tons of CO2). Carbon emissions (tons of CO2) generated during the production process of industrial products (such as cement clinker, lime, etc.).

[0050] Carbon emissions per unit of energy consumption refer to the amount of carbon dioxide emitted by industrial enterprises within the park for each unit of energy consumed, i.e.:

[0051] in, Carbon emissions per unit of energy in the target industrial park (tons of CO2 / tons of standard coal). Carbon emissions (tons of CO2) for the target industrial park; This represents the total energy consumption of the park (tons of standard coal).

[0052] Step 5: If the carbon emissions meet the preset carbon emission requirements, calculate the full life cycle cost of the target park during the preset planning period based on the third parameter data related to economic indicators in the basic parameter data corresponding to the alternative energy support scheme. Calculate the total life-cycle cost of the target park during the pre-planning period using the following formula:

[0053]

[0054] Where LCC is the total lifecycle cost of the target park over n years; The initial construction cost of the target park; Let be the operating cost of the target park in year t; a is the preset discount rate (%). The target park's subsidy income over n years; The material and fuel costs of the park in year t; The target park's operation and maintenance cost in year t; The cost of treating waste gas, wastewater, and solid waste in the target industrial park in year t; The green certificate transaction cost for the target park in year t; Let be the carbon trading cost for the target park in year t.

[0055]

[0056] in, The green certificate trading price in year t (RMB / certificate); The number of green certificates (units) purchased for the target park in year t. This represents the number of green certificates sold by the new energy power generation companies in the target industrial park in year t. One green certificate corresponds to 1 MWh of renewable energy.

[0057]

[0058] in, The transaction price of the national carbon emission trading market in year t (yuan / ton CO2); The trading price of Chinese Certified Emission Reductions (CCER) (RMB / ton CO2). For year t, the annual emission allowance (tons of CO2) allocated to the enterprise. Let be the quantity (tons of CO2) of CCERs purchased by the target industrial park in year t. A negative number indicates that the company is making a profit through the national carbon emissions trading market.

[0059] Step 6: Construct a multi-objective evaluation matrix based on the total energy consumption, carbon emissions, and life-cycle cost of each alternative energy solution. Step 7: Based on the pre-stored weight parameters corresponding to energy consumption indicators, carbon emission indicators, and economic indicators, perform weighted normalization on the multi-objective evaluation matrix to obtain the comprehensive evaluation value of each alternative energy matching scheme. Step 8: Select the alternative energy supply plan with the highest comprehensive evaluation value as the target energy supply plan that matches the target industrial park.

[0060] In practical implementation, for each alternative energy supply scheme, a pairwise comparison matrix can be established based on the proportional scaling table corresponding to the analytic hierarchy process, and the first weight value corresponding to each specified indicator can be calculated based on the pairwise comparison matrix. The Analytic Hierarchy Process (AHP) determines relative weights by comparing each specified indicator pairwise. The specific calculation process is as follows: (1) Based on the AHP scaling table shown in Table 1, establish a pairwise comparison matrix. The specific values ​​of each element in the pairwise comparison matrix can be determined by the stakeholders, as follows:

[0061] Where A is a pairwise comparison matrix, The comparison result of the i-th specified indicator with the j-th specified indicator is given, where n is the number of specified indicators. In this scheme, the specified indicators include: energy consumption indicators, economic indicators and carbon emission indicators, i.e., n is 3.

[0062] Table 1. AHP Scale Table

[0063] (2) Calculate the weight values ​​of each specified indicator based on the pairwise comparison matrix A. The calculation formula is as follows:

[0064]

[0065] in, For the first i The first weight value of a specified indicator; n is the number of specified indicators; The comparison result of the i-th specified indicator with the j-th specified indicator; is the comparison result of the k-th specified indicator with the j-th specified indicator; W is the weight matrix composed of the first weight values ​​of each specified indicator calculated based on AHP.

[0066] (3) Perform a consistency check on the pairwise comparison matrix A. The calculation method is as follows:

[0067] in, As a consistency indicator; is the largest eigenvalue of the pairwise comparison matrix A; n is the number of specified indicators; RI is the average random consistency index, and specific values ​​are shown in Table 2. When the value is less than 0.1, the first weight value obtained by AHP calculation can be considered reasonable and reliable.

[0068] Table 2. Values ​​of the average random consistency index RI

[0069] Based on the total energy consumption, carbon emissions, and life-cycle cost corresponding to the alternative energy support scheme, a multi-objective evaluation matrix is ​​constructed; based on the multi-objective evaluation matrix, the information entropy of each specified indicator is calculated, and the second weight value corresponding to each specified indicator is calculated based on the information entropy; In practical implementation, the multi-objective evaluation matrix can be normalized according to the first normalization method to obtain the normalized first multi-objective evaluation matrix; based on the normalized first multi-objective evaluation matrix, the information entropy of each specified indicator can be calculated. The entropy weight method calculates weights based on the degree of differentiation among alternative energy supply options for each specified indicator. This is achieved by leveraging the information-expressing characteristic of entropy; that is, the greater the difference in evaluation results for a specified indicator among the alternative energy supply options, the more information it contains, and the lower its entropy, the greater its weight. The specific calculation process is as follows: (1) Based on the calculation results of each specified indicator of each alternative energy supply scheme, establish a multi-objective evaluation matrix:

[0070] in, The calculation result for the j-th specified indicator of the i-th alternative energy supply scheme, that is, each indicator value in the multi-objective evaluation matrix is ​​the calculation result of the three specified indicators of each alternative energy supply scheme calculated above (i.e., total energy consumption TE, carbon emissions). (Life Cycle Cost, LCC); In the multi-objective evaluation matrix, m represents the total number of alternative energy solutions, and n represents the total number of specified indicators.

[0071] (2) Normalize the multi-objective evaluation matrix according to the following normalization method to obtain the normalized first multi-objective evaluation matrix:

[0072]

[0073] in, for The index value after normalization; The minimum value in the specified index j; The maximum value in the specified index j; This represents the normalized result of alternative energy supply scheme i under specified index j; m represents the total number of alternative energy supply schemes.

[0074] (3) Calculate the information entropy of each specified indicator based on the normalized first multi-objective evaluation matrix:

[0075] in, The information entropy of the specified index j; m represents the total number of alternative energy supply options; The normalized result of alternative energy supply scheme i under specified index j.

[0076] (4) Calculate the second weight value of each specified indicator based on the entropy weighting method according to the information entropy:

[0077] in, The second weight value of the specified index j based on the entropy weight method; The information entropy of a specified index j.

[0078] Based on the first and second weight values ​​mentioned above, the target weight value corresponding to each specified indicator is obtained. Based on the target weight value, the target energy support scheme that matches the target park is determined from multiple alternative energy support schemes.

[0079] By combining AHP and entropy weighting methods to calculate the target weight values ​​for each specified indicator, the target weight values ​​reflect both the importance of the specified indicator to stakeholders and reduce the influence of human interference and subjective factors. The target weight value for each specified indicator is obtained by weighting the first and second weight values ​​according to preset weight coefficients. The specific calculation process is as follows:

[0080] in, The target weight value calculated by combining AHP and entropy weighting for a specified index j. The first weight value calculated based on the AHP method for the specified index j; The second weight value calculated based on the entropy weight method for the specified index j. These are the weight variable parameters (corresponding to the preset weight parameters mentioned above). When The larger the value, the greater the influence of the first weight value based on the AHP method in the target weight value, and the stronger the subjectivity; when The smaller the value, the greater the influence of the second weight value based on the entropy weight method in the target weight value, and the stronger the objectivity; when When the value is 0, the target weight value is the second weight value based on the entropy weight method; when... When the value is 1, the final weight result is the first weight value based on AHP.

[0081] The steps described above, which determine the target energy supply scheme that matches the target industrial park from multiple alternative energy supply schemes based on target weight values, can be implemented through the following steps: Normalize the multi-objective evaluation matrix according to a preset normalization method to obtain a normalized second multi-objective evaluation matrix; process the normalized second multi-objective evaluation matrix according to target weight values ​​to obtain a third multi-objective evaluation matrix; determine the positive and negative ideal solutions for each specified indicator based on the third multi-objective evaluation matrix; calculate the relative fit of each alternative energy supply scheme (corresponding to the comprehensive evaluation value mentioned above) based on the positive and negative ideal solutions for each specified indicator; and determine the alternative energy supply scheme with the highest relative fit as the target energy supply scheme that matches the target industrial park.

[0082] The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) ranks alternative energy solutions based on their relative closeness to the idealized target (positive and negative ideal solutions), precisely quantifying the differences between all alternative energy solutions. A positive ideal solution is the one that achieves the best results for all specified indicators, while a negative ideal solution is the one that achieves the worst results for all specified indicators. The specific calculation process is as follows: (1) Based on the calculation results of each specified indicator of each alternative energy supply scheme, establish a multi-objective evaluation matrix:

[0083] in, The calculation result for the j-th specified indicator of the i-th alternative energy supply scheme, that is, each indicator value in the multi-objective evaluation matrix is ​​the calculation result of the three specified indicators of each alternative energy supply scheme calculated above (i.e., total energy consumption TE, carbon emissions). (Life Cycle Cost, LCC); In the multi-objective evaluation matrix, m represents the total number of alternative energy solutions, and n represents the total number of specified indicators.

[0084] (2) Normalize the multi-objective evaluation matrix according to the following normalization method to obtain the normalized second multi-objective evaluation matrix:

[0085] in, The normalized result of alternative energy supply scheme i under specified index j; The calculation result of alternative energy supply scheme i under specified index j; m represents the total number of alternative energy supply schemes.

[0086] (3) Based on the normalized second multi-objective evaluation matrix and the objective weight values, calculate the weighted third multi-objective evaluation matrix:

[0087] in, The result of calculating the alternative energy support scheme i based on the corresponding target weight value of the specified indicator j; The normalized result of alternative energy supply scheme i under specified index j; The target weight value for the specified indicator j.

[0088] (4) Based on the third multi-objective matrix, determine the positive and negative ideal solutions for each specified index:

[0089]

[0090] in, and These are the positive and negative ideal solutions for each specified index, respectively. For the first specified index, the positive ideal solution, For the second specified index, the positive ideal solution is... and so on. This is the positive ideal solution for the nth specified index; The negative ideal solution for the first specified index. For the second specified index, the negative ideal solution is given, and so on. The negative ideal solution for the nth specified index; The result of calculating the alternative energy supply scheme i based on the specified indicator j according to the corresponding target weight value; due to total energy consumption TE, carbon emissions Both Life Cycle Cost (LCC) and Total Life Cycle Cost (LCC) are cost-based indicators. Therefore, the minimum value represents a positive ideal solution, and the maximum value represents a negative ideal solution.

[0091] (5) Calculate the distance of each alternative energy supply scheme from the positive and negative ideal solutions to obtain the relative proximity; rank the alternative energy supply schemes according to their relative proximity to determine their priority order. The relative proximity is calculated as follows:

[0092] in, The relative proximity of alternative energy supply solutions i; n represents the total number of specified indicators; The result of calculating the alternative energy support scheme i based on the corresponding target weight value of the specified indicator j; For the negative ideal solution of the specified index j; This is the positive ideal solution for the specified index j.

[0093] After calculating the relative proximity of each alternative energy supply scheme i, the alternative energy supply scheme with the highest relative proximity can be determined as the target energy supply scheme that matches the target park.

[0094] The aforementioned process involves a multi-objective optimization process, including energy supply and demand balance, energy consumption evaluation, economic evaluation, and carbon emission evaluation. Among these, energy supply and demand balance is a mandatory constraint, and lower values ​​for energy consumption, economic efficiency, and carbon emission indicators have a better impact. The weights of each specified indicator are calculated using the analytic hierarchy process (AHP) and entropy weight method. Based on the results of energy consumption, economic efficiency, and carbon emission indicators, a multi-criteria decision-making method is employed to compare various alternative energy supply schemes.

[0095] Compared to existing technologies that suffer from fragmented energy systems, singular optimization objectives, and insufficient adaptation to new circumstances, this solution constructs an integrated energy system based on the construction of low-zero carbon industrial parks. This system integrates energy sources, grids, loads, and storage; multi-energy complementarity; and supply-demand interaction. While meeting the relevant standards and constraints for low-zero carbon industrial park construction, it incorporates multiple objectives, including energy consumption, economic efficiency, and carbon emissions, into the optimization model. At the energy level, it coordinates the supply of electricity, heat, cooling, and compressed air, and introduces new models such as integrated energy services and demand-side response under the new energy system. At the economic level, it systematically considers the impact of mechanisms such as electricity market trading, carbon market trading, and green certificate trading on costs and benefits. At the carbon emission level, it closely adheres to the latest requirements for low-zero carbon industrial parks and optimizes the park's energy system. This solution can respond to the differentiated needs of investors and other stakeholders in terms of energy consumption, economic efficiency, and low carbon emissions under different scenarios, providing quantifiable and comparable technical support for industrial park energy planning and investment decisions.

[0096] It should be noted that the aforementioned Analytic Hierarchy Process (AHP), Entropy Weight Method (WHMP), and TOPSIS are all computer-executable mathematical algorithms commonly used by those skilled in the art when solving multi-objective optimization problems. Essentially, they are technical processing methods for objective data. In this embodiment, these algorithms are executed automatically by a computer to select the optimal configuration parameters from multiple alternative solutions that satisfy physical constraints, rather than for human decision-making or business management activities.

[0097] For ease of understanding, see Figure 3 The flowchart shown represents another method for determining a multi-energy complementary energy support scheme applied to the construction of low-zero carbon industrial parks, and includes the following steps: Step 1: Assess the park's needs for electricity, heat, cooling, compressed air, etc.

[0098] Step 2: Establish an energy support plan for the park, construct the source, grid, load and storage architecture within the park. The plan should fully cover energy supply, network, load and energy storage units, and construct a comprehensive energy system structure that covers multiple energy forms such as electricity, heat, cooling and compressed air, and takes into account the energy flow, material flow and capital flow, and clarify the interaction and correlation mechanism between various elements.

[0099] Step 3: Collect basic parameter data such as energy, economy and carbon emissions corresponding to the energy supporting plan, and store them in the system database.

[0100] Step 4: Perform energy supply and demand balance calculations. Considering the fluctuation characteristics of wind and solar power output, perform supply and demand balance calculations for various energy sources in the park under different operating scenarios to ensure the overall system meets energy conservation constraints. Calculate the corresponding energy consumption and verify whether the energy consumption performance of this scheme meets the park's total energy consumption and unit GDP energy consumption requirements. If it meets the requirements, proceed to Step 5; otherwise, return to Step 2.

[0101] Step 5: Perform carbon emission calculation. Based on the principles of energy conservation and matter conservation, calculate the carbon emissions. Verify whether the carbon emission indicators of this plan meet the relevant standards and constraints for the construction of low-zero carbon industrial parks (such as whether they meet the requirements for carbon emissions per unit of energy consumption and the proportion of direct green electricity supply in low-zero carbon industrial parks). If they meet the requirements, proceed to Step 6; otherwise, return to Step 2.

[0102] Step 6: Perform economic calculations. Based on the principles of energy conservation and matter conservation, calculate the system operating costs and energy supply revenue, and consider the impact of mechanisms such as electricity market trading, carbon quota trading, and green certificate trading on costs and revenues.

[0103] Step 7: Execute the multi-objective optimization model. Calculate the weights of each specified indicator using the analytic hierarchy process (AHP) and entropy weight method, and rank the various evaluation schemes using TOPSIS to find the optimal energy matching scheme.

[0104] Step 8: Output the optimal solution for energy matching in the low-zero carbon park, that is, output the multi-energy complementary integrated energy solution for building a low-zero carbon park (i.e. the target energy matching solution mentioned above), and end the process.

[0105] like Figure 4 The diagram shows a system analysis module. This module is used to establish energy conservation and conversion relationships between different energy forms such as electricity, heat, cold, and compressed air, complete the supply and demand balance calculation of multi-energy systems, and on this basis, calculate energy consumption, system costs and benefits, and carbon emissions under different energy supply schemes, while also considering electricity markets, carbon markets, and green certificate trading mechanisms.

[0106] like Figure 5 The diagram illustrates a system optimization module used to execute a multi-objective optimization model. Under the premise of meeting energy and matter conservation laws and relevant low-zero carbon industrial park construction standards, the analytic hierarchy process (AHP) and entropy weight method are used to determine the corresponding weights for energy consumption, economic efficiency, and carbon emissions based on the interests of investors and other stakeholders in different scenarios. This allows for multi-objective optimization solutions to be obtained for different alternative energy supply schemes, ultimately leading to an evaluation result and the target energy supply scheme that meets the requirements.

[0107] This proposal presents a modeling and optimization method for a multi-energy complementary integrated energy system applicable to the construction of low-zero carbon industrial parks. This technical solution uses the industrial park as its boundary and an integrated source-grid-load-storage architecture as its basic framework, constructing a model covering electricity, heat, cooling, compressed air, material flow, and capital flow. Under the premise of satisfying energy and material conservation laws and relevant low-zero carbon industrial park construction standards, the solution achieves optimal solutions for multiple objectives, including energy consumption, carbon emissions, and economic benefits, through the organic coordination and optimization of various energy production, transmission, distribution, conversion, storage, and consumption processes.

[0108] This plan helps to accelerate the construction of a multi-energy complementary integrated energy system for low-zero carbon park construction, effectively guides decision-makers to select the energy matching scheme that best meets the needs of the park, and optimizes the dynamic relationship between the complex energy structure and diversified load demand of the park under the premise of meeting the relevant standards and requirements for low-zero carbon park construction, as well as energy consumption and carbon emission assessment requirements, and constructs an economical and competitive multi-energy complementary integrated energy solution for the park.

[0109] Decision-makers can determine the optimal multi-energy complementary integrated energy solution for the park by comprehensively considering key factors such as energy consumption, carbon emissions, and economic benefits, based on the park's actual energy demand and its own clean energy resource endowment.

[0110] This invention provides a device for determining a multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks, such as... Figure 6 As shown, the device includes: The acquisition module 60 is used to acquire multiple alternative energy supply solutions for the target park, as well as basic parameter data of each alternative energy supply solution associated with multiple specified indicators; among which, the multiple specified indicators include: energy consumption indicators, economic indicators and carbon emission indicators. The first calculation module 61 is used to calculate the total energy consumption of the target park for each alternative energy supply scheme based on the first parameter data related to the energy consumption index in the basic parameter data corresponding to the alternative energy supply scheme. The second calculation module 62 is used to calculate the carbon emissions of the target park based on the second parameter data associated with the carbon emission index in the basic parameter data corresponding to the alternative energy matching scheme if the total energy consumption meets the preset energy consumption requirements. The third calculation module 63 is used to calculate the full life cycle cost of the target park during the preset planning period, based on the third parameter data related to economic indicators in the basic parameter data corresponding to the alternative energy support scheme, if the carbon emissions meet the preset carbon emission requirements. The determination module 64 is used to perform a weighted comprehensive evaluation based on the total energy consumption, carbon emissions and life cycle cost of each alternative energy solution according to the preset multi-objective optimization rules, and to determine the target energy solution that matches the target park based on the configuration parameters of the alternative energy solution with the best evaluation value.

[0111] The aforementioned device for determining multi-energy complementary energy matching schemes for the construction of low-zero carbon parks calculates the total energy consumption, carbon emissions, and life-cycle cost of each alternative energy matching scheme. In other words, when determining the target energy matching scheme, it comprehensively considers energy consumption indicators, economic indicators, and carbon emission indicators. By adopting a multi-objective optimization approach, it can automatically and quickly select the optimal energy matching scheme that meets the requirements for the construction of low-zero carbon parks for the target park.

[0112] Furthermore, each alternative energy supply scheme is determined based on a preset energy system; the preset energy system includes: source side, grid side, load side, and storage side; wherein, the source side includes: wind power, photovoltaic, coal-fired cogeneration, gas-fired cogeneration, biomass cogeneration, external power grid, and heat pump; the grid side includes: power grid, heating network, cooling network, and compressed air network; the load side includes: electrical load, heat load, cooling load, compressed air load, and adjustable load; the storage side includes: energy storage equipment and thermal storage equipment; the first calculation module is also used to: determine whether multiple energy sources satisfy their respective energy balance formulas based on the first parameter data related to energy consumption indicators in the basic parameter data corresponding to the alternative energy supply scheme; wherein, multiple energy sources include: electrical energy, heat energy, cooling energy, and compressed air; if each energy source satisfies its respective energy balance formula, it is determined that each energy source satisfies energy conservation, and the total energy consumption of the target park is calculated.

[0113] Furthermore, the energy balance formula for electrical energy is:

[0114]

[0115] in, Contribute to photovoltaic power; Powering wind turbines; It provides power to coal-fired power plants, gas-fired power plants, and biomass cogeneration units; The power purchased by the target industrial park from the external power grid; The discharge power of the energy storage device; The electricity sold by the target industrial park to the external power grid; Within the target park The sum of the electricity loads of all users in the park; For the electrical load of refrigeration equipment; This refers to the electrical power required for the heat pump. The charging power for energy storage devices.

[0116] Furthermore, the energy balance formula corresponding to thermal energy is:

[0117] in, It outputs thermal power to coal-fired cogeneration, gas-fired cogeneration, and biomass combined heat and power units; The heat pump outputs heat power; Purchase heat from external sources for the target industrial park; The heat release power of the thermal storage device; Within the target park The sum of the heat loads of users in each park; To sell heat to external entities within the target industrial park; This refers to the heat storage capacity of the thermal storage equipment.

[0118] Furthermore, the energy balance formula corresponding to cold energy is:

[0119] in, To output cooling power to refrigeration equipment; Purchase cooling capacity from external sources for the target industrial park; Within the target park The sum of cooling loads of users in each park; The amount of cooling capacity sold to external parties from the target industrial park.

[0120] The energy balance formula for compressed air is:

[0121] in, The equipment outputs compressed air power. Within the target park The sum of compressed air loads of users in each park.

[0122] Furthermore, the carbon emissions of the target park are calculated using the following formula:

[0123] in, The carbon emissions of the target industrial park; Carbon emissions generated from the use of fossil fuels as fuel within the target industrial park; In the process of energy processing and conversion, the input energy is processed or converted into other carbon-containing secondary energy through a certain technological process; Indirect carbon emissions from net electricity and heat intake within the target industrial park; Carbon emissions generated during the production process of industrial products.

[0124] Furthermore, the total life-cycle cost of the target park during the pre-planning period is calculated using the following formula:

[0125]

[0126] Where LCC is the total lifecycle cost of the target park over n years; The initial construction cost of the target park; Let be the operating cost of the target park in year t; a is the preset discount rate (%). The target park's subsidy income over n years; The material and fuel costs of the park in year t; The target park's operation and maintenance cost in year t; The cost of treating waste gas, wastewater, and solid waste in the target industrial park in year t; The green certificate transaction cost for the target park in year t; Let be the carbon trading cost for the target park in year t.

[0127] Furthermore, the determination module is also used to: construct a multi-objective evaluation matrix based on the total energy consumption, carbon emissions, and life-cycle cost corresponding to each alternative energy supply scheme; perform weighted normalization processing on the multi-objective evaluation matrix based on pre-stored weight parameters corresponding to energy consumption indicators, carbon emission indicators, and economic indicators to obtain the comprehensive evaluation value of each alternative energy supply scheme; and determine the alternative energy supply scheme with the highest comprehensive evaluation value as the target energy supply scheme that matches the target park.

[0128] The device for determining the multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned method for determining the multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks. For the sake of brevity, any parts of the device for determining the multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks that are not mentioned in the embodiment can be referred to the corresponding content in the aforementioned method for determining the multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks.

[0129] This invention also provides an electronic device, see [link to relevant documentation]. Figure 7 As shown, the electronic device includes a processor 130 and a memory 131. The memory 131 stores machine-executable instructions that can be executed by the processor 130. The processor 130 executes the machine-executable instructions to implement the above-mentioned method for determining a multi-energy complementary energy matching scheme for the construction of low-zero carbon parks.

[0130] Furthermore, Figure 7 The electronic device shown also includes a bus 132 and a communication interface 133, with the processor 130, the communication interface 133 and the memory 131 connected via the bus 132.

[0131] The memory 131 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 133 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 132 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 7 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0132] Processor 130 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 130 or by instructions in software form. Processor 130 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 131, and processor 130 reads the information in memory 131 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0133] This invention also provides a machine-readable storage medium storing machine-executable instructions. When these machine-executable instructions are called and executed by a processor, they cause the processor to implement the above-described method for determining a multi-energy complementary energy matching scheme for the construction of low-zero carbon industrial parks. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0134] The computer program product of the method for determining the multi-energy complementary energy matching scheme for the construction of low-zero carbon industrial parks provided in this embodiment of the invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0135] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining a multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks, characterized in that, The method is executed by a computer and includes the following steps: Obtain multiple alternative energy supply solutions for the target park, as well as basic parameter data for each alternative energy supply solution that are associated with multiple specified indicators; wherein, the multiple specified indicators include: energy consumption indicators, economic indicators, and carbon emission indicators; For each of the alternative energy supply schemes, the total energy consumption of the target park is calculated based on the first parameter data associated with the energy consumption index in the basic parameter data corresponding to the alternative energy supply scheme. If the total energy consumption meets the preset energy consumption requirements, the carbon emissions of the target park are calculated based on the second parameter data associated with the carbon emission index in the basic parameter data corresponding to the alternative energy support scheme. If the carbon emissions meet the preset carbon emission requirements, the full life cycle cost of the target park during the preset planning period is calculated based on the third parameter data associated with the economic indicators in the basic parameter data corresponding to the alternative energy support scheme. Based on the total energy consumption, carbon emissions, and life-cycle cost corresponding to each of the alternative energy supply schemes, a weighted comprehensive evaluation is performed according to a preset multi-objective optimization rule, and a target energy supply scheme that matches the target park is determined based on the configuration parameters of the alternative energy supply scheme with the best evaluation value.

2. The method according to claim 1, characterized in that, Each of the aforementioned alternative energy solutions is determined based on a preset energy system; the preset energy system includes: source side, grid side, load side, and storage side; wherein, the source side includes: wind power, photovoltaic power, coal-fired power generation, gas-fired power generation, biomass power generation, external power grid, and heat pump; the grid side includes: power grid, heating network, cooling network, and compressed air network; the load side includes: electrical load, heat load, cooling load, compressed air load, and adjustable load; the storage side includes: energy storage equipment and thermal storage equipment; The steps for calculating the total energy consumption of the target park based on the first parameter data associated with the energy consumption index from the basic parameter data corresponding to the alternative energy support scheme include: Based on the basic parameter data corresponding to the alternative energy supply scheme, the first parameter data associated with the energy consumption index is used to determine whether the various energy sources meet their respective energy balance formulas; wherein, the various energy sources include: electrical energy, thermal energy, cold energy and compressed air; If each energy source satisfies its corresponding energy balance formula, and it is determined that each energy source satisfies energy conservation, then the total energy consumption of the target park can be calculated.

3. The method according to claim 2, characterized in that, The energy balance formula corresponding to the electrical energy is: in, Contribute to photovoltaic power; Powering wind turbines; It provides power to the coal-fired power plant, the gas-fired power plant, and the biomass cogeneration unit; The power purchased by the target industrial park from the external power grid; The discharge power of the energy storage device; The electricity sold by the target industrial park to the external power grid; Within the target park The sum of the electricity loads of all users in the park; For the electrical load of refrigeration equipment; This refers to the electrical power required for the heat pump. The charging power of the energy storage device.

4. The method according to claim 2, characterized in that, The energy balance formula corresponding to the thermal energy is: in, The thermal power is output to the coal-fired cogeneration unit, the gas-fired cogeneration unit, and the biomass cogeneration unit. The heat pump outputs heat power; Purchase heat from external sources for the target industrial park; The heat release power of the heat storage device; Within the target park The sum of the heat loads of users in each park; To sell heat to external entities from the target industrial park; The thermal storage power of the thermal storage device is denoted as .

5. The method according to claim 2, characterized in that, The energy balance formula corresponding to the cold energy is: in, To output cooling power to refrigeration equipment; Purchase cooling capacity from external sources for the target industrial park; Within the target park The sum of cooling loads of users in each park; The target area sells cooling capacity to external parties; The energy balance formula for the compressed air is: in, The equipment outputs compressed air power. Within the target park The sum of compressed air loads of users in each park.

6. The method according to claim 1, characterized in that, The carbon emissions of the target park shall be calculated using the following formula: in, The carbon emissions of the target industrial park; Carbon emissions generated from the use of fossil fuels as fuel within the target industrial park; In the process of energy processing and conversion, the input energy is processed or converted into other carbon-containing secondary energy through a certain technological process; The indirect carbon emissions contained in the net intake of electricity and heat within the target park; Carbon emissions generated during the production process of industrial products.

7. The method according to claim 1, characterized in that, The total life-cycle cost of the target park during the preset planning period is calculated using the following formula: Wherein, LCC is the total lifecycle cost of the target park over n years; The initial construction cost of the target park; Let be the operating cost of the target park in year t; a is the preset discount rate (%). Let n be the subsidy income of the target park over n years; Let be the material and fuel cost of the park in year t; Let be the operation and maintenance cost of the target park in year t; Let be the cost of treating waste gas, wastewater, and solid waste in the target industrial park in year t. Let be the green certificate transaction cost for the target park in year t; Let be the carbon trading cost of the target industrial park in year t.

8. The method according to claim 1, characterized in that, Based on the total energy consumption, carbon emissions, and life-cycle cost corresponding to each of the alternative energy solutions, a weighted comprehensive evaluation is performed according to a preset multi-objective optimization rule. The steps for determining the target energy solution matching the target industrial park based on the configuration parameters of the alternative energy solution with the best evaluation value include: A multi-objective evaluation matrix is ​​constructed based on the total energy consumption, carbon emissions, and life-cycle cost corresponding to each of the alternative energy solutions. Based on the pre-stored weight parameters corresponding to the energy consumption index, carbon emission index, and economic index, the multi-objective evaluation matrix is ​​weighted and normalized to obtain the comprehensive evaluation value of each alternative energy matching scheme. The alternative energy supply plan with the highest comprehensive evaluation value is selected as the target energy supply plan that matches the target industrial park.

9. A device for determining a multi-energy complementary energy scheme for the construction of low-zero carbon industrial parks, characterized in that, The device includes: The acquisition module is used to acquire multiple alternative energy supply solutions for the target park, as well as basic parameter data of each alternative energy supply solution associated with multiple specified indicators; wherein, the multiple specified indicators include: energy consumption indicators, economic indicators and carbon emission indicators. The first calculation module is used to calculate the total energy consumption of the target park for each of the alternative energy supply schemes, based on the first parameter data associated with the energy consumption index in the basic parameter data corresponding to the alternative energy supply scheme. The second calculation module is used to calculate the carbon emissions of the target park based on the second parameter data associated with the carbon emission index in the basic parameter data corresponding to the alternative energy matching scheme if the total energy consumption meets the preset energy consumption requirements. The third calculation module is used to calculate the full life cycle cost of the target park within the preset planning period, based on the third parameter data associated with the economic indicators in the basic parameter data corresponding to the alternative energy support scheme, if the carbon emissions meet the preset carbon emission requirements. The determination module is used to perform a weighted comprehensive evaluation based on the total energy consumption, carbon emissions, and life cycle cost corresponding to each of the alternative energy supply schemes, according to a preset multi-objective optimization rule, and to determine the target energy supply scheme that matches the target park based on the configuration parameters of the alternative energy supply scheme with the best evaluation value.

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