Rural integrated energy network planning method and system considering dynamic load distribution

Abstract

This invention relates to the field of power grid planning technology and discloses a planning method and system for rural integrated energy networks that considers dynamic load allocation. It establishes a dynamic load allocation matrix for rural integrated energy networks at different time granularities, enabling flexible adjustment of the output ratio of different equipment based on seasonal, monthly, or even daily load fluctuations. This completely solves the energy waste caused by structural mismatch between supply and demand. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, an objective function is established to maximize primary energy savings, carbon dioxide emission reduction, and annual total operating cost reduction. Equipment performance constraints, energy balance constraints, and planning area constraints are also established. This enables organic coordination and multi-energy complementarity among different energy sources, thereby improving rural energy utilization efficiency and reducing carbon emissions and operating costs.

Description

Technical Field

[0001] This invention relates to the field of power grid planning technology, and in particular to a method and system for planning rural integrated energy grids that considers dynamic load distribution. Background Technology

[0002] Against the backdrop of continuous rural economic development, rural households' demand for energy such as electricity, heat, gas, and cooling is constantly increasing. However, the dispersed residences of rural residents lead to higher energy transmission costs, and the over-reliance on traditional primary energy sources such as coal, fuel oil, and straw, coupled with a lack of efficient energy infrastructure, results in insufficient energy supply reliability, increased carbon emissions, and resource waste.

[0003] Renewable energy resources such as solar and biomass energy are widely distributed in rural areas, but the development and planning of various energy resources are currently relatively independent, failing to achieve energy linkage and synergy, making it difficult to maximize resource utilization efficiency. Existing rural energy grid planning studies mostly focus on small-scale microgrids, lacking planning studies for integrated energy grids, and lacking analysis of the degree of dependence of different energy supply structures on external energy sources. The roles of investment and construction entities and construction paths are also unclear.

[0004] Meanwhile, in the existing integrated energy grid, the electricity-to-heat ratio of power generation units does not match the actual electricity-to-heat ratio required by buildings, resulting in energy waste; biomass energy is mostly used by direct combustion, which is inefficient, and although biomass gasification technology can improve utilization efficiency, its integrated application in the integrated energy grid is insufficient; although ground source heat pumps can balance electricity and heat loads, the traditional fixed load distribution method cannot adapt to the seasonal, monthly and daily fluctuations of rural loads, limiting the improvement of the overall performance of the energy grid. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a rural integrated energy grid planning method and system that takes into account dynamic load distribution, which can improve rural energy utilization efficiency and reduce carbon emissions and operating costs.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A rural integrated energy grid planning method considering dynamic load allocation includes: A dynamic load allocation matrix for a rural integrated energy network at different time granularities is established. The dynamic load allocation matrix includes the ratio of heat load provided by ground source heat pumps to total heat load and the ratio of cooling load provided by ground source heat pumps to total cooling load. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, an objective function is established with the goal of maximizing the primary energy saving rate, carbon dioxide emission reduction rate, and annual total operating cost reduction rate. Equipment performance operation constraints, energy balance constraints, and planning area constraints are also established. A rural integrated energy network planning optimization model is generated based on the objective function, the equipment performance operation constraints, the energy balance constraints, and the planning area constraints. The planning optimization model of the rural integrated energy network is solved based on the dynamic load allocation matrix to obtain the planning results.

[0007] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A rural integrated energy grid planning system considering dynamic load allocation includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps of the aforementioned rural integrated energy grid planning method considering dynamic load allocation.

[0008] The beneficial effects of this invention are as follows: It establishes a dynamic load allocation matrix for rural integrated energy networks at different time granularities. This dynamic load allocation matrix includes the ratio of heat load provided by ground source heat pumps to the total heat load and the ratio of cooling load provided by ground source heat pumps to the total cooling load. This allows for flexible adjustment of the output ratio of different equipment based on seasonal, monthly, and even daily load fluctuations, completely solving the energy waste caused by structural mismatch between supply and demand. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, an objective function is established to maximize primary energy savings, carbon dioxide emission reduction, and annual total operating cost reduction. Equipment performance constraints, energy balance constraints, and planning area constraints are also established, enabling organic coordination and multi-energy complementarity among different energy sources. The planning optimization model of the rural integrated energy network is solved based on the dynamic load allocation matrix to obtain planning results, thereby improving rural energy utilization efficiency and reducing carbon emissions and operating costs. Attached Figure Description

[0009] Figure 1 This is a flowchart of a rural integrated energy network planning method considering dynamic load distribution, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of a rural integrated energy network planning system that considers dynamic load distribution, according to an embodiment of the present invention. Detailed Implementation

[0010] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0011] In existing technologies, rural residents live in scattered locations and rely excessively on traditional primary energy sources such as coal, fuel oil, and straw, resulting in low energy efficiency in rural areas and increased carbon emissions and operating costs.

[0012] To at least address the aforementioned problems, the present invention provides a rural integrated energy network planning method and system considering dynamic load distribution, applicable to rural integrated energy network planning scenarios that consider multiple energy resources such as solar energy, biomass energy, and geothermal energy. The specific implementation methods are described below: Please refer to Figure 1 One embodiment of the present invention is as follows: A rural integrated energy grid planning method considering dynamic load allocation includes: S1. Establish a dynamic load allocation matrix for the rural integrated energy network at different time granularities. The dynamic load allocation matrix includes the ratio of heat load provided by the ground source heat pump to the total heat load and the ratio of cooling load provided by the ground source heat pump to the total cooling load.

[0013] The user's cooling load is supplied jointly by the absorption chiller and the ground source heat pump in cooling mode, while the user's heating load is met by the heat flowing through the heat exchanger and the heat provided by the ground source heat pump in heating mode. During the heating and cooling seasons, the rural integrated energy network experiences significant load differences between seasons, months, and days. If a fixed value is used... and Distributing resources in this way makes it difficult to achieve optimal operation throughout the year, considering both the heating and cooling seasons. Based on this characteristic, and There is an issue of reasonable allocation. A dynamic load allocation matrix can be used at different time granularities. Optimization and The value, and The range is 0-1.

[0014] The dynamic load allocation matrix is ​​specifically as follows: ; In the formula, Represents the dynamic load distribution matrix. Representing different time granularities The ratio of the cooling load provided by the ground source heat pump to the total cooling load. Representing different time granularities The ratio of the heat load provided by the ground source heat pump to the total heat load.

[0015] Among them, the duration of the cooling season and the duration of the heating season and When determined, The row dimension can be reduced to one dimension: .

[0016] In addition, dynamic load allocation It can be dynamically configured according to actual needs. Specifically, when When set to 8760, dynamic load distribution means that a fixed load ratio is used for distribution during the heating and cooling seasons; when set to... When set to 730, dynamic load sharing represents the load ratio optimized monthly; when When set to 24, dynamic load allocation represents the daily optimized load ratio. Because the internal elements of dynamic load allocation must be integers, and ground source heat pump equipment has a certain thermal inertia, therefore... The minimum value is set to 24, and at the same time It must be divisible by 8760 to ensure the rationality of load distribution and the stable operation of the system.

[0017] This approach, by constructing a dynamic load allocation matrix, specifically addresses the shortcomings of existing technologies, such as the fixed heat-to-electricity ratio of power generation units and the inability of traditional ground-source heat pump allocation methods to adapt to rural load fluctuations, leading to energy waste. The dynamic load allocation matrix divides the year into heating, cooling, and transitional seasons, constructing a dynamic allocation matrix with hourly steps that includes heating and cooling allocation ratios. It flexibly adjusts the load allocation ratio at different time granularities (e.g., 24 hours per day or 730 hours per month), achieving precise simulation and flexible adjustment of energy flow. This method promotes the organic coordination and multi-energy complementarity among various energy sources such as solar, biomass, and geothermal energy, enabling the system output characteristics to better match the dynamic demands of the load side. This significantly improves rural energy utilization efficiency and effectively reduces system carbon emissions and overall operating costs.

[0018] S2. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, establish an objective function with the goal of maximizing the primary energy saving rate, carbon dioxide emission reduction rate, and annual total operating cost reduction rate, and establish equipment performance operation constraints, energy balance constraints, and planning area constraints, specifically including S21-S212: The energy input-side equipment includes a power generation unit, solar photovoltaic panels, and solar thermal collectors. The energy conversion-side equipment includes a chiller, a gas boiler, and a ground source heat pump. The energy storage-side equipment includes electrical energy storage and thermal energy storage. The auxiliary equipment includes heat exchangers and waste heat recovery devices.

[0019] The power generation unit provides primarily electrical energy and some heat energy. The heat energy is recovered from the high-temperature gases and liquids generated during power generation via a heat conversion device. Solar photovoltaic (PV) technology, as an advanced technology for efficiently utilizing solar energy, demonstrates outstanding flexibility and broad application potential. Its basic principle relies on the photovoltaic effect of solar panels, realizing the direct conversion of solar energy into electrical energy. The power generation efficiency of solar PV is affected by various factors, including but not limited to ambient temperature, solar radiation intensity, and the rated power of the modules themselves. Solar collectors can achieve the conversion of light energy into heat energy.

[0020] In rural integrated energy networks, cooling loads are typically met by electric chillers and absorption chillers. Electric chillers work by pressurizing a liquid refrigerant and absorbing heat through vaporization to achieve cooling. Absorption chillers, a unique refrigeration technology, consist of an absorber and an evaporator. Unlike traditional electric chillers, absorption chillers do not rely on electricity; instead, they use thermal energy as a power source to drive the refrigeration cycle. This thermal energy source is diverse, including renewable energy sources like solar power and waste heat recovered from industrial equipment such as internal combustion engines and gas turbines. Furthermore, the requirements for thermal energy quality are relatively relaxed. Gas-fired boilers meet thermal energy shortages by consuming natural gas. Based on their main functional modules, they can be divided into two main components: a fuel control system and a ventilation control system. During operation, the heat released from natural gas combustion is mainly consumed by the heat load and heat loss. Ground source heat pumps provide both heating and cooling, and can also supply hot water. Compared to other equipment, they are more energy-efficient for the same effect and do not produce greenhouse gases during operation.

[0021] Electrical energy storage can significantly improve the overall economic efficiency of the power grid, ensure the reliability of power supply to users, and maintain stable power quality for users. Thermal energy storage can peak-shaving and valley-filling of heat loads, thereby ensuring that rural integrated energy grids can operate in an economical and efficient manner.

[0022] In the power generation unit, the gas is mixed with compressed air and burned to generate high-temperature flue gas. After passing through the waste heat recovery device, the energy contained in this flue gas can not only be used for heating, but also converted into the energy required for cooling.

[0023] Biomass gasification systems are advanced technologies for energy conversion using biomass resources. Their core mechanism involves using gasification media such as air and steam to induce a series of chemical reactions in the biomass feedstock, including pyrolysis, oxidation, and reduction reforming. This ultimately converts the biomass feedstock into combustible gases primarily composed of carbon monoxide, hydrogen, methane, and low-molecular-weight hydrocarbons. The system mainly consists of a feeding system, a gasification reactor, a syngas purification system, and a post-processing system. The type of gasifier is a key factor affecting the performance of biomass gasification systems. Gasifiers can be broadly classified into fixed-bed and fluidized-bed types. Fixed-bed gasifiers are further subdivided into three structures based on the flow direction of the gasifying agent: top-suction, bottom-suction, and horizontal-suction. In practical industrial applications, the selection of the gasifier type requires comprehensive consideration of the characteristics of the biomass fuel, such as fuel type, particle size, and moisture content. The rural integrated energy grid uses downdraft gasifiers, which have significant advantages. On the one hand, the syngas produced has a lower content of tar and ash. On the other hand, it is more suitable for small and medium-sized application scenarios and can respond quickly to load changes.

[0024] Once the energy consumed by the biomass gasification gas in the power generation unit is determined, the total energy required for biomass fuel can be calculated, specifically: ; In the formula, Represents the solid energy of biomass. This indicates the fuel input energy consumption of the power generation unit. This indicates the power of the cleaning equipment. Indicates the power output of biomass gasification; The energy conversion rate in the biomass gasification process is evaluated using the cooling power, defined as the energy ratio of biomass gasification gas to biomass fuel. The calculation formula is as follows: ; In the formula, Indicates the cooling power of the biomass gasification system. This indicates the calorific value of biomass gasification gas. The gaseous energy representing the output of biomass gasification gas. This indicates the low calorific value of biomass gasification gas.

[0025] The cooling power of a biomass gasification system is used to evaluate the energy conversion efficiency of the biomass gasification process. Specifically, it refers to the ratio of the energy contained in the gasified gas to the energy of the original biomass fuel when the biomass feedstock is converted into biomass gas through the gasification reaction. In essence, it measures the energy utilization level of the process of "converting solid biomass feedstock into combustible gasification gas". The higher the cooling power, the less energy is lost during the gasification process, and the more fully the energy of the biomass feedstock is converted into the energy of the gasified gas.

[0026] S21. Calculate the primary energy consumption of the rural integrated energy network based on the interaction power between the rural integrated energy network and the power grid, as well as the biomass energy and natural gas consumed by the rural integrated energy network. Specifically: ; In the formula, This indicates the primary energy consumption of the rural integrated energy network. Indicates that the rural integrated energy network is in The power of constant interaction with the power grid. Indicates the power generation efficiency of the power grid. Indicates power grid transmission efficiency. Indicates in The biomass energy consumed by the rural integrated energy network at all times. Indicates in The amount of natural gas consumed by the rural integrated energy network at any given time.

[0027] S22. Calculate the primary energy saving rate based on the primary energy consumption of the traditional distribution network and the primary energy consumption of the rural integrated energy network, specifically as follows: ; In the formula, Indicates the primary energy saving rate, This indicates the primary energy consumption of a traditional distributed energy supply network.

[0028] S23. Calculate the annual carbon dioxide emissions of the rural integrated energy network based on the interaction power between the rural integrated energy network and the power grid, as well as the biomass energy and natural gas consumed by the rural integrated energy network, specifically: ; In the formula, This indicates the annual carbon dioxide emissions of the rural integrated energy network. This represents the carbon dioxide emission coefficient of the power grid. This represents the carbon dioxide emission coefficient of biomass. This indicates the carbon dioxide emission coefficient of natural gas.

[0029] S24. Calculate the carbon dioxide emission reduction rate based on the annual carbon dioxide emissions of the traditional distribution network and the annual carbon dioxide emissions of the rural integrated energy network, specifically as follows: ; In the formula, Indicates the carbon dioxide emission reduction rate. This represents the annual carbon dioxide emissions of a traditional distribution network.

[0030] S25. Calculate the annual operating cost of the rural integrated energy network based on the total annual equipment cost, total annual operating cost, and total annual labor cost, specifically as follows: ; In the formula, This indicates the annual operating cost of the rural integrated energy network. This represents the total annual equipment cost. This represents the total annual operating cost. This represents the total annual labor cost.

[0031] The formula for calculating the total annual equipment cost is as follows: ; In the formula, Indicates the interest rate. Indicates the lifespan of the equipment. Indicates the total number of devices. This indicates the configuration cost of the equipment.

[0032] The total annual operating cost mainly consists of the annual gas purchase cost, the annual biomass cost, and the annual electricity purchase cost. The calculation formula is as follows: ; ; In the formula, This indicates the annual gas purchase cost. Indicates the annual cost of biomass. This indicates the annual electricity purchase cost. Indicates the price of biomass. This indicates the amount of biomass consumed.

[0033] S26. Calculate the annual total operating cost reduction rate based on the annual total operating cost of the traditional distribution network and the annual operating cost of the rural integrated energy network, specifically as follows: ; In the formula, This indicates the annual total operating cost reduction rate. This represents the total annual operating cost of a traditional distribution network.

[0034] S27. A linear weighted method is used to establish an objective function that maximizes the primary energy saving rate, the carbon dioxide emission reduction rate, and the annual total operating cost reduction rate, specifically as follows: ; In the formula, This represents the sum of primary energy savings rate, carbon dioxide emission reduction rate, and annual total operating cost reduction rate. , and These represent the first weighting factor, the second weighting factor, and the third weighting factor, respectively. Indicates the primary energy saving rate, Indicates the carbon dioxide emission reduction rate. This indicates the annual reduction rate of total operating costs.

[0035] In this way, by using a linear weighting method, conflicting objectives of economic cost, energy efficiency and environmental emission reduction across different dimensions are integrated into a unified comprehensive evaluation index. This not only effectively solves the problem of choosing the Pareto optimal solution set, which is common in multi-objective optimization, but also gives decision-makers a high degree of flexibility. They can adjust the weighting coefficients based on the actual policy orientation or resource endowment of rural areas to find the best balance between reducing operating expenses, saving fossil energy and reducing carbon emissions. This maximizes the overall benefits of the network and achieves the optimal solution for development and utilization while ensuring the safe operation of the system.

[0036] S28. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, establish equipment performance constraints, electrical energy storage operation constraints, and thermal energy storage operation constraints.

[0037] During the optimization process, each device must maintain a dynamic balance between input and output, and its output power must not exceed its rated maximum capacity. Specifically, it must be ensured that the power of each device in cold, hot, and electric output modes strictly meets the preset power range limit. The specific device performance constraints are as follows: ; In the formula, This indicates the lower limit of the output power of the power supply equipment. Indicates the output power of the power supply equipment. Indicates the upper limit of the output power of the power supply equipment. This indicates the lower limit of the output power of the heating equipment. Indicates the output power of the heating equipment. This indicates the upper limit of the output power of the heating equipment. This indicates the lower limit of the output power of the cooling equipment. This indicates the output power of the cooling equipment. This indicates the upper limit of the output power of the cooling equipment.

[0038] Furthermore, to ensure effective energy balance within a scheduling cycle, the initial and final states of charge of the energy storage must remain consistent. Based on this premise, the operation of the energy storage must also comply with the aforementioned energy storage operation constraints, specifically: ; In the formula, Indicates the lower limit of electrical energy storage capacity. This indicates the upper limit of electrical energy storage capacity. Indicates in Real-time energy storage capacity, This represents the electrical energy storage capacity at the initial moment. Indicates in Real-time energy storage capacity, Indicates the planning period. The logical variable representing the charging of electrical energy storage. This indicates that the energy storage is in a charging state. This indicates that the electrical energy storage is in a discharging state. A logical variable representing the discharge of stored electrical energy. This indicates that the electrical energy storage is in a discharging state. This indicates that the energy storage is in a charging state. This indicates the lower limit of the charging power of electric energy storage. This indicates the upper limit of the charging power of the energy storage system. Indicates in Real-time energy storage charging power, Indicates in The discharge power of the energy storage at any time. This indicates the lower limit of the discharge power of the electrical energy storage. This indicates the upper limit of the discharge power of the energy storage.

[0039] Among them, The energy storage capacity at any given time is: ; In the formula, Indicates in Real-time energy storage capacity, Indicates the discharge rate of electrical energy storage. This indicates the charging efficiency of electrical energy storage. This indicates the discharge efficiency of the electrical energy storage.

[0040] The specific operating constraints of the thermal energy storage are as follows: ; In the formula, Indicates the lower limit of thermal energy storage capacity. Indicates the upper limit of thermal energy storage capacity. Indicates in Real-time thermal energy storage capacity, This represents the thermal energy storage capacity at the initial moment. Indicates in Real-time thermal energy storage capacity, The logical variable representing the heat absorption of thermal energy storage. This indicates that the thermal energy storage is in a heat absorption state. This indicates that the thermal energy storage is in a heat-releasing state. The logical variable representing the heat released by thermal energy storage. This indicates that the thermal energy storage is in a heat-releasing state. This indicates that the thermal energy storage is in a heat absorption state. This indicates the lower limit of thermal energy storage capacity. This indicates the upper limit of thermal energy storage capacity. Indicates in Real-time thermal energy storage capacity This indicates the lower limit of the heat release capacity of thermal energy storage. Indicates in Real-time thermal energy storage and heat release power, This indicates the upper limit of the heat release power of thermal energy storage.

[0041] Among them, The thermal energy storage capacity at any given time is: ; In the formula, Indicates in Real-time thermal energy storage capacity, Indicates the heat loss rate. This indicates the heat storage efficiency. This indicates the heat release efficiency of thermal energy storage.

[0042] S29. Obtain the equipment performance operation constraints based on the equipment performance constraints, the electrical energy storage operation constraints, and the thermal energy storage operation constraints.

[0043] Equipment performance constraints can ensure equipment output efficiency and extend equipment service life.

[0044] S210. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, establish electrical balance constraints and thermal balance constraints.

[0045] The rural integrated energy grid will prioritize the use of electricity generated by solar photovoltaic power. If there is surplus electricity generated by solar photovoltaic power, it will be stored in energy storage. When the electricity generated by solar photovoltaic power cannot meet the demand, the electricity stored in energy storage will be used first. Only when neither solar photovoltaic power nor energy storage can meet the user's demand will the power generation unit be activated to generate electricity or provide heat. If the power generation unit still has a power or heat deficit when operating at full capacity, the energy grid will purchase electricity from the grid to meet the electricity load demand, or start the gas boiler to supplement the combustion to meet the heat load demand.

[0046] Based on this operational logic, the specific electrical balance constraint conditions are as follows: ; In the formula, This indicates that electricity is purchased from the power grid. This indicates the electricity generated by solar photovoltaic power. This represents the electricity generated by the power generation unit. This indicates the discharge state of electrical energy storage. This represents the discharge power of the stored energy at the current moment. This represents the charging state bit variable of electrical energy storage. This indicates the charging power of the energy storage at the current moment. This indicates the electricity consumed by the ground source heat pump. Indicates rural electricity load. This refers to the abandoned power in the system that cannot be utilized or stored.

[0047] The charging and discharging state bit variables of energy storage are represented by Boolean values ​​(0 or 1), and their changes are driven by both the system's real-time energy surplus / deficit and economic dispatch logic: when distributed power generation has excess output and meets the energy storage access conditions, the charging state bit variable switches to 1 while the discharging state bit variable is forced to 0; conversely, when load demand is high or the cost of purchasing electricity is high and energy storage is needed to support it, the discharging state bit variable switches to 1 while the charging state bit variable returns to 0. This dynamic switching based on mutual exclusion constraints ensures that the energy storage system can only be in a single operating mode during any given physical time period, thereby accurately simulating energy flow and avoiding logic distortion caused by simultaneous charging and discharging.

[0048] Where, for any At any given moment, the amount of electricity stored in the energy storage system. and Battery level at any time and Charge amount at any time and discharge quantity Regarding the balance relationship of electrical energy storage: ; In the formula, express The charge capacity of the electrical energy storage at any time. express The charge capacity of the electrical energy storage at any time. This indicates the discharge efficiency of electrical energy storage. This indicates the charging efficiency of electrical energy storage.

[0049] The electricity generated by the power generation unit is: ; In the formula, This indicates the fuel input energy consumption of the power generation unit. This indicates the power generation capacity of the power generation unit.

[0050] The electricity generated by solar photovoltaic power is: ; ; ; In the formula, This indicates the installed area of ​​solar photovoltaic systems. This indicates the irradiance of the environment in which solar photovoltaic cells are located. This indicates the power generation capacity of solar photovoltaic systems. This indicates the standard power output of solar photovoltaic (PV) systems. Indicates the temperature coefficient of solar photovoltaic power. Indicates ambient temperature. The standard temperature for solar photovoltaic power is indicated. This represents the irradiance coefficient of solar photovoltaic power. This represents the logarithm of the following value, with base e. This indicates the rated temperature of the photovoltaic cell.

[0051] The electricity consumed by a ground source heat pump includes the electricity consumed for heating and the electricity consumed for cooling, which is: ; ; ; In the formula, This indicates the power consumption of a ground source heat pump, describes its variable operating characteristics under different load rates, and is used to correct or calculate the actual operating power. COP , , , Both represent constants. This indicates the amount of heat output by the ground source heat pump. This indicates the electricity consumed by a ground source heat pump for heating. This indicates the electricity consumed by the ground source heat pump for cooling. This indicates the amount of heat output from a ground source heat pump. This indicates the amount of heat output by the ground source heat pump for cooling. Indicates the coefficient of performance (COP) of a ground source heat pump for heating. This represents the coefficient of performance (COP) of a ground-source heat pump for cooling. Wherein, when... When all heat loads come from the heat exchanger, the ground source heat pump does not work; when At that time, all cooling loads came from the absorption chiller. Therefore and As a load allocation ratio, it needs to be selected and evaluated reasonably.

[0052] The thermal balance constraint conditions are specifically as follows: ; In the formula, This indicates the output power of the electric chiller. This indicates the output power of the absorption chiller. This indicates the heat output of the solar collector. This indicates the heat output of the waste heat recovery device. This indicates the heat output of the gas-fired boiler. This variable represents the heat release state of thermal energy storage. When the value of this variable is 1, it indicates the "on" state, meaning that the thermal energy storage is not currently in a heat absorption state (it may be at rest or releasing heat). When the value of this variable is 0, it indicates the "off" state, meaning that the thermal energy storage is currently in a heat absorption (energy storage) state. This indicates the heat release capacity of the thermal energy storage at the current moment. This variable represents the heat absorption state of thermal energy storage. When the value of this variable is 1, it indicates the "on" state, meaning that the thermal energy storage is not currently releasing heat (it may be at rest or absorbing heat). When the value of this variable is 0, it indicates the "off" state, meaning that the thermal energy storage is currently releasing heat. This represents the heat absorption capacity of the thermal energy storage at the current moment. This indicates the ratio of the cooling load provided by the ground source heat pump to the total cooling load. This indicates the ratio of the heat load provided by the ground source heat pump to the total heat load. Indicates cooling load. Indicates heat load, This represents the coefficient of performance (COP) of an absorption chiller. This indicates the heat exchanger's heat exchange efficiency. This indicates wasted calories.

[0053] For any At any given moment, the amount of heat stored in thermal energy and Heat storage at all times and Constantly replenishing heat and heat release Regarding the balance relationship of thermal energy storage: ; In the formula, express The amount of heat stored in thermal energy storage at all times. This indicates the heat release efficiency of thermal energy storage. This indicates the heat absorption efficiency of thermal energy storage.

[0054] The heat output of the solar collector is: ; ; ; In the formula, This indicates the installation area of ​​the solar collector. Indicates the irradiance of the solar collector. Indicates the power of the solar collector. Indicates radiated power. and These represent the first correction factor and the second correction factor, respectively. This represents the ratio of the difference between the standard temperature and the actual temperature and radiation intensity of a solar collector. This indicates the inlet temperature of the solar collector. This indicates the outlet temperature of the solar collector. and All vary with the seasons (temperature). This indicates the actual temperature of the solar collector.

[0055] The output power of the electric chiller is: ; In the formula, This indicates the electrical energy input to the electric chiller. This indicates the cooling capacity of the electric chiller.

[0056] The output power of the absorption chiller is: ; In the formula, This indicates the input energy of the absorption chiller.

[0057] The heat output of the gas-fired boiler is: ; In the formula, This indicates the amount of fuel input to the gas-fired boiler. This indicates the heat conversion power of a gas-fired boiler.

[0058] The heat load is: ; In the formula, This indicates the energy input to the heat exchanger. This indicates the conversion power of the heat exchanger.

[0059] The heat output of the waste heat recovery device is: ; ; In the formula, This indicates that the power generation unit can recover waste heat energy. This indicates the standard power of the power generation unit. This represents the relative power coefficient, which is a function of the volumetric calorific value of the fuel. Indicates heat recovery power; When biomass gasification gas is used as fuel instead of natural gas, the power output of the power generation unit will change. The mathematical model for the power output after changing the fuel is expressed as follows: ; In the formula, This indicates the power output of the power generation unit after changing the fuel. The relative power coefficient is: ; In the formula, This indicates the low calorific value of biomass gasification gas. This indicates the low calorific value of natural gas.

[0060] S211. Based on the electrical balance constraint condition and the thermal balance constraint condition, the energy balance constraint condition is obtained.

[0061] Energy balance constraints can ensure that the supply and demand of energy such as electricity, gas, and heat in the energy grid are balanced at any time.

[0062] S212. Establish planning area constraints, specifically: ; In the formula, This indicates the maximum installable area.

[0063] The planned area constraints can ensure the availability of site resources for equipment installation.

[0064] S3. Generate a rural integrated energy network planning optimization model based on the objective function, the equipment performance operation constraints, the energy balance constraints, and the planning area constraints.

[0065] S4. Solve the rural integrated energy network planning optimization model based on the dynamic load allocation matrix to obtain the planning results.

[0066] Specifically, based on the dynamic load allocation matrix, a metaheuristic optimization algorithm is used to solve the rural integrated energy network planning optimization model to obtain the planning results, as follows: (1) Initialize the parameters of the metaheuristic optimization algorithm: set key parameters such as the initial population size, maximum number of iterations, search step size and convergence threshold; (2) Randomly select equipment models to determine the initial population, and calculate the fitness value of each population under the constraints; (3) Perform operations such as population update, fitness value screening, and search space adjustment, and gradually approach the optimal solution by updating the population iteration position through individual optimization and group cooperation; (4) When the maximum number of iterations is reached or the change in fitness value over multiple generations is less than the convergence threshold, the iteration converges and the optimal capacity of each device is output. (5) Substitute the optimal capacity of each device into the rural integrated energy network planning optimization model to generate planning results.

[0067] The planning results include the optimal capacity of each device (e.g., photovoltaic installation area, solar collector installation area, etc.), the globally optimal operation and scheduling scheme (the core of which is the dynamic optimal scheduling matrix), and the performance index values ​​of system optimization (e.g., primary energy saving rate, carbon dioxide emission reduction rate, annual total operating cost reduction rate).

[0068] In this way, because the rural integrated energy network planning and optimization model involves complex nonlinear constraints, multi-time period coupling, and an objective function composed of multiple rate of return indicators, traditional gradient-based algorithms are prone to getting stuck in local optima and have difficulty handling discontinuous search spaces. However, metaheuristic algorithms, with their powerful global search capabilities and the characteristic of not relying on the derivative information of the objective function, can more effectively handle such high-dimensional combinatorial optimization problems, and find the globally optimal system capacity configuration and operation scheduling scheme more quickly while ensuring computational efficiency.

[0069] According to another aspect of the invention, Figure 2 This is a schematic diagram illustrating a rural integrated energy grid planning system considering dynamic load allocation according to an embodiment of the present invention. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps of a rural integrated energy grid planning method considering dynamic load allocation as described above.

[0070] In summary, the rural integrated energy network planning method and system of the present invention, which considers dynamic load distribution, is based on a model of energy input (photovoltaics, solar collectors, power generation units), conversion (refrigeration units, boilers, ground source heat pumps), energy storage, and biomass gasification system. It is no longer a simple power supply or heating system, but rather converts waste heat generated by power generation into thermal or cold energy through waste heat recovery devices, and uses ground source heat pumps to balance the electric and thermal loads. Through multi-energy complementarity, previously isolated resources are integrated into a dynamically interconnected network, significantly improving the maximization of resource utilization. Furthermore, the introduction of a biomass gasification system, using a downdraft gasifier to convert solid feedstock into syngas, and evaluating conversion efficiency using a cold gas power formula, results in syngas with low tar content, enabling rapid response to load changes. This upgrades the extensive "direct combustion" to a refined "gasification-based" system. "Electricity / Heating" significantly improves energy conversion efficiency while reducing carbon emissions. Furthermore, a dynamic load allocation matrix is ​​introduced, defining dynamic allocation ratios (heat load ratio and cooling load ratio). Instead of setting fixed values, a dynamic allocation matrix is ​​constructed, which can flexibly adjust the output ratio of ground source heat pumps and other equipment according to seasonal, monthly, and even daily load fluctuations, completely solving the energy waste caused by structural mismatch between supply and demand. A multi-objective function with three dimensions is established: primary energy saving rate analysis of natural gas and biomass consumption; carbon dioxide emission reduction rate including the emission coefficient of grid interaction power; and annual total operating cost reduction rate covering equipment configuration costs, interest rates, and operation and maintenance costs. The optimal capacity is iteratively solved using a metaheuristic algorithm, providing an optimal planning scheme for rural integrated energy networks that balances cost savings, energy conservation, and carbon reduction.

[0071] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A rural integrated energy network planning method considering dynamic load allocation, characterized in that, include: A dynamic load allocation matrix for a rural integrated energy network at different time granularities is established. The dynamic load allocation matrix includes the ratio of heat load provided by ground source heat pumps to total heat load and the ratio of cooling load provided by ground source heat pumps to total cooling load. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, an objective function is established with the goal of maximizing the primary energy saving rate, carbon dioxide emission reduction rate, and annual total operating cost reduction rate. Equipment performance operation constraints, energy balance constraints, and planning area constraints are also established. A rural integrated energy network planning optimization model is generated based on the objective function, the equipment performance operation constraints, the energy balance constraints, and the planning area constraints. The planning optimization model of the rural integrated energy network is solved based on the dynamic load allocation matrix to obtain the planning results.

2. The rural integrated energy network planning method considering dynamic load allocation according to claim 1, characterized in that, Establish a dynamic load allocation matrix for the rural integrated energy network at different time granularities, specifically as follows: ； In the formula, Represents the dynamic load distribution matrix. Representing different time granularities The ratio of the cooling load provided by the ground source heat pump to the total cooling load. Representing different time granularities The ratio of the heat load provided by the ground source heat pump to the total heat load.

3. The rural integrated energy network planning method considering dynamic load allocation according to claim 1, characterized in that, Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the aforementioned rural integrated energy network, an objective function is established to maximize the primary energy saving rate, carbon dioxide emission reduction rate, and annual total operating cost reduction rate, including: The primary energy consumption of the rural integrated energy network is calculated based on the interaction power between the rural integrated energy network and the power grid, as well as the amount of biomass energy and natural gas consumed by the rural integrated energy network. The primary energy saving rate is calculated based on the primary energy consumption of the traditional distribution network and the primary energy consumption of the rural integrated energy network. The annual carbon dioxide emissions of the rural integrated energy network are calculated based on the interaction power between the rural integrated energy network and the power grid, as well as the amount of biomass energy and natural gas consumed by the rural integrated energy network. The carbon dioxide emission reduction rate is calculated based on the annual carbon dioxide emissions of the traditional distribution network and the annual carbon dioxide emissions of the rural integrated energy network. The annual operating cost of the rural integrated energy network is calculated based on the total annual equipment cost, total annual operating cost, and total annual labor cost. The annual total operating cost reduction rate is calculated based on the annual total operating cost of the traditional distribution network and the annual operating cost of the rural integrated energy network. A linear weighted method is used to establish an objective function that maximizes the primary energy saving rate, the carbon dioxide emission reduction rate, and the annual total operating cost reduction rate.

4. A rural integrated energy network planning method considering dynamic load allocation according to claim 3, characterized in that, The primary energy consumption of the rural integrated energy network is calculated based on the interaction power between the rural integrated energy network and the power grid, as well as the amount of biomass energy and natural gas consumed by the rural integrated energy network. Specifically: ； In the formula, This indicates the primary energy consumption of the rural integrated energy network. Indicates that the rural integrated energy network is in The power of constant interaction with the power grid. Indicates the power generation efficiency of the power grid. Indicates power grid transmission efficiency. Indicates in The biomass energy consumed by the rural integrated energy network at all times. Indicates in The amount of natural gas consumed by the rural integrated energy network at any given time; The annual carbon dioxide emissions of the rural integrated energy network are calculated based on the interaction power between the rural integrated energy network and the power grid, as well as the amount of biomass energy and natural gas consumed by the rural integrated energy network. Specifically: ； In the formula, This indicates the annual carbon dioxide emissions of the rural integrated energy network. This represents the carbon dioxide emission coefficient of the power grid. This represents the carbon dioxide emission coefficient of biomass. Indicates the carbon dioxide emission coefficient of natural gas; The annual operating cost of the rural integrated energy network is calculated based on the total annual equipment cost, total annual operating cost, and total annual labor cost, as follows: ； In the formula, This indicates the annual operating cost of the rural integrated energy network. This represents the total annual equipment cost. This represents the total annual operating cost. This represents the total annual labor cost.

5. A rural integrated energy network planning method considering dynamic load allocation according to claim 3, characterized in that, A linear weighted method is used to establish an objective function that maximizes the primary energy saving rate, the carbon dioxide emission reduction rate, and the annual total operating cost reduction rate, specifically as follows: ； In the formula, This represents the sum of primary energy savings rate, carbon dioxide emission reduction rate, and annual total operating cost reduction rate. , and These represent the first weighting factor, the second weighting factor, and the third weighting factor, respectively. Indicates the primary energy saving rate, Indicates the carbon dioxide emission reduction rate. This indicates the annual reduction rate of total operating costs.

6. A rural integrated energy network planning method considering dynamic load allocation according to claim 1, characterized in that, Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the aforementioned rural integrated energy network, the following constraints are established for equipment performance operation, energy balance, and planned area: Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, establish equipment performance constraints, electrical energy storage operation constraints, and thermal energy storage operation constraints; The equipment performance operation constraints are obtained based on the equipment performance constraints, the electrical energy storage operation constraints, and the thermal energy storage operation constraints. Based on the energy input-side equipment, energy conversion-side equipment, energy storage-side equipment, auxiliary equipment, and biomass gasification system of the rural integrated energy network, establish electrical balance constraints and thermal balance constraints; Based on the electrical balance constraint condition and the thermal balance constraint condition, the energy balance constraint condition is obtained; Establish planning area constraints.

7. A rural integrated energy network planning method considering dynamic load allocation according to claim 6, characterized in that, The specific performance constraints of the equipment are as follows: ； In the formula, Indicates the lower limit of the output power of the power supply equipment. Indicates the output power of the power supply equipment. Indicates the upper limit of the output power of the power supply equipment. This indicates the lower limit of the output power of the heating equipment. Indicates the output power of the heating equipment. This indicates the upper limit of the output power of the heating equipment. This indicates the lower limit of the output power of the cooling equipment. Indicates the output power of the cooling equipment. Indicates the upper limit of the output power of the cooling equipment; The specific constraints for the operation of the energy storage are as follows: ； In the formula, This indicates the lower limit of electrical energy storage capacity. This indicates the upper limit of electrical energy storage capacity. Indicates in Real-time energy storage capacity, This represents the electrical energy storage capacity at the initial moment. Indicates in Real-time energy storage capacity, Indicates the planning period. The logical variable representing the charging of electrical energy storage. This indicates that the energy storage is in a charging state. This indicates that the electrical energy storage is in a discharging state. The logical variable representing the discharge of stored electrical energy. This indicates that the electrical energy storage is in a discharging state. This indicates that the energy storage is in a charging state. This indicates the lower limit of the charging power of electric energy storage. This indicates the upper limit of the charging power of the energy storage system. Indicates in Real-time energy storage charging power, Indicates in The discharge power of the energy storage at any time. This indicates the lower limit of the discharge power of the electrical energy storage. Indicates the upper limit of the discharge power of the electrical energy storage; The specific operating constraints of the thermal energy storage are as follows: ； In the formula, Indicates the lower limit of thermal energy storage capacity. Indicates the upper limit of thermal energy storage capacity. Indicates in Real-time thermal energy storage capacity, This represents the thermal energy storage capacity at the initial moment. Indicates in Real-time thermal energy storage capacity, The logical variable representing the heat absorption of thermal energy storage. This indicates that the thermal energy storage is in a heat absorption state. This indicates that the thermal energy storage is in a heat-releasing state. The logical variable representing the heat released by thermal energy storage. This indicates that the thermal energy storage is in a heat-releasing state. This indicates that the thermal energy storage is in a heat absorption state. This indicates the lower limit of thermal energy storage capacity. This indicates the upper limit of thermal energy storage capacity. Indicates in Real-time thermal energy storage capacity This indicates the lower limit of the heat release capacity of thermal energy storage. Indicates in Real-time thermal energy storage and heat release power, This indicates the upper limit of the heat release power of thermal energy storage.

8. A rural integrated energy network planning method considering dynamic load allocation according to claim 1, characterized in that, The rural integrated energy network planning optimization model is solved based on the dynamic load allocation matrix, and the planning results include: Based on the dynamic load allocation matrix, a metaheuristic optimization algorithm is used to solve the rural integrated energy network planning optimization model to obtain the planning results.

9. A rural integrated energy grid planning system considering dynamic load distribution, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements each step of the rural integrated energy network planning method considering dynamic load distribution as described in any one of claims 1 to 8.

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