A rural residential building light storage direct flexible key equipment capacity configuration method and system

Abstract

The present application belongs to the field of building power distribution and new energy, and provides a rural residential building light storage direct flexible key equipment capacity configuration method and system, which comprises calculating the annual photovoltaic power generation according to the layout of rural residential building group and the installable area of roof photovoltaic, selecting the corresponding light storage direct flexible system topology based on the relative proportion of annual photovoltaic power generation and annual power consumption load; determining the photovoltaic installed capacity based on the annual photovoltaic power generation, taking the upper limit of grid accessible capacity as the constraint boundary; establishing a capacity optimization configuration model with the maximum self-sufficiency rate and the maximum on-grid rate as the target, solving the capacity optimization configuration model based on the photovoltaic installed capacity, and determining the optimal total capacity of energy storage and the optimal distribution proportion of indoor energy storage. The present application solves the problems of unreasonable equipment configuration, poor economy and weak interaction with the grid of rural light storage direct flexible system, and realizes rural residential energy autonomy, efficient photovoltaic consumption and friendly grid connection.

Description

Technical Field

[0001] This invention belongs to the field of building power distribution and new energy technology, specifically relating to a method and system for configuring the capacity of key equipment for photovoltaic, energy storage, direct current and flexible power transmission in rural residential buildings. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In rural areas, building rooftops offer ample usable space and abundant photovoltaic resources, making them suitable for developing distributed energy. However, photovoltaic power generation is affected by weather and sunshine, resulting in significant intermittency and fluctuations in output. Direct connection to the rural power grid can easily cause voltage fluctuations, line overloads, and other problems, impacting the safe and stable operation of the local power grid.

[0004] The photovoltaic-storage-DC-flexible system, as a technical solution integrating photovoltaics, energy storage, DC power supply, and flexible control, can alleviate grid pressure while improving photovoltaic absorption capacity. However, research on such systems for rural residences is still insufficient, especially in terms of equipment capacity configuration, lacking optimization methods that take into account the electricity consumption characteristics of rural households, photovoltaic installation conditions, and system structural characteristics. This results in existing systems often having poor operating economics, low self-consumption rates of photovoltaic power, disordered grid connection of surplus electricity, and a lack of effective flexible interaction between the system and the grid.

[0005] Furthermore, existing capacity configuration methods are mostly focused on urban buildings, failing to fully consider the significant differences in the timing characteristics of rural residential electricity loads, the large usable rooftop area, and the fact that photovoltaic power generation often far exceeds the electricity needs of individual households. Particularly in energy storage configuration, current technologies often emphasize individual household configurations without systematically studying coordination strategies between household energy storage and village-level centralized energy storage. Therefore, it is difficult to achieve efficient energy self-governance at the village level and orderly, adjustable power interaction with the external power grid. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method and system for configuring the capacity of key photovoltaic-storage-direct-current-flexible energy storage equipment in rural residential buildings. This invention improves the system's economic efficiency, local photovoltaic grid integration rate, and grid-friendly interaction capabilities through coordinated planning of household and village-level energy storage.

[0007] According to some embodiments, the first aspect of the present invention provides a method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible photovoltaic systems in rural residential buildings, employing the following technical solution: A method for configuring the capacity of key photovoltaic, energy storage, direct current, and flexible solar power systems in rural residential buildings, comprising: The annual photovoltaic power generation is calculated based on the layout of rural residential buildings and the area of ​​rooftop photovoltaic installations. Based on the relative ratio of the annual photovoltaic power generation to the annual electricity load, the corresponding photovoltaic-storage-DC-flexible system topology is selected. Based on the annual photovoltaic power generation, the photovoltaic installed capacity is determined with the upper limit of the grid's acceptable access capacity as the constraint boundary. With the goals of maximizing load self-sufficiency and grid connection rate, a capacity optimization configuration model is established. Based on the photovoltaic installed capacity, the capacity optimization configuration model is solved to determine the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

[0008] Furthermore, the calculation of the annual photovoltaic power generation based on the layout of rural residential building complexes and the installable area of ​​rooftop photovoltaic systems includes: Based on the layout of rural residential building complexes, determine the suitable rooftop photovoltaic installation area; The installed capacity per unit area is determined based on the available rooftop photovoltaic installation area and the nominal power of the photovoltaic modules. The theoretical total installed capacity is calculated based on the installed capacity per unit area, the rooftop available area coefficient, and the rooftop photovoltaic installation area. The annual photovoltaic power generation is estimated using the theoretical total installed capacity, local typical annual solar irradiance, and system overall efficiency.

[0009] Furthermore, the corresponding photovoltaic-storage-DC-flexible system topology is selected based on the relative ratio of the annual photovoltaic power generation to the annual electricity load. If the ratio of annual photovoltaic power generation to annual electricity load is greater than 1, then a public photovoltaic topology should be selected. If the ratio of annual photovoltaic power generation to annual electricity load is equal to 1, then a self-consumption-first photovoltaic topology is selected.

[0010] Furthermore, the capacity optimization configuration model, which aims to maximize load self-sufficiency and network access rate, includes: Based on the power drawn from the grid and the power sent to the grid, a two-level objective function is constructed to maximize load self-sufficiency and grid connection rate. Using power balance constraints, energy storage operation constraints, capacity allocation constraints, converter and line capacity constraints, and photovoltaic curtailment constraints as constraints, a capacity optimization configuration model is established based on the constraints and a two-layer objective function.

[0011] Furthermore, based on the power drawn from the grid and the power transmitted to the grid, a two-tier objective function is constructed to maximize load self-sufficiency and grid connection rate, including: The total amount of electricity drawn from the grid is calculated based on the power drawn from the grid per unit time and the total time step. The load self-sufficiency rate is determined based on the total amount of electricity drawn from the grid, and a high-level objective function is constructed to maximize the load self-sufficiency rate. The total photovoltaic power fed into the grid is calculated based on the power supplied to the grid per unit time and the total time step. The grid connection rate is determined based on the total photovoltaic power fed into the grid, and the low-level objective function is constructed by maximizing the grid connection rate. The high-level objective function and the low-level objective function are used as the two-level objective function.

[0012] Furthermore, the determination of the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage based on the photovoltaic installed capacity solution capacity optimization configuration model includes: Based on the relationship between installed photovoltaic capacity and load self-sufficiency rate, the goal is to maximize load self-sufficiency rate. The capacity optimization configuration model is solved using an optimization algorithm to obtain a set of optimal solutions for total energy storage capacity and indoor energy storage allocation ratio. With the goal of maximizing the grid connection rate on the optimal solution set, the capacity optimization configuration model is solved based on the optimization algorithm to obtain the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

[0013] According to some embodiments, the second aspect of the present invention provides a capacity configuration system for key equipment of photovoltaic, energy storage, direct current and flexible photovoltaic systems in rural residential buildings, adopting the following technical solution: A capacity configuration system for key photovoltaic, energy storage, direct current, and flexible solar power equipment in rural residential buildings includes: The topology selection module is configured to calculate the annual photovoltaic power generation based on the layout of rural residential buildings and the rooftop photovoltaic installation area, and select the corresponding photovoltaic-storage-DC-flexible system topology based on the relative ratio of the annual photovoltaic power generation to the annual electricity load. The installed capacity calculation module is configured to determine the photovoltaic installed capacity based on the annual photovoltaic power generation and with the upper limit of the grid's acceptable access capacity as a constraint boundary. The capacity configuration module is configured to establish a capacity optimization configuration model with the goal of maximizing load self-sufficiency and grid connection rate. Based on the photovoltaic installed capacity, the capacity optimization configuration model is solved to determine the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

[0014] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium.

[0015] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible circuitry in rural residential buildings as described in the first embodiment above.

[0016] According to some embodiments, a fourth aspect of the present invention provides a computer device.

[0017] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible power transmission in rural residential buildings as described in the first embodiment above.

[0018] According to some embodiments, a fifth aspect of the present invention provides a computer program product or computer program.

[0019] A computer program product or computer program includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible circuitry in rural residential buildings as described in the first embodiment above.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention achieves a high proportion of energy autonomy at the village level. Through the systematic configuration of photovoltaic capacity in step two, it ensures that the annual power generation reaches or exceeds the annual electricity demand of the entire village. Combined with the coordinated optimization of household-village two-level energy storage in step three, it enables rural residential building complexes to achieve power self-sufficiency for most of the year, significantly reducing dependence on rural power distribution networks and enhancing the independence and resilience of rural energy systems.

[0021] This invention improves the economic efficiency of the entire system lifecycle. Topology adaptation selection avoids equipment idleness or energy loss caused by mismatch between topology structure and resource endowment from the source. The energy storage capacity optimization model, while meeting the self-sufficiency target, reduces redundant investment by reasonably allocating the ratio of indoor and public energy storage, maximizes electricity sales revenue and subsidy utilization, effectively shortens the investment payback period, and improves the overall economic efficiency of the system.

[0022] This invention ensures grid friendliness and renewable energy consumption. By coordinating public and indoor energy storage, it smooths out fluctuations in photovoltaic output, enabling smooth grid connection of photovoltaic power and avoiding voltage overload and line overload caused by the instantaneous injection of large-scale photovoltaic power into rural power grids. At the same time, the flexible regulation capability of energy storage increases the upper limit of the grid's acceptance of distributed photovoltaic power, realizing orderly interaction of "generation-consumption-storage-transmission".

[0023] This invention enhances system flexibility and scalability, making full use of the rapid response capability of residential energy storage and the large-capacity regulation capability of public energy storage to form a hierarchical and adjustable resource pool. This architecture is naturally adapted to advanced application scenarios such as future demand response and virtual power plant aggregation, providing flexible interfaces and expansion space for rural building clusters to integrate into the new power system. Attached Figure Description

[0024] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0025] Figure 1 This is a flowchart illustrating a method for configuring the capacity of key photovoltaic, energy storage, direct current, and flexible solar power equipment in rural residential buildings, as described in an embodiment of the present invention. Figure 2 This is a schematic diagram of a typical topology of a rural residential photovoltaic-storage-flexible system with a self-use priority photovoltaic topology in an embodiment of the present invention; Figure 3 This is a schematic diagram of a typical topology of a rural residential photovoltaic-storage DC-flexible system with a self-use priority photovoltaic topology in an embodiment of the present invention; Figure 4 This is a contour map of the system self-sufficiency rate under different photovoltaic capacity and energy storage allocation ratios in the embodiments of the present invention; Figure 5 This is a contour map of the grid connection rate of the system under different photovoltaic capacity and energy storage allocation ratios in the embodiments of the present invention. Detailed Implementation

[0026] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0027] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0028] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0029] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0030] Example 1 like Figure 1As shown, this embodiment provides a method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible power transmission in rural residential buildings. This embodiment uses the application of this method to a server as an example for illustration. It is understood that this method can also be applied to terminals, and can also be applied to systems including terminals, servers, and other components, and can be implemented through interaction between the terminal and the server. The server can be an independent physical server, a server cluster composed of multiple physical servers, or a distributed system. It can also be a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network servers, cloud communication, middleware services, domain name services, CDN security services, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be directly or indirectly connected via wired or wireless communication, which is not limited herein. In this embodiment, the method includes the following steps: The annual photovoltaic power generation is calculated based on the layout of rural residential buildings and the area of ​​rooftop photovoltaic installations. Based on the relative ratio of the annual photovoltaic power generation to the annual electricity load, the corresponding photovoltaic-storage-DC-flexible system topology is selected. Based on the annual photovoltaic power generation, the photovoltaic installed capacity is determined with the upper limit of the grid's acceptable access capacity as the constraint boundary. With the goals of maximizing load self-sufficiency and grid connection rate, a capacity optimization configuration model is established. Based on the photovoltaic installed capacity, the capacity optimization configuration model is solved to determine the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

[0031] Specifically, the detailed processing steps of the method described in this embodiment include: Step S1: Calculate the annual photovoltaic power generation based on the layout of rural residential buildings and the rooftop photovoltaic installation area. Based on the relative ratio of the annual photovoltaic power generation to the annual electricity load, select the corresponding photovoltaic-storage-DC-flexible system topology. The photovoltaic-storage-DC-flexible system topology includes either a self-use priority photovoltaic topology or a public photovoltaic topology; such as Figure 2 and Figure 3 As shown, a schematic diagram of a typical photovoltaic-storage-DC-flexible system for rural residences with two self-consumption-priority photovoltaic topologies is presented. Step S1.1: Calculate the annual photovoltaic power generation based on the layout of rural residential buildings and the area where rooftop photovoltaics can be installed; Based on the layout of rural residential building complexes and the installable area of ​​rooftop photovoltaic systems, the installed capacity per unit area is calculated, thereby determining the theoretical total installed capacity, including: Based on the layout of rural residential building complexes, determine the suitable rooftop photovoltaic installation area; Specifically, this involves measuring or estimating the total area of ​​suitable rooftop photovoltaic installations throughout the village. (Unit: m²) is the total area after deducting obstacles such as chimneys and skylights; The installed capacity per unit area is determined based on the available rooftop photovoltaic installation area and the nominal power of the photovoltaic modules, as follows: Determine the nominal power based on the selected photovoltaic module model. (Unit: kW / block) and rooftop photovoltaic installation area (Unit: m² / block), calculate the installed capacity per unit area. (Unit: kW / m²), the formula is as follows:

[0032] The theoretical total installed capacity is calculated based on the installed capacity per unit area, the rooftop usable area factor, and the rooftop photovoltaic installation area. :

[0033] in, This is the roof usable area coefficient (excluding unusable parts such as chimneys and skylights).

[0034] The annual photovoltaic power generation is estimated using the theoretical total installed capacity, local typical annual solar irradiance, and system overall efficiency. Power generation estimation: using local typical annual solar irradiance data (Unit: kWh / m²) and overall system efficiency (Including losses from component degradation, dust, inverters, etc.), estimated annual power generation .

[0035]

[0036] in, The irradiance under standard test conditions is typically 1 kW / m². Step S1.2: Based on the relative ratio of the annual photovoltaic power generation to the annual electricity load, select the corresponding photovoltaic-storage-DC-flexible system topology; If the ratio of annual photovoltaic power generation to annual electricity load is greater than 1, then a public photovoltaic topology should be selected. If the ratio of annual photovoltaic power generation to annual electricity load is equal to 1, then a self-consumption-first photovoltaic topology is selected.

[0037] Specifically, when selecting the topology of a photovoltaic-storage-DC-flexible system, the first step is to assess the relative ratio (PE) of photovoltaic power generation to electricity load.

[0038] A PE value greater than 1 (PV power generation >> electricity load): When PV power generation is high (e.g., PE=8), the PV power generation far exceeds the system's own electricity consumption, and the system's primary goal is to output electricity to the grid. In this case, the public PV topology has a higher load fulfillment rate technically, a higher annual net return economically, and a lower system investment. This is because centralized public energy storage management is more efficient and reduces losses from multi-stage conversion within the household.

[0039] A PE value of 1 (PV power generation = electricity load): When PV power generation is comparable to electricity load, the system prioritizes both self-sufficiency and grid connection. In this case, the self-consumption-first PV topology has a slight economic advantage (slightly higher annual net income) and can achieve a higher grid-connected power volume. This is because indoor energy storage prioritizes the consumption of local PV power, reducing converter losses when transmitting power to the village bus (when there is surplus power to the grid, Topology 1 has one more household-to-village DC / DC converter than Topology 2).

[0040] Step S2: Based on the total annual photovoltaic power generation, determine the photovoltaic installed capacity using the upper limit of the grid's acceptable access capacity as a constraint boundary; Obtain the village's annual electricity load .

[0041] When the annual photovoltaic power generation exceeds the annual electricity load, the photovoltaic installed capacity is determined by using the upper limit of the grid's acceptable access capacity as a constraint boundary.

[0042] At this point, it is necessary to verify the capacity of the transformer in the distribution area and the thermal stability limit of the line. The upper limit of the grid's acceptable access capacity is used as the constraint boundary for the final installed capacity to ensure that large-scale photovoltaic output will not cause reverse overload or voltage over-limit of the grid.

[0043] Step S3: With the goal of maximizing load self-sufficiency and grid connection rate, establish a capacity optimization configuration model, solve the capacity optimization configuration model based on photovoltaic installed capacity, and determine the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage. Step S3.1: Based on the power drawn from the grid and the power fed back to the grid, construct a two-layer objective function to maximize load self-sufficiency and grid connection rate, including: The total amount of electricity drawn from the grid is calculated based on the power drawn from the grid per unit time and the total time step. The load self-sufficiency rate is determined based on the total amount of electricity drawn from the grid, and a high-level objective function is constructed to maximize the load self-sufficiency rate.

[0044]

[0045] in, It is the load self-sufficiency rate, which measures the degree to which the system is independent of the power grid, such as... Figure 4 As shown, It is the total electricity drawn from the power grid. yes The power drawn from the power grid at any given time; It is the total time step.

[0046] The total photovoltaic power fed into the grid is calculated based on the power supplied to the grid per unit time and the total time step. The grid connection rate is determined based on the total photovoltaic power fed into the grid, and the low-level objective function is constructed by maximizing the grid connection rate.

[0047]

[0048] in, Grid connection rate is a measure of the effective output of photovoltaic power generation, such as... Figure 5 As shown, This refers to the amount of electricity generated by photovoltaic power generation. This is the total power generation from photovoltaic power. yes The power output constantly supplied to the power grid. It is the total time step; The high-level objective function and the low-level objective function are used as the two-level objective function.

[0049] Step S3.2: Using power balance constraints, energy storage operation constraints, capacity allocation constraints, converter and line capacity constraints, and photovoltaic curtailment constraints as constraints, establish a capacity optimization configuration model that includes indoor energy storage and public energy storage based on the constraints and a two-layer objective function. Among them, power balance constraints:

[0050] in, yes Solar power output at all times yes The discharge power that stores energy at all times. yes Charging power for continuous energy storage yes Load power at any given time yes The total power loss of the system at any given moment; Energy storage operation constraints:

[0051]

[0052]

[0053] in, yes State of charge at time t, It is the minimum state of charge allowed for energy storage. It is the maximum state of charge allowed by energy storage. This is the maximum charging power of the energy storage. It is the maximum discharge power of the energy storage; Capacity allocation constraints:

[0054]

[0055] in, It is the total indoor energy storage capacity. It is the total public energy storage capacity. It refers to the allocation ratio of indoor energy storage. It is the total energy storage capacity; Converter and line capacity constraints:

[0056]

[0057] in, It is the maximum allowable power of the converter (such as AC / DC capacity). yes Real-time line transmission power, This is the maximum allowable transmission power of the line; Solar curtailment constraints:

[0058] in, yes The amount of solar power curtailed at any given time; Step S3.3: Based on the relationship between installed optical capacity and load self-sufficiency rate, first, with the goal of maximizing load self-sufficiency rate, solve the capacity optimization configuration model using an optimization algorithm to obtain a set of optimal solutions for total energy storage capacity and indoor energy storage allocation ratio. Then, with the goal of maximizing grid connection rate, solve the capacity optimization configuration model using an optimization algorithm to obtain the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage. The steps are as follows: 1. First-level optimization (primary optimization): Solution: Maximum (equivalent to) With the minimum as the sole objective, run the optimization model.

[0059] Output: A set of optimal solutions for the total energy storage capacity and the allocation ratio of indoor energy storage. All solutions in this set (i.e., different solutions) , All combinations can achieve the same maximum (For example, 99.5%). Due to non-ideal factors such as converter losses and line losses, there may not be a solution that satisfies this condition. Reaching an absolute 100%, therefore It is at the forefront.

[0060] 2. Second-level optimization (sub-optimization): Problem definition: Given a first-level optimal solution (i.e., ...) Under the premise that the maximum possible value has been reached, Optimization is performed with maximizing as the sole objective. ; Solve for: In the optimal solution set In the middle, looking for what can make The largest configuration option.

[0061] Output: The final optimal solution The optimal solution includes the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

[0062] In this embodiment, the two objectives (self-sufficiency and grid connection) are in competition when resources are limited (such as energy storage capacity and line capacity). Simply weighting and summing the two objectives would introduce subjective weighting and make it difficult to clearly define priorities. For rural energy systems, energy self-sufficiency is the primary and rigid objective; therefore, a hierarchical optimization approach is adopted to clearly define priorities. The processing method in this embodiment ensures that, under any circumstances, the system first achieves the maximum possible energy self-sufficiency, and then, on this basis, connects as much surplus, clean photovoltaic power to the grid as possible to generate revenue. For example, to achieve a 100% self-sufficiency rate (… When all energy storage is placed at a public end, the required total capacity is minimized; appropriately allocating a portion of energy storage to indoor areas ( ), can be kept At the same time, slightly increase the internet access rate ( This is because it reduces household-to-village conversion losses. This provides a precise quantitative basis for engineering design and investment decisions.

[0063] The fundamental value of rural photovoltaic systems lies in achieving energy self-sufficiency and contributing surplus electricity. Therefore, in terms of optimization, self-sufficiency takes precedence over grid connection. At the same time, optimizing the allocation of indoor / public energy storage can balance the relationship between low local consumption losses (an advantage of indoor energy storage) and strong complementarity in global dispatch (an advantage of public energy storage).

[0064] The relationship between photovoltaic installed capacity and load self-sufficiency rate is as follows: the larger the photovoltaic installed capacity and the smaller the load self-sufficiency rate, the larger the allocated energy storage capacity. This means that if less photovoltaic power is used, more energy storage should be configured. Conversely, the smaller the photovoltaic installed capacity and the larger the load self-sufficiency rate, the smaller the allocated energy storage capacity. This means that if more photovoltaic power is used, less energy storage should be configured.

[0065] In the optimal total energy storage capacity, the rated capacity of each DC converter and bidirectional AC / DC converter is determined based on the maximum output of photovoltaic power, the energy storage charging and discharging power, the peak load and the grid interaction requirements, to ensure the safe and stable operation of the system.

[0066] The converter capacity is determined by the principle of meeting the power flow requirements under extreme operating conditions. There is no single fixed formula, but it can be calculated using the following process: 1. Bidirectional AC / DC converter (grid-connected point converter) capacity SAC / DC Consider the following scenarios: a. Maximum power consumption: The power supplied by the grid during peak load periods at night or when there is no light.

[0067] b. Maximum power fed back: The power that needs to be fed back to the grid when the photovoltaic output is at its maximum and the load is at its minimum.

[0068] c. System regulation requirements: The bidirectional power regulation range that may be required when participating in grid frequency regulation or demand response.

[0069] Calculation formula:

[0070] in, It is the rated capacity of the bidirectional AC / DC converter. For safety factors (e.g., values ​​of 1.1 to 1.2), and These are the maximum charging power and maximum discharging power of energy storage, which need to be obtained through system time-series simulation or load curve analysis.

[0071] 2. DC / DC converter capacity Photovoltaic DC / DC converter: Capacity ≥ Maximum DC output power of the photovoltaic array .

[0072] Energy storage DC / DC converter: Capacity ≥ Maximum charging / discharging power of stored energy .

[0073] Household-village bidirectional DC / DC converter (only required for self-use priority topologies): The capacity must meet the maximum interactive power between a single household and the village-level bus. This depends on the extreme mismatch between the household's photovoltaic, load, and energy storage, and needs to be determined through household-level simulation, as shown in the following formula:

[0074] in, It is the capacity of the household-to-village bidirectional DC / DC converter. This is the maximum interactive power of the household-to-village busbar. This is the maximum interactive power from the village-level busbar to the household; By configuring energy storage and flexible load regulation, peak shaving and valley filling can be achieved, significantly reducing [the impact of load fluctuations]. The required SAC / DC capacity (reduced by approximately 29.1% in the reported cases) is a significant economic advantage of the PV-Storage DC-Flexible system.

[0075] After obtaining the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage, a distributed control strategy is formulated based on the DC bus voltage signal to coordinate the power of photovoltaic, energy storage, load and charging pile, so as to realize the autonomous operation of the system, the maximum absorption of photovoltaic power, and flexible interaction with the grid.

[0076] Distributed control strategy is a type of autonomous and coordinated control without a central controller, based on DC bus voltage signal. Its core idea is that the level of DC bus voltage represents the power surplus or deficit of the system, and each device autonomously adjusts its own power according to the bus voltage detected locally.

[0077] 1. Control Logic (PU Characteristic Curve): AC / DC on the grid side: As a voltage regulator, it compares the actual power exchange between the building and the grid with the expected value. If there is a deviation, it fine-tunes the DC bus voltage setting value. If the power demand is too high, it reduces the voltage; if the power demand is insufficient, it increases the voltage.

[0078] Photovoltaic DC / DC: It operates in MPPT (maximum power output) mode within the normal voltage range. When the voltage is too high (indicating over-generation), it enters power curtailment mode to actively curtail the solar power to prevent the voltage from continuing to rise.

[0079] Energy storage DC / DC: It operates in voltage droop control mode, setting a voltage reference band (dead zone); it charges when the voltage is higher than the band, and the higher the voltage, the faster it charges; it discharges when the voltage is lower than the band, and the lower the voltage, the faster it discharges.

[0080] Adjustable / disposable loads (such as air conditioners): Increase power when voltage rises and decrease power when voltage drops. Disconnect directly when voltage falls below critical limits.

[0081] Charging station: Similar to a load, the charging power is adjusted according to the voltage.

[0082] 2. Work process: When photovoltaic power generation exceeds electricity consumption, the system experiences a power surplus, causing the bus voltage to rise. At this time, energy storage begins charging, loads such as air conditioners automatically increase their power, and charging piles accelerate charging to absorb the excess photovoltaic power. If the voltage rises to its limit, the photovoltaic system begins to be curtailed.

[0083] When photovoltaic power generation is low and electricity consumption is high, the system experiences power shortages, leading to a drop in bus voltage. At this time, energy storage begins to discharge, adjustable loads automatically reduce power, and charging piles slow down charging, collectively reducing the demand for electricity from the grid. Simultaneously, the grid's AC / DC converters draw power from the grid to maintain voltage.

[0084] Advantages: No complex communication network required, fast response speed, high reliability, easy expansion, and very suitable for widely distributed and numerous terminal devices in buildings.

[0085] Taking a village in northern China consisting of 18 households as an example, the village's annual electricity consumption is approximately 55,000 kWh. There is ample capacity available for rooftop photovoltaic installations, and the installed capacity is configured according to the principle of installing as much as possible, ensuring that its annual power generation is approximately eight times the load. A photovoltaic topology prioritizing self-consumption is adopted.

[0086] 1. Photovoltaic configuration: Based on the roof area and local irradiance data, the total installed photovoltaic capacity of the whole village is determined to be 2 MW, with an annual power generation of approximately 2.4 million kWh.

[0087] 2. Optimized Energy Storage Configuration: An optimization model is established to minimize grid draw and maximize grid connection. Calculations show that to achieve 100% load self-sufficiency throughout the year, the required total energy storage capacity is approximately 78% of the village's average daily load. The optimized allocation ratio is: approximately 70% of the energy storage capacity is configured within individual households, and 30% is configured on the village-level public bus. This configuration balances system self-sufficiency and grid connection rates while reducing converter losses.

[0088] 3. Converter configuration: Based on the peak photovoltaic power, peak load and energy storage charging and discharging power, the capacity of the village-level bidirectional AC / DC converter is determined to be 500 kW, and the capacity of the bidirectional DC / DC converter for each household is 20 kW.

[0089] 4. Economic Analysis: The initial investment for the system is approximately RMB 8.187 million, with annual electricity sales revenue of approximately RMB 1.006 million and an investment payback period of approximately 8.5 years. If electric agricultural machinery is considered as equivalent energy storage, battery investment can be further reduced, and the payback period shortened.

[0090] With the above configuration, this rural residential photovoltaic-storage-DC-flexible system can achieve full-year electricity self-sufficiency and smoothly and orderly connect surplus photovoltaic power to the grid, becoming a grid-friendly distributed energy producer.

[0091] Example 2 This embodiment provides a capacity configuration system for key equipment in rural residential buildings, including: The topology selection module is configured to calculate the annual photovoltaic power generation based on the layout of rural residential buildings and the rooftop photovoltaic installation area, and select the corresponding photovoltaic-storage-DC-flexible system topology based on the relative ratio of the annual photovoltaic power generation to the annual electricity load. The installed capacity calculation module is configured to determine the photovoltaic installed capacity based on the annual photovoltaic power generation and with the upper limit of the grid's acceptable access capacity as a constraint boundary. The capacity configuration module is configured to establish a capacity optimization configuration model with the goal of maximizing load self-sufficiency and grid connection rate. Based on the photovoltaic installed capacity, the capacity optimization configuration model is solved to determine the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

[0092] The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1 above. It should be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0093] The descriptions of each embodiment in the above embodiments have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0094] The proposed system can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and the division of modules described above is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed.

[0095] Example 3 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible photovoltaic systems in rural residential buildings as described in Embodiment 1 above.

[0096] Example 4 This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible photovoltaic systems in rural residential buildings as described in Embodiment 1 above.

[0097] Example 5 This embodiment provides a computer program product or computer program, including computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current and flexible circuitry in rural residential buildings as described in Embodiment 1 above.

[0098] Those skilled in the art will understand that embodiments of the present invention can provide methods, systems, or computer program products. Therefore, the present invention can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0099] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0102] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0103] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for configuring the capacity of key photovoltaic, energy storage, direct current, and flexible solar power equipment in rural residential buildings, characterized in that, include: The annual photovoltaic power generation is calculated based on the layout of rural residential buildings and the area of ​​rooftop photovoltaic installations. Based on the relative ratio of the annual photovoltaic power generation to the annual electricity load, the corresponding photovoltaic-storage-DC-flexible system topology is selected. Based on the annual photovoltaic power generation, the photovoltaic installed capacity is determined with the upper limit of the grid's acceptable access capacity as the constraint boundary. With the goals of maximizing load self-sufficiency and grid connection rate, a capacity optimization configuration model is established. Based on the photovoltaic installed capacity, the capacity optimization configuration model is solved to determine the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

2. The method for configuring the capacity of key photovoltaic, energy storage, direct current, and flexible solar power equipment in rural residential buildings as described in claim 1, characterized in that, The calculation of annual photovoltaic power generation based on the layout of rural residential building complexes and the installable area of ​​rooftop photovoltaic systems includes: Based on the layout of rural residential building complexes, determine the suitable rooftop photovoltaic installation area; The installed capacity per unit area is determined based on the available rooftop photovoltaic installation area and the nominal power of the photovoltaic modules. The theoretical total installed capacity is calculated based on the installed capacity per unit area, the rooftop available area coefficient, and the rooftop photovoltaic installation area. The annual photovoltaic power generation is estimated using the theoretical total installed capacity, local typical annual solar irradiance, and system overall efficiency.

3. The method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible solar power in rural residential buildings as described in claim 1, characterized in that, The corresponding photovoltaic-storage-DC-flexible system topology is selected based on the relative ratio of the annual photovoltaic power generation to the annual electricity load. If the ratio of annual photovoltaic power generation to annual electricity load is greater than 1, then a public photovoltaic topology should be selected. If the ratio of annual photovoltaic power generation to annual electricity load is equal to 1, then a self-consumption-first photovoltaic topology is selected.

4. The method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible photovoltaic systems in rural residential buildings as described in claim 1, characterized in that, The capacity optimization configuration model, aimed at maximizing load self-sufficiency and maximizing network access rate, includes: Based on the power drawn from the grid and the power sent to the grid, a two-level objective function is constructed to maximize load self-sufficiency and grid connection rate. Using power balance constraints, energy storage operation constraints, capacity allocation constraints, converter and line capacity constraints, and photovoltaic curtailment constraints as constraints, a capacity optimization configuration model is established based on the constraints and a two-layer objective function.

5. The method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible photovoltaic systems in rural residential buildings as described in claim 4, characterized in that, Based on the power drawn from and fed back to the grid, a two-tier objective function is constructed to maximize load self-sufficiency and grid connection rate, including: The total amount of electricity drawn from the grid is calculated based on the power drawn from the grid per unit time and the total time step. The load self-sufficiency rate is determined based on the total amount of electricity drawn from the grid, and a high-level objective function is constructed to maximize the load self-sufficiency rate. The total photovoltaic power fed into the grid is calculated based on the power supplied to the grid per unit time and the total time step. The grid connection rate is determined based on the total photovoltaic power fed into the grid, and the low-level objective function is constructed by maximizing the grid connection rate. The high-level objective function and the low-level objective function are used as the two-level objective function.

6. The method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible photovoltaic systems in rural residential buildings as described in claim 1, characterized in that, The capacity optimization configuration model based on photovoltaic installed capacity determines the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage, including: Based on the relationship between installed optical capacity and load self-sufficiency rate, the goal is to maximize load self-sufficiency rate. The capacity optimization configuration model is solved using an optimization algorithm to obtain a set of optimal solutions for total energy storage capacity and indoor energy storage allocation ratio. With the goal of maximizing the grid connection rate on the optimal solution set, the capacity optimization configuration model is solved based on the optimization algorithm to obtain the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

7. A capacity configuration system for key equipment in rural residential buildings, characterized in that: include: The topology selection module is configured to calculate the annual photovoltaic power generation based on the layout of rural residential buildings and the rooftop photovoltaic installation area, and select the corresponding photovoltaic-storage-DC-flexible system topology based on the relative ratio of the annual photovoltaic power generation to the annual electricity load. The installed capacity calculation module is configured to determine the photovoltaic installed capacity based on the annual photovoltaic power generation and with the upper limit of the grid's acceptable access capacity as a constraint boundary. The capacity configuration module is configured to establish a capacity optimization configuration model with the goal of maximizing load self-sufficiency and grid connection rate. Based on the photovoltaic installed capacity, the capacity optimization configuration model is solved to determine the optimal total energy storage capacity and the optimal allocation ratio of indoor energy storage.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current and flexible photovoltaic systems in rural residential buildings as described in any one of claims 1-6.

9. A computer device, 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 program, it implements the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current and flexible photovoltaic systems in rural residential buildings as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps in the method for configuring the capacity of key equipment for photovoltaic, energy storage, direct current, and flexible photovoltaic systems in rural residential buildings as described in any one of claims 1-6.

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