A novel method for optimal configuration of energy storage in rural distribution network

Abstract

The present application relates to a kind of new rural distribution network energy storage optimization configuration method, comprising: with the total cost of distribution network construction and operation to build objective function;With new energy consumption rate and penetration, the longest off-grid time and interactive power to build constraint function;Optimization algorithm is used to solve energy storage capacity optimal solution;With the grid structure and operating characteristics of distribution network, the reasonable position node and capacity of energy storage power station are optimized and configured, to achieve hierarchical, zonal configuration;The operating power curve under four scenarios of non-heating season typical day under grid connection, heating season typical day under grid connection, non-heating season typical day under off-grid mode and heating season typical day under off-grid mode is measured and calculated, and power balance analysis is carried out;The power purchase power is the interactive power of distribution network and large power grid.The present application can effectively improve the consumption capacity of the proposed distributed photovoltaic body, and is helpful to the safe and stable operation of power system.

Description

Technical Field

[0001] This invention relates to the field of energy storage technology, and specifically to a novel method for optimizing the configuration of energy storage in rural power distribution networks. Background Technology

[0002] With the development of distributed renewable energy, its impact on the power grid is gradually becoming apparent. On the one hand, the intermittent and fluctuating output of renewable energy is detrimental to the safe and stable operation of the power grid. On the other hand, the widespread adoption of distributed renewable energy generation and the continuous increase in its grid-connected capacity pose significant challenges to renewable energy consumption and power grid peak and frequency regulation. Energy storage technology plays a crucial role in achieving the safe and stable operation of new power systems and has become an important means to smooth the output of distributed renewable energy generation, improve renewable energy consumption, and enhance the economic efficiency of the distribution network. Summary of the Invention

[0003] The purpose of this invention is to provide a new method for optimizing the energy storage configuration of rural distribution networks, which can effectively improve the absorption capacity of distributed photovoltaic power and contribute to the safe and stable operation of the power system.

[0004] The technical solution of the present invention:

[0005] A novel method for optimizing the allocation of energy storage in rural power distribution networks includes the following steps: constructing an objective function based on the total construction and operation cost of the power distribution network; constructing a constraint function based on the renewable energy absorption rate and penetration rate, the longest off-grid time, and the interactive power volume; solving for the optimal energy storage capacity using an optimization algorithm; optimizing the allocation of energy storage power stations with appropriate locations and capacities based on the grid structure and operating characteristics of the power distribution network, achieving layered and zoned allocation; calculating the operating power curves for four scenarios: typical days in the non-heating season under grid connection, typical days in the heating season under grid connection, typical days in the non-heating season under off-grid mode, and typical days in the heating season under off-grid mode. The operating power curves include photovoltaic output, load power, energy storage power, purchased power, and energy storage SOC curves, and performing power balance analysis; the purchased power refers to the interactive power between the power distribution network and the main power grid.

[0006] Preferably, the planned energy storage configuration includes the following conditions: the energy storage has an adjustable SOC range of 5%-95% during operation; a genetic algorithm is used to solve the planning model; the planning period is calculated as 20 years to obtain the optimal solution for energy storage capacity configuration; the allocation of energy storage battery devices is based on the on-site open space distribution, the actual capacity requirements of black start and sub-microgrid operation, and the configuration is carried out in a hierarchical and zoned manner while meeting the overall functional requirements of the distribution network.

[0007] Preferably, the energy storage configuration planning and design is based on the total cost of construction and operation of the distribution network as the objective function to determine the optimal capacity configuration scheme of the energy storage system in the distribution network. Specifically, it includes the following steps: (1) establishing the objective function; (2) setting constraints; (3) optimizing variables; and (4) optimizing algorithms.

[0008] Preferably, establishing the objective function includes the following steps:

[0009] 1) Equipment purchase and installation investment costs

[0010] The investment cost of purchasing and installing energy storage equipment is related to its capacity, and the calculation formula is as follows:

[0011] C pi =c es,pi S es (1)

[0012] In the formula, c es,pi It is the purchase and installation cost per unit capacity of energy storage; S es It refers to the energy storage capacity;

[0013] 2) Equipment operation and maintenance costs

[0014] The operation and maintenance costs of energy storage equipment are related to the planned lifespan and capacity, and the calculation formula is as follows:

[0015] C om =c es,om S es T py (2)

[0016] In the formula, c es,om This refers to the annual operating and maintenance cost per unit capacity of energy storage equipment; T py It refers to the planning period;

[0017] 3) Replacement cost of energy storage equipment

[0018] During the planning period, aging of energy storage equipment leads to a reduction in actual usable capacity, failing to achieve the expected results, necessitating the replacement of energy storage equipment. The formula for calculating the replacement cost of energy storage equipment is as follows:

[0019] C r =c es,r S es N es,r (3)

[0020] In the formula, c es,r It is the replacement cost per unit capacity of energy storage equipment; N es,r This refers to the number of times energy storage equipment will be replaced during the planning period;

[0021] 4) Electricity purchase cost

[0022] Electricity purchase cost refers to the cost incurred by the distribution network to purchase electricity from other distribution networks when the electricity generated by wind, solar, and energy storage cannot meet the load demand. The calculation formula is...

[0023]

[0024] In the formula, c p It is the cost of purchasing electricity per unit of electricity; P load,t It is the power consumption of the load during time period t; and These are the maximum power generation capacities of wind turbines and photovoltaic systems during time period t, respectively. and These represent the energy storage discharge and charging power during time period t, respectively; Δt is the time step. T represents the amount of electricity that the distribution network needs to purchase from the grid during time period t; y It is the total number of time periods in a year;

[0025] The total cost of power distribution network construction and operation is the sum of equipment purchase and installation investment costs, equipment operation and maintenance costs, energy storage equipment replacement costs, and electricity purchase costs, i.e.:

[0026] C = C pi +C om +C r +C p (5).

[0027] Preferably, setting constraints includes the following steps:

[0028] 1) Constraints on renewable energy consumption rate

[0029]

[0030]

[0031] 1-W aban / W res ≥α ar (8)

[0032] In the formula, W aban and W res These are the total amount of wind and solar power curtailed in a year and the maximum generating capacity of wind and solar power; α ar It is the lower limit of the renewable energy consumption rate;

[0033] 2) Constraints on the penetration rate of new energy sources

[0034]

[0035] (W res -W aban ) / W load ≥α pr (10)

[0036] In the formula, W load It is the total annual electricity load; P r This is the lower limit of the penetration rate of new energy sources;

[0037] 3) Longest offline time

[0038] Based on input load and resource data, conduct year-round operation simulations and create the longest off-grid operation record on target lines with relatively concentrated new energy and energy storage resources;

[0039] 4) Electricity exchanged with external power grids

[0040] By rationally configuring energy storage capacity and improving charging and discharging operation strategies, the annual interaction power between the target distribution network and the external power grid is constrained to not exceed 50% of the annual power consumption of the microgrid load, thereby maximizing the regional energy self-balance.

[0041] Preferably, the optimization variable is the energy storage capacity S. es As an optimization variable, its optimal value is obtained through an optimization algorithm; the optimization variable is constrained by investment and site factors, and its value range is:

[0042]

[0043] In the formula, This is the upper limit of the capacity of energy storage devices;

[0044] For capacity planning design problems, the genetic algorithm is selected for solution.

[0045] Preferred operating curves for typical days of the distribution network during the non-heating season under grid-connected mode: plotted from actual data.

[0046] During the day, some of the energy generated by photovoltaics is stored, and at night, it continuously supplies power to the load. In this scenario, the distribution network has the ability to operate independently and will feed power back to the external power grid when the energy storage SOC is high in the afternoon and the photovoltaic power output is greater than the load.

[0047] The preferred daily operating curve of the distribution network under grid-connected mode during the heating season: plotted from actual data.

[0048] During the heating season, the heat pump load is relatively large, and the energy provided by photovoltaics cannot meet the total load demand. In this case, the distribution network needs to purchase electricity to ensure the normal operation of the heat pump load. The energy storage is in a high standby power state, reserving sufficient power for off-grid operation of the microgrid in the event of external grid failure, and charging the energy storage when the load is low at night.

[0049] Grid-connected mode: Charging during off-peak electricity prices ensures the energy storage system has a high reserve capacity; when the main transformer or line transmission power is detected to be greater than the set upper limit threshold, the energy storage system discharges to ensure that the main transformer / line is not overloaded; during the heating season, the lower limit of the energy storage system's SOC is set to a higher level to ensure reliable power supply to the load when the external power grid fails.

[0050] Preferred operating curves for typical days of the distribution network in off-grid mode during the non-heating season: plotted from actual data.

[0051] Because the overall load of the station is relatively small, it can achieve a certain period of time for the entire station to operate off-grid. That is, in the morning, as the photovoltaic output gradually increases, it can charge the energy storage while meeting the load demand. After that, when the photovoltaic output is insufficient, the energy storage will meet the load demand. At this time, because the line load is low, the overall off-grid capability is strong, and it can meet the off-grid operation for a certain number of consecutive days during the non-heating season.

[0052] Preferred, typical daily operating curves of the distribution network under off-grid mode during the heating season: plotted from actual data.

[0053] During the heating season, the heat pump load is relatively large, and the energy provided by photovoltaics generally cannot meet the total load demand. During the heating season, in off-grid mode, energy storage starts to supply power to the load from a high standby state to support the operation of the distribution network.

[0054] In this situation, the distribution network needs to achieve energy balance during off-grid operation by using the group control of heat pumps, based on the expected power outage time, wind and solar resources, energy storage SOC and load information.

[0055] During off-grid operation, the adjustable heat pump load is reduced by group dispatch and control and rotating heating to minimize the impact of power outages on users, ensuring the continuous and stable operation of the distribution network and improving the electricity experience of villagers. After a fault, the energy storage is charged while meeting the power constraints of the feeder to restore a high standby power state, so as to ensure the energy storage SOC value for the next off-grid operation.

[0056] Off-grid mode: Energy storage serves as the main power source to support the stability of system voltage and frequency. The energy storage SOC needs to be controlled within a reasonable range to prevent overcharging and over-discharging from affecting the lifespan of the energy storage battery.

[0057] The beneficial effects of this invention are:

[0058] This invention optimizes the configuration of energy storage power stations with appropriate locations and capacities, effectively addressing the challenges of long repair times and difficulties in large-area power outages due to single-power source failures, as well as the electricity supply problem caused by insufficient external power transmission capacity after clean heating. It avoids the need for high-investment modifications to external power lines and effectively enhances the absorption capacity of the proposed distributed photovoltaic power station, contributing to the safe and stable operation of the power system.

[0059] Compared to traditional power grid upgrades, this project can reduce power grid infrastructure investment by at least several million yuan while achieving the same improvement in power supply reliability. It enables full awareness of equipment status, automatic fault monitoring, and rapid handling, improving equipment operation and maintenance levels and saving tens of thousands of yuan in labor maintenance costs per district annually.

[0060] Through photovoltaic, wind turbine and supporting coal-to-electricity projects, more than 5 million kilowatt-hours of electricity can be replaced annually. Based on the calculation that 1 kilowatt-hour of thermal power generation requires burning 0.4 kg of standard coal and emitting 0.997 kg of carbon dioxide, more than 2,000 tons of coal can be reduced annually, and more than 5,000 tons of carbon dioxide emissions can be reduced. Attached Figure Description

[0061] Figure 1 This is a schematic diagram of the power distribution network connection in Baiyangdian, according to an embodiment of the present invention.

[0062] Figure 2 This is a typical daily power curve diagram for grid connection during the non-heating season, according to an embodiment of the present invention.

[0063] Figure 3 This is a typical daily SOC curve of energy storage during the non-heating season in an embodiment of the present invention.

[0064] Figure 4 This is a typical daily power curve for grid-connected heating during an embodiment of the present invention.

[0065] Figure 5 This is a typical daily SOC curve of energy storage during the grid-connected heating season according to an embodiment of the present invention.

[0066] Figure 6 This is a typical daily power curve of the Guolikou substation during the non-heating season, as shown in this embodiment of the invention.

[0067] Figure 7 This is a typical daily energy storage SOC curve of the Guolikou off-grid station during the non-heating season, according to an embodiment of the present invention.

[0068] Figure 8 This is a typical daily power curve of the Guolikou 521 line during the off-grid non-heating season, according to an embodiment of the present invention.

[0069] Figure 9 This is a typical daily energy storage SOC curve of the Guolikou 521 line off-grid during the non-heating season, according to an embodiment of the present invention.

[0070] Figure 10 This is a typical daily power curve for off-grid heating during an embodiment of the present invention.

[0071] Figure 11 This is a typical daily SOC curve of off-grid heating season according to an embodiment of the present invention. Detailed Implementation

[0072] 1. Optimized Energy Storage Configuration

[0073] The 35kV Guolikou Substation is located in the eastern part of Baiyangdian Lake, with a transformer capacity of 2×10MVA and two main transformers operating in parallel. Guolikou Substation has only one 35kV incoming line, with its upstream power source being the 110kV Punan Substation. It is a single-power supply line with a secondary T-connection, and the power supply line path is 8.44km long, of which 4.5km is located within the Baiyangdian Lake area. The only incoming power line was originally the Xin'an-Guolikou 35kV line, but was later switched to the Punan-Guolikou 35kV line. Any line fault, maintenance, or relocation will cause a complete power outage at Guolikou Substation. See [link / details]. Figure 1 ;

[0074] The energy storage optimization configuration aims to enable continuous off-grid operation for 4 hours in the core scenic area of ​​Baiyangdian (historically, the average repair time for line faults in the Baiyangdian area is 4 hours), possess off-grid black start capability for the 35kV Guolikou substation, and achieve seamless on-grid / off-grid switching with the external power grid. Based on this, it will ensure long-term off-grid operation of the Guolikou 521 line as much as possible.

[0075] 1.1 Planning Model

[0076] The planning model uses the total cost of distribution network construction and operation as the objective function to determine the optimal capacity configuration scheme of energy storage systems within the distribution network.

[0077] (1) Objective function

[0078] 1) Equipment purchase and installation investment costs

[0079] The investment cost of purchasing and installing energy storage equipment is related to its capacity, and the calculation formula is as follows:

[0080] C pi =c es,pi S es (1)

[0081] In the formula, c es,pi It is the purchase and installation cost per unit capacity of energy storage; S es It refers to the energy storage capacity.

[0082] 2) Equipment operation and maintenance costs

[0083] The operation and maintenance costs of energy storage equipment are related to the planned lifespan and capacity, and the calculation formula is as follows:

[0084] C om =c es,om S es T py (2)

[0085] In the formula, c es,om This refers to the annual operating and maintenance cost per unit capacity of energy storage equipment; T py It refers to the planning period.

[0086] 3) Replacement cost of energy storage equipment

[0087] During the planning period, aging of energy storage equipment leads to a reduction in actual usable capacity, failing to achieve the expected results, necessitating the replacement of the energy storage equipment. The formula for calculating the replacement cost of energy storage equipment is as follows:

[0088] C r =c es,r S es N es,r (3)

[0089] In the formula, c es,r It is the replacement cost per unit capacity of energy storage equipment; N es,r This refers to the number of times energy storage equipment will be replaced during the planning period.

[0090] 4) Electricity purchase cost

[0091] Electricity purchase cost refers to the cost incurred by the distribution network to purchase electricity from other distribution networks when the electricity generated by wind, solar, and energy storage cannot meet the load demand. The calculation formula is...

[0092]

[0093] In the formula, c p It is the cost of purchasing electricity per unit of electricity; P load,t It is the power consumption of the load during time period t; and These are the maximum power generation capacities of wind turbines and photovoltaic systems during time period t, respectively. and These represent the energy storage discharge and charging power during time period t, respectively; Δt is the time step, taken as 1 hour. T represents the amount of electricity that the distribution network needs to purchase from the grid during time period t; y It is the total number of time periods in a year.

[0094] The total cost of power distribution network construction and operation is the sum of equipment purchase and installation investment costs, equipment operation and maintenance costs, energy storage equipment replacement costs, and electricity purchase costs, i.e.:

[0095] C = C pi +C om +C r +C p (5)

[0096] (2) Constraints

[0097] 1) Constraints on renewable energy consumption rate

[0098]

[0099]

[0100] 1-W aban / W res ≥α ar (8)

[0101] In the formula, W aban and W res These are the total amount of wind and solar power curtailed in a year and the maximum generating capacity of wind and solar power; α ar This is the lower limit of the renewable energy consumption rate, which is taken as 0.8 here.

[0102] 2) Constraints on the penetration rate of new energy sources

[0103]

[0104] (W res -W aban ) / W load ≥α pr (10)

[0105] In the formula, W load It is the total annual electricity load; P r This is the lower limit of the penetration rate of new energy sources, which is taken as 0.2 here.

[0106] 3) Longest offline time

[0107] Based on input load and resource data, we will conduct year-round operation simulations. During the heating season, the Guolikou substation will achieve 4 hours of off-grid operation. At the same time, we will strive to create the longest off-grid operation record on the 10kV Guolikou 521 line, where new energy and energy storage resources are relatively concentrated.

[0108] 4) Electricity exchanged with external power grids

[0109] By rationally configuring energy storage capacity and improving charging and discharging operation strategies, the annual interaction power between the Baiyangdian power distribution network and the external power grid is constrained to not exceed 50% of the annual power consumption of the microgrid load, thereby maximizing the regional energy self-balance.

[0110] (3) Optimize variables

[0111] Energy storage capacity S es As an optimization variable, its optimal value is obtained through an optimization algorithm. The optimization variable is constrained by factors such as investment and location, and therefore has a certain range of values.

[0112]

[0113] In the formula, This is the upper limit of the capacity of energy storage devices.

[0114] (4) Optimization Algorithm

[0115] For the above capacity planning and design problem, a genetic algorithm (GA) is selected for solution.

[0116] 1.2 Planning Scheme

[0117] The energy storage system has an adjustable SOC range of 5%-95% during operation, and the electricity purchase price from the distribution network is settled according to the rural power grid price in Hebei Province (0.52 yuan / kWh). The unit price of energy storage is calculated at 2500 yuan / kWh. A genetic algorithm is used to solve the planning model, with a planning period of 20 years, and the optimal solution for energy storage capacity configuration is found to be 11.3 MWh. The model solution results are shown in Table 1.

[0118] The allocation of the 11.3MWh energy storage battery device is mainly based on the on-site open space distribution, the actual capacity requirements of black start and sub-microgrid operation, and the hierarchical and zoned configuration, while meeting the overall functional requirements of the Baiyangdian power distribution network:

[0119] (1) Guolikou Energy Storage Station

[0120] According to the on-site survey results, the open area on the east side of the 35kV Guolikou substation is relatively large. In order to meet the black start requirements of the 35kV substation, a grid-type energy storage device of 6000kWh / 6000kW will be installed here. Although it is slightly smaller than the maximum load of Guolikou substation (6.52MW), it can meet the black start requirements of Guolikou substation most of the time and will be connected to Guolikou substation via a 10kV dedicated line.

[0121] (2) Wangjiazai Energy Storage Cluster

[0122] To ensure uninterrupted power supply to Wangjiazai during the emergency repair period (4 hours) of the external power lines in the heating season, and in conjunction with the group dispatch and control strategy, the energy storage capacity requirement of Wangjiazai Village is 3300kWh, distributed in four locations: the auxiliary village (1500kWh / 1500kW), the wharf square (100kWh / 100kW), the school (1000kWh / 500kW), and the farm (700kWh / 500kW), all of which are existing facilities.

[0123] Among them, the 1500kWh energy storage in Fucun is the main energy storage for the Wangjiazai microgrid, which mainly provides voltage and frequency support for the microgrid and can achieve black start. It is connected to nearby lines at a voltage level of 10kV. The energy storage at the dock square is connected to the dock square distribution transformer (630kVA) at a voltage level of 0.4kV. This distribution transformer carries low-voltage loads of the village committee and mutual aid association, and is of high importance. The energy storage at the school and the energy storage at the farm are connected to the surrounding distribution transformers at a voltage level of 0.4kV, which improves the power supply reliability of important loads such as Wangjiazai Primary School and farmhouses with heavy tourist reception tasks.

[0124] (3) Baiyangdian Cultural Park Energy Storage Station

[0125] The remaining 2000kWh / 2000kW energy storage device will be deployed in the open space north of the Baiyangdian Cultural Park scenic area and connected to the 10kV Guolikou 521 line via a dedicated transformer.

[0126] Table 1. Model Solution Results

[0127]

[0128] 2. Power Balance Analysis

[0129] Based on the planned energy storage and new energy configuration capacity, the power curves for four scenarios—typical days in the non-heating season and typical days in the heating season—are calculated under grid-connected / off-grid modes. These curves include photovoltaic output, load power, energy storage power, and purchased power (i.e., the interaction power between the distribution network and the main power grid) and the energy storage SOC curve.

[0130] 2.1 Typical daily operating curves of distribution network under grid-connected mode during non-heating season

[0131] Typical daily operating curves of the Baiyangdian power distribution network under grid-connected mode are as follows: Figures 2 to 3 As shown. During the non-heating season, the load is relatively small, and the energy provided by photovoltaics can generally meet the load demand. Energy storage plays a role in peak shaving and valley filling, storing some of the energy generated by photovoltaics during the day and continuously supplying power to the load at night. In this scenario, the distribution network has a strong independent operating capability and will feed back a certain amount of power to the external power grid in the afternoon when the energy storage SOC is high and the photovoltaic power generation output is greater than the load.

[0132] 2.2 Typical daily operating curves of the distribution network during the heating season under grid-connected mode

[0133] Typical daily operating curves of grid-connected distribution networks during the heating season are as follows: Figure 4 and Figure 5 As shown, during the heating season, the heat pump load is relatively large, and the energy provided by photovoltaic power generally cannot meet the total load demand. In this case, the distribution network needs to purchase more electricity to ensure the normal operation of the heat pump load, and the energy storage is in a high standby state. This is mainly to reserve sufficient electricity for off-grid operation of the microgrid in the event of an external grid failure, and to charge the energy storage when the load is low at night.

[0134] Grid-connected mode: Charging occurs during off-peak electricity periods to ensure the energy storage system has a high reserve capacity. When the power transmission of the 35kV main transformer or the 521 line exceeds the set threshold, the energy storage system discharges to prevent overload of the main transformer / line. During the heating season, the lower limit of the energy storage system's State of Charge (SOC) is set at a higher level to ensure reliable power supply to the load in the event of an external power grid failure.

[0135] 2.3 Typical daily operating curves of distribution network under off-grid mode during non-heating season

[0136] The typical daily operating curve of the Guolikou 35kV substation during the non-heating season under off-grid mode is as follows: Figure 6 and Figure 7 As shown, due to the relatively small load of the entire station, it can achieve a maximum of nearly 16 hours of off-grid operation. That is, after 9:00 AM, as the photovoltaic output gradually increases, it can charge the energy storage while meeting the load demand. After that, when the photovoltaic output is insufficient, the energy storage will meet the load demand. Figure 8 and Figure 9 The typical daily operating curve of the Guolikou 521 line during the non-heating season is shown in the diagram, based on the planned energy storage configuration. At this time, due to the low load on the Guolikou 521 line, its off-grid capacity is strong, allowing for continuous off-grid operation for 7 days during the non-heating season.

[0137] 2.4 Typical daily operating curves of the distribution network during the heating season under off-grid mode

[0138] Typical daily operating curves of off-grid power distribution networks during the heating season are as follows: Figure 10 and Figure 11 As shown, the Baiyangdian power distribution network experiences relatively high heat pump loads during the heating season, and the energy provided by photovoltaic power generally cannot meet the total load demand. During the heating season, in off-grid mode, energy storage begins to supply power to the load from a high standby state, supporting the operation of the power distribution network.

[0139] In this scenario, the distribution network needs to achieve energy balance during off-grid operation through group control and dispatch of heat pumps, based on anticipated outage times, wind and solar resources, energy storage SOC, and load information. For the entire 35kV Guolikou substation power supply area, group control and dispatch of the 1378 coal-to-electricity air source heat pump loads in Wangjiazai Village is expected to reduce the regional load by 1.04MW, enabling continuous off-grid operation for more than 4 hours during the heating season. Analysis of historical outage data from the Guolikou substation shows that the average duration of each outage is approximately 4 hours, and the off-grid capacity meets the requirements for covering the average outage duration.

[0140] As can be seen from the graph, the simulated power outage time is from 10:00 to 15:00, which is 5 hours, longer than the average power outage time.

[0141] During off-grid operation, by using group control and rotating heating, the adjustable heat pump load is reduced while minimizing the impact of power outages on users, ensuring the continuous and stable operation of the distribution network and improving the electricity experience for villagers. After a fault, the energy storage is charged while meeting the power constraints of the feeder, restoring a high standby power state to ensure the SOC value of the energy storage for the next off-grid operation.

[0142] Off-grid mode: Energy storage serves as the main power source to support the stability of system voltage and frequency. The energy storage SOC needs to be controlled within a reasonable range to prevent overcharging and over-discharging from affecting the lifespan of the energy storage battery.

[0143] Taking Baiyangdian in Xiong'an New Area as an example, this invention addresses the challenges of long repair times and difficulties in large-area power outages due to single-power-source failures at the Baiyangdian 35kV Guolikou substation, as well as the insufficient power transmission capacity of external lines after clean heating in Wangjiazai Village. This is achieved through optimized configuration of energy storage power stations with appropriate locations and capacities, providing a more economical and feasible solution to the problems of insufficient power transmission capacity in Wangjiazai Village after clean heating. The invention avoids the need for expensive external power line modifications, fulfills the requirements of the Baiyangdian ecological environment governance and protection plan, and effectively enhances the absorption capacity of the proposed distributed photovoltaic power generation system, contributing to the safe and stable operation of the power system.

[0144] Compared to traditional power grid upgrades, this project can reduce power grid infrastructure investment by at least several million yuan while achieving the same improvement in power supply reliability. It enables full awareness of equipment status, automatic fault monitoring, and rapid handling, improving equipment operation and maintenance levels and saving tens of thousands of yuan in labor maintenance costs per district annually.

[0145] Through photovoltaic, wind turbine and supporting coal-to-electricity projects, more than 5 million kilowatt-hours of electricity can be replaced annually. Based on the calculation that 1 kilowatt-hour of thermal power generation requires burning 0.4 kg of standard coal and emitting 0.997 kg of carbon dioxide, more than 2,000 tons of coal can be reduced annually, and more than 5,000 tons of carbon dioxide emissions can be reduced.

[0146] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A novel method for optimizing the configuration of energy storage in rural power distribution networks, characterized in that, The objective function is constructed using the total cost of distribution network construction and operation; the constraint function is constructed using the renewable energy absorption rate and penetration rate, the longest off-grid time, and the interactive power; the optimal solution for energy storage capacity is solved using optimization algorithms; energy storage power stations with reasonable location nodes and capacities are optimized and configured in combination with the grid structure and operating characteristics of the distribution network, achieving layered and zoned configuration; the operating power curves are calculated for four scenarios: typical days in the non-heating season under grid connection, typical days in the heating season under grid connection, typical days in the non-heating season under off-grid mode, and typical days in the heating season under off-grid mode. The operating power curves include photovoltaic output, load power, energy storage power, purchased power, and energy storage SOC curves, and power balance analysis is performed; the purchased power refers to the interactive power between the distribution network and the main grid. Typical daily operating curves of the distribution network during the heating season under off-grid mode: During the heating season, the heat pump load is relatively high, and the energy provided by photovoltaics cannot meet the total load demand. During the heating season, in off-grid mode, energy storage starts to supply power to the load from a high standby state to support the operation of the distribution network. In this scenario, the distribution network achieves energy balance during off-grid operation by using group control and regulation of heat pumps, based on the expected outage time, wind and solar resources, energy storage SOC, and load information. During off-grid operation, the adjustable heat pump load is reduced by group dispatching and control and rotating heating to minimize the impact of power outages on users, ensuring the continuous and stable operation of the distribution network and improving the electricity experience of villagers. After a fault, the energy storage is charged while meeting the power constraints of the feeder, restoring a high standby power state and ensuring the energy storage SOC value for the next off-grid operation. Off-grid mode: Energy storage serves as the main power source to support stable system voltage and frequency, and the energy storage SOC is controlled within a reasonable range to prevent overcharging and over-discharging from affecting the lifespan of the energy storage battery.

2. The novel rural power distribution network energy storage optimization configuration method according to claim 1, characterized in that, The energy storage plan includes the following conditions: the energy storage's state of charge (SOC) is adjustable within a range of 5%-95% during operation; a genetic algorithm is used to solve the planning model; the planning period is calculated as 20 years to obtain the optimal solution for energy storage capacity configuration; the allocation of energy storage battery devices is based on the actual capacity requirements of the site's open space distribution, black start, and sub-microgrid operation, and is carried out in a hierarchical and zoned manner while meeting the overall functional requirements of the distribution network.

3. The novel rural power distribution network energy storage optimization configuration method according to claim 1, characterized in that, Energy storage configuration capacity planning and design is based on the total cost of construction and operation of the distribution network as the objective function to determine the optimal capacity configuration scheme of the energy storage system in the distribution network. Specifically, it includes the following steps: (1) establishing the objective function; (2) setting constraints; (3) optimizing variables; and (4) optimizing algorithms.

4. The novel rural power distribution network energy storage optimization configuration method according to claim 3, characterized in that, Establishing the objective function includes the following steps: 1) Equipment purchase and installation investment costs The investment cost of purchasing and installing energy storage equipment is related to its capacity, and the calculation formula is as follows: （1） In the formula, It is the purchase and installation cost per unit capacity of energy storage; It refers to the energy storage capacity; 2) Equipment operation and maintenance costs The operation and maintenance costs of energy storage equipment are related to the planned lifespan and capacity, and the calculation formula is as follows: （2） In the formula, This refers to the annual operating and maintenance cost per unit capacity of energy storage equipment. T py It refers to the planning period; 3) Replacement cost of energy storage equipment During the planning period, aging of energy storage equipment leads to a reduction in actual usable capacity, failing to achieve the expected results, necessitating the replacement of energy storage equipment. The formula for calculating the replacement cost of energy storage equipment is as follows: （3） In the formula, c es,r It is the replacement cost per unit capacity of energy storage equipment; N es,r This refers to the number of times energy storage equipment will be replaced during the planning period; 4) Electricity purchase cost Electricity purchase cost refers to the cost incurred by the distribution network to purchase electricity from other distribution networks when the electricity generated by wind, solar, and energy storage cannot meet the load demand. The calculation formula is... （4） In the formula, c p It is the cost of purchasing electricity per unit of electricity; P load,t It is the power consumption of the load during time period t; These are the maximum power generation capacities of wind turbines and photovoltaic systems during time period t, respectively. These are the energy storage discharge and charging power during time period t, respectively. It is the time step; This represents the amount of electricity that the distribution network needs to purchase from the grid during time period t. T y It is the total number of time periods in a year; The total cost of power distribution network construction and operation is the sum of equipment purchase and installation investment costs, equipment operation and maintenance costs, energy storage equipment replacement costs, and electricity purchase costs, i.e.: （5）。 5. A novel method for optimizing the configuration of energy storage in rural power distribution networks according to claim 4, characterized in that, Setting constraints includes the following steps: 1) Constraints on renewable energy absorption rate In the formula, W aban and W res These are the total amount of wind and solar power curtailed in a year and the maximum generating capacity of wind and solar power, respectively. It is the lower limit of the renewable energy consumption rate; 2) Constraints on the penetration rate of new energy sources In the formula, W load It is the total annual electricity consumption. This is the lower limit of the penetration rate of new energy sources; 3) Longest offline time Based on input load and resource data, conduct year-round operation simulations and create the longest off-grid operation record on target lines with relatively concentrated new energy and energy storage resources; 4) Electricity exchanged with external power grids By rationally configuring energy storage capacity and improving charging and discharging operation strategies, the annual interaction power between the target distribution network and the external power grid is constrained to not exceed 50% of the annual power consumption of the microgrid load, thereby maximizing the regional energy self-balance.

6. A novel method for optimizing the configuration of energy storage in rural power distribution networks according to claim 5, characterized in that, The optimization variable is the energy storage capacity. S es As an optimization variable, its optimal value is obtained through an optimization algorithm; the optimization variable is constrained by investment and site factors, and its value range is: （11） In the formula, This is the upper limit of the capacity of energy storage devices; For capacity planning design problems, the genetic algorithm is selected for solution.

7. A novel method for optimizing the configuration of energy storage in rural power distribution networks according to claim 1, characterized in that, Typical daily operating curves of the distribution network under grid-connected mode during the non-heating season: During the day, some of the energy generated by photovoltaics is stored, and at night, it continuously supplies power to the load. In this scenario, the distribution network has the ability to operate independently and will feed power back to the external power grid when the energy storage SOC is high in the afternoon and the photovoltaic power output is greater than the load.

8. A novel method for optimizing the configuration of energy storage in rural power distribution networks according to claim 1, characterized in that, Typical daily operating curves of the distribution network during the heating season under grid-connected mode: During the heating season, the heat pump load is relatively large, and the energy provided by photovoltaics cannot meet the total load demand. In this case, the distribution network needs to purchase electricity to ensure the normal operation of the heat pump load. The energy storage is in a high standby power state, reserving sufficient power for off-grid operation of the microgrid in the event of external grid failure, and charging the energy storage when the load is low at night. Grid-connected mode: Charging during off-peak electricity prices ensures the energy storage system has a high reserve capacity; when the main transformer or line transmission power is detected to be greater than the set threshold limit, the energy storage system discharges to ensure that the main transformer / line is not overloaded; during the heating season, the lower limit of the energy storage system's SOC is set to a high level to ensure reliable power supply to the load when the external power grid fails.

9. A novel method for optimizing the configuration of energy storage in rural power distribution networks according to claim 1, characterized in that, Typical daily operating curves of the distribution network in off-grid mode during the non-heating season: Because the overall load of the station is relatively small, it can achieve a certain period of time for the entire station to operate off-grid. That is, in the morning, as the photovoltaic output gradually increases, it can charge the energy storage while meeting the load demand. After that, when the photovoltaic output is insufficient, the energy storage will meet the load demand. At this time, because the line load is low, the overall off-grid capability is strong, and it can meet the off-grid operation for a certain number of consecutive days during the non-heating season.

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