Urban power grid flexible partition energy scheduling method based on time sequence production simulation

Abstract

The invention discloses an urban power grid flexible partition energy scheduling method based on time sequence production simulation, and belongs to the technical field of power scheduling, and the method comprises the steps: carrying out the time sequence production simulation of the unit output of each independent region according to the system output data of each independent region in an urban power grid, and constructing a region power state model; modeling is carried out on the electric vehicle charging behavior, the energy storage load condition, the ice storage system load condition and the power utilization side power utilization load in the independent area, and a regional energy dispatching curve is obtained; performing load optimization on the regional power state model according to the regional energy scheduling curve; and based on the electric power surplus condition and the electric power gap condition of each region, performing partitioned electric power dispatching on the urban power grid through an electric power balance model. Therefore, by implementing the application, the problem that energy balance of each subarea of the urban power grid is difficult to realize and the resource utilization rate is difficult to improve due to insufficient flexibility of energy allocation of the urban power grid in the prior art can be solved.

Description

Technical Field

[0001] This application belongs to the field of power dispatching technology, specifically relating to a flexible zoned energy dispatching method and system for urban power grids based on time-series production simulation. Background Technology

[0002] The "flexible" in flexible zoning refers to its adaptability and controllability. Therefore, flexible zoning has the advantages of dynamically adjusting the power exchange capacity between different areas of the power grid and adjusting the electrical boundaries of each zone. Flexible DC interconnection can realize the exchange of power between multiple zones. Urban power grids that have been connected to a high proportion of renewable energy can achieve multi-point power supply from multiple power sources by adopting inter-regional flexible DC interconnection, thereby enhancing energy mutual assistance between zones.

[0003] Time-series production simulation (TSMS) considers the output of each generating unit on an hourly basis and calculates the absorption value, making it an important tool for optimizing the long-term operation of urban power grids. Based on load / renewable energy time-series curves, TMS treats renewable energy output, system load, and conventional unit output as a sequence changing over time. It considers factors such as system power balance, system reserves, peak shaving, unit ramp-up, unit start-up and shutdown, and grid transmission capacity, performing time-period simulations to build models that describe the power balance in different time periods, providing data support for optimal power resource scheduling. However, current TMS technologies mainly target independent regions and rarely address energy sharing between flexible zones. Summary of the Invention

[0004] This application proposes a flexible zoned energy dispatching method for urban power grids based on time-series production simulation, which can solve the problem that the energy allocation flexibility of urban power grids is insufficient in the existing technology, making it difficult to achieve energy balance and improve resource utilization in different zones of the urban power grid.

[0005] The first aspect of this application provides a flexible zoned energy dispatching method for urban power grids based on time-series production simulation, the method comprising:

[0006] Based on the system output data of each independent area in the urban power grid, time-series production simulation is performed on the unit output of the independent area to construct a regional power state model that characterizes the power balance of the independent area at each time point.

[0007] By modeling the electric vehicle charging behavior, energy storage load, ice storage cooling system load, and electricity demand load within the independent area, a regional energy dispatch curve is obtained; wherein, the regional energy dispatch curve includes the electric vehicle load curve, the energy storage load curve, the ice storage cooling system load curve, and the electricity demand response curve.

[0008] Based on the regional energy dispatch curve, the regional power state model is optimized for load to obtain the power balance model of each independent region.

[0009] Based on the power surplus and power deficit of each independent region, the power balance model is used to carry out zoned power dispatch within the urban power grid through flexible DC interconnection channels.

[0010] The above scheme first conducts time-series production simulations of unit output in individual areas within the urban power grid. The simulated output results are used to assess the power balance status of independent areas at different times, generating a regional power state model that characterizes whether the region's power is balanced, in surplus, or in deficit during a given period. By introducing other facilities within the independent areas, load optimization is performed during periods of power imbalance in the regional power state model, enabling independent areas to achieve power balance autonomously. Furthermore, the external support and absorption capacity of each area's power is statistically analyzed. Power that independent areas cannot absorb independently is transmitted to other areas in urgent need of power through flexible DC interconnection channels, achieving energy mutual assistance between different areas of the urban power grid. This improves the overall operational stability and energy utilization rate of the power grid system, systematically solves the problem of power surplus and deficit mismatch between regions, and significantly enhances the regional coordination capability of the power grid.

[0011] In one possible implementation of the first aspect, based on the system output data of each independent area in the urban power grid, a time-series production simulation is performed on the unit output of the independent area to construct a regional power state model characterizing the power balance of the independent area at each time point, specifically as follows:

[0012] Collect system output data of generator sets and energy storage devices in the independent area to construct the regional net load curve and the regional adjustable output range;

[0013] Based on the regional net load curve and the regional adjustable output range, the supporting output transmitted from the independent region to other regions and the absorbable output obtained from other regions are calculated to obtain the power supply and demand regulation capability of the independent region.

[0014] Based on the preset unit maintenance plan, the power output of the units in the independent area is simulated in a time sequence using the power supply and demand regulation capability, thereby constructing a regional power status model.

[0015] The aforementioned scheme first conducts individual power balance forecasts for each independent area within the urban power grid. By simulating the power output of each independent area, and considering the adjustable output range of generating units and changes in the net load of the area, it assesses the power supply and demand regulation capabilities of each independent area, providing accurate data support for subsequent flexible DC interconnection between areas. Furthermore, it incorporates generating unit maintenance plans to further correct for the load conditions of each independent area, achieving accurate forecasts of the power balance in each area.

[0016] In one possible implementation of the first aspect, based on a preset unit maintenance plan, the power output of the units in the independent area is simulated in a time-series manner using the power supply and demand regulation capability to construct a regional power state model, specifically as follows:

[0017] Calculate the supported output of the generator set under start-up conditions, and take the period containing the maximum average value of the supported output as the planned maintenance period;

[0018] The generator sets are sorted according to their serial numbers during the planned maintenance period to obtain the generator set maintenance plan.

[0019] The power supply and demand regulation capability is optimized according to the unit maintenance plan. Based on the optimized power supply and demand regulation capability and the load demand of the independent area, the output sequence and magnitude of the generator units are scheduled from the perspectives of power balance and power imbalance, respectively. The power imbalance includes power surplus and power shortage.

[0020] The scheduling results of each generator unit are statistically analyzed to construct the regional power status model.

[0021] In one possible implementation of the first aspect, a regional energy dispatch curve is obtained by modeling the electric vehicle charging behavior, energy storage load, ice storage cooling system load, and electricity consumption load within the independent area, specifically as follows:

[0022] Based on the vehicle flow characteristics and battery state of charge of electric vehicles, the total charging power of all electric vehicles in the independent area is predicted, and an electric vehicle load curve is constructed.

[0023] Based on the charging and discharging periods of the energy storage system, the annual charging and discharging power of the independent area is aggregated to construct an energy storage load curve;

[0024] The operating load of the ice storage system is calculated based on its usage characteristics, and a load curve for the ice storage system is constructed.

[0025] Based on the energy consumption demand and operating period of the electrical equipment, the power load on the power consumption side of the independent area is modeled, and the power demand response curve on the power consumption side is constructed.

[0026] The aforementioned scheme addresses imbalances within independent regions by incorporating electric vehicles, energy storage systems, ice storage systems, and electricity demand to readjust the region's total load. By leveraging the load curves of these facilities, it achieves efficient synergy among different resources within the independent region, laying the foundation for energy support in that region.

[0027] In one possible implementation of the first aspect, the total charging power of all electric vehicles in the independent area is predicted based on the vehicle flow characteristics and battery state of charge of the electric vehicles, and an electric vehicle load curve is constructed, specifically as follows:

[0028] A spatial transfer probability matrix is ​​constructed by predicting the migration probability of electric vehicles between different regions in different time periods.

[0029] Based on the spatial transition probability matrix, analyze the charging and discharging start time, destination, first departure point, driving time, driving mileage, and parking time of electric vehicles to construct vehicle flow characteristics;

[0030] The remaining battery power of electric vehicles after the end of their journey is predicted based on vehicle flow characteristics, and the charging characteristics of electric vehicles are determined based on the prediction results; wherein, the charging characteristics include charging power, battery initial state of charge, and charging start time.

[0031] The total charging power of all electric vehicles in the independent area is calculated based on the charging characteristics to construct the electric vehicle load curve.

[0032] The above scheme introduces load regulation for electric vehicles within an independent region to address imbalances. By predicting the charging demand of electric vehicles within the region, the impact of the charging power provided by all electric vehicles on the total regional load is assessed, providing data support for achieving regional power balance through adjusting charging power.

[0033] In one possible implementation of the first aspect, the operating load of the ice storage system is calculated based on the characteristics of the ice storage system, and a load curve of the ice storage system is constructed, specifically as follows:

[0034] The system capacity, maximum charging power, maximum cooling power, and initial state of charge are extracted from the usage characteristics of the ice storage system to construct the system usage characteristics;

[0035] Based on the system usage characteristics and the preset cooling energy efficiency ratio, calculate the storage time of the ice storage system from the start of cooling to the cooling capacity reaching the system capacity.

[0036] Based on the cold storage duration and the system usage characteristics, the operating load of the ice storage system is calculated, and a load curve for the ice storage system is constructed.

[0037] In one possible implementation of the first aspect, the electricity load on the electricity consumption side of the independent area is modeled based on the energy consumption demand and operating period of the electrical equipment, and an electricity demand response curve is constructed, specifically as follows:

[0038] Based on the energy consumption demand and operating time, the flexibility of power consumption time and energy storage characteristics of electrical equipment are evaluated, and the equipment power consumption characteristics of the electrical equipment are constructed.

[0039] Based on the power consumption characteristics of the equipment, the power load on the power consumption side is divided into uncontrollable load, transferable load, and interruptible load;

[0040] Based on the power consumption and power range of electrical equipment, uncontrollable loads, transferable loads and interruptible loads are modeled respectively to obtain the demand response curves on the power consumption side.

[0041] The above solution addresses the different characteristics of electrical equipment by predicting the electricity load on the electricity consumption side in multiple scenarios, thereby achieving accurate modeling of the electricity demand on the electricity consumption side and improving the accuracy of load adjustment within the region.

[0042] In one possible implementation of the first aspect, load optimization is performed on the regional power state model based on the regional energy dispatch curve to obtain the power balance model for each of the independent regions, specifically as follows:

[0043] A three-level optimization strategy is constructed, with the electric vehicle load curve as the first level, the energy storage load curve as the second level, and the ice storage cooling system load curve and the electricity demand response curve as the third level.

[0044] For the periods of power imbalance in the regional power state model, the total system load of the independent region is scheduled according to the order of the three-level optimization strategy to obtain the power balance model.

[0045] The above scheme introduces different types of resources for regional energy dispatch, achieving efficient coordination among various regulatory resources. By combining electric vehicles, ice storage systems, energy storage systems, and demand response in an orderly manner, the regulatory potential of various flexible resources is maximized while ensuring system safety.

[0046] In one possible implementation of the first aspect, based on the power surplus and power deficit of each independent region, regional power dispatch is performed within the urban power grid via a flexible DC interconnection channel using the power balance model, specifically as follows:

[0047] By statistically analyzing the power imbalance in each independent region, we can identify power deficit zones that require power support and power surplus zones that need power consumption.

[0048] The power output to be supported in the power deficit zone and the power output to be absorbed in the power surplus zone are obtained from the power balance model, respectively.

[0049] Based on the magnitude of the required output and the required absorption output, power dispatch is performed on the power shortage zone and the power surplus zone through a flexible DC interconnection channel.

[0050] The above scheme, while completing the individual energy regulation of a region, further regulates the power imbalance between zones. By transmitting power between power deficit zones and power surplus zones, it achieves coordinated optimization from power balance between zones to inter-zone mutual assistance, effectively solving the problem of insufficient regulation capacity caused by traditional methods that only consider a single region, and significantly improving the overall operational reliability of the system.

[0051] In one possible implementation of the first aspect, power dispatch is performed on the power deficit zone and the power surplus zone through a flexible DC interconnection channel based on the magnitude of the power output to be supported and the power output to be absorbed, specifically as follows:

[0052] Based on the nearest distance between each independent region, the search direction of the power surplus zone within the urban power grid is determined;

[0053] Based on the search direction, the power surplus partition is traversed through the power deficit partition, and the transmission line path that can meet the power demand is determined by comparing the size of the power to be supported and the power to be absorbed.

[0054] By combining all the aforementioned transmission line paths, power dispatch is carried out in the power deficit zones and the power surplus zones to achieve power balance in the urban power grid.

[0055] The above scheme realizes flexible DC support between regions based on the spatial distance between regions, solves the problem of mismatch between regional power surplus and deficit, and significantly enhances the regional coordination capability of the power grid. Attached Figure Description

[0056] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0057] Figure 1This is a schematic diagram illustrating the specific process of a flexible zoned energy dispatching method for urban power grids based on time-series production simulation, provided in one embodiment of this application. Detailed Implementation

[0058] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0059] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0060] First Embodiment

[0061] Urban power grids suffer from problems such as uncoordinated power source and load distribution, insufficient local power supply capacity, and a lack of reactive power and voltage regulation methods. Therefore, enhancing energy mutual assistance between different zones and solving the power supply and demand balance problem of urban power grids is currently a major challenge. This application's embodiments prioritize the power balance within independent zones, and then, by statistically analyzing the cross-regional power support and absorption needs of each zone, perform power regulation within the entire urban power grid system to achieve energy mutual assistance between zones and improve the overall energy utilization rate of the urban power grid.

[0062] like Figure 1 As shown, to address the problem of insufficient flexibility in energy allocation in existing urban power grids, which makes it difficult to achieve energy balance and improve resource utilization across different urban power grid zones, the first embodiment of this application provides a detailed flowchart of a flexible zoned energy dispatching method for urban power grids based on time-series production simulation. This embodiment of the flexible zoned energy dispatching method for urban power grids based on time-series production simulation includes steps S1 to S4, detailed below:

[0063] Step S1: Based on the system output data of each independent area in the urban power grid, perform time-series production simulation on the unit output of the independent area to construct a regional power state model that characterizes the power balance of the independent area at each time point.

[0064] In urban power grids, an independent region generally refers to a unit capable of achieving internal power self-balancing, and its division is mainly based on the physical structure of the power grid. In the embodiments of this application, power balance within the independent region is first achieved by constructing various models, and then energy mutual assistance for the entire urban power grid is achieved by scheduling power between independent regions, further improving the operational stability and energy utilization rate of the power grid system.

[0065] First, for an independent region, the output of various generator sets and energy storage devices in the region is simulated. By constructing the region's net load curve and the region's adjustable output range, the load fluctuation of the independent region in each time period is determined.

[0066] The net load curve P of the region Pure The calculation formula is as follows:

[0067] P Pure =P l -P New -P Nl -P West -P Small_hydro ;

[0068] In the formula, P1 is the total regional load, P New P contributes to new energy sources in independent regions N1 For the nuclear power generation capacity of an independent region, P West To independently receive power transmitted from the West to the East, P Small_hydro The total output of local small hydroelectric power stations in an independent region.

[0069] The adjustable power output range for the aforementioned region is primarily based on the installed capacity of adjustable power sources within the region, calculated by determining the range between the minimum technical output and the total installed capacity. The adjustable power sources include coal-fired power generating units, gas-fired power generating units, and the power supply capacity of 500kV substations. Coal-fired units can be further divided into conventional coal-fired units and combined heat and power (CHP) coal-fired units, while gas-fired units include start-stop peak-shaving units and CHP gas-fired units.

[0070] In addition, to simplify the model, the power supply capacity of a 500kV substation can be equivalently regarded as a gas turbine unit with start-stop peak-shaving characteristics.

[0071] The specific expressions for the minimum technical output and total installed capacity are as follows:

[0072]

[0073] In the formula, These are the sum of the minimum technical output and installed capacity of adjustable power sources, respectively; the minimum technical output of conventional coal-fired power plants, cogeneration coal-fired power plants, cogeneration gas-fired power plants, start-up and shutdown gas-fired power plants, and 500kV substation power supplies are the minimum technical outputs of the corresponding types of operational units, respectively. sum; These represent the maximum output of the corresponding type of generating unit, and the installed capacity of the corresponding type of operating generating unit. sum; N Coal_Con N Coal_Ther N Gas_Con NGas_Ther N Supply These represent the number of units of the corresponding type. s represents the operating status of unit i, where 0 indicates unit i is stopped and 1 indicates unit i is running.

[0074] The power balance status of an independent region can be categorized into three scenarios: First, the region may achieve power self-balancing but still has room for adjustment, allowing for power exchange with external regions by increasing or decreasing power generation; second, it may experience a power surplus, possessing the capability to provide external power support; and third, it may experience a power deficit, requiring the receipt of power from external sources. Therefore, to improve the assessment accuracy of the power supply and demand regulation capability of an independent region and the prediction accuracy of its power balance status, this application embodiment also considers the supportable output that the independent region can transmit to other regions and the absorbable output that it can obtain from other regions.

[0075] To quantify the power supply and demand regulation capacity of an independent region, the supported output and the absorbable output are calculated. The supported output is obtained based on the difference between the maximum power supply capacity of the independent region and the actual demand, and the specific calculation formula is as follows:

[0076]

[0077] P Backup (t)=P l (t)*0.02;

[0078] In the formula, P Supprot For the supported output force, P Backup (t) is for spinning reserve, calculated as 2% of the total regional load.

[0079] If the supported output is positive, it indicates that the independent area can provide power support to other areas.

[0080] The absorbable output depends on the difference between the current net load of the area and the minimum technical output of the adjustable power supply, and the specific calculation formula is as follows:

[0081]

[0082] In the formula, P Consumption The output force that can be absorbed.

[0083] Furthermore, this application embodiment also considers the load impact caused by unit maintenance. In this application embodiment, a planned maintenance period of 30 days is scheduled annually for conventional coal-fired power units, cogeneration coal-fired power units, and cogeneration gas-fired power units within an independent region. The supported output of the generator unit under operating conditions is calculated, and the 30 consecutive days with the strongest supported output are identified as the planned maintenance period. Here, "strongest" refers to the maximum average supported output.

[0084] During the planned maintenance period, the generator sets are sorted according to their serial numbers for maintenance until all units have completed maintenance.

[0085] Then, based on the unit maintenance plan, the supported output and the absorbed output are recalculated to obtain the adjusted power supply and demand regulation capacity. Next, local output simulation is performed under three scenarios based on the power supply and demand status of an independent region. These scenarios are divided into power balance, power surplus, and power deficit, with the latter two representing power imbalance.

[0086] When the absorbable output is less than 0, it indicates that the independent region is in a state of power surplus, and the local power generation capacity exceeds the current load demand. Therefore, all adjustable power sources are set to operate at the minimum technical output, and the surplus power is transmitted through the flexible DC interconnection channel. At this time, the output expression of the adjustable power source is:

[0087]

[0088] In the formula, P Unit This is to determine the final output of various generating units after adjustments.

[0089] When the supported output is less than 0, it indicates that the independent area is experiencing a power shortage, and the local power generation capacity cannot meet the current load demand. Therefore, all adjustable power sources are set to operate at maximum output, and power is obtained from the outside through a flexible DC interconnection channel. At this time, the output expression of the adjustable power source is:

[0090]

[0091] When both the supported output and the absorbable output are greater than 0, it indicates that the independent region is in a state of power balance, and the local power generation capacity can meet the current load demand. In this case, the power dispatch is carried out in the following order: coal-fired power plants take priority over combined heat and power (CHP) units, CHP units take priority over 500kV substations, and 500kV substations take priority over gas-fired power plants for peak shaving. Specifically, the actual output of each unit is set according to its minimum technical output. After setting, the remaining power to be allocated is calculated, and then the remaining power is incrementally allocated according to the set unit priorities until the total load demand of the region is met. If the total load demand is already met at a certain type of unit, the subsequent units are set to operate at minimum output.

[0092] Finally, the output scheduling results of each generator unit under the three conditions are statistically analyzed, and the regional power state model of the independent region is used to characterize the power balance of the independent region at each time.

[0093] The specific expression for the regional power state model ΔP is as follows:

[0094] ΔP(t)=P Pure (t)+P Backup (t)-P Coal_Con (t)+P Coal_Ther (t)+P Gas_Ther (t)+P Gas_Start (t)+P Supply (t);

[0095] In the formula, P Pure For the area's net load, P Backup (t) is for rotational standby, P Coal_Con P Gas_Ther P Gas_Start P represents the output of the coal-fired power unit, the combined heat and power (CHP) coal-fired power unit, the combined heat and power (CHP) gas-fired power unit, and the 500kV substation, respectively. Supprot The power output that can be supported.

[0096] When ΔP equals 0, it indicates that the independent region is in a state of power balance at that moment; when ΔP is greater than 0, it indicates that the independent region is in a state of power surplus at that moment; when ΔP is less than 0, it indicates that the independent region is in a state of power deficit at that moment.

[0097] Step S2: By modeling the electric vehicle charging behavior, energy storage load, ice storage cooling system load, and electricity consumption load within the independent area, a regional energy dispatch curve is obtained.

[0098] In order to achieve power balance in an independent area, this application embodiment introduces various adjustable resources to adjust the load during periods of power imbalance in the power state model of the area, thereby minimizing the total power imbalance in the independent area by adjusting the load of various adjustable resources.

[0099] The embodiments of this application mainly model the electric vehicle charging behavior, energy storage load, ice storage cooling system load, and electricity consumption load on the consumer side within an independent area, and construct their load fluctuation curves at different time periods to provide data support for regional load regulation.

[0100] The vehicle flow characteristics of electric vehicles are extracted by the spatial transition probability matrix. The vehicle flow characteristics are combined with the battery state of charge to predict the total charging power of all electric vehicles in an independent area and construct the electric vehicle load curve.

[0101] The spatial transition probability matrix is ​​used to characterize the travel and charging patterns of electric vehicles, reflecting the migration patterns of vehicles between residential, work, commercial, and leisure areas at different times during weekdays and weekends. Assuming an independent area contains R sub-regions, the day is divided into k time periods, each corresponding to a specific spatial transition probability matrix Q(k) to describe the vehicle flow characteristics between sub-regions within that time period. The specific expression is as follows:

[0102]

[0103] In the formula, Let be the migration probability of an electric vehicle traveling from region i to region j at time k.

[0104] Based on the spatial transition probability matrix, the charging and discharging start time, destination, first departure location, driving time, driving mileage, and parking time of electric vehicles are analyzed, and the corresponding vehicle driving features are extracted.

[0105] The charging / discharging start time of the electric vehicle is extracted from the spatial transition probability matrix using a normal distribution, thus obtaining the probability density function f of the charging / discharging start time. det (t s ):

[0106]

[0107] In the formula, t s The charging / discharging start time is [the specified time]. The standard deviation of the charging / discharging start time is given. The average value at the start of the charging / discharging process.

[0108] Except for the initial trip, the starting point of each subsequent trip is the destination of the previous trip, thus forming a continuous travel chain. Therefore, the initial trip location is randomly selected from region i to region j using a uniform random sampling method.

[0109] The destination of the journey is determined based on the initial departure time using the spatial transition probability matrix.

[0110] Furthermore, a log-normal distribution is used to distinguish between regions, weekdays, and rest days. The driving time, driving mileage, and parking time of electric vehicles are extracted from the spatial transition probability matrix, using the following specific formulas:

[0111]

[0112] In the formula, t tr Let μ and σ be the objects to be extracted, and let μ and σ be the expected value and standard deviation of the objects to be extracted. The values ​​are different for weekdays and rest days.

[0113] After each leg of the electric vehicle's journey, the remaining battery power is predicted based on the acquired vehicle driving characteristics. If the remaining battery power meets the condition (E×SOC)... i -d i If (×k)≤0.4E, then charging is determined. Where E is the battery capacity in kilowatt-hours; d i Let k be the distance of the i-th trip, in km; k is the power consumption of the electric vehicle per kilometer.

[0114] Charging can be done in two ways: fast charging and slow charging. Choose fast charging if the following formula is met; otherwise, choose slow charging:

[0115] (E×SOC i -d i ×k+P s ×t c ≥0.2E;

[0116] Based on the above charging characteristics, the battery state of charge of the electric vehicle at the start of its (i+1)th trip is determined by the following expression:

[0117]

[0118] In the formula, η is the charging efficiency, which is generally taken as 0.9; P s This indicates whether it's a slow or fast charging power.

[0119] Based on charging power, battery initial state of charge (including battery state of charge before and after charging), charging start time, battery capacity, and the start and end times of disordered charging, the total charging power P of the electric vehicle is calculated. load The specific expression is:

[0120]

[0121] In the formula, N represents the total number of electric vehicles; t sn The charging start time for the nth electric vehicle; t en The charging end time for the nth electric vehicle; p n (t) represents the charging power of the nth electric vehicle at time t.

[0122] Based on the total charging power, construct an electric vehicle load curve showing the change of load generated by electric vehicles over time within an independent area.

[0123] Modeling the energy storage load mainly involves first constructing the load curve of electrochemical energy storage in an independent region, and then aggregating the daily charge and discharge power of electrochemical energy storage throughout the year to construct the energy storage load curve.

[0124] For example, an electrochemical energy storage system operating in an independent area adopts a "two-charge, two-discharge" mode: the first charge is performed during off-peak hours (00:00-08:00) and during normal hours (19:00-24:00; 8:00-10:00) to fully utilize the off-peak electricity price advantage; the first discharge is performed during the morning peak hours (10:00-12:00); and a second charge is performed during the midday normal hours (12:00-14:00) to provide energy for the second discharge during the evening peak hours (14:00-19:00). Therefore, the electrochemical energy storage system charges during the daily off-peak hours (0:00-8:00) and normal hours (12:00-14:00), and discharges during the daily peak hours (10:00-12:00 and 14:00-19:00). Treating the charging power of the electrochemical energy storage station as negative and the discharging power as positive, the daily charging and discharging power p of the electrochemical energy storage station is... b (t) is defined as follows:

[0125]

[0126] In the formula, q b For the electricity generated by electrochemical energy storage power plants, t dk The charging time for electrochemical energy storage stations between 0:00 and 8:00; p bd p represents the discharge power of the electrochemical energy storage power station. bc This refers to the charging power of electrochemical energy storage power plants.

[0127] Then, the annual charge and discharge power of the electrochemical energy storage plants is aggregated, transforming the dispersed charge and discharge characteristics of electrochemical energy storage into dispatchable load curves, thus generating energy storage load curves. First, 15-minute load curves for the electrochemical energy storage plants are generated. The specific expression is as follows:

[0128]

[0129] In the formula, h represents hours and k represents time.

[0130] Then Four-point average downsampling was performed, and the final aggregated data yielded the annual energy storage load curve P. year :

[0131]

[0132] In the formula, d represents the energy storage load for a single day, and d represents the number of days.

[0133] This application also introduces an ice storage system and electricity-side loads to optimize the regional power state model.

[0134] An ice storage system is a device that uses electricity to turn water into ice. It can be used to smooth out peak and valley loads and balance electrical loads. To construct a load curve for an ice storage system, it is necessary to extract data such as system capacity, maximum charging power, maximum cooling power, and initial state of charge from the system's usage characteristics to build key system usage features.

[0135] Considering the varying capacities of ice storage tanks in different types of ice storage systems, we can assume that the maximum capacity of each ice storage tank is uniformly distributed within the range of 2700 kWh to 3300 kWh, and its probability density function f storage_limit (E tank The expression for ) is:

[0136]

[0137] In the formula, E tank The maximum capacity of the ice storage tank can be considered as the capacity of the ice storage system.

[0138] The charging power and cooling power of each ice storage system are assumed to be uniformly distributed within the range of 450kW to 550kW, and their probability density function f ice_power (p ice_max The expression for ) is:

[0139]

[0140] In the formula, p ice_max This refers to the maximum charging power / maximum cooling power of the ice storage system.

[0141] Assuming that the initial state of charge of each ice storage system is uniformly distributed within the range of 0.1 to 0.2, its probability density function f soc (soc start The expression for ) is:

[0142]

[0143] In the formula, soc start This represents the initial state of charge of the ice storage system.

[0144] Then, based on the system's usage characteristics and the preset cooling energy efficiency ratio, the system's cold storage duration is calculated. The cold storage duration refers to the time required for the ice storage tank in the ice storage system to fill completely from the start of cold storage, expressed as t. charge as follows:

[0145]

[0146] In the formula, E tank For the maximum capacity of the ice storage tank, μ charge η represents the energy conversion efficiency during the cold storage process. tank p is the cooling energy efficiency ratio.ice This represents the maximum cooling capacity.

[0147] Based on the cold storage time from the start to the full system capacity and the system usage characteristics obtained above, the operating load of the ice storage system is calculated, and the ice storage system load curve is constructed.

[0148] The ice storage system load curve P ICS The specific expression is:

[0149] p ICS =p rm +p ice_discharge -p ice_charge ;

[0150] In the formula, p rm p is the output power of the electric chiller. ice_discharge To generate cooling power for melting ice, p ice_charge This refers to the power for charging and cold storage.

[0151] For the calculation of electricity load on the electricity consumption side, considering that the operating time and energy consumption requirements of different electrical equipment are different, the electricity load needs to be modeled separately for each case.

[0152] Optionally, in this application embodiment, the power load on the power consumption side is divided into uncontrollable load, transferable load, and interruptible load based on the power consumption characteristics of the power consumption equipment. The power consumption characteristics are determined by evaluating the flexibility of the power consumption period and the energy storage characteristics of the power consumption equipment in combination with the operating period and energy consumption requirements of the power consumption equipment.

[0153] Uncontrollable loads refer to loads whose electricity demand cannot be regulated by the power grid, such as lighting equipment. Their power supply or disconnection will affect the user's normal life, so they do not participate in the electricity demand response. Therefore, such loads are not considered when calculating the demand response curve on the electricity demand side, and there is no need to model such loads.

[0154] Transferable loads refer to equipment with energy storage characteristics, or equipment without energy storage characteristics but with flexible electricity usage periods. This type of electrical equipment is designated by type A. TL1 Its characteristics are described as follows:

[0155]

[0156] In the formula, Minimum power reduction is the minimum power that can be reduced during a single interrupt event. To maximize power reduction, The earliest start time of interruption is the earliest allowed start time for interrupting load aggregate a. This is the latest time to end the interruption; V is the minimum power consumption required for electrical equipment belonging to the category of transferable loads to complete its task. a1 It has the characteristics of a transferable load.

[0157] During the operating period, the power consumption of the equipment should be within the allowable range; at the end of the operating period, its power consumption should meet the minimum energy consumption requirement. Based on the formula for the characteristics of transferable loads mentioned above, the power consumption P of the transferable load type of electrical equipment in time period t can be obtained. a,t The expression:

[0158]

[0159] Interruptible loads, such as air conditioners and water heaters, have flexible power consumption characteristics, and short-term power outages will not have a significant impact on users, but may deviate somewhat from their usual electricity usage habits. These types of electrical equipment use type A. TL2 Its characteristics are described by the following formula:

[0160]

[0161] In the formula, Minimum power reduction is the minimum power that can be reduced during a single interrupt event. To maximize power reduction, The earliest start time of interruption is the earliest allowed start time for interrupting load aggregate a. This is the latest time to end the interruption; V is the minimum user comfort requirement that electrical equipment classified as interruptible load must meet. a2 For transferable load characteristics

[0162] The start and stop times of interruptible loads vary dynamically according to needs. When the actual state of the electrical equipment meets the user's comfort requirements, its minimum power consumption can be 0; conversely, when the electrical equipment does not meet the requirements, its minimum power consumption is the rated power of the appliance. Based on the characteristics of transferable loads described in the above formula, the power consumption P of the electrical equipment belonging to interruptible loads during time period t is... a,t The description is as follows:

[0163]

[0164] In the formula, θ a,t This represents the actual comfort level of the user with electrical equipment a during time period t.

[0165] Therefore, transferable loads and interruptible loads are selected as typical demand response objects, and the load fluctuations under these conditions are calculated to construct the demand response curves on the electricity consumption side.

[0166] Finally, by integrating the load curves of electric vehicles, energy storage, ice storage systems, and electricity demand response curves, a regional energy dispatch curve is obtained.

[0167] Step S3: Optimize the load of the regional power state model based on the regional energy dispatch curve to obtain the power balance model of each independent region.

[0168] When flexible DC interconnection within an independent region fails to achieve power balance across the entire region, a three-level optimization strategy is employed to schedule the total system load of the independent region using the regional power state model during periods where power imbalance still exists, thereby minimizing the total power imbalance in the region.

[0169] In this embodiment, a three-level optimization strategy is constructed, with the electric vehicle load curve as the first level, the energy storage load curve as the second level, and the ice storage cooling system load curve and the electricity demand response curve as the third level.

[0170] For the aforementioned periods of power imbalance, the charging behavior of electric vehicles in the independent area is first adjusted according to the electric vehicle load curve to reduce the total power imbalance in the area. Then, the total load of the area is recalculated. If a power imbalance still exists, an energy storage system is introduced for load regulation. Under the first two levels of regulation, if periods of power imbalance still exist in the independent area, power balance will be achieved by scheduling the load of the ice storage cooling system and the electricity consumption side load.

[0171] Based on the above power dispatching process, it can be seen that a three-level optimization strategy is introduced into the regional power state model to achieve efficient coordination of different regulation resources and construct a power balance model for the independent region. This power balance model, through the orderly combination of electric vehicles, energy storage systems, ice storage systems, and demand response on the electricity consumption side, maximizes the regulation potential of various flexible resources while ensuring system safety, and minimizes the power imbalance in the independent region.

[0172] Step S4: Based on the power surplus and power deficit of each independent region, the power balance model is used to carry out zoned power dispatch within the urban power grid through a flexible DC interconnection channel.

[0173] After completing the power balance adjustment within each independent zone, the power balance status of each zone is detected to identify the power deficit zones that require power support and the power surplus zones that need power consumption. These power deficit zones and power surplus zones are independent zones where overall regional power balance cannot be achieved even under the aforementioned power balance model. Therefore, they need to obtain or transmit power from external sources to achieve regional energy mutual assistance within the urban power grid.

[0174] The system identifies power deficit and surplus zones within the urban power grid and uses corresponding power balance models to determine the required output and capacity to be absorbed. Based on these values, path matching is performed within the urban power grid to find pathways for power transmission between the power deficit and surplus zones.

[0175] Furthermore, this embodiment of the application adopts the principle of "from near to far" to determine the search direction of the path. For regions with power surplus or deficit, priority is given to examining the regions closest to them, determining whether these other regions have the corresponding capacity to provide external power support or absorb external power, and comparing their power supply and demand regulation capabilities with the amount of regulation power required by the power deficit region or the power surplus region. If other regions can provide or absorb sufficient power, inter-regional flexible direct regulation is directly carried out to achieve energy mutual assistance; if the power supply and demand regulation capabilities of other regions cannot meet the demand, support is sought from the next closest region, and so on, until the power balance demand of the target region is met or there are no available resources.

[0176] For example, suppose a city's power grid comprises N independent regions, where i ∈ {1, 2, 3, ..., N}. When a certain independent region i experiences a power shortage at time t, i.e., ΔP... i If (t) < 0, then the region is considered a power shortage zone and needs to seek power support from other zones. If the external support capacity of independent region j at time t is... Its capacity to absorb external power is Under the premise of satisfying the flexible DC transmission capacity constraints, power support matching is performed starting from the nearest independent region j in the power shortage zone, as shown in the following expression:

[0177]

[0178] ΔP i (t)=ΔP i (t)+P i,j (t);

[0179]

[0180] In the formula, P i,j (t) represents the power supplied from partition j to partition i, if ΔP i (t)<0 and If all resources are exhausted, continue to the next nearest partition k for support matching, until ΔP. i The corresponding transmission line path is obtained until (t)≥0 or no support is available.

[0181] Similarly, for areas with surplus electricity, it is necessary to transmit the excess electricity to other areas through flexible DC interconnection channels. The matching process for the transmission line paths is as follows:

[0182]

[0183] ΔP i (t)=ΔP i (t)+P j,i (t);

[0184]

[0185] In the formula, P i,j (t) represents the electricity transferred from surplus power region i to power region j, if ΔP i If (t) < 0 and the absorption capacity of the current partition j is insufficient, then continue to search for the next more distant partition k to receive power until the surplus is completely sent out or there is no available absorption capacity, thereby obtaining the corresponding transmission line path.

[0186] Based on the obtained transmission line routes, power dispatch is carried out in the power deficit zones and the power surplus zones to achieve overall power balance of the urban power grid and improve overall energy utilization.

[0187] Therefore, the aforementioned inter-regional flexible DC support mechanism based on spatial distance priority solves the problem of mismatch between regional power surplus and deficit, significantly enhances the regional coordination capability of the power grid, and achieves energy mutual assistance.

[0188] Implementing the embodiments of this application has the following beneficial effects:

[0189] This application's embodiments first conduct time-series production simulations of unit output for individual areas within the urban power grid. The simulated output results are then used to evaluate the power balance status of each independent area during different time periods, generating a regional power state model that characterizes whether the area's power is balanced, in surplus, or in deficit during a given time period. By introducing other facilities within the independent areas, load optimization is performed on the power imbalance periods in the regional power state model, enabling each independent area to autonomously achieve power balance. Furthermore, the external support and absorption capabilities of each area's power are statistically analyzed. Power that an independent area cannot autonomously absorb is transmitted to other areas in urgent need of power through flexible DC interconnection channels, achieving energy mutual assistance between different areas of the urban power grid. This improves the overall operational stability and energy utilization rate of the power grid system, systematically solves the problem of power surplus and deficit mismatch between regions, and significantly enhances the regional coordination capability of the power grid.

[0190] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. In particular, it should be noted that any modifications, equivalent substitutions, or improvements made by those skilled in the art within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for flexible partition energy scheduling of urban power grid based on time-series production simulation, characterized in that, The method comprises the following steps: According to the system output data of each independent area in the urban power grid, the unit output of the independent area is simulated in time sequence production, and a regional power state model representing the power balance of the independent area at each time is constructed; By modeling the charging behavior of electric vehicles, the energy storage load condition, the ice storage system load condition and the electricity demand of the electricity side in the independent area, a regional energy dispatching curve is obtained; wherein the regional energy dispatching curve includes an electric vehicle load curve, an energy storage load curve, an ice storage system load curve and an electricity side demand response curve; According to the regional energy dispatching curve, the load optimization of the regional power state model is carried out, and a power balance model of each independent area is obtained; Based on the power surplus and power gap of each independent area, the power balance model is used to carry out regional power dispatching in the urban power grid through the flexible DC interconnection channel. 2.The flexible partition energy dispatching method for urban power grid based on time-series production simulation according to claim 1, wherein, According to the system output data of each independent area in the urban power grid, the unit output of the independent area is simulated in time sequence production, and a regional power state model representing the power balance of the independent area at each time is constructed, specifically: Collecting the system output data of the generator set and energy storage equipment in the independent area, constructing a regional net load curve and a regional adjustable output range; According to the regional net load curve and the regional adjustable output range, the supportable output of the independent area to other areas and the acceptable output of the independent area from other areas are calculated, and the energy supply and demand adjustment capacity of the independent area is obtained; Based on the preset unit maintenance plan, the energy supply and demand adjustment capacity is used to simulate the unit output of the independent area in time sequence production, and the regional power state model is constructed. 3.The flexible zoning energy dispatching method for urban power grid based on timing production simulation according to claim 2, characterized in that, Based on the preset unit maintenance plan, the energy supply and demand adjustment capacity is used to simulate the unit output of the independent area in time sequence production, and the regional power state model is constructed, specifically: Calculate the supportable output of the generator set under the condition of starting, and take the period containing the maximum average value of the supportable output as the planned maintenance period; In the planned maintenance period, the generator set is maintained in sequence according to the unit number, and the unit maintenance plan is obtained; According to the unit maintenance plan, the energy supply and demand adjustment capacity is optimized, and the output order and size of the generator set are dispatched from the power balance and power imbalance conditions respectively by using the optimized energy supply and demand adjustment capacity and the load demand of the independent area; wherein the power imbalance condition includes power surplus and power shortage condition; Statistical results of each generator set are obtained, and the regional power state model is constructed. 4.The flexible zoning energy dispatching method for urban power grid based on timing production simulation according to claim 1, characterized in that, According to the vehicle flow characteristics and battery state of charge of electric vehicles, the total charging power of all electric vehicles in the independent area is predicted, and an electric vehicle load curve is constructed; ​ According to the charging and discharging period of the energy storage system, the annual charging and discharging power of the independent area is aggregated to construct an energy storage load curve; The ice storage system load curve is constructed by calculating the ice storage system operation load according to the ice storage system use characteristics; According to the energy consumption demand and operation period of the electrical equipment, the electrical side power load of the independent area is modeled to construct an electrical side demand response curve.

5. The method of claim 4, wherein, The total charging power of all electric vehicles in the independent area is predicted according to the vehicle flow characteristics and battery state of charge of the electric vehicles, and an electric vehicle load curve is constructed, specifically: A space transfer probability matrix is constructed by predicting the migration probability of electric vehicles between different areas in each period; The vehicle flow characteristics are constructed by analyzing the charging and discharging starting time, travel destination, first travel location, travel duration, travel mileage and parking duration of the electric vehicles based on the space transfer probability matrix; The remaining power of the electric vehicles after completing the trip is predicted according to the vehicle flow characteristics, and the charging characteristics of the electric vehicles are determined through the prediction results; wherein the charging characteristics include charging power, battery initial state of charge and charging start time; The total charging power of all electric vehicles in the independent area is calculated according to the charging characteristics, and an electric vehicle load curve is constructed.

6. The method of claim 4, wherein, The ice storage system load curve is constructed by calculating the ice storage system operation load according to the ice storage system use characteristics, specifically: The system use characteristics are constructed by extracting the system capacity, maximum charging power, maximum refrigeration power and initial state of charge from the ice storage system use characteristics; The ice storage system load curve is constructed by calculating the ice storage system operation load according to the ice storage system use characteristics and the preset refrigeration energy efficiency ratio. The ice storage system load curve is constructed by calculating the ice storage system operation load according to the ice storage system use characteristics and the preset refrigeration energy efficiency ratio.

7. The method of claim 1, wherein, The electrical side demand response curve is constructed by modeling the electrical side power load of the independent area according to the energy consumption demand and operation period of the electrical equipment, specifically: The electrical equipment power consumption characteristics are constructed by evaluating the electrical equipment power consumption flexibility and energy storage characteristics in combination with the energy consumption demand and operation period; The electrical side power load is divided into uncontrollable load, transferable load and interruptible load according to the electrical equipment power consumption characteristics; The uncontrollable load, transferable load and interruptible load are modeled according to the power consumption and power consumption interval of the electrical equipment to obtain the electrical side demand response curve. 8.The flexible zoning energy dispatching method for urban power grid based on time-series production simulation according to claim 1, wherein, The power balance model of each independent area is obtained by load optimization of the regional power state model according to the regional energy dispatching curve, specifically: A three-level optimization strategy is constructed with the electric vehicle load curve as the first level, the energy storage load curve as the second level, and the ice storage system load curve and electrical side demand response curve as the third level; The system total load of the independent area is dispatched according to the level order of the three-level optimization strategy for the power imbalance period in the regional power state model to obtain the power balance model. 9.The flexible zoning energy dispatching method for urban power grid based on time-series production simulation according to claim 1, wherein, The power balance model is used to perform regional power dispatching in the urban power grid through the flexible DC interconnection channel based on the power surplus and power gap of each independent region, specifically as follows: The power imbalance of each independent region is counted to determine the power gap region needing power support and the power surplus region needing power consumption; The supported output of the power gap region and the consumed output of the power surplus region are obtained from the power balance model respectively; The power gap region and the power surplus region are dispatched through the flexible DC interconnection channel according to the size of the supported output and the consumed output.

10. The method of claim 9, wherein, The power gap region and the power surplus region are dispatched through the flexible DC interconnection channel according to the size of the supported output and the consumed output, specifically as follows: The search direction of the power surplus region in the urban power grid is determined based on the nearest distance between each independent region; The power surplus region is traversed through the power gap region according to the search direction, and the transmission line path that can meet the consumed output is determined by comparing the size of the supported output and the consumed output; The power gap region and the power surplus region are dispatched in combination with all the transmission line paths, so that the urban power grid reaches power balance.

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