A method and apparatus for energy dispatching in dual-sided service areas

Abstract

This application provides an energy dispatching method and apparatus for two-sided service areas. The method includes: constructing a first optimization problem, including a first objective function aimed at minimizing the electricity purchase cost of the two-sided service areas and multiple constraints; solving the first optimization problem to obtain a first optimal solution, including first predicted values ​​of relevant parameters of electricity and charging in the two-sided service areas for each time period; constructing a second optimization problem based on the first optimal solution, including a second objective function aimed at minimizing the planned deviation penalty of the two-sided service areas and multiple constraints; solving the second optimization problem to obtain a second optimal solution, including second predicted values ​​of relevant parameters of electricity and charging in the two-sided service areas for each time period; and performing energy dispatching on the two-sided service areas according to the second optimal solution. This application improves the energy dispatching efficiency of the two-sided service areas by constructing two optimization problems, realizing the coordinated dispatching of tidal traffic flow and energy flow on both sides.

Description

Technical Field

[0001] This application relates to the field of intelligent transportation technology, and in particular to an energy dispatching method and apparatus for dual-sided service areas. Background Technology

[0002] Existing microgrids in highway service areas typically operate independently. Because the transformers on both sides cannot be directly interconnected, when one service area has sufficient photovoltaic power generation or surplus energy storage, the other side still needs to purchase electricity from the main grid at high prices during peak load periods. This prevents cross-regional energy sharing, resulting in energy waste and increased operating costs. Furthermore, the unbalanced traffic flow and tidal flow in the two-way service areas prevent the effective fulfillment of charging needs.

[0003] Existing dispatch strategies are mostly based on photovoltaic-storage-charging optimization models for single-sided service areas, failing to fully explore and utilize the spatiotemporal complementarity of loads between two-sided service areas. This results in low local photovoltaic consumption rates and low overall system energy efficiency. Due to the lack of a two-sided coordinated dispatch mechanism, existing technologies require each service area to be equipped with a large-capacity energy storage system to cope with peak load demands in its respective direction. This leads to low utilization of energy storage equipment, long investment payback periods, and poor overall system economics. Summary of the Invention

[0004] In view of this, this application provides an energy dispatching method and apparatus for dual-sided service areas to solve the above-mentioned technical problems.

[0005] In a first aspect, embodiments of this application provide an energy dispatching method for a dual-sided service area, applied to a DC interconnected dual-sided service area, comprising:

[0006] The first optimization problem is constructed, including: a first objective function aimed at minimizing the electricity purchase cost of both service areas and multiple constraints; the first optimal solution is obtained by solving the first optimization problem, including the first predicted values ​​of the relevant parameters of electricity and charging in both service areas at each time period;

[0007] Based on the first optimal solution, a second optimization problem is constructed, including: a second objective function with the goal of minimizing the planned deviation penalty of the two service areas and multiple constraints; the second optimization problem is solved to obtain the second optimal solution, including the second predicted values ​​of the relevant parameters of the power and charging of the two service areas in each time period;

[0008] Energy scheduling is performed on both service areas based on the second optimal solution.

[0009] Secondly, embodiments of this application provide an energy dispatching device for a dual-side service area, applied to a DC-interconnected dual-side service area, comprising:

[0010] The first processing unit is used to construct a first optimization problem, including: a first objective function aimed at minimizing the electricity purchase cost of both service areas and multiple constraints; and to solve the first optimization problem to obtain a first optimal solution, including the first predicted values ​​of the relevant parameters of electricity and charging in both service areas at each time period.

[0011] The second processing unit is used to construct a second optimization problem based on the first optimal solution, including: a second objective function with the goal of minimizing the planned deviation penalty of the two service areas and multiple constraints; and to solve the second optimization problem to obtain the second optimal solution, including the second predicted values ​​of the relevant parameters of the power and charging of the two service areas in each time period.

[0012] The scheduling unit is used to perform energy scheduling on both service areas according to the second optimal solution.

[0013] Thirdly, embodiments of this application provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of embodiments of this application.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the methods of embodiments of this application.

[0015] Fifthly, embodiments of this application provide a computer program product, including a computer program / instructions, which, when executed by a processor, implement the method of embodiments of this application.

[0016] This application improves the scheduling efficiency of power grid, photovoltaic, energy storage system, charging equipment and bidirectional energy transmission in both service areas by constructing two optimization problems, reduces the dependence of single service areas on large-capacity energy storage systems, reduces redundant configuration costs, and reduces the carbon emission intensity of electricity; avoids resource waste caused by high grid input power, improves resource utilization, and realizes coordinated scheduling of traffic flow and energy flow. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 A schematic diagram of the DC interconnection of the two service areas provided in an embodiment of this application;

[0019] Figure 2 A schematic diagram of a single-sided service area microgrid topology provided in an embodiment of this application;

[0020] Figure 3 A flowchart illustrating the energy scheduling method for dual-side service areas provided in this application embodiment;

[0021] Figure 4 A functional structure diagram of an energy dispatching device for a dual-service area provided in an embodiment of this application;

[0022] Figure 5 This is a functional structure diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0025] First, a brief introduction to the design concept of the embodiments of this application will be given.

[0026] Currently, highway service areas on both sides generally adopt a dual-transformer independent power supply mode. The transformers on both sides can be connected to different access points of the external power grid, or share the same external power grid access point. During normal operation, the low-voltage busbars on both sides operate independently in sections, and the bus tie switch is in the open state, making it impossible to achieve mutual power supply between the two sides. When a fault occurs in the power supply system on one side, by closing the AC bus tie switch, the transformer on the other side can provide emergency power to the load in the faulty area.

[0027] To address the shortcomings in the existing energy coordination and scheduling of service areas on both sides of highways, such as Figure 1As shown, this application proposes a microgrid topology suitable for dual-side service areas, aiming to achieve efficient energy exchange and coordinated operation between adjacent service areas. The dual-side service areas include a first service area and a second service area (opposite service areas). Energy exchange between the two service areas is achieved through a DC interconnection cabinet. This cabinet, serving as the core hub for energy exchange between the two service areas, has its input terminals connected to the local low-voltage AC buses of both service areas and incorporates a bidirectional power electronic converter (rectifier / inverter). This device eliminates the stringent requirements for frequency and phase synchronization in AC interconnection, allowing the two microgrids to operate relatively independently in terms of electrical parameters. Furthermore, based on preset energy dispatch strategies or real-time commands, and combined with the photovoltaic output, energy storage state of charge, load demand, and grid price signals on both sides, it dynamically optimizes the direction and power of energy transmission, thereby improving the overall energy utilization efficiency of the system (promoting local photovoltaic consumption and optimizing energy storage charging and discharging strategies) and operational flexibility (supporting power exchange, load transfer, and smoothing power fluctuations). This is a key technological support for constructing an efficient, reliable, and intelligent dual-side coordinated microgrid.

[0028] Existing dual-service area microgrid topologies typically use AC bus tie switches for power switching and emergency power supply. However, the electrical structure and control logic of these AC bus tie switches are not specifically designed for continuous power transmission and dynamic energy dispatch, making them unable to withstand bidirectional power flow for extended periods and lacking real-time adjustment capabilities for power flow direction and amplitude. Consequently, they struggle to support efficient and flexible energy coordination between the dual-service areas. The dual-service area microgrid topology proposed in this application, based on DC interconnection technology, not only eliminates the stringent frequency and phase synchronization requirements of AC interconnection, allowing the two microgrids to operate relatively independently in terms of electrical parameters, but also dynamically optimizes energy transmission direction and power levels based on preset energy dispatch strategies or real-time control commands, combined with the photovoltaic power generation, energy storage system state of charge, load demand, and grid price signals on both sides. This effectively improves the overall energy utilization efficiency of the system.

[0029] like Figure 2 As shown, each service area is independently equipped with a photovoltaic array, energy storage system, charging pile cluster, and transformer unit. The photovoltaic array is used to convert solar energy into electrical energy, thereby generating clean electricity and providing renewable energy input for the system. The energy storage system is used to store currently unused photovoltaic power, or to purchase electricity from the external grid during periods of low grid electricity prices for energy storage, in order to reduce the cost of purchasing electricity during peak periods, and to release electricity when load demand is high or photovoltaic output is insufficient to meet the load's electricity demand. The charging pile cluster is used to represent and respond to the charging needs of electric vehicles, realizing the orderly charging and discharging management of electric vehicles. The transformer is used to realize voltage level conversion, transmit power to various electrical devices, and is responsible for power access and transmission with the external grid.

[0030] This application constructs a DC interconnection topology between service areas on both sides of a highway to achieve flexible power dispatch and energy sharing between the microgrids on both sides. When there is a surplus of photovoltaic / energy storage in one service area, electricity can be transmitted to the service area on the other side during peak load periods, thereby effectively breaking the "energy island" state and improving the overall energy utilization efficiency.

[0031] Based on this, this application proposes an energy scheduling method for dual-side service areas. This method comprehensively considers the energy flow direction, equipment operation constraints, and power balance relationship of the photovoltaic-storage-charging system in dual-side service areas to achieve synergistic optimization of system operation economy and low carbon emissions.

[0032] After introducing the application scenarios and design concepts of the embodiments of this application, the technical solutions provided by the embodiments of this application will be described below.

[0033] like Figure 3 As shown, this application provides an energy dispatching method for a dual-sided service area, applied to a DC-connected dual-sided service area, including:

[0034] Step 101: Construct the first optimization problem, including: a first objective function with the goal of minimizing the electricity purchase cost of both service areas and multiple constraints; solve the first optimization problem to obtain the first optimal solution, including the first predicted values ​​of the relevant parameters of electricity and charging in both service areas at each time period;

[0035] For example, the time period is 1 hour long, the number of time periods is 24, and the time periods are: [0,1],[1,2], ,[23,24].

[0036] Step 102: Construct a second optimization problem based on the first optimal solution, including: a second objective function with the goal of minimizing the planned deviation penalty of the two service areas and multiple constraints; solve the second optimization problem to obtain the second optimal solution, including the second predicted values ​​of the relevant parameters of the power and charging of the two service areas in each time period;

[0037] Step 103: Perform energy scheduling on both service areas according to the second optimal solution.

[0038] This application improves the scheduling efficiency of power grid, photovoltaic, energy storage system, charging equipment and bidirectional energy transmission in both service areas by constructing two optimization problems, reduces the dependence of single service areas on large-capacity energy storage systems, reduces redundant configuration costs, and reduces the carbon emission intensity of electricity; avoids resource waste caused by high grid input power, improves resource utilization, and realizes coordinated scheduling of traffic flow and energy flow.

[0039] In some embodiments, the dual-side service area includes: a first service area and a second service area;

[0040] Construct the first objective function; including:

[0041] Construction period First cost function of the first service area :

[0042]

[0043] in, For grid electricity price, Input power to the power grid of the first service area; The penalty coefficient for unmet charging needs of electric vehicles. To meet the unmet charging needs of electric vehicles in the first service area;

[0044] Construction period The first cost function of the second service area :

[0045] in, Input power to the power grid of the second service area; To meet the unmet electric vehicle charging needs of the second service area;

[0046] First objective function for:

[0047] .

[0048] In some embodiments, the multiple constraints include:

[0049] During the period The input energy of each service area within the region equals the output energy. The input energy equals the sum of the grid's power generation, energy storage discharge power, and grid input power; the output energy equals the sum of energy storage charging power, the electric vehicle charging demand that can be met, photovoltaic power abandonment, and transmission power.

[0050]

[0051] in, For time period The power generation capacity of the power grid in the first service area For time period The energy storage discharge power of the first service area; For time period The energy storage charging power of the first service area For time period The first service area can meet the charging needs of electric vehicles. For time period The amount of photovoltaic power abandoned in the first service area For time period The transmission power from the first service area to the second service area;

[0052] During the period The charging demand in each service area within the region equals the sum of the electric vehicle charging demand that can be met and the electric vehicle charging demand that cannot be met:

[0053]

[0054] in, For time period The charging needs of the first service area;

[0055] During the period The energy storage systems in different service areas cannot charge and discharge simultaneously:

[0056]

[0057] During the period The transmission power between the two service areas is less than the maximum transmission power of the DC interconnection system, and power transmission between the two service areas can only be carried out in one direction.

[0058]

[0059]

[0060]

[0061] in, For time period The transmission power from the first service area to the second service area; For time period The transmission power from the second service area to the first service area; This represents the maximum power transmitted in a DC interconnect system.

[0062] In some embodiments, the multiple constraints also include:

[0063] During the period The energy storage charging power in each service area shall not exceed the maximum charging power, and the energy storage discharging power in each service area shall not exceed the maximum discharging power.

[0064]

[0065] in, This represents the maximum charging and discharging power of the energy storage system.

[0066] During the period The power input to the grid in each service area shall not exceed the maximum power output of the grid.

[0067]

[0068] in, This represents the maximum power output of the power grid.

[0069] During the period The state of charge (SOC) of the energy storage systems in each service area is maintained between the minimum and maximum capacity of the energy storage systems.

[0070]

[0071] in, For time period The charge status of the first service area; The minimum capacity of the energy storage system for the first service area; This is the maximum capacity of the energy storage system in the first service area.

[0072] During the period The state of charge (SOC) of each service area within the service area satisfies the SOC update formula compared to the SOC of the previous time period:

[0073]

[0074] in, For time period The charge status of the first service area in the previous time period. To Perform differentiation; The rated capacity of the energy storage battery for the first service area; To improve the charging and discharging efficiency of energy storage batteries;

[0075] During the period The load rate of each service area is less than the maximum load rate of the transformer:

[0076]

[0077] in, For time period Load rate of the first service area within the city; This represents the maximum load rate of the transformer.

[0078] In some embodiments, the method further includes:

[0079] Based on the photovoltaic power generation parameters of the power grid in both service areas, calculate the power generation of the power grid in both service areas at each time period;

[0080] Based on highway parameters and historical traffic flow data, the charging demand of service areas on both sides is calculated for each time period.

[0081] In this embodiment, among the parameters in the first objective function and multiple constraints, the power generation and charging demand of the grid in the two service areas at each time period are pre-calculated.

[0082] In some embodiments, the method further includes:

[0083] Acquisition Time Period Total solar irradiance on the photovoltaic panels in the first service area and ambient temperature ;

[0084] Calculation period Surface temperature of photovoltaic panels :

[0085]

[0086] in, Light intensity under standard test conditions; This refers to the nominal operating battery temperature.

[0087] Calculation period The power generation capacity of the first service area's power grid :

[0088]

[0089] in, This refers to the derating factor for photovoltaic power generation equipment under standard test conditions. This refers to the rated power of the photovoltaic power generation equipment under standard test conditions. The power temperature coefficient under standard test conditions. This refers to the surface temperature of the photovoltaic panel under standard test conditions.

[0090] Using the same method, the time period can be calculated. The power generation capacity of the power grid in the second service area.

[0091] In some embodiments, the method further includes:

[0092] Obtain highway parameters and historical traffic flow data. Highway parameters include the locations of several entrances, exits, service areas, and the number of charging stations at each service area. Historical traffic flow data includes time periods. Traffic flow and the percentage of electric vehicles at each entrance;

[0093] For time period For each entrance, the parameters of electric vehicles are sampled using the Monte Carlo simulation method to obtain multiple simulated electric vehicles that are consistent with the traffic flow at the entrance; the parameters of the electric vehicles include: battery capacity, initial state of charge of the battery, origin and destination of the trip;

[0094] Based on the parameters and energy consumption model of each simulated electric vehicle, when it is determined that the battery is insufficient or the user is willing to actively charge, the charging location and charging amount in the next service area are determined.

[0095] Based on time period The total charging amount of all simulated electric vehicles in each service area is used to determine the time period. The charging needs of each service area;

[0096] Time period The average charging demand across all service areas is used to determine the time period. The charging needs of the first service area.

[0097] Using the same method, the time period can be calculated. The charging needs of the second service area.

[0098] The method in this embodiment is suitable for predicting charging demand at newly built highway service areas.

[0099] In some embodiments, the method further includes:

[0100] Time period for obtaining target service area Historical traffic flow data includes: the number of vehicles entering the service area, the percentage of electric vehicles, and the percentage of electric vehicles that need charging;

[0101] The calculation period is based on the number of vehicles entering the target service area, the proportion of electric vehicles, and the proportion of electric vehicles requiring charging. The total number of charging vehicles;

[0102] The charging amount of each electric vehicle was sampled using the Monte Carlo simulation method to obtain multiple charging demands.

[0103] Based on time period The total number of charging vehicles and the multiple charging needs of each electric vehicle are used to determine the time period. The charging needs of the target service area.

[0104] The method in this embodiment is suitable for calculating the charging demand of existing highway service areas.

[0105] In some embodiments, the first optimal solution includes: the first grid input power prediction value for each service area in each time period, the first energy storage charging and discharging power prediction value for each service area in each time period (equal to the maximum value of the first energy storage charging power prediction value and the first energy storage discharging power prediction value), the first photovoltaic abandonment prediction value for each service area in each time period, the first unmet electric vehicle charging demand prediction value for each service area in each time period, the first transmission power prediction value transmitted from the first service area to the second service area in each time period, and the first transmission power prediction value transmitted from the second service area to the first service area.

[0106] In some embodiments, a second objective function is constructed based on the first optimal solution, including:

[0107] Construction period The second cost function of the first service area :

[0108]

[0109] in, For time period The ratio of the duration to 60 minutes; if the duration of the time slot is 1 hour, then... ; For time period Energy storage charging and discharging power of the first service area:

[0110]

[0111] For time period The predicted input power of the first power grid in the first service area. For time period Predicted first energy storage charging and discharging power of the first service area For time period The first transmission power prediction value transmitted from the first service area to the second service area. For time period The predicted value of the first photovoltaic abandonment in the first service area. Time period The first electric vehicle charging demand forecast that cannot be met in the first service area; The deviation penalty factor for the power grid purchase plan, in units of ; The deviation penalty factor for the energy storage charging and discharging plan, in units of ; This is the deviation penalty factor for the DC interconnection transmission plan, in units of ; The deviation penalty factor for the photovoltaic usage plan, in units of ; Deviation penalty factor for unmet electric vehicle charging demand plans, in units of ;

[0112] Based on the same construction steps of the second cost function of the first service area, the construction period The second cost function of the second service area ;

[0113] The minimum sum of the second cost functions of the first service area and the second service area across all time periods is determined as the second objective function. :

[0114] ).

[0115] The constraints of the second objective function are the same as those of the first objective function.

[0116] In some embodiments, the second optimal solution includes: the second grid input power prediction value for each service area in each time period, the second energy storage charging and discharging power prediction value for each service area in each time period, the second photovoltaic abandonment prediction value for each service area in each time period, the second state of charge prediction value for each service area in each time period, the second unmet electric vehicle charging demand prediction value for each service area in each time period, the second transmission power prediction value from the first service area to the second service area in each time period, and the second transmission power prediction value from the second service area to the first service area.

[0117] In this embodiment, the second optimal solution has higher accuracy than the first optimal solution.

[0118] Specifically, for the first objective function and the second objective function, the CBC (COIN-OR Branch and Cut) open-source solver can be used for mathematical optimization modeling and solving.

[0119] Based on the same inventive concept, this application provides an energy dispatching device for a dual-sided service area, applied to a DC-interconnected dual-sided service area. (See reference...) Figure 4 As shown, the energy dispatching device 200 for dual-service areas provided in this application embodiment includes at least:

[0120] The first processing unit 201 is used to construct a first optimization problem, including: a first objective function aimed at minimizing the electricity purchase cost of the two-sided service areas and multiple constraints; and to solve the first optimization problem to obtain a first optimal solution, including the first predicted values ​​of the electricity and charging-related parameters of the two-sided service areas in each time period.

[0121] The second processing unit 202 is used to construct a second optimization problem based on the first optimal solution, including: a second objective function with the goal of minimizing the planned deviation penalty of the two-sided service areas and multiple constraints; and to solve the second optimization problem to obtain the second optimal solution, including the second predicted values ​​of the relevant parameters of the power and charging of the two-sided service areas in each time period.

[0122] The scheduling unit 203 is used to perform energy scheduling on both service areas according to the second optimal solution.

[0123] It should be noted that the principle of the dual-service area energy scheduling device 200 provided in this application embodiment to solve the technical problem is similar to the method provided in this application embodiment. Therefore, the implementation of the dual-service area energy scheduling device 200 provided in this application embodiment can refer to the implementation of the method provided in this application embodiment, and the repeated parts will not be described again.

[0124] Based on the same inventive concept, embodiments of this application also provide an electronic device, such as... Figure 5 As shown, it includes a memory and a processor. The memory stores an executable program, and the processor executes the executable program to implement the steps of the energy scheduling method for dual-side service areas provided in the above embodiments.

[0125] The aforementioned processor can be a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0126] Since the electronic device described in this application embodiment is an electronic device equipped with a memory that implements the dual-service area energy scheduling method disclosed in this application embodiment, those skilled in the art can understand the structure and variations of the electronic device described in this application embodiment based on the dual-service area energy scheduling method described in this application embodiment, and therefore will not be described again here.

[0127] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the energy scheduling method for dual-side service areas provided in the above embodiments.

[0128] The storage medium in this embodiment may be included in an electronic device; or it may exist independently and not be assembled into an electronic device. The storage medium carries one or more computer programs, which, when executed, implement the steps of the energy scheduling method for dual-side service areas provided in the above embodiment.

[0129] It should be understood that the various solutions in this embodiment have the same technical effects as those in the above method embodiments, and will not be repeated here.

[0130] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. Optionally, specific examples in this embodiment can refer to the examples described in any embodiment of this application, which will not be repeated here. Obviously, those skilled in the art should understand that the various modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular hardware and software combination.

[0131] This application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the dual-service area energy scheduling method provided in the above embodiments.

[0132] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions targeted in the blocks may occur in a different order than those targeted in the drawings. For example, two consecutively represented blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0133] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. Multitasking and parallel processing may be advantageous in certain environments. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this application. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

Claims

1. A method for energy scheduling of a double-sided service area, applied to a double-sided service area of a direct current interconnection, characterized in that, The method comprises: constructing a first optimization problem, comprising a first objective function aiming to minimize the purchase cost of electricity in the two-sided service area and a plurality of constraint conditions; and solving the first optimization problem to obtain a first optimal solution, comprising a first predicted value of a parameter related to electricity and charging of the two-sided service area in each time period; constructing a second optimization problem based on the first optimal solution, comprising a second objective function aiming to minimize the planned deviation penalty of the two-sided service area and a plurality of constraint conditions; and solving the second optimization problem to obtain a second optimal solution, comprising a second predicted value of a parameter related to electricity and charging of the two-sided service area in each time period; performing energy scheduling on the two-sided service area according to the second optimal solution; the two-sided service area comprises a first service area and a second service area; and the first objective function is constructed to comprise: a first cost function for a first service area of the time period a first cost function for a first service area of the time period : wherein, is the grid price, is the grid input power of the first service area; is a penalty coefficient for the electric vehicle charging demand that cannot be met, is the electric vehicle charging demand of the first service area that cannot be met; a first cost function for a first service area a second cost function for a second service area : wherein, a power grid input power for the second service area; an unmet electric vehicle charging demand for the second service area; First objective function is: ； the first optimal solution comprises a first predicted value of grid input power of each service area in each time period, a first predicted value of storage charging and discharging power of each service area in each time period, a first predicted value of photovoltaic abandonment of each service area in each time period, a first predicted value of unmet electric vehicle charging demand of each service area in each time period, a first predicted value of transmission power transmitted from the first service area to the second service area in each time period, and a first predicted value of transmission power transmitted from the second service area to the first service area in each time period; the second objective function is constructed based on the first optimal solution to comprise: a first service area of the first service zone a second cost function of a first service area of the first service zone : wherein, is the duration of the time period; when the duration of the time period is 1 hour, then ; ; is the duration of the time period; when the duration of the time period is 1 hour, then is the first service area of the time period a first grid import power forecast value for the first service area for the time period, a first energy storage charge-discharge power forecast value for the first service area for the time period, a first transmission power forecast value for the first service area to the second service area for the time period, a first photovoltaic curtailment forecast value for the first service area for the time period, a first electric vehicle charging demand that cannot be satisfied forecast value for the first service area for the time period; a deviation penalty coefficient for the grid electricity purchase plan, a deviation penalty coefficient for the energy storage charge-discharge plan, a deviation penalty coefficient for the DC interconnection transmission plan, unit is; a deviation penalty coefficient for the photovoltaic use plan; a deviation penalty coefficient for the electric vehicle charging demand that cannot be satisfied plan;​​​​​ a build period a second cost function for a second service area of the first service area ; determining a minimum value of a sum of the first cost function of the first service area and the second cost function of the second service area for all time periods as a second objective function : 。 2. The method of claim 1, wherein, the plurality of constraint conditions comprise: input energy of each service area is equal to output energy, the input energy is equal to the sum of grid power generation, storage discharging power and grid input power; and the output energy is equal to storage charging power, met electric vehicle charging demand, photovoltaic abandonment and transmission power; charging demand of each service area is equal to the sum of met electric vehicle charging demand and unmet electric vehicle charging demand; storage system of each service area cannot charge and discharge at the same time; transmission power between the two-sided service areas is less than the maximum transmission power of the DC interconnection system, and only unidirectional power transmission is allowed between the two-sided service areas.

3. The method of claim 2, wherein, the plurality of constraint conditions further comprise: storage charging power of each service area is not more than the maximum charging power, and storage discharging power of each service area is not more than the maximum discharging power; grid input power of each service area is not more than the maximum grid power; state of charge of the storage system of each service area is maintained between the minimum capacity and the maximum capacity of the storage system; state of charge of each service area in the current time period and state of charge of each service area in the last time period satisfy a state of charge update formula; load rate of each service area is less than the maximum transformer load rate.

4. The method of claim 2, wherein, The method further comprises: calculating grid power generation of the two-sided service area in each time period based on photovoltaic power generation parameters of the grid of the two-sided service area; calculating charging demand of the two-sided service area in each time period based on parameters of the expressway and historical traffic data.

5. The method of claim 1, wherein, The second optimal solution comprises: a second power grid input power prediction value of each service area in each period, a second energy storage charging and discharging power prediction value, a second photovoltaic abandonment amount prediction value, a second state of charge prediction value, a second unmet electric vehicle charging demand prediction value, and a second transmission power prediction value transmitted from the first service area to the second service area and a second transmission power prediction value transmitted from the second service area to the first service area.

6. An energy scheduling device of a double-sided service area, applied to a double-sided service area of a direct current interconnection, characterized in that, Comprise: The first processing unit is configured to construct a first optimization problem, comprising: a first objective function with a minimum bilateral service area power purchase cost as an objective and a plurality of constraint conditions; and solve the first optimization problem to obtain a first optimal solution, comprising a first prediction value of an energy and charging related parameter of the bilateral service area in each period; The second processing unit is configured to construct a second optimization problem based on the first optimal solution, comprising: a second objective function with a minimum bilateral service area planning deviation penalty as an objective and a plurality of constraint conditions; and solve the second optimization problem to obtain a second optimal solution, comprising a second prediction value of an energy and charging related parameter of the bilateral service area in each period; The scheduling unit is configured to perform energy scheduling on the bilateral service area according to the second optimal solution; The bilateral service area comprises: a first service area and a second service area; and the first objective function is constructed, comprising: a first cost function for a first service area of the time period a first cost function for a first service area of the time period : wherein, is the grid price, is the grid input power of the first service area; is a penalty coefficient for the electric vehicle charging demand that cannot be met, is the electric vehicle charging demand of the first service area that cannot be met; a construction period a first cost function for the second service area : wherein, a power grid input power for the second service area; an unmet electric vehicle charging demand for the second service area; First objective function is: ； The first optimal solution comprises: a first power grid input power prediction value of each service area in each period, a first energy storage charging and discharging power prediction value of each service area in each period, a first photovoltaic abandonment amount prediction value of each service area in each period, a first unmet electric vehicle charging demand prediction value of each service area in each period, a first transmission power prediction value transmitted from the first service area to the second service area in each period and a first transmission power prediction value transmitted from the second service area to the first service area in each period; The second objective function is constructed based on the first optimal solution, comprising: a first service area of the first service zone a second cost function of a first service area of the first service zone : wherein, is the duration of the time period; when the duration of the time period is 1 hour, then ; ; is the energy storage charging and discharging power of the first service area of the time period ; a first grid import power forecast value for a first service area for a time period, a first storage charge-discharge power forecast value for a first service area for a time period, a first transmission power forecast value for a first service area to a second service area for a time period, a first PV curtailment forecast value for a first service area for a time period, a first electric vehicle charging demand that cannot be met forecast value for a first service area for a time period; a deviation penalty coefficient for a grid purchase power plan, a deviation penalty coefficient for a storage charge-discharge plan, a deviation penalty coefficient for a DC interconnection transmission plan, unit is; a deviation penalty coefficient for a PV use plan; a deviation penalty coefficient for an electric vehicle charging demand that cannot be met plan;​​​​​ a build period a second cost function for a second service area of the first service area ; determining a minimum value of a sum of the first cost function of the first service area and the second cost function of the second service area for all time periods as a second objective function : 。 7. An electronic device, comprising: Comprise: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1-5 when executing the computer program.

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