Optimized scheduling method and device for distributed resources and program product

Abstract

The embodiment of the invention discloses an optimal scheduling method for distributed resources, which comprises the following steps: acquiring target power utilization demand data of a target power grid in a preset scheduling time period and energy physical parameters of a power supply system, and determining target scheduling total power of a first type of energy in the power supply system according to the target demand data and the energy physical parameters, the first type of energy comprises at least one first type of energy power supply unit, and the energy physical parameters comprise first unit physical parameters corresponding to each first type of energy power supply unit; determining reference power and reference cost corresponding to each first type of energy power supply unit according to the target scheduling total power and the plurality of first unit physical parameters; and determining a target scheduling power corresponding to each first type of energy power supply unit according to the plurality of reference powers and the plurality of reference costs, and scheduling the first type of energy power supply unit according to the target scheduling power. The scheduling cost of distributed resources can be reduced, and the resource utilization rate of the distributed resources is improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of distributed resource scheduling, and in particular to a method, device, electronic device, storage medium and program product for optimizing scheduling of distributed resources. Background Art

[0002] In recent years, with the continuous development of renewable energy generation technology and energy storage technology and the continuous decline in costs, distributed resources have achieved rapid growth due to their multiple advantages such as small investment, flexible installation, environmental friendliness, helping to improve power supply reliability and reduce electricity costs, and being close to the user side. With the application of distributed resources, distributed resources can participate in the internal interactive operation of the aggregate through aggregation and according to the internal rules of the aggregate. However, the nonlinear, time-varying, and time-series coupling characteristics of distributed resource scheduling characteristics make the scheduling capacity and scheduling cost of distributed resources have complex nonlinear characteristics.

[0003] The existing research on the dispatching mode of distributed resources in the prior art is generally based on the global optimization solution of reporting detailed physical models. In the prior art, in the global optimization solution based on detailed physical models, it is necessary to model and optimize all distributed energy contained in the aggregate. The global optimization will be difficult to solve due to the large scale of variables, and it also depends on each aggregate to provide its detailed physical model to the superior dispatching agency, which has low dispatching efficiency and high dispatching cost. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, electronic device, storage medium and program product for optimizing the scheduling of distributed resources, which can reduce the scheduling cost of distributed resources and improve the resource utilization of distributed resources.

[0005] According to one aspect of the present invention, a method for optimizing scheduling of distributed resources is provided, comprising:

[0006] Obtain target power demand data of the target power grid in a preset scheduling period and energy physical parameters of the power supply system, and determine the target scheduling total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, wherein the first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include first unit physical parameters corresponding to each of the first type of energy power supply units;

[0007] Determine the reference power and reference cost corresponding to each of the first type energy power supply units according to the target dispatching total power and a plurality of physical parameters of the first units;

[0008] The target dispatching power corresponding to each of the first-type energy power supply units is determined according to a plurality of reference powers and a plurality of reference costs, and the first-type energy power supply units are dispatched according to the target dispatching power.

[0009] According to another aspect of the present invention, there is provided a distributed resource optimization scheduling device, comprising:

[0010] A target scheduling total power determination module is used to obtain target power demand data of a target power grid in a preset scheduling period and energy physical parameters of a power supply system, and determine a target scheduling total power of a first type of energy in a power supply system according to the target demand data and the energy physical parameters, wherein the first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include first unit physical parameters corresponding to each first type of energy power supply unit;

[0011] A reference data determination module, used to determine the reference power and reference cost corresponding to each of the first type energy power supply units according to the target dispatching total power and a plurality of physical parameters of the first units;

[0012] A scheduling module is used to determine the target scheduling power corresponding to each first-type energy power supply unit according to multiple reference powers and multiple reference costs, and schedule the first-type energy power supply unit according to the target scheduling power.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for optimizing scheduling of distributed resources described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for optimizing scheduling of distributed resources described in any embodiment of the present invention when executed.

[0018] According to another aspect of the present invention, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the distributed resource optimization scheduling method described in any embodiment of the present invention is implemented.

[0019] The embodiment of the present invention obtains the target power demand data of the target power grid in the preset scheduling period and the energy physical parameters of the power supply system, determines the target scheduling total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, and can determine the corresponding scheduling power according to the physical parameter information of the power supply system, thereby improving the scheduling efficiency and reducing the scheduling cost. The first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include the first unit physical parameters corresponding to each first type of energy power supply unit. By determining the reference power and reference cost corresponding to each first type of energy power supply unit according to the target scheduling total power and multiple first unit physical parameters, and determining the target scheduling power corresponding to each first type of energy power supply unit according to multiple reference powers and multiple reference costs, the first type of energy power supply unit is scheduled according to the target scheduling power. It can reduce the scheduling cost of each distributed resource in the power supply system and improve the resource utilization rate of each distributed resource.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a distributed resource optimization scheduling method provided in Embodiment 1 of the present invention;

[0023] Figure 2 is a flow chart of another distributed resource optimization scheduling method provided in Embodiment 2 of the present invention;

[0024] Figure 3 It is a structural diagram of a distributed resource optimization scheduling device provided in Embodiment 3 of the present invention;

[0025] Figure 4 It is a structural schematic diagram of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment 1

[0029] Figure 1 A flowchart of a distributed resource optimization scheduling method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of scheduling distributed resources in a power supply system. The method can be executed by a distributed resource optimization scheduling device. The distributed resource optimization scheduling device can be implemented in the form of hardware and / or software. The distributed resource optimization scheduling device can be configured in an electronic device. Figure 1 As shown, the method may include:

[0030] S110. Obtain the target electricity demand data of the target power grid during a preset scheduling period and the energy physical parameters of the power supply system, and determine the target scheduling total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, wherein the first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include first unit physical parameters corresponding to each first type of energy power supply unit.

[0031] Among them, the target power grid can be a power grid responsible for providing power supply to a specific area or user. The preset scheduling period can be a time period preset for power scheduling. The length of the preset time period can be one day or one hour, and the present invention does not specifically limit the length of the preset time period. The power demand data can be the total power demand that the power supply system of the target power grid is expected to provide during the preset scheduling period. For example, the target power grid estimates that the power consumption gap within two hours after one hour is 100 megawatts based on the power consumption and power supply conditions in the power grid. Then 100 megawatts is the target power demand data of the target power grid within two hours after one hour.

[0032] Among them, the power supply system can be a system for responding to the power demand data of the target power grid during the preset scheduling period and providing power to the target power grid. The power supply system may include the first type of energy and the second type of energy. The first type of energy may be an energy that aggregates multiple distributed energy sources, the amount of electricity provided fluctuates within a certain range, and the cost accounting needs to involve multiple factors. The first type of energy includes multiple types of distributed energy, such as renewable energy (such as wind power, photovoltaic), energy storage system, controllable load and electric vehicle, etc. The amount of electricity provided by the energy fluctuates greatly, and the scheduling cost accounting is relatively complex. The first type of energy includes at least one first type of energy power supply unit, and the first type of energy power supply unit may be a power supply unit provided by renewable energy (such as wind power, photovoltaic), energy storage system, controllable load or electric vehicle, etc. The amount of electricity provided by the energy fluctuates greatly, and the scheduling cost accounting is relatively complex. The second type of energy may be a power supply energy in the power supply system that can provide stable electricity to the power supply system, and the scheduling cost is easier to calculate. For example, coal power, gas power and hydropower are based on fossil fuels or natural resources to generate electricity and can provide stable electricity. The second type of energy includes at least one second type of energy power supply unit, which can be a coal-fired power unit, a gas-fired power unit, a hydropower unit, or other units that generate electricity based on fossil fuels or natural resources and can provide stable electricity.

[0033] Among them, the energy physical parameters include the first unit physical parameters corresponding to each first type energy power supply unit and the second unit physical parameters corresponding to each second type energy power supply unit. The first unit physical parameters may be physical characteristic parameters or equipment basic parameters of each power supply unit in the first type energy power supply unit. For example, the first unit physical parameters may include unit output power, unit voltage, unit current, power factor, equipment temperature, energy storage state (for energy storage system), controllable load state (for controllable load), etc. and other specific parameters corresponding to the first type energy power supply unit. The second unit physical parameters may be physical characteristic parameters or equipment basic parameters of each power supply unit in the second type energy power supply unit. For example, the second unit physical parameters may include unit output power, unit voltage, unit current, fuel consumption rate, equipment temperature and emission parameters, etc. and other specific parameters corresponding to the second type energy power supply unit.

[0034] Among them, the target scheduling total power can be the total electric power that needs to be scheduled and actually output by the first type of energy in the power supply system under the condition that the total scheduling cost of the first type of energy in the power supply system is the lowest within the preset scheduling period in order to provide electricity demand close to the target power grid.

[0035] Optionally, the target dispatching total power of the first type of energy in the power supply system is determined according to the target demand data and the physical parameters of the energy, including: determining the dispatching power value and the second real-time dispatching cost of each second type energy power supply unit in a preset dispatching period according to multiple physical parameters of the second units, and determining the first real-time dispatching cost and dispatching penalty cost of each first type energy power supply unit in the preset dispatching period according to multiple physical parameters of the first units; obtaining a reference power corresponding to the first type of energy according to the first constraint, multiple dispatching power values, the first real-time dispatching cost, the second real-time dispatching cost, the dispatching penalty cost, the number of first type energy power supply units and the number of second type energy power supply units; obtaining the equivalent net load of the first type of energy and the adjustable power of the adjustable units in the first type of energy, solving the first objective function according to the first constraint, the equivalent net load and the adjustable power, and obtaining the target dispatching total power of the first type of energy.

[0036] Among them, the dispatch power value may be the electric power that each second type energy power supply unit is scheduled to output during the preset dispatch period. The dispatch power value may be the dispatch power value of each second type energy power supply unit determined based on one or more conditions such as the power demand of the power grid, the physical parameters of the unit, or the dispatch strategy. The second real-time dispatch cost may be the cost incurred by using the second type energy power supply unit to generate electricity during the real-time dispatch process. For example, at least one of the fuel cost, equipment maintenance cost, and operating cost. It should be noted that since the second type of energy (such as coal power, gas power, and hydropower) can usually provide stable power and the dispatch cost is easier to calculate, these costs can be estimated more accurately. The first real-time dispatch cost may refer to the cost incurred by using the first type energy power supply unit during the real-time dispatch process. The first real-time dispatch cost may include at least one of the costs such as equipment depreciation, maintenance costs, charging and discharging costs of the energy storage system, or dispatch costs of controllable loads. Since the power output of the first type of energy fluctuates greatly and the dispatch cost calculation is more complicated, these costs may be difficult to accurately estimate. The dispatch penalty cost may be the additional cost incurred by the first type of energy when the first type of energy power supply unit fails to output the specified power according to the dispatch plan. The dispatch penalty cost can be used to encourage the power supply units in the first type of energy to operate strictly according to the dispatch plan to ensure the stability and reliability of the power grid.

[0037] Among them, the number of first-type energy power supply units may be the number of power supply units in the first-type energy. The number of second-type energy power supply units may be the number of power supply units in the second-type energy. The equivalent net load of the first-type energy may be the net load in the first-type energy after excluding the output of non-adjustable units such as wind and solar, that is, the load that requires the adjustable units in the first-type energy to output during the preset scheduling period. The adjustable units in the first-type energy may be units that can perform power regulation in the first-type energy, such as adjustable units such as micro-turbine units or energy storage units in the first-type energy. The adjustable power of the adjustable units in the first-type energy may be the real-time power of the adjustable units in the first-type energy at different times within the preset adjustment period, which may be a variable in the scheduling process. By adjusting its value, the scheduling cost of the power supply system can be minimized.

[0038] The first objective function may be a mathematical expression for minimizing the dispatch cost of the first type of energy. Optionally, the first objective function may be expressed by the following formula:

[0039]

[0040] Among them, c * (t, ΔP Grid (t)) is the first objective function of the first type of energy, C is the dispatch cost of the first type of energy, ΔPGrid (t) is the target dispatching total power, The real-time power of the first type of energy that satisfies the minimum dispatch cost;

[0041] The real-time power of the first type of energy that satisfies the minimum scheduling cost is determined by the following formula:

[0042]

[0043] Among them, P g (t) is the power of the adjustable unit in the first type of energy at time t, arg min is the variable P when the scheduling cost C reaches the minimum value g The value of (t).

[0044] The first constraint condition may be a constraint condition for ensuring the power balance of the power supply system and meeting other operation requirements. Optionally, the first constraint condition may be expressed by the following formula:

[0045]

[0046] Among them, ΔP Grid (t) is the real-time dispatch power, that is, the target dispatch total power, It is the equivalent net load, which is the net load obtained by deducting the output of the non-adjustable units in the first type of energy from the total load of the first type of energy.

[0047] The target dispatching total power refers to the total power that the first type of energy in the power supply system needs to be dispatched and actually output in order to provide power demand close to the target power grid and minimize the dispatching cost of the first type of energy within the preset dispatching period. The target dispatching total power can be obtained by solving the first objective function while satisfying the first constraint condition, and is the total power that the first type of energy needs to be dispatched and actually output with the lowest dispatching cost of the first type of energy.

[0048] Optionally, the total dispatch cost can be obtained according to the first constraint, multiple dispatch power values, the first real-time dispatch cost, the second real-time dispatch cost, the dispatch penalty cost, the number of first-type energy power supply units, and the number of second-type energy power supply units by the following formula, and the reference power with the lowest dispatch cost of the first-type energy can be obtained by solving the lowest total dispatch cost of the power supply system:

[0049] minC=C TPP +C VPP

[0050]

[0051] Among them, minC is the minimum dispatching cost of the power supply system, CTPP is the total dispatch cost of the second type of energy, C VPP is the total dispatch cost of the second type of energy, N TPP is the number of second type energy supply units, T is the duration corresponding to the preset scheduling period, is the second real-time dispatch cost of the i-th second-type energy power supply unit in the second-type energy at time t, δp i (t) is the dispatching power value of the i-th second-type energy power supply unit in the second-type energy at time t, N VPP The number of first-type energy supply units, net C，i is the first real-time dispatch cost of the i-th first-type energy power supply unit in the first-type energy at time t, λ f is the scheduling penalty cost, net A，i It is the participation decision variable of the i-th first-type energy power supply unit in the first-type energy. It is 1 when participating in the dispatch and 0 when not participating.

[0052] By obtaining the target electricity demand data of the target power grid during the preset scheduling period and the energy physical parameters of the power supply system, and then determining the target scheduling total power of the first type of energy in the power supply system, it is possible to ensure that the scheduling cost of the power supply system is minimized, and then optimize the scheduling strategy of the first type of energy to minimize the scheduling cost of the power supply system.

[0053] Optionally, after determining the reference power corresponding to the first type of energy, a real-time scheduling instruction of the first type of energy corresponding to the reference power may be generated, and a scheduling cost corresponding to the real-time scheduling instruction of the first type of energy may be obtained by mapping through a pre-built mapping model. Exemplarily, the mapping model may be represented by the following formula:

[0054] {t, ΔP Grid (t)}→{c * (t, ΔP Grid (t))}

[0055] Optionally, after determining the reference power corresponding to the first type of energy and generating the real-time dispatch instruction of the first type of energy corresponding to the reference power, the real-time dispatch instruction can also be analyzed by a pre-built feasibility analysis model to determine whether the first type of energy in the power supply system can fully respond to the real-time dispatch instruction requirements of the power supply system. Exemplarily, the feasibility analysis model can analyze the real-time dispatch instruction by the following formula:

[0056] {t, ΔP Grid (t)}→{A(ΔP Grid (t))}

[0057] Where A(ΔP Grid(t)) represents the real-time dispatching instruction of the power grid ΔP Grid (t) Is it feasible? The calculation formula is as follows:

[0058] A(ΔP Grid (t)) = f A (minC(ΔP Grid (t)))

[0059] Among them, if ΔP is given Grid (t) and the first objective function has a solution, then f A (minC(ΔP Grid (t))) is 1, otherwise it is 0. C is the total real-time optimal dispatch cost of the adjustable units in the first type of energy, which is the real-time power of the adjustable units in the first type of energy. function.

[0060] Optionally, since the output of new energy in the first type of energy is time-varying, during real-time operation, the first type of energy is packaged and trained for its scheduling characteristics for a certain period of time in the future based on the real-time operating status every real-time scheduling cycle (usually 5 minutes or 15 minutes) using the rolling updated internal prediction data of the first type of energy, thereby continuously improving the accuracy of scheduling characteristic packaging.

[0061] S120. Determine the reference power and reference cost corresponding to each first type energy power supply unit according to the target dispatching total power and multiple physical parameters of the first units.

[0062] The reference power may be the power corresponding to the minimum dispatching cost of each first-type energy power supply unit in the first-type energy, which is determined after comprehensive calculation based on the physical parameters of multiple first-type energy units in the first-type energy. The reference cost may be the unit power cost corresponding to the minimum dispatching cost of each first-type energy power supply unit in the first-type energy, which is determined based on the reference power of each first-type energy power supply unit in the first-type energy after obtaining the reference power of each first-type energy power supply unit in the first-type energy.

[0063] Optionally, determining a reference power and a reference cost corresponding to each first-type energy power supply unit based on a target scheduling total power and multiple physical parameters of the first units may include: determining the reference power corresponding to each first-type energy power supply unit based on the target scheduling total power and multiple physical parameters of the first units; determining a first scheduling cost when each first-type energy power supply unit participates in power supply system scheduling and a second scheduling cost when not participating in power supply system scheduling based on multiple physical parameters of the first units; determining a reference cost corresponding to each first-type energy power supply unit based on the reference power, first scheduling cost and second scheduling cost corresponding to each first-type energy power supply unit.

[0064] The first dispatching cost may be the total dispatching cost of the first type of energy when any one of the first type of energy power supply units in the first type of energy participates in the power supply system dispatching. The second dispatching cost may be the total dispatching cost of the first type of energy when any one of the first type of energy power supply units in the first type of energy does not participate in the power supply system dispatching.

[0065] Optionally, the reference power corresponding to each first type energy power supply unit can be determined according to the target dispatch total power and the physical parameters of multiple units by the following formula:

[0066]

[0067] in, is the reference power of the i-th first type energy power supply unit at time t;

[0068] Optionally, the reference cost corresponding to each first-type energy power supply unit can be determined according to the reference power corresponding to each first-type energy power supply unit, the first scheduling cost and the second scheduling cost by the following formula:

[0069]

[0070] Among them, C' is the second scheduling cost, C is the first scheduling cost, is the reference cost of the i-th first-type energy power supply unit at time t, is the reference power of the i-th first type energy power supply unit at time t.

[0071] By determining the reference power corresponding to each first-type energy power supply unit according to the target scheduling total power and multiple physical parameters of the first units; determining the first scheduling cost of each first-type energy power supply unit when participating in the power supply system scheduling and the second scheduling cost when not participating in the power supply system scheduling according to the multiple physical parameters of the first units; determining the reference cost corresponding to each first-type energy power supply unit according to the reference power, the first scheduling cost and the second scheduling cost corresponding to each first-type energy power supply unit, it is possible to take into account the scheduling cost of each first-type energy power supply unit in the first-type energy while considering the lowest scheduling cost of the first-type energy, and can improve the scheduling efficiency while reducing the scheduling cost of the first-type energy and each first-type energy power supply unit in the first-type energy.

[0072] S130. Determine a target dispatching power corresponding to each first-type energy power supply unit according to a plurality of reference powers and a plurality of reference costs, and dispatch the first-type energy power supply unit according to the target dispatching power.

[0073] Among them, the target scheduling power can be the electric power that each first type energy power supply unit should actually output during a preset scheduling period, determined based on a combination of multiple reference powers and multiple reference costs.

[0074] By determining the target dispatching power of each first-type energy power supply unit, and sending the target dispatching power of each first-type energy power supply unit to the corresponding first-type energy power supply unit, the first-type energy power supply unit is dispatched according to the target dispatching power. The power demand of the target power grid can be met, while the dispatching cost of the first-type energy is reduced and the dispatching efficiency is improved.

[0075] The embodiment of the present invention obtains the target power demand data of the target power grid in the preset scheduling period and the energy physical parameters of the power supply system, determines the target scheduling total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, and can determine the corresponding scheduling power according to the physical parameter information of the power supply system, thereby improving the scheduling efficiency and reducing the scheduling cost. The first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include the first unit physical parameters corresponding to each first type of energy power supply unit. By determining the reference power and reference cost corresponding to each first type of energy power supply unit according to the target scheduling total power and multiple first unit physical parameters, and determining the target scheduling power corresponding to each first type of energy power supply unit according to multiple reference powers and multiple reference costs, the first type of energy power supply unit is scheduled according to the target scheduling power. It can reduce the scheduling cost of each distributed resource in the power supply system and improve the resource utilization rate of each distributed resource.

[0076] Embodiment 2

[0077] Figure 2 This is a flowchart of another distributed resource optimization scheduling method provided by the second embodiment of the present invention. Based on the above embodiment, this embodiment further refines the target scheduling power corresponding to each first type energy power supply unit according to multiple reference powers and multiple reference costs. Figure 2 As shown, the method may include:

[0078] S210. Obtain the target electricity demand data of the target power grid during a preset scheduling period and the energy physical parameters of the power supply system, and determine the target scheduling total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, wherein the first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include first unit physical parameters corresponding to each first type of energy power supply unit.

[0079] S220. Determine the reference power and reference cost corresponding to each first type energy power supply unit according to the target dispatching total power and multiple physical parameters of the first units.

[0080] S230, obtaining the total dispatch cost of the second energy of the second type of energy in the power supply system and the dispatch decision variables and participating decision variables of each first type energy power supply unit in the first type of energy.

[0081] Among them, the scheduling decision variable can be the variable value of each first-type energy power supply unit in the first-type energy participating in or not participating in the first-type energy scheduling. For example, the scheduling decision variable can be set to 1 when participating in the grid scheduling is selected, and the scheduling decision variable can be set to 0 when participating in the grid scheduling is not selected. The scheduling decision variable can be determined by the scheduling cost of each first-type energy power supply unit and the total cost of the first-type energy scheduling, or can be determined by other methods. The participation decision variable can be the variable value of each first-type energy power supply unit in the first-type energy participating in or not participating in the first-type energy scheduling. For example, when the first-type energy power supply unit participates in the first-type energy scheduling, its corresponding participation decision variable can be set to 1, and when the first-type energy power supply unit does not participate in the first-type energy scheduling, its corresponding participation decision variable can be set to 0.

[0082] Optionally, the participating decision variables of each first-type energy power supply unit in the first-type energy can be determined by the following formula:

[0083]

[0084] in, is the decision variable of the i-th first-type energy power supply unit in the first-type energy at time t, is the reference cost of the i-th first-type energy power supply unit in the first-type energy at time t, is the real-time dispatch cost of the i-th first-type energy power supply unit in the first-type energy, It is the reference power of the i-th first-type energy power supply unit in the first-type energy at time t.

[0085] S240. Solve the second objective function according to the total dispatch cost of the second energy, the dispatch decision variables of each first-type energy power supply unit, the participating decision variables, the reference power, the reference cost and the second constraint condition to obtain the target dispatch power corresponding to each first-type energy power supply unit, and dispatch the first-type energy power supply unit according to the target dispatch power.

[0086] Optionally, the second objective function can be expressed by the following formula:

[0087]

[0088] Among them, C TPP is the total dispatch cost of the second energy source, NVPP The number of units of the first type of energy supply units, is the decision variable of the i-th first-type energy power supply unit in the first-type energy at time t, is the scheduling decision variable of the i-th first-type energy power supply unit in the first-type energy at time t, is the reference cost of the i-th first-type energy power supply unit in the first-type energy at time t, is the reference power of the i-th first-type energy power supply unit in the first-type energy at time t;

[0089] Optionally, the second constraint can be expressed by the following formula:

[0090]

[0091] Among them, N TPP is the number of the second type of energy supply units, δP i (t) is the dispatching power of the i-th second type energy power supply unit at time t, Real-time dispatch of total power for the power supply system.

[0092] By obtaining the total dispatching cost of the second energy of the second type of energy in the power supply system and the dispatching decision variables and participating decision variables of each first type energy power supply unit in the first type energy, and solving the second objective function according to the total dispatching cost of the second energy, the dispatching decision variables of each first type energy power supply unit, participating decision variables, reference power, reference cost and the second constraint condition, the target dispatching power corresponding to each first type energy power supply unit is obtained, which can meet the electricity demand of the target power grid, and at the same time reduce the dispatching cost of the first type energy and each first type energy power supply unit in the first type energy, thereby improving the dispatching efficiency.

[0093] The embodiment of the present invention obtains the target power demand data of the target power grid in the preset scheduling period and the energy physical parameters of the power supply system, determines the target scheduling total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, and can determine the corresponding scheduling power according to the physical parameter information of the power supply system, thereby improving the scheduling efficiency and reducing the scheduling cost. By determining the reference power and reference cost corresponding to each first type energy power supply unit according to the target scheduling total power and the physical parameters of multiple first units, and determining the target scheduling power corresponding to each first type energy power supply unit according to multiple reference powers and multiple reference costs, the first type energy power supply unit is scheduled according to the target scheduling power. It is possible to reduce the scheduling cost of each first type energy power supply unit, the second type energy power supply unit and the entire power supply system in the power supply system, and improve the resource utilization rate of each distributed resource.

[0094] Embodiment 3

[0095] Figure 3 This is a schematic diagram of the structure of a distributed resource optimization scheduling device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a target scheduling total power determination module 310, a reference data determination module 320, and a scheduling module 330.

[0096] Specifically, the target dispatching total power determination module 310 can be used to obtain the target power demand data of the target power grid in the preset dispatching period and the energy physical parameters of the power supply system, and determine the target dispatching total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, wherein the first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include the first unit physical parameters corresponding to each first type of energy power supply unit; the reference data determination module 320 can be used to determine the reference power and reference cost corresponding to each first type of energy power supply unit according to the target dispatching total power and multiple first unit physical parameters; the dispatching module 330 can be used to determine the target dispatching power corresponding to each first type of energy power supply unit according to multiple reference powers and multiple reference costs, and dispatch the first type of energy power supply unit according to the target dispatching power. The power supply system also includes a second type of energy, the second type of energy includes at least one second type of energy power supply unit, and the energy physical parameters also include the second unit physical parameters corresponding to each second type of energy power supply unit.

[0097] Furthermore, the target scheduling total power determination module 310 can be specifically used to: determine the scheduling power value and the second real-time scheduling cost of each second type energy power supply unit in a preset scheduling period according to multiple second unit physical parameters, and determine the first real-time scheduling cost and scheduling penalty cost of each first type energy power supply unit in the preset scheduling period according to multiple first unit physical parameters; solve the first objective function according to the first constraint condition, multiple scheduling power values, the first real-time scheduling cost, the second real-time scheduling cost, the scheduling penalty cost, the number of first type energy power supply units and the number of second type energy power supply units to obtain a reference power corresponding to the first type of energy; obtain the equivalent net load of the first type of energy and the adjustable power of the adjustable units in the first type of energy, and solve the first objective function according to the first constraint condition, the equivalent net load and the adjustable power to obtain the target scheduling total power of the first type of energy.

[0098] Furthermore, the first objective function can be expressed by the following formula:

[0099]

[0100] Among them, c * (t, ΔP Grid(t)) is the first objective function of the first type of energy, C is the dispatch cost of the first type of energy, ΔP Grid (t) is the target dispatching total power, The real-time power of the first type of energy that satisfies the minimum dispatch cost;

[0101] The real-time power of the first type of energy that satisfies the minimum scheduling cost is determined by the following formula:

[0102]

[0103] Among them, P g (t) is the power of the adjustable unit in the first type of energy at time t, arg min is the variable P when the scheduling cost C reaches the minimum value g The value of (t).

[0104] Furthermore, the first constraint can be expressed by the following formula:

[0105]

[0106] Among them, ΔP Grid (t) is the reference power, It is the equivalent net load, which is the net load obtained by deducting the output of the non-adjustable units in the first type of energy from the total load of the first type of energy.

[0107] Furthermore, the reference data determination module 320 is specifically used to: determine the reference power corresponding to each first-type energy power supply unit according to the target scheduling total power and multiple unit physical parameters; determine the first scheduling cost of each first-type energy power supply unit when participating in the power supply system scheduling and the second scheduling cost when not participating in the power supply system scheduling according to multiple first-type unit physical parameters; determine the reference cost corresponding to each first-type energy power supply unit according to the reference power, the first scheduling cost and the second scheduling cost corresponding to each first-type energy power supply unit.

[0108] Furthermore, the reference data determination module 320 is further specifically used to: determine the reference power corresponding to each first type energy power supply unit according to the target dispatching total power and the physical parameters of the multiple units through the following formula:

[0109]

[0110] in, is the reference power of the i-th first type energy power supply unit at time t;

[0111] Further, the reference data determination module 320 is further specifically used to: determine the reference cost corresponding to each first type energy power supply unit according to the reference power corresponding to each first type energy power supply unit, the first scheduling cost and the second scheduling cost through the following formula:

[0112]

[0113] Among them, C' is the second scheduling cost, C is the first scheduling cost, is the reference cost of the i-th first-type energy power supply unit at time t, is the reference power of the i-th first type energy power supply unit at time t.

[0114] Furthermore, the scheduling module 330 is specifically used to: obtain the total scheduling cost of the second energy of the second type of energy in the power supply system and the scheduling decision variables and participating decision variables of each first type energy power supply unit in the first type of energy; solve the second objective function according to the total scheduling cost of the second energy, the scheduling decision variables, participating decision variables, reference power, reference cost and the second constraint condition of each first type energy power supply unit to obtain the target scheduling power corresponding to each first type energy power supply unit.

[0115] Furthermore, the second objective function can be expressed by the following formula:

[0116]

[0117] Among them, C TPP is the total dispatch cost of the second energy source, N VPP The number of units of the first type of energy supply units, is the decision variable of the i-th first-type energy power supply unit in the first-type energy at time t, is the scheduling decision variable of the i-th first-type energy power supply unit in the first-type energy at time t, is the reference cost of the i-th first-type energy power supply unit in the first-type energy at time t, It is the reference power of the i-th first-type energy power supply unit in the first-type energy at time t.

[0118] Furthermore, the second constraint can be expressed by the following formula:

[0119]

[0120] Among them, N TPP is the number of the second type of energy supply units, δP i (t) is the dispatching power of the i-th second type energy power supply unit at time t, Real-time dispatch of total power for the power supply system.

[0121] The above-mentioned distributed resource optimization scheduling device can execute the distributed resource optimization scheduling method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in this embodiment, please refer to the distributed resource optimization scheduling method provided by any embodiment of the present invention.

[0122] Since the distributed resource optimization scheduling device introduced above is a device that can execute the distributed resource optimization scheduling method in the embodiment of the present invention, based on the distributed resource optimization scheduling method introduced in the embodiment of the present invention, the technical personnel of the field can understand the specific implementation of the distributed resource optimization scheduling device of the present embodiment and its various variations, so how the distributed resource optimization scheduling device implements the distributed resource optimization scheduling method in the embodiment of the present invention is not introduced in detail here. As long as the technical personnel of the field implement the device used by the distributed resource optimization scheduling method in the embodiment of the present invention, it belongs to the scope of protection of this application.

[0123] Embodiment 4

[0124] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0125] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0126] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0127] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the optimization scheduling method of distributed resources.

[0128] In some embodiments, the method for optimizing the scheduling of distributed resources may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for optimizing the scheduling of distributed resources described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for optimizing the scheduling of distributed resources in any other appropriate manner (e.g., by means of firmware).

[0129] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0130] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0131] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0132] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0133] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0134] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0135] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0136] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed resource optimization scheduling method, characterized in that: include: Obtain target power demand data of the target power grid in a preset scheduling period and energy physical parameters of the power supply system, and determine the target scheduling total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters, wherein the first type of energy includes at least one first type of energy power supply unit, and the energy physical parameters include first unit physical parameters corresponding to each of the first type of energy power supply units; Determine the reference power and reference cost corresponding to each of the first type energy power supply units according to the target dispatching total power and a plurality of physical parameters of the first units; The target dispatching power corresponding to each of the first-type energy power supply units is determined according to a plurality of reference powers and a plurality of reference costs, and the first-type energy power supply units are dispatched according to the target dispatching power.

2. The method according to claim 1, characterized in that: The power supply system further includes a second type of energy, the second type of energy includes at least one second type of energy power supply unit, and the energy physical parameters further include second unit physical parameters corresponding to each second type of energy power supply unit; determining the target dispatching total power of the first type of energy in the power supply system according to the target demand data and the energy physical parameters includes: Determine the dispatch power value and the second real-time dispatch cost of each second type energy power supply unit in the preset dispatch period according to the plurality of physical parameters of the second units, and determine the first real-time dispatch cost and the dispatch penalty cost of each first type energy power supply unit in the preset dispatch period according to the plurality of physical parameters of the first units; Obtain a reference power corresponding to the first type of energy according to the first constraint condition, the multiple dispatch power values, the first real-time dispatch cost, the second real-time dispatch cost, the dispatch penalty cost, the number of first type energy power supply units and the number of second type energy power supply units; Obtain the equivalent net load of the first type of energy and the adjustable power of the adjustable units within the first type of energy, solve the first objective function according to the first constraint condition, the equivalent net load and the adjustable power, and obtain the target dispatching total power of the first type of energy.

3. The method according to claim 2, characterized in that The first objective function is expressed by the following formula: Among them, c * (t, ΔP Grid (t)) is the first objective function of the first type of energy, C is the dispatch cost of the first type of energy, ΔP Grid (t) is the target dispatching total power, The real-time power of the first type of energy that satisfies the minimum dispatch cost; The real-time power of the first type of energy that satisfies the minimum scheduling cost is determined by the following formula: Among them, P g (t) is the power of the adjustable unit in the first type of energy at time t, arg min is the variable P when the scheduling cost C reaches the minimum value g The value of (t).

4. The method according to claim 2, characterized in that: The first constraint is expressed by the following formula: Among them, ΔP Grid (t) is the reference power, The equivalent net load is the net load obtained by deducting the output of the non-adjustable units in the first type of energy from the total load of the first type of energy.

5. The method according to claim 1, characterized in that The determining, according to the target dispatched total power and the physical parameters of the plurality of the first units, the reference power and the reference cost corresponding to each of the first type energy power supply units comprises: Determine the reference power corresponding to each of the first type energy power supply units according to the target dispatching total power and a plurality of physical parameters of the first units; Determine, based on a plurality of physical parameters of the first units, a first dispatching cost for each of the first type energy power supply units when participating in power supply system dispatching and a second dispatching cost when not participating in power supply system dispatching; The reference cost corresponding to each of the first-type energy power supply units is determined according to the reference power corresponding to each of the first-type energy power supply units, the first scheduling cost and the second scheduling cost.

6. The method according to claim 5, characterized in that The reference power corresponding to each of the first type energy power supply units is determined according to the target dispatched total power and a plurality of physical parameters of the first units by the following formula: in, is the reference power of the i-th first type energy power supply unit at time t.

7. The method according to claim 5, characterized in that The reference cost corresponding to each of the first type of energy supply units is determined according to the reference power corresponding to each of the first type of energy supply units, the first scheduling cost and the second scheduling cost by the following formula: Wherein, C′ is the second scheduling cost, C is the first scheduling cost, is the reference cost of the i-th first-type energy power supply unit at time t, is the reference power of the i-th first type energy power supply unit at time t.

8. The method according to claim 1, characterized in that: The determining the target dispatching power corresponding to each of the first-type energy power supply units according to the multiple reference powers and the multiple reference costs includes: Obtain the total dispatch cost of the second energy of the second type of energy in the power supply system and the dispatch decision variables and participating decision variables of each of the first type of energy power supply units in the first type of energy; The second objective function is solved according to the total dispatching cost of the second energy, the dispatching decision variables of each first type energy power supply unit, the participating decision variables, the reference power, the reference cost and the second constraint condition to obtain the target dispatching power corresponding to each first type energy power supply unit.

9. The method according to claim 8, characterized in that The second objective function is expressed by the following formula: Among them, C TPP is the total dispatch cost of the second energy source, N VPP The number of units of the first type of energy supply units, is the decision variable of the i-th first-type energy power supply unit in the first-type energy at time t, is the scheduling decision variable of the i-th first-type energy power supply unit in the first-type energy at time t, is the reference cost of the i-th first-type energy power supply unit in the first-type energy at time t, is the reference power of the i-th first-type energy power supply unit in the first-type energy at time t; The second constraint is expressed by the following formula: Among them, N TPP is the number of the second type of energy supply units, δP i (t) is the dispatching power of the i-th second type energy power supply unit at time t, The total power of the power supply system is dispatched in real time.

10. A computer program product comprising computer instructions, characterized in that: When the computer instruction is executed by a processor, the distributed resource optimization scheduling method as described in any one of claims 1 to 9 is implemented.

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