Scheduling control method of multi-energy complementary power generation system and multi-energy complementary power generation system

Abstract

The invention discloses a dispatching control method of a multi-energy complementary power generation system and the multi-energy complementary power generation system, and belongs to the technical field of multi-energy complementary power generation systems. The scheduling control method for the multi-energy complementary power generation system comprises the steps of adjusting an input parameter of a first model by taking the minimum total cost corresponding to the multi-energy complementary power generation system output by the first model as a target, and obtaining a first numerical value of a working parameter corresponding to each distributed power generation device; under the condition that each distributed power generation device operates based on the first numerical value, taking the maximum total revenue corresponding to the energy storage device output by the second model as a target, adjusting the input parameter of the second model, and obtaining a second numerical value of the working parameter corresponding to the energy storage device; and based on the second numerical value of the working parameter corresponding to the energy storage equipment, adjusting the input parameter of the first model. According to the dispatching control method of the multi-energy complementary power generation system, energy waste is effectively reduced, the cost is reduced, and therefore economic benefits are improved.

Description

Technical Field

[0001] The present application belongs to the technical field of multi-energy complementary power generation systems, and in particular, relates to a dispatching control method for a multi-energy complementary power generation system and a multi-energy complementary power generation system. Background Art

[0002] The multi-energy complementary power generation system can provide various forms of energy according to user needs, and combine existing energy, resources and technical conditions to achieve optimal utilization of energy resources. In related technologies, energy storage technology is added to the multi-energy complementary power generation system to establish an economical, environmentally friendly, safe and high-quality energy system. However, the above technology may cause waste in the process of energy resource utilization, resulting in high costs and low economic benefits. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a dispatching control method of a multi-energy complementary power generation system and a multi-energy complementary power generation system, which effectively reduces energy waste, reduces costs, and thus improves economic benefits.

[0004] In a first aspect, the present application provides a dispatching control method for a multi-energy complementary power generation system, wherein the multi-energy complementary power generation system includes an energy storage device and a plurality of distributed power generation devices; the method includes:

[0005] Taking the minimum total cost corresponding to the multi-energy complementary power generation system output by the first model as the goal, adjusting the input parameters of the first model to obtain the first value of the working parameter corresponding to each of the distributed power generation devices; wherein the first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each of the distributed power generation devices and the electricity price information;

[0006] When each of the distributed power generation devices is operated based on the first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device; wherein the second model is pre-constructed based on the working parameter of the energy storage device and the electricity price information;

[0007] Based on the second value of the working parameter corresponding to the energy storage device, the input parameter of the first model is adjusted; the working parameter is used to perform scheduling control on the multi-energy complementary power generation system.

[0008] According to the dispatching and control method of the multi-energy complementary power generation system of the present application, the first value of the working parameter corresponding to the distributed power generation equipment is determined when the total cost corresponding to the multi-energy complementary power generation system obtained by solving the first model is minimized; based on the first value and the second model, the total benefit corresponding to the energy storage equipment is maximized as the goal to solve, and the second value of the working parameter corresponding to the energy storage equipment is obtained when the total benefit is maximized, and the input parameters of the first model are further adjusted based on the second value. The first model corrects the economic cost of the multi-energy complementary power generation system based on the optimization result of the energy storage equipment dispatching strategy of the second model, and optimizes the dispatching strategy of each distributed discharge equipment, so as to determine the multi-energy complementary power generation system. The optimal scheduling strategy for each device in the power generation system. During the optimization process, the first value determined by the first model can be used to optimize the second model, and the second value of the second model can in turn optimize the first model. The two models interact with each other and are optimized repeatedly. On the basis of reducing costs and improving economic benefits, the utilization rate of each distributed discharge device is maximized as much as possible, and when the utilization rate of each distributed discharge device is maximized, the energy storage device is in the best charging and discharging state. The determined optimal scheduling strategy can give priority to the use of clean energy, reduce the phenomenon of abandoned solar and wind power, and effectively reduce energy waste and improve the comprehensive utilization rate of energy while meeting load demand.

[0009] According to the dispatching control method of the multi-energy complementary power generation system of the present application, the input parameters of the first model are adjusted with the goal of minimizing the total cost corresponding to the multi-energy complementary power generation system output by the first model to obtain the first value of the working parameter corresponding to each of the distributed power generation devices, including:

[0010] Determine a first target constraint based on at least one of the upper and lower output limit constraints corresponding to the energy storage device and each of the multiple distributed power generation devices, the total power ramp constraint corresponding to each device, the interactive power constraint between the multi-energy complementary power generation system and the distribution network, and the working time constraint corresponding to each device;

[0011] Based on the first target constraint, with the goal of minimizing the total cost corresponding to the multi-energy complementary power generation system output by the first model, the input parameters of the first model are adjusted to obtain the first values ​​of the working parameters corresponding to each of the distributed power generation devices.

[0012] According to the dispatching control method of the multi-energy complementary power generation system of the present application, the plurality of distributed power generation devices include gas equipment; the first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each of the distributed power generation devices and the electricity price information, and includes:

[0013] Based on the working parameters of the gas equipment and the gas price information, construct a first sub-model for outputting the natural gas consumption cost corresponding to the gas equipment;

[0014] Based on the energy storage device and the operating cost of a target device among the plurality of distributed power generation devices and the operating parameters of the target device, construct a second sub-model for outputting the operating cost of the target device;

[0015] Based on the working parameters of the energy storage device and the electricity price information, constructing a third sub-model for outputting the interaction benefits between the multi-energy complementary power generation system and the distribution network;

[0016] The first model is determined by fusing at least one of the first sub-model, the second sub-model and the third sub-model.

[0017] According to the dispatching control method of the multi-energy complementary power generation system of the present application, when each of the distributed power generation devices is operated based on the first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain the second value of the working parameter corresponding to the energy storage device, including:

[0018] Determining a second target constraint based on at least one of an operation constraint corresponding to the energy storage device and a power constraint at the beginning and end of a scheduling period;

[0019] Based on the second target constraint, with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model, the input parameters of the second model are adjusted to obtain second values ​​of the operating parameters corresponding to the energy storage device.

[0020] According to the dispatching control method of the multi-energy complementary power generation system of the present application, the second model is pre-constructed based on the working parameters of the energy storage device and the electricity price information, and includes:

[0021] It is pre-constructed based on the discharge coefficient of the energy storage device, the coefficient following the real-time electricity price changes, the electricity selling price, the electricity purchasing price, the maximum electricity selling price in a natural day, the maximum electricity purchasing price in a natural day, the charging and discharging state and the charging and discharging power of the energy storage device.

[0022] According to the dispatching control method of the multi-energy complementary power generation system of the present application, the adjusting the input parameter of the first model based on the second value of the working parameter corresponding to the energy storage device includes:

[0023] Taking the minimum total cost of the multi-energy complementary power generation system output by the first model as the goal, taking the second value of the working parameter corresponding to the energy storage device as input, adjusting other input parameters of the first model, and optimizing the first value of the working parameter corresponding to each of the distributed power generation devices;

[0024] When each of the distributed power generation devices is operated based on the optimized first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device;

[0025] In a case where the total benefit is greater than the total benefit of the last optimization, returning to the step of adjusting the input parameters of the first model based on the second value of the working parameter corresponding to the energy storage device;

[0026] When the total benefit is not greater than the total benefit of the last optimization, the optimization is terminated.

[0027] In a second aspect, the present application provides a dispatching control device for a multi-energy complementary power generation system, wherein the multi-energy complementary power generation system includes an energy storage device and a plurality of distributed power generation devices; the device includes:

[0028] A first processing module is used to adjust the input parameters of the first model with the goal of minimizing the total cost corresponding to the multi-energy complementary power generation system output by the first model, so as to obtain a first value of the working parameter corresponding to each of the distributed power generation devices; wherein the first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each of the distributed power generation devices and the electricity price information;

[0029] A second processing module is used to adjust the input parameters of the second model to obtain a second value of the working parameter corresponding to the energy storage device, with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model, when each of the distributed power generation devices is operated based on the first value; wherein the second model is pre-constructed based on the working parameter of the energy storage device and the electricity price information;

[0030] The third processing module is used to adjust the input parameters of the first model based on the second value of the working parameter corresponding to the energy storage device; the working parameter is used to dispatch and control the multi-energy complementary power generation system.

[0031] According to the dispatching control device of the multi-energy complementary power generation system of the present application, the first value of the working parameter corresponding to the distributed power generation equipment is determined when the total cost corresponding to the multi-energy complementary power generation system obtained by solving the first model is minimized; based on the first value and the second model, the total benefit corresponding to the energy storage equipment is maximized to obtain the second value of the working parameter corresponding to the energy storage equipment when the total benefit is maximized, and the input parameters of the first model are further adjusted based on the second value. The first model corrects the economic cost of the multi-energy complementary power generation system based on the optimization result of the energy storage equipment dispatching strategy of the second model, and optimizes the dispatching strategy of each distributed discharge equipment, thereby determining the multi-energy complementary power generation system. The optimal scheduling strategy for each device in the power generation system. During the optimization process, the first value determined by the first model can be used to optimize the second model, and the second value of the second model can in turn optimize the first model. The two models interact with each other and are optimized repeatedly. On the basis of reducing costs and improving economic benefits, the utilization rate of each distributed discharge device is maximized as much as possible, and when the utilization rate of each distributed discharge device is maximized, the energy storage device is in the best charging and discharging state. The determined optimal scheduling strategy can give priority to the use of clean energy, reduce the phenomenon of abandoned solar and wind power, and effectively reduce energy waste and improve the comprehensive utilization rate of energy while meeting load demand.

[0032] In a third aspect, the present application provides a multi-energy complementary power generation system, comprising:

[0033] Energy storage equipment;

[0034] A plurality of distributed power generation devices, each of which is electrically connected to the energy storage device;

[0035] Based on the dispatching control device of the multi-energy complementary power generation system as described in the second aspect, the dispatching control device of the multi-energy complementary power generation system is electrically connected to the energy storage device and each of the distributed power generation devices respectively.

[0036] In a fourth aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the dispatching control method of the multi-energy complementary power generation system as described in the first aspect above is implemented.

[0037] In a fifth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the dispatching control method for a multi-energy complementary power generation system as described in the first aspect above.

[0038] In a sixth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the dispatching control method of the multi-energy complementary power generation system as described in the first aspect above.

[0039] The above one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

[0040] By determining the first value of the working parameter corresponding to the distributed power generation equipment under the condition that the total cost corresponding to the multi-energy complementary power generation system obtained by solving the first model is minimized; based on the first value and the second model, the total benefit corresponding to the energy storage equipment is maximized as the goal to solve, and the second value of the working parameter corresponding to the energy storage equipment under the condition that the total benefit is maximized is obtained, and the input parameters of the first model are further adjusted based on the second value. The first model corrects the economic cost of the multi-energy complementary power generation system based on the optimization result of the energy storage equipment scheduling strategy of the second model, and optimizes the scheduling strategy of each distributed discharge equipment, so as to determine the optimal scheduling strategy of each equipment in the multi-energy complementary power generation system. In the optimization process, the first value determined by the first model can be used to optimize the second model, and the second value of the second model can in turn optimize the first model. The two models interact with each other and are continuously optimized in a circular manner. On the basis of reducing costs and improving economic benefits, the utilization rate of each distributed discharge equipment is maximized as much as possible, and when each distributed discharge equipment is maximized, the energy storage equipment is in the best charging and discharging state. The determined optimal scheduling strategy can give priority to the use of clean energy, reduce the phenomenon of abandoned light and abandoned wind, and effectively reduce energy waste and improve the comprehensive utilization rate of energy under the condition of meeting load demand.

[0041] Furthermore, by selecting one or more of the output upper and lower limit constraints corresponding to the energy storage device and each of the multiple distributed power generation devices, the total power climbing constraints corresponding to each device, the interactive power constraints between the multi-energy complementary power generation system and the distribution network, and the working time constraints corresponding to each device, the first target constraint is determined to ensure that the multi-energy complementary power generation system operates within a safe range based on the first target constraint, and to ensure the economy of each distributed power generation device; the first model is constrained by the constraint conditions in the first target constraint to perform an optimization solution, and the first value of the working parameter corresponding to each distributed power generation device is obtained, thereby effectively improving the solution rate.

[0042] Furthermore, the second model is constrained by the operating constraints corresponding to the energy storage device and the power constraints at the beginning and end of the scheduling cycle to solve the second model, and the second values ​​of the working parameters corresponding to the energy storage device are obtained when the total benefit of the energy storage device is maximized, so that the determined second values ​​are subsequently fed back to the first model to further iterate and optimize the first model, improve the operating stability of the multi-energy complementary power generation system, and improve the economic benefits.

[0043] Furthermore, through the correlation between multiple parameters, multiple sub-models are effectively constructed, and by fusing multiple sub-models, a first model is obtained, and a model for determining the total cost corresponding to the multi-energy complementary power generation system is effectively constructed, so that the input parameters are adjusted based on the first model to determine the specific values ​​of the working parameters of each distributed power generation equipment when the total cost is minimized, and then the scheduling strategy is determined based on the obtained values, thereby improving the rationality and scientific nature of the scheduling strategy formulation, thereby improving the economic benefits of the multi-energy complementary power generation system.

[0044] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0046] Figure 1 It is one of the flow charts of the dispatching control method of the multi-energy complementary power generation system provided in the embodiment of the present application;

[0047] Figure 2 This is the second flow chart of the dispatching control method of the multi-energy complementary power generation system provided in the embodiment of the present application;

[0048] Figure 3 It is a structural schematic diagram of a dispatching control device for a multi-energy complementary power generation system provided in an embodiment of the present application;

[0049] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0051] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0052] In combination with the accompanying drawings, the dispatching control method of the multi-energy complementary power generation system, the dispatching control device of the multi-energy complementary power generation system, the multi-energy complementary power generation system, the electronic device and the readable storage medium provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0053] Among them, the dispatching control method of the multi-energy complementary power generation system can be applied to the terminal, and can be specifically executed by the hardware or software in the terminal.

[0054] The terminal includes but is not limited to portable communication devices such as mobile phones or tablet computers. It should also be understood that in some embodiments, the terminal may not be a portable communication device, but a desktop computer.

[0055] In the following various embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse and a joystick.

[0056] The scheduling and control method for a multi-energy complementary power generation system provided in an embodiment of the present application may be executed by the multi-energy complementary power generation system, or by a scheduling and control device of the multi-energy complementary power generation system arranged on the multi-energy complementary power generation system, or by a server electrically connected (wired or wirelessly connected) to the multi-energy complementary power generation system, or by a user terminal communicatively connected to the multi-energy complementary power generation system, including but not limited to a mobile terminal and a non-mobile terminal.

[0057] like Figure 1 As shown, the dispatching control method of the multi-energy complementary power generation system includes: step 110, step 120 and step 130.

[0058] The multi-energy complementary power generation system may include: energy storage equipment and multiple distributed power generation equipment.

[0059] Step 110, with the goal of minimizing the total cost corresponding to the multi-energy complementary power generation system output by the first model, adjusting the input parameters of the first model to obtain a first value of the working parameter corresponding to each distributed power generation device;

[0060] In this step, the total cost corresponding to the multi-energy complementary power generation system is the cost generated by the multi-energy complementary power generation system.

[0061] The first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each distributed power generation device and the electricity price information.

[0062] The input parameters of the first model are parameters used to determine the total cost corresponding to the multi-energy complementary power generation system.

[0063] The input parameters of the first model may include: operating parameters of the energy storage device, operating parameters of each distributed power generation device and electricity price information.

[0064] Each distributed power generation equipment may be: wind power generation equipment, photovoltaic power generation equipment, gas power generation equipment, etc.

[0065] The operating parameters of the energy storage device include but are not limited to the charge and discharge state and the charge and discharge power.

[0066] The operating parameters of each distributed power generation device include but are not limited to the dispatching and operating conditions of each distributed power generation device.

[0067] Electricity price information includes but is not limited to electricity sales price and electricity purchase price.

[0068] The first value is a specific value of an operating parameter corresponding to each distributed power generation device.

[0069] The first value of the working parameter corresponding to each distributed power generation device is used to characterize the dispatching operation status of each distributed power generation device.

[0070] During the actual implementation process, the input parameters of the first model can be continuously adjusted so that the total cost corresponding to the multi-energy complementary power generation system output by the first model is minimized, so as to obtain the first value of the working parameters corresponding to each distributed power generation equipment corresponding to the minimum total cost.

[0071] Step 120: When each distributed power generation device operates based on the first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device;

[0072] In this step, the second model is pre-constructed based on the operating parameters of the energy storage device and the electricity price information.

[0073] It is understandable that energy storage equipment plays a role in value-added and invisible economic scheduling in multi-energy complementary power generation systems.

[0074] The total income corresponding to the energy storage equipment is the economic benefit brought by the value-added of the energy storage equipment in the multi-energy complementary power generation system.

[0075] The second value is a specific value of an operating parameter corresponding to the energy storage device.

[0076] The second value of the operating parameter corresponding to the energy storage device is used to characterize the charging and discharging state of the energy storage device.

[0077] In the actual implementation process, after obtaining the first value of each distributed power generation device operating based on the minimum total cost, the input parameters of the second model are adjusted based on the first value and the total benefit corresponding to the energy storage device as the maximum target to obtain the second value corresponding to each working parameter of the energy storage device when the energy storage device can obtain the maximum total benefit.

[0078] Step 130: Adjust the input parameters of the first model based on the second value of the operating parameter corresponding to the energy storage device.

[0079] In this step, the operating parameters are used to perform dispatching control on the multi-energy complementary power generation system.

[0080] The working parameters include: working parameters corresponding to distributed power generation equipment and working parameters corresponding to energy storage equipment, etc.

[0081] The first model sends the first value of each distributed power generation device to the second model, and the second model sends the second value of the energy storage device to the first model. The first model adjusts the input parameters of the first model based on the second value, and solves the optimal scheduling strategy of the multi-energy complementary power generation system and the optimal acting point state of the energy storage device through continuous optimization and iteration.

[0082] like Figure 2 As shown, the first value of the working parameter corresponding to each distributed power generation device in the multi-energy complementary power generation system of the upper model (i.e., the first model) is sent to the lower model (i.e., the second model) to optimize the charging and discharging state and the charging and discharging power of the energy storage device based on the first value, and the second value of the working parameter corresponding to the optimal charging and discharging state of the energy storage device is sent to the upper model. Based on the second value, the input parameters of the first model are adjusted to continuously iterate and optimize the first model.

[0083] According to the dispatching and controlling method of the multi-energy complementary power generation system provided in the embodiment of the present application, the first value of the working parameter corresponding to the distributed power generation equipment is determined when the total cost corresponding to the multi-energy complementary power generation system obtained by solving the first model is minimized; based on the first value and the second model, the total benefit corresponding to the energy storage equipment is maximized as the goal to solve, and the second value of the working parameter corresponding to the energy storage equipment is obtained when the total benefit is maximized, and the input parameters of the first model are further adjusted based on the second value. The first model corrects the economic cost of the multi-energy complementary power generation system based on the optimization result of the energy storage equipment dispatching strategy of the second model, and optimizes the dispatching strategy of each distributed discharge equipment, thereby determining The optimal scheduling strategy for each device in the multi-energy complementary power generation system. During the optimization process, the first value determined by the first model can be used to optimize the second model, and the second value of the second model can in turn optimize the first model. The two models interact with each other and are continuously optimized in a cycle. On the basis of reducing costs and improving economic benefits, the utilization rate of each distributed discharge device is maximized as much as possible, and when the utilization rate of each distributed discharge device is maximized, the energy storage device is in the best charging and discharging state. The determined optimal scheduling strategy can give priority to the use of clean energy, reduce the phenomenon of abandoned light and wind, and effectively reduce energy waste and improve the comprehensive utilization rate of energy while meeting load demand.

[0084] In some embodiments, step 130 may further include:

[0085] Taking the minimum total cost corresponding to the multi-energy complementary power generation system output by the first model as the goal, taking the second value of the working parameter corresponding to the energy storage device as input, adjusting other input parameters of the first model, and optimizing the first value of the working parameter corresponding to each distributed power generation device;

[0086] When each distributed power generation device is operated based on the optimized first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device;

[0087] When the total benefit is greater than the total benefit of the last optimization, returning to the step of adjusting the input parameters of the first model based on the second value of the working parameter corresponding to the energy storage device;

[0088] When the total benefit is not greater than the total benefit of the previous optimization, the optimization is terminated.

[0089] In this embodiment, during the actual execution process, the first value of the working parameter corresponding to each distributed power generation device is determined by the first model.

[0090] In the process of determining the first values ​​of the working parameters corresponding to each distributed power generation device, the second values ​​of the working parameters corresponding to the energy storage device are input into the first model, and the minimum total cost corresponding to the multi-energy complementary power generation system output by the first model is used as an adjustment target. After multiple adjustments, if a smaller total cost can no longer be found, the first values ​​of the working parameters corresponding to each distributed power generation device are determined.

[0091] Each distributed power generation device operates based on the first value, and determines a second value of the operating parameter of the energy storage device through the second model.

[0092] In the process of determining the second value of the working parameter corresponding to the energy storage device, the maximum total benefit corresponding to the energy storage device output by the second model is used as an adjustment target. After multiple adjustments, if no greater total benefit can be found, the second value of the working parameter corresponding to the energy storage device is determined, and the second value is sent to the first model. Based on the second value, the input parameter of the first model is adjusted, and this process is repeated continuously to iteratively optimize the first model and the second model.

[0093] During the optimization process, the total revenue output by the second model may continue to increase. When the total revenue output by the second model increases and then starts to decrease, the first value and the second value corresponding to the total revenue before the decrease are determined as the optimal scheduling strategy, and the optimization ends.

[0094] The upper model passes the dispatching and operating conditions of each distributed power generation equipment to the lower model, and the lower model returns the optimized charging and discharging status and charging and discharging power of the energy storage equipment to the upper model for further optimization; then, the upper model corrects the total economic cost of the multi-energy complementary power generation system based on the optimization result of the charging and discharging dispatching strategy of the energy storage equipment by the lower model, and optimizes the dispatching and operating conditions of each distributed power generation equipment, and passes it to the lower layer again; finally, through continuous optimization iterations, the optimal dispatching strategy of the multi-energy complementary power generation system under the optimal economic conditions of the multi-energy complementary power generation system and the optimal charging and discharging status of the energy storage equipment are solved to improve the economic benefits of the system.

[0095] According to the scheduling and control method of a multi-energy complementary power generation system provided in an embodiment of the present application, the second model is optimized by the first value determined by the first model, and the first model is optimized by the second value determined by the second model. The first model and the second model are continuously iterated and optimized until the maximum total benefit is obtained, thereby effectively determining the optimal scheduling strategy, reducing energy waste, and improving the economic benefits of the multi-energy complementary power generation system.

[0096] In some embodiments, step 110 may further include:

[0097] Determine a first target constraint based on at least one of the output upper and lower limit constraints corresponding to the energy storage device and each of the multiple distributed power generation devices, the total power ramp constraint corresponding to each device, the interactive power constraint between the multi-energy complementary power generation system and the distribution network, and the working time constraint corresponding to each device;

[0098] Based on the first objective constraint, with the goal of minimizing the total cost of the multi-energy complementary power generation system output by the first model, the input parameters of the first model are adjusted to obtain the first values ​​of the working parameters corresponding to each distributed power generation device.

[0099] In this embodiment, the upper and lower output limits are constraints set to ensure the economic efficiency of the equipment.

[0100] The output upper and lower limits can be determined based on the following formula:

[0101] P i_min <P i <P i-max

[0102] Among them, P i is the output of the i-th distributed generation equipment; P i-min is the minimum output of distributed generation equipment; P i-max It is the maximum output of distributed power generation equipment.

[0103] The total power ramp constraint is a constraint condition for constraining the rate of each device.

[0104] The total power ramp constraint can be determined based on the following formula:

[0105] P i (t)-P i (t-1)≤P i-up

[0106] P i (t-1)-P i (t)≤P i-down

[0107] Among them, P i (t) is the rate of the i-th distributed generation device at the acquisition time t; P i (t-1) is the rate of the i-th distributed generation device at the collection time t-1; P i-up is the maximum ramp rate of distributed generation equipment; P i_down is the maximum drop rate of distributed generation equipment.

[0108] The interactive power constraint between the multi-energy complementary power generation system and the distribution network is a power constraint condition for the electric energy generated by the multi-energy complementary power generation system to interact through the distribution network.

[0109] The interactive power constraint between the multi-energy complementary power generation system and the distribution network can be determined based on the following formula:

[0110] P ex_min ≤P ex ≤P ex_max

[0111] Among them, P ex is the interaction power between the multi-energy complementary power generation system and the distribution network; P ex_min is the minimum value of the interaction power between the multi-energy complementary power generation system and the distribution network; P ex-max It is the maximum value of the interaction power between the multi-energy complementary power generation system and the distribution network.

[0112] The working time constraint is the operating time constraint of each device.

[0113] The working time constraint can be determined based on the following formula:

[0114]

[0115] in, is the operating time of the i-th distributed discharge device at the t-1-th acquisition time; is the shortest running time preset for the i-th distributed discharge device at each collection time; T i of(t-1) is the downtime duration of the i-th distributed discharge device at the t-1-th acquisition time; is the shortest downtime duration preset for the i-th distributed discharge device at each collection time; U i (t-1) is the start / stop state of the i-th distributed discharge device at the t-1-th acquisition time; U i (t) is the start / stop state of the i-th distributed discharge device at the t-th acquisition moment; U i (t) = 1 means the distributed discharge equipment is in operation, U i (t) = 0 means that the distributed discharge equipment is in shutdown state.

[0116] The first objective constraint is the constraint used to solve the first model.

[0117] In some embodiments, one, two or three of the following can be selected from the upper and lower output limit constraints corresponding to each device in the energy storage device and multiple distributed power generation devices, the total power climbing constraints corresponding to each device, the interactive power constraints between the multi-energy complementary power generation system and the distribution network, and the working time constraints corresponding to each device, and the selected one or more constraints can be determined as the first target constraint.

[0118] Based on the first objective constraint, with the goal of minimizing the total cost of the multi-energy complementary power generation system output by the first model, the input parameters of the first model are adjusted to solve for the first values ​​of the working parameters corresponding to each distributed power generation device.

[0119] According to the dispatching and control method of a multi-energy complementary power generation system provided in an embodiment of the present application, a first target constraint is determined by selecting one or more of the output upper and lower limit constraints corresponding to an energy storage device and each of a plurality of distributed power generation devices, the total power climbing constraint corresponding to each device, the interactive power constraint between the multi-energy complementary power generation system and the distribution network, and the working time constraint corresponding to each device, so as to ensure that the multi-energy complementary power generation system operates within a safe range based on the first target constraint and ensure the economy of each distributed power generation device; the first model is constrained by the constraint conditions in the first target constraint to perform an optimization solution, and a first value of the working parameter corresponding to each distributed power generation device is obtained, thereby effectively improving the solution rate.

[0120] In some embodiments, the plurality of distributed power generation devices include gas equipment; the first model is pre-built based on the working parameters of the energy storage device, the working parameters of each distributed power generation device and the electricity price information, and may further include:

[0121] Based on the working parameters of the gas equipment and the gas price information, a first sub-model for outputting the natural gas consumption cost corresponding to the gas equipment is constructed;

[0122] Based on the operating cost of the target device among the energy storage device and the plurality of distributed power generation devices and the working parameters of the target device, construct a second sub-model for outputting the operating cost of the target device;

[0123] Based on the working parameters of the energy storage equipment and the electricity price information, a third sub-model is constructed to output the interactive benefits between the multi-energy complementary power generation system and the distribution network;

[0124] At least one of the first sub-model, the second sub-model, and the third sub-model is integrated to determine the first model.

[0125] In this embodiment, the gas equipment includes but is not limited to: a gas turbine and a gas boiler.

[0126] The target device is any distributed power generation device among a plurality of distributed power generation devices.

[0127] The first sub-model is used to calculate the natural gas consumption cost.

[0128] In some embodiments, based on the working parameters of the gas equipment and the gas price information, constructing a first sub-model for outputting the natural gas consumption cost corresponding to the gas equipment may also include:

[0129] A first sub-model is constructed based on the first natural gas consumption of the gas turbine in a unit time, the second natural gas consumption of the gas boiler in a unit time, and the gas price information.

[0130] In this embodiment, the first sub-model can be determined based on the following formula:

[0131]

[0132] Among them, F fu Cost of natural gas consumption; is the first natural gas consumption of the gas turbine per unit time; is the second natural gas consumption of the gas boiler per unit time; ρ gas For gas price information.

[0133] The second sub-model is used to calculate the operating cost of the output target equipment.

[0134] The second sub-model can be determined based on the following formula:

[0135]

[0136] Among them, F m is the operating cost of the target device, α i is the operating cost of the i-th distributed generation equipment; P i (t) is the output power of the ith distributed generation device at the tth collection time.

[0137] The third sub-model is used to calculate the interaction benefits between the multi-energy complementary power generation system and the distribution network.

[0138] In some embodiments, based on the working parameters of the energy storage device and the electricity price information, constructing a third sub-model for outputting the interactive benefits between the multi-energy complementary power generation system and the distribution network may also include:

[0139] Based on the working parameters of the energy storage device and the net load shortfall power corresponding to the multi-energy complementary power generation system, the interaction power between the multi-energy complementary power generation system and the distribution network is determined;

[0140] Based on the interactive power and electricity price information, a third sub-model is constructed to output the interactive benefits between the multi-energy complementary power generation system and the distribution network.

[0141] In this embodiment, the interaction power between the multi-energy complementary power generation system and the distribution network can be determined based on the following formula:

[0142]

[0143] Among them, P ex (t) is the interaction power between the multi-energy complementary power generation system and the distribution network; is the charging power of the energy storage device at the collection time t; is the charging state of the energy storage device at the collection time t; is the discharge power of the energy storage device at the acquisition time t; is the discharge state of the energy storage device at the acquisition time t; P lap (t) is the net load shortfall power of the multi-energy complementary power generation system at the acquisition time t.

[0144] The third sub-model can be determined based on the following formula:

[0145]

[0146] Among them, F ex is the interaction benefit between the multi-energy complementary power generation system and the distribution network, ρ se (t) is the electricity price sold by the multi-energy complementary power generation system to the distribution network at the tth collection time; ρ be (t) is the electricity purchase price of the multi-energy complementary power generation system from the distribution network at the tth collection time; P ex (t) is the interaction power between the multi-energy complementary power generation system and the distribution network.

[0147] In the actual implementation process, ex When (t)>0, the multi-energy complementary power generation system sends power to the distribution network; when P ex When (t)<0, the multi-energy complementary power generation system purchases electricity from the distribution network.

[0148] In the actual execution process, the first model can be obtained by fusing the first sub-model, the second sub-model and the third sub-model.

[0149] The first model can be determined based on the following formula:

[0150] minF=F fu +F m -F ex

[0151] Among them, minF is the minimum total cost; F fu is the natural gas consumption cost; F m is the operating cost of the target equipment; F ex It is the interaction power between the multi-energy complementary power generation system and the distribution network.

[0152] In some embodiments, fusing at least one of the first sub-model, the second sub-model, and the third sub-model to determine the first model may further include:

[0153] Obtain the construction cost of the multi-energy complementary power generation system;

[0154] The first model is determined by integrating the first sub-model, the second sub-model, the third sub-model and at least one of the construction costs of the multi-energy complementary power generation system.

[0155] In this embodiment, the first model can be determined based on the following formula:

[0156] minF=F fu +F m -F ex +F ST

[0157] Among them, minF is the minimum total cost; F fu is the natural gas consumption cost; F m is the operating cost of the target equipment; F ex is the interaction power between the multi-energy complementary power generation system and the distribution network; F ST It is the construction cost of multi-energy complementary power generation system.

[0158] According to the dispatching and control method of a multi-energy complementary power generation system provided in an embodiment of the present application, multiple sub-models are effectively constructed through the correlation between multiple parameters, and a first model is obtained by fusing multiple sub-models, so as to effectively construct a model for determining the total cost corresponding to the multi-energy complementary power generation system, so as to adjust the input parameters based on the first model, and determine the specific values ​​of the working parameters of each distributed power generation equipment when the total cost is minimized, so as to determine the dispatching strategy based on the obtained values, improve the rationality and scientific nature of the dispatching strategy formulation, and thus improve the economic benefits of the multi-energy complementary power generation system.

[0159] In some embodiments, the second model is pre-built based on the operating parameters and electricity price information of the energy storage device, and may also include:

[0160] It is pre-constructed based on the discharge coefficient of the energy storage device, the coefficient that follows the real-time electricity price changes, the electricity selling price, the electricity purchasing price, the maximum electricity selling price within a natural day, the maximum electricity purchasing price within a natural day, the charging and discharging status of the energy storage device, and the charging and discharging power.

[0161] In this embodiment, the second model can be determined based on the following formula:

[0162] F ES =F ES_dis +F ES_ch

[0163] Among them, F ES is the total revenue corresponding to the energy storage equipment; F ES_dis F is the discharge income of energy storage equipment; ES_ch Profits from charging energy storage devices.

[0164] Among them, the discharge benefit of energy storage equipment can be determined based on the following formula:

[0165]

[0166] in, A is the discharge income of energy storage equipment; LDP is the correlation coefficient between the discharge state of the energy storage device and the real-time electricity price and load shortage; is the discharge power of the energy storage device at the acquisition time t; is the discharge state of the energy storage device at the acquisition time t; α LDP (t) is the discharge coefficient of the energy storage device; δ dis is the coefficient that follows the real-time electricity price changes in the discharge state; ρ se (t) is the electricity price at the collection time t; ρ se_max It is the maximum electricity selling price in a natural day.

[0167] In the actual implementation process, when the load shortage power of the multi-energy complementary power generation system is large at the time of collection t, α LDP The larger (t) is, the more the energy storage device tends to discharge.

[0168] Among them, the charging income of energy storage equipment can be determined based on the following formula:

[0169]

[0170] Among them, F ES_ch Profit from charging energy storage equipment; B LDP It is the correlation coefficient between the charging state of the energy storage device and the real-time store and load shortage; is the charging power of the energy storage device at the collection time t; is the charging state of the energy storage device at the collection time t; The charging efficiency of the energy storage device; is the discharge efficiency of the energy storage device; ch is the coefficient that follows the real-time electricity price changes under charging state; ρ be (t) is the electricity purchase price at the collection time t; ρ be_max It is the maximum electricity purchase price within a natural day.

[0171] In the actual implementation process, when the load shortage power of the multi-energy complementary power generation system is small at the collection time t, B LDP The larger, the more energy storage devices tend to charge.

[0172] In the actual implementation process, the second model can be determined based on the above formula to obtain the total revenue corresponding to the energy storage device output by the second model.

[0173] According to the dispatching and control method of a multi-energy complementary power generation system provided in an embodiment of the present application, a second model is jointly constructed through multiple working parameters and electricity price information, including the discharge coefficient of the energy storage device, the coefficient that follows the real-time electricity price changes, the electricity selling price, the electricity purchasing price, the maximum electricity selling price within a natural day, the maximum electricity purchasing price within a natural day, the charging and discharging state of the energy storage device, and the charging and discharging power, so as to determine the total revenue of the energy storage device based on the second model, improve the accuracy of the total revenue, and subsequently formulate a reasonable dispatching strategy based on the total revenue, improve energy utilization, and improve economic benefits.

[0174] In some embodiments, step 120 may further include:

[0175] Determining a second target constraint based on at least one of an operation constraint corresponding to the energy storage device and a power constraint at the beginning and end of the scheduling period;

[0176] Based on the second objective constraint, with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model, the input parameters of the second model are adjusted to obtain second values ​​of the working parameters corresponding to the energy storage device.

[0177] In this embodiment, the operation constraint is a constraint condition of the energy storage device during operation.

[0178] The power constraints at the beginning and end of the scheduling period are constraints in the process of scheduling the energy storage equipment.

[0179] The second objective constraint is a constraint used to solve the second model.

[0180] The operation constraints can be determined based on the following formula:

[0181]

[0182] in, is the discharge power of the energy storage device at the acquisition time t; is the minimum discharge power of the energy storage device; is the maximum discharge power of the energy storage device; is the charging power of the energy storage device at the collection time t; The minimum value of charging power for energy storage devices; The maximum value of the charging power of the energy storage device; S ES (t) is the power of the energy storage device at the collection time t; is the minimum value of the energy storage device’s power; is the maximum value of the energy storage device’s power; is the initial capacity of the energy storage device; is the charging power of the energy storage device at the collection time t; is the charging state of the energy storage device at the collection time t; The charging efficiency of the energy storage device; is the discharge power of the energy storage device at the acquisition time t; is the discharge state of the energy storage device at the acquisition time t; is the discharge efficiency of the energy storage device.

[0183] The power constraints at the beginning and end of the scheduling period can be determined based on the following formula:

[0184]

[0185] Among them, S ES (0) is the power of the energy storage device at the time of collection 0; S ES (T) is the remaining power of the energy storage device at the collection time T; 0≤T≤24; is the loss rate of the energy storage equipment; is the charging power of the energy storage device at the collection time t; is the charging state of the energy storage device at the collection time t; The charging efficiency of the energy storage device; is the discharge power of the energy storage device at the acquisition time t; is the discharge state of the energy storage device at the acquisition time t; is the discharge efficiency of the energy storage device.

[0186] In the actual implementation process, the power of the energy storage device is the same at the beginning and end of the scheduling cycle to facilitate the scheduling of the next cycle.

[0187] In some embodiments, a second target constraint can be determined based on the operating constraints corresponding to the energy storage device. Based on the second target constraint, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the operating parameter corresponding to the energy storage device.

[0188] In some embodiments, a second target constraint can be determined based on the power constraint at the beginning and end of the scheduling period corresponding to the energy storage device. Based on the second target constraint, the input parameters of the second model can be adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device.

[0189] In some embodiments, a second target constraint can be determined based on the operating constraints corresponding to the energy storage device and the power constraints at the beginning and end of the scheduling cycle. Based on the second target constraint, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the operating parameter corresponding to the energy storage device.

[0190] According to the scheduling and control method for a multi-energy complementary power generation system provided in an embodiment of the present application, the second model is constrained by the operating constraints corresponding to the energy storage device and the power constraints at the beginning and end of the scheduling period to solve the second model, and the second values ​​of the working parameters corresponding to the energy storage device are obtained when the total benefit of the energy storage device is maximized, so that the determined second values ​​are subsequently fed back to the first model to further iterate and optimize the first model, thereby improving the operating stability of the multi-energy complementary power generation system and improving the economic benefits.

[0191] The dispatching control method of the multi-energy complementary power generation system provided in the embodiment of the present application can be executed by a dispatching control device of the multi-energy complementary power generation system. In the embodiment of the present application, the dispatching control device of the multi-energy complementary power generation system executing the dispatching control method of the multi-energy complementary power generation system is taken as an example to illustrate the dispatching control device of the multi-energy complementary power generation system provided in the embodiment of the present application.

[0192] The embodiment of the present application also provides a dispatching control device for a multi-energy complementary power generation system.

[0193] like Figure 3 As shown, the dispatching control device of the multi-energy complementary power generation system includes: a first processing module 310 , a second processing module 320 and a third processing module 330 .

[0194] The first processing module 310 is used to adjust the input parameters of the first model with the goal of minimizing the total cost corresponding to the multi-energy complementary power generation system output by the first model, and obtain the first value of the working parameter corresponding to each distributed power generation device; wherein the first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each distributed power generation device and the electricity price information;

[0195] The second processing module 320 is used to adjust the input parameters of the second model to obtain a second value of the working parameter corresponding to the energy storage device, with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model, when each distributed power generation device is operated based on the first value; wherein the second model is pre-constructed based on the working parameter of the energy storage device and the electricity price information;

[0196] The third processing module 330 is used to adjust the input parameters of the first model based on the second value of the working parameter corresponding to the energy storage device; the working parameter is used to perform scheduling control on the multi-energy complementary power generation system.

[0197] According to the dispatching and controlling device of the multi-energy complementary power generation system provided by the embodiment of the present application, the first value of the working parameter corresponding to the distributed power generation equipment is determined when the total cost corresponding to the multi-energy complementary power generation system obtained by solving the first model is minimized; based on the first value and the second model, the total benefit corresponding to the energy storage equipment is maximized as the goal to solve, and the second value of the working parameter corresponding to the energy storage equipment is obtained when the total benefit is maximized, and the input parameters of the first model are further adjusted based on the second value. The first model corrects the economic cost of the multi-energy complementary power generation system based on the optimization result of the energy storage equipment dispatching strategy of the second model, and optimizes the dispatching strategy of each distributed discharge equipment, thereby determining The optimal scheduling strategy for each device in the multi-energy complementary power generation system. During the optimization process, the first value determined by the first model can be used to optimize the second model, and the second value of the second model can in turn optimize the first model. The two models interact with each other and are continuously optimized in a cycle. On the basis of reducing costs and improving economic benefits, the utilization rate of each distributed discharge device is maximized as much as possible, and when the utilization rate of each distributed discharge device is maximized, the energy storage device is in the best charging and discharging state. The determined optimal scheduling strategy can give priority to the use of clean energy, reduce the phenomenon of abandoned light and wind, and effectively reduce energy waste and improve the comprehensive utilization rate of energy while meeting load demand.

[0198] In some embodiments, the first processing module 310 may also be used to:

[0199] Determine a first target constraint based on at least one of the output upper and lower limit constraints corresponding to the energy storage device and each of the multiple distributed power generation devices, the total power ramp constraint corresponding to each device, the interactive power constraint between the multi-energy complementary power generation system and the distribution network, and the working time constraint corresponding to each device;

[0200] Based on the first objective constraint, with the goal of minimizing the total cost of the multi-energy complementary power generation system output by the first model, the input parameters of the first model are adjusted to obtain the first values ​​of the working parameters corresponding to each distributed power generation device.

[0201] In some embodiments, the plurality of distributed power generation devices include gas-fired devices; the first processing module 310 may also be used to:

[0202] Based on the working parameters of the gas equipment and the gas price information, a first sub-model for outputting the natural gas consumption cost corresponding to the gas equipment is constructed;

[0203] Based on the operating cost of the target device among the energy storage device and the plurality of distributed power generation devices and the working parameters of the target device, construct a second sub-model for outputting the operating cost of the target device;

[0204] Based on the working parameters of the energy storage equipment and the electricity price information, a third sub-model is constructed to output the interactive benefits between the multi-energy complementary power generation system and the distribution network;

[0205] At least one of the first sub-model, the second sub-model, and the third sub-model is integrated to determine the first model.

[0206] In some embodiments, the second processing module 320 may also be used to:

[0207] Determining a second target constraint based on at least one of an operation constraint corresponding to the energy storage device and a power constraint at the beginning and end of the scheduling period;

[0208] Based on the second objective constraint, with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model, the input parameters of the second model are adjusted to obtain second values ​​of the working parameters corresponding to the energy storage device.

[0209] In some embodiments, the second processing module 320 may also be used to:

[0210] It is pre-constructed based on the discharge coefficient of the energy storage device, the coefficient that follows the real-time electricity price changes, the electricity selling price, the electricity purchasing price, the maximum electricity selling price within a natural day, the maximum electricity purchasing price within a natural day, the charging and discharging status of the energy storage device, and the charging and discharging power.

[0211] In some embodiments, the third processing module 330 may also be used to:

[0212] Taking the minimum total cost corresponding to the multi-energy complementary power generation system output by the first model as the goal, taking the second value of the working parameter corresponding to the energy storage device as input, adjusting other input parameters of the first model, and optimizing the first value of the working parameter corresponding to each distributed power generation device;

[0213] When each distributed power generation device is operated based on the optimized first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device;

[0214] When the total benefit is greater than the total benefit of the last optimization, returning to the step of adjusting the input parameters of the first model based on the second value of the working parameter corresponding to the energy storage device;

[0215] When the total benefit is not greater than the total benefit of the previous optimization, the optimization is terminated.

[0216] The dispatching control device of the multi-energy complementary power generation system in the embodiment of the present application can be a multi-energy complementary power generation system, or an electronic device connected to the multi-energy complementary power generation system, or a component in the multi-energy complementary power generation system or the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or it can be other devices other than the terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0217] The dispatching control device of the multi-energy complementary power generation system in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0218] The dispatching control device of the multi-energy complementary power generation system provided in the embodiment of the present application can achieve Figure 1 to Figure 2 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0219] In some embodiments, Figure 4 As shown, an embodiment of the present application also provides an electronic device 400, including a processor 401, a memory 402, and a computer program stored in the memory 402 and executable on the processor 401. When the program is executed by the processor 401, each process of the above-mentioned dispatching control method embodiment of the multi-energy complementary power generation system is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0220] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0221] The embodiment of the present application also provides a multi-energy complementary power generation system.

[0222] In some embodiments, the multi-energy complementary power generation system includes: an energy storage device, a plurality of distributed power generation devices, and a dispatching control device based on the multi-energy complementary power generation system as described in any of the above embodiments.

[0223] In this embodiment, each distributed power generation device is electrically connected to the energy storage device.

[0224] In some embodiments, the plurality of distributed power generation devices may include at least one of a wind power generation device, a photovoltaic power generation device, and a gas power generation device.

[0225] In this embodiment, the gas equipment may also include: a gas turbine and a gas boiler, etc.

[0226] According to the multi-energy complementary power generation system provided in the embodiment of the present application, the first value of the working parameter corresponding to the distributed power generation equipment is determined when the total cost corresponding to the multi-energy complementary power generation system obtained by solving the first model is minimized; based on the first value and the second model, the total benefit corresponding to the energy storage equipment is maximized as the goal to solve, and the second value of the working parameter corresponding to the energy storage equipment is obtained when the total benefit is maximized, and the input parameters of the first model are further adjusted based on the second value. The first model corrects the economic cost of the multi-energy complementary power generation system based on the optimization result of the energy storage equipment scheduling strategy of the second model, and optimizes the scheduling strategy of each distributed discharge equipment, thereby determining the multi-energy complementary The optimal scheduling strategy for each device in the power generation system. During the optimization process, the first value determined by the first model can be used to optimize the second model, and the second value of the second model can in turn optimize the first model. The two models interact with each other and are optimized repeatedly. On the basis of reducing costs and improving economic benefits, the utilization rate of each distributed discharge device is maximized as much as possible, and when the utilization rate of each distributed discharge device is maximized, the energy storage device is in the best charging and discharging state. The determined optimal scheduling strategy can give priority to the use of clean energy, reduce the phenomenon of abandoned solar and wind power, and effectively reduce energy waste and improve the comprehensive utilization rate of energy while meeting load demand.

[0227] The embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned dispatching control method embodiment of the multi-energy complementary power generation system are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0228] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0229] An embodiment of the present application also provides a computer program product, including a computer program, which implements the scheduling control method of the above-mentioned multi-energy complementary power generation system when executed by a processor.

[0230] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0231] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned scheduling control method embodiment of the multi-energy complementary power generation system, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0232] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0233] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0234] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0235] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0236] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0237] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A dispatching control method for a multi-energy complementary power generation system, characterized in that: The multi-energy complementary power generation system includes an energy storage device and a plurality of distributed power generation devices; the method includes: Taking the minimum total cost corresponding to the multi-energy complementary power generation system output by the first model as the goal, adjusting the input parameters of the first model to obtain the first value of the working parameter corresponding to each of the distributed power generation devices; wherein the first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each of the distributed power generation devices and the electricity price information; When each of the distributed power generation devices is operated based on the first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device; wherein the second model is pre-constructed based on the working parameter of the energy storage device and the electricity price information; Based on the second value of the working parameter corresponding to the energy storage device, the input parameter of the first model is adjusted; the working parameter is used to perform scheduling control on the multi-energy complementary power generation system.

2. The dispatching control method of a multi-energy complementary power generation system according to claim 1, characterized in that: Taking the minimum total cost corresponding to the multi-energy complementary power generation system output by the first model as the goal, adjusting the input parameters of the first model to obtain the first values ​​of the working parameters corresponding to each of the distributed power generation devices, including: Determine a first target constraint based on at least one of the upper and lower output limit constraints corresponding to the energy storage device and each of the multiple distributed power generation devices, the total power ramp constraint corresponding to each device, the interactive power constraint between the multi-energy complementary power generation system and the distribution network, and the working time constraint corresponding to each device; Based on the first target constraint, with the goal of minimizing the total cost corresponding to the multi-energy complementary power generation system output by the first model, the input parameters of the first model are adjusted to obtain the first values ​​of the working parameters corresponding to each of the distributed power generation devices.

3. The dispatching control method of a multi-energy complementary power generation system according to claim 1, characterized in that: The plurality of distributed power generation devices include gas equipment; the first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each of the distributed power generation devices and electricity price information, and includes: Based on the working parameters of the gas equipment and the gas price information, construct a first sub-model for outputting the natural gas consumption cost corresponding to the gas equipment; Based on the energy storage device and the operating cost of a target device among the plurality of distributed power generation devices and the operating parameters of the target device, construct a second sub-model for outputting the operating cost of the target device; Based on the working parameters of the energy storage device and the electricity price information, constructing a third sub-model for outputting the interaction benefits between the multi-energy complementary power generation system and the distribution network; The first model is determined by fusing at least one of the first sub-model, the second sub-model and the third sub-model.

4. The dispatching control method of a multi-energy complementary power generation system according to any one of claims 1 to 3, characterized in that: When each of the distributed power generation devices is operated based on the first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device, including: Determining a second target constraint based on at least one of an operation constraint corresponding to the energy storage device and a power constraint at the beginning and end of a scheduling period; Based on the second target constraint, with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model, the input parameters of the second model are adjusted to obtain second values ​​of the operating parameters corresponding to the energy storage device.

5. The dispatching control method of a multi-energy complementary power generation system according to any one of claims 1 to 3, characterized in that: The second model is pre-constructed based on the operating parameters of the energy storage device and the electricity price information, and includes: It is pre-constructed based on the discharge coefficient of the energy storage device, the coefficient following the real-time electricity price changes, the electricity selling price, the electricity purchasing price, the maximum electricity selling price in a natural day, the maximum electricity purchasing price in a natural day, the charging and discharging state and the charging and discharging power of the energy storage device.

6. The dispatching control method of a multi-energy complementary power generation system according to any one of claims 1 to 3, characterized in that: The adjusting the input parameter of the first model based on the second value of the operating parameter corresponding to the energy storage device includes: Taking the minimum total cost of the multi-energy complementary power generation system output by the first model as the goal, taking the second value of the working parameter corresponding to the energy storage device as input, adjusting other input parameters of the first model, and optimizing the first value of the working parameter corresponding to each of the distributed power generation devices; When each of the distributed power generation devices is operated based on the optimized first value, the input parameters of the second model are adjusted with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model to obtain a second value of the working parameter corresponding to the energy storage device; In a case where the total benefit is greater than the total benefit of the last optimization, returning to the step of adjusting the input parameters of the first model based on the second value of the working parameter corresponding to the energy storage device; When the total benefit is not greater than the total benefit of the last optimization, the optimization is terminated.

7. A dispatching control device for a multi-energy complementary power generation system, characterized in that: The multi-energy complementary power generation system includes an energy storage device and a plurality of distributed power generation devices; the device includes: A first processing module is used to adjust the input parameters of the first model with the goal of minimizing the total cost corresponding to the multi-energy complementary power generation system output by the first model, so as to obtain a first value of the working parameter corresponding to each of the distributed power generation devices; wherein the first model is pre-constructed based on the working parameters of the energy storage device, the working parameters of each of the distributed power generation devices and the electricity price information; A second processing module is used to adjust the input parameters of the second model to obtain a second value of the working parameter corresponding to the energy storage device, with the goal of maximizing the total revenue corresponding to the energy storage device output by the second model, when each of the distributed power generation devices is operated based on the first value; wherein the second model is pre-constructed based on the working parameter of the energy storage device and the electricity price information; The third processing module is used to adjust the input parameters of the first model based on the second value of the working parameter corresponding to the energy storage device; the working parameter is used to dispatch and control the multi-energy complementary power generation system.

8. A multi-energy complementary power generation system, characterized in that: include: Energy storage equipment; A plurality of distributed power generation devices, each of which is electrically connected to the energy storage device; Based on the dispatching and control device of the multi-energy complementary power generation system as claimed in claim 7, the dispatching and control device of the multi-energy complementary power generation system is electrically connected to the energy storage device and each of the distributed power generation devices respectively.

9. The multi-energy complementary power generation system according to claim 8, characterized in that: The multiple distributed power generation equipment includes at least one of wind power generation equipment, photovoltaic power generation equipment and gas equipment.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the dispatching control method of the multi-energy complementary power generation system as described in any one of claims 1-6 is implemented.

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