Low-carbon factory power system

Abstract

The application provides a low-carbon factory power system, and relates to the technical field of low-carbon power systems.The low-carbon factory power system comprises a test bench, photovoltaic power generation equipment, an energy storage module, an external power grid and a control device.The test bench is unidirectionally and electrically connected with the photovoltaic power generation equipment, and the test bench is also bidirectionally and electrically connected with the energy storage module.The photovoltaic power generation equipment is unidirectionally and electrically connected with the energy storage module and the external power grid respectively.The test bench is unidirectionally and electrically connected with the external power grid.The energy storage module is bidirectionally and electrically connected with the external power grid.The control device is bidirectionally and communicatively connected with the test bench, the photovoltaic power generation equipment, the energy storage module and the external power grid.The low-carbon factory power system provided by the application can arrange test operation according to the power generation capacity of the photovoltaic power generation equipment, realizes intelligent operation of the factory power system, ensures that the electric energy provided by the photovoltaic power generation equipment is consumed by the test operation of the test bench, and improves the energy utilization efficiency of the factory power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of low-carbon power systems, in particular to a low-carbon factory power system. BACKGROUND

[0002] Green and low-carbon of the factory power system is the inevitable requirement for the development of the ecological civilization era, and at the same time, the stability, safety and efficiency of power supply of the factory power system after green and low-carbon should be ensured. Therefore, for the complex factory power system with uncertain power generation end and uncertain power consumption end, intelligent operation control can greatly improve the operation level of the factory power system.

[0003] Taking a factory as an energy power equipment factory for example, the test bench in the energy power equipment factory, such as the test bench of the steam turbine and the gas turbine in the factory, consumes electric power in the speed-up debugging stage, and outputs electric power to the outside in the load-up debugging stage, and the net electric power flow changes greatly with the change of the test state. When there is excess electric power in the load-up debugging stage, the existing way is to dissipate the excess electric power by using a wind resistance, but this will cause energy waste.

[0004] Therefore, the operation of the existing factory power system is limited by the characteristics of fixed production plan, uncertain power consumption and power generation state of the test bench, the electric energy provided by the factory photovoltaic power generation equipment and the test bench load-up stage power system cannot be consumed in time, the electric energy utilization efficiency is low, and the carbon emission intensity is high. SUMMARY

[0005] The present application aims at the deficiencies in the prior art, and provides a low-carbon factory power system, so as to solve the problems of low electric energy utilization efficiency and high carbon emission intensity existing in the existing factory power system.

[0006] To achieve the above-mentioned purpose, the technical solutions adopted by the embodiments of the present application are as follows:

[0007] In a first aspect, the embodiments of the present application provide a low-carbon factory power system, which comprises a test bench, a photovoltaic power generation equipment, an energy storage module, an external power grid and a control device.

[0008] The test bench is unidirectionally electrically connected with the photovoltaic power generation equipment; the test bench is further bidirectionally electrically connected with the energy storage module; the photovoltaic power generation equipment is unidirectionally electrically connected with the energy storage module and the external power grid respectively; the test bench is unidirectionally electrically connected with the external power grid; and the energy storage module is further bidirectionally electrically connected with the external power grid.

[0009] The control device is bidirectionally communicatively connected with the test bench, the photovoltaic power generation equipment, the energy storage module and the external power grid respectively.

[0010] In a possible implementation example, the low-carbon factory power system further includes a load device.

[0011] The load device is unidirectionally connected to the test bench in power, and is bidirectionally connected to the control device in communication.

[0012] In a possible implementation example, the low-carbon factory power system further includes a production device.

[0013] The production device is unidirectionally connected to the photovoltaic power generation device, the external power grid and the energy storage module in power, respectively.

[0014] In a possible implementation example, the test bench includes a plurality of test bench positions, which correspond to a plurality of power grades, respectively, to perform test running operations on the steam turbines or gas turbines of the plurality of power grades.

[0015] In a second aspect, an embodiment of the present application provides an intelligent control method of a low-carbon factory power system, applied to the control device, and the intelligent control method includes the following steps.

[0016] According to the production plan of the production device in the low-carbon factory power system in a preset future time period and the historical power consumption load corresponding to the historical production plan, a preset power consumption load prediction algorithm is used for time series prediction to obtain the predicted power consumption load of the production device in the preset future time period.

[0017] According to the historical power generation load of the photovoltaic power generation device in the low-carbon factory power system, a preset power generation load prediction algorithm is used for time series prediction to predict the first predicted power generation load of the photovoltaic power generation device in the preset future time period.

[0018] According to the predicted power consumption load and the first predicted power generation load, a predicted energy storage load in the preset future time period is obtained.

[0019] According to the predicted energy storage load, a predicted test running plan in the preset future time period is generated.

[0020] According to the first predicted power generation load and the predicted energy storage load, the predicted test running plan is optimized.

[0021] According to the optimized predicted test running plan, the test bench is controlled to perform test running operations in the preset future time period.

[0022] In a possible implementation example, the method further includes the following steps.

[0023] According to the first predicted power generation load, the production plan is optimized.

[0024] According to the optimized production plan, the production equipment is controlled to perform production work in the preset future time period.

[0025] In a possible implementation example, before the predicted energy storage load in the preset future time period is obtained according to the predicted power consumption load and the first predicted power generation load, the method further includes:

[0026] According to the weather forecast in the preset future time period, a second predicted power generation load of the photovoltaic power generation device in the preset future time period is obtained by using photovoltaic physical model information corresponding to the photovoltaic power generation device for simulation prediction.

[0027] According to the second predicted power generation load and the first predicted power generation load, a target predicted power generation load of the photovoltaic power generation device in the preset future time period is obtained.

[0028] The predicted energy storage load in the preset future time period is obtained according to the predicted power consumption load and the first predicted power generation load, including:

[0029] The predicted energy storage load in the preset future time period is obtained according to the predicted power consumption load and the target predicted power generation load.

[0030] In a possible implementation example, the method further includes:

[0031] An actual power corresponding to at least one key evaluation index of the low-carbon factory power system is obtained.

[0032] According to the actual power corresponding to each key evaluation index, an index parameter of each key evaluation index is calculated respectively.

[0033] In a possible implementation example, the method further includes:

[0034] According to the index parameter of each key evaluation index, the power consumption load prediction algorithm and / or the power generation load prediction algorithm is updated.

[0035] In a third aspect, an embodiment of the present application provides a computer device, including a processor, a storage medium, and a bus, the storage medium stores program instructions executable by the processor, an intelligent running algorithm model, and an electric power flow running history database, when the computer device runs, the processor and the storage medium communicate through the bus, the processor executes the program instructions to execute the steps of the control method of the low-carbon factory power system.

[0036] The present application has the following beneficial effects:

[0037] The low-carbon factory power system provided by the application comprises a test bench, a photovoltaic power generation device, an energy storage module, an external power grid and a control device. The test bench is unidirectionally connected in power with the photovoltaic power generation device, and is bidirectionally connected in power with the energy storage module. The photovoltaic power generation device is unidirectionally connected in power with the energy storage module and the external power grid respectively. The test bench is unidirectionally connected in power with the external power grid. The control device is bidirectionally connected in communication with the test bench, the photovoltaic power generation device, the energy storage module and the external power grid respectively. The low-carbon factory power system provided by the application can obtain the power generation amount of the photovoltaic power generation device at the current time by the control device, and arrange the test operation according to the power generation amount of the photovoltaic power generation device, so as to realize the intelligent operation of the factory power system. The electric energy provided by the photovoltaic power generation device is just consumed by the test operation of the test bench and the factory production equipment, so as to realize the recovery of the unstable power generation of the test bench and improve the energy utilization efficiency of the factory power system. The influence of the test state uncertainty of the test bench and the intermittence of the photovoltaic power generation on the control stability of the factory power grid is solved. In the embodiment, the photovoltaic power generation device converts light energy into electric energy to provide the electric energy required by the test operation and the factory production equipment. The conversion of the light energy into the electric energy reduces the carbon emission, so as to play a low-carbon environmental protection role and make the factory power system more green and low-carbon. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0039] Figure 1 Structure schematic diagram of a low-carbon factory power system provided by an embodiment of the application;

[0040] Figure 2 Structure schematic diagram of a low-carbon factory power system provided by an embodiment of the application;

[0041] Figure 3 Structure schematic diagram of a low-carbon factory power system provided by an embodiment of the application;

[0042] Figure 4 Flow schematic diagram of an intelligent control method of a low-carbon factory power system provided by an embodiment of the application;

[0043] Figure 5 Flow schematic diagram of an optimization method of a production plan provided by an embodiment of the application;

[0044] Figure 6A flowchart of a method for optimizing the obtained power generation load according to an embodiment of the present application is provided.

[0045] Figure 7 A flowchart of a method for evaluating a low-carbon factory power system according to an embodiment of the present application is provided.

[0046] Figure 8 A structural diagram of a computer device according to an embodiment of the present application is provided. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings for the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application.

[0048] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art without creative labor based on the embodiments in the present application are within the scope of protection of the present application.

[0049] In the description of the present application, it should be noted that if the terms "upper", "lower", etc. indicate the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the product of the present application is usually placed, only for the convenience of describing the present application and simplifying the description, and it does not indicate or imply that the device or element must have a particular orientation, be constructed and operated in a particular orientation, therefore it cannot be understood as a limitation of the present application.

[0050] In addition, the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0051] It should be noted that the features in the embodiments of the present application can be combined with each other without conflict.

[0052] This application addresses factory power systems. Taking a factory as an energy and power equipment plant as an example, the existing factory power system is limited by the fixed nature of the factory's production plan and must operate according to the production plan. However, due to the uncertainty of the power consumption and power generation status of the test bench, the power provided by the photovoltaic power generation equipment and the test bench during the load increase phase cannot be used in a timely manner, resulting in low power utilization efficiency.

[0053] Therefore, embodiments of this application provide a low-carbon factory power system, control method, and equipment, which can solve the problems existing in existing factory power systems.

[0054] The following examples, in conjunction with the accompanying drawings, provide specific illustrations of the low-carbon factory power system provided in this application.

[0055] This application provides a possible implementation of a low-carbon factory power system. Figure 1 This is one of the structural schematic diagrams of a low-carbon factory power system provided in an embodiment of this application.

[0056] like Figure 1 As shown, the low-carbon factory's power system includes: a test bench 1, a photovoltaic power generation device 2, an energy storage module 3, an external power grid 4, and a control device 5. The test bench 1 is unidirectionally connected to the photovoltaic power generation device 2, and bidirectionally connected to the energy storage module 3. The photovoltaic power generation device 2 is unidirectionally connected to both the energy storage module 3 and the external power grid 4. The test bench 1 is also unidirectionally connected to the external power grid 4, and the energy storage module 3 is bidirectionally connected to the external power grid 4. The control device 5 has bidirectional communication connections with the test bench 1, the photovoltaic power generation device 2, the energy storage module 3, and the external power grid 4.

[0057] In the embodiment, the test bench 1 can be used for test running operation of the equipment produced by the factory (the test running operation refers to testing the produced equipment, for example, the equipment produced by a steam turbine factory is steam turbine and gas turbine (the steam turbine factory can produce both steam turbine and gas turbine, or only one of them, which is not limited here), the test running operation is to test the produced steam turbine or gas turbine by the test bench 1); the photovoltaic power generation equipment 2 is used for converting light energy into electric energy (for example, the photovoltaic power generation equipment 2 can be a solar panel); the energy storage module 3 can be used for storing the residual electric energy not used in the operation of the factory power system (for example, the energy storage equipment can be an energy storage module); the external power grid 4, for example, a power supply company, can provide a power source other than the photovoltaic power generation equipment 2; the control device 5 can be any computer device integrated with the control method of the factory power system, and the control device 5 is bidirectionally connected with the test bench 1, the photovoltaic power generation equipment 2, the energy storage module 3 and the external power grid 4, based on the communication connection, the control device 5 can be used for controlling the electric energy flow direction of the test bench 1, the photovoltaic power generation equipment 2, the energy storage module 3 and the external power grid 4, and can also receive the information sent by the test bench 1, the photovoltaic power generation equipment 2, the energy storage module 3 and the external power grid 4 to the control device 5, according to the information, the control device 5 can control the operation of the factory power system (for example, the information received by the control device 5 can be the operation condition of the test bench 1, the current power consumption of the test bench 1, the current power generation of the photovoltaic power generation equipment 2, the storage power of the energy storage module 3, the maximum power provided by the external power grid 4, etc.).

[0058] The photovoltaic power generation equipment 2 and the test bench 1 are unidirectionally connected in electric power. The photovoltaic power generation equipment 2 can transmit the electric energy converted from light energy to the test bench 1 through the unidirectional electric power connection between the photovoltaic power generation equipment 2 and the test bench 1, for the test running operation of the test bench 1 on the equipment.

[0059] The test bench 1 and the energy storage module 3 are in bidirectional power connection. When the test bench 1 is performing a test operation, if the power provided by the photovoltaic power generation device 2 to the test bench 1 is insufficient to support the test bench 1 to complete the test task of the device, the control device 5 can receive the information sent by the test bench 1, and based on the information, the control device 5 can control the energy storage device to deliver the stored power in the energy storage device to the test bench 1; when the power provided by the photovoltaic power generation device 2 to the test bench 1 is too much, or the test operation of the test bench 1 generates power (for example, the test bench 1 tests a steam turbine, and the steam turbine can be used for power generation, so when the test bench 1 tests the steam turbine for power generation, the steam turbine will generate power), the test operation of the test bench 1 cannot consume all the power provided by the photovoltaic power generation device 2, and the control device 5 can control the test bench 1 to deliver the remaining power (the remaining power refers to the power provided by the photovoltaic power generation device 2 after the test operation is completed) to the energy storage device, and at this time, the energy storage device can store the power delivered thereto.

[0060] The photovoltaic power generation device 2 is unidirectionally connected to the energy storage module 3 and the external power grid 4. Since the photovoltaic power generation device 2 converts light energy into electric energy, when there is no test operation task, the photovoltaic power generation device 2 will also convert the light energy in its environment into electric energy, but at the current time, there is no test operation to consume the electric energy provided by the photovoltaic power generation device 2, and at this time, the photovoltaic power generation device 2 can deliver the converted electric energy to the energy storage module 3, and the energy storage module 3 can store the delivered electric energy. However, the storage capacity of the energy storage device has an upper limit, and when the storage capacity of the energy storage module 3 reaches the upper limit, the energy storage module 3 cannot continue to store the electric energy delivered by the photovoltaic power generation device 2, and at this time, the photovoltaic power generation device 2 can also deliver the electric energy to the external power grid 4.

[0061] The test bench 1 is also unidirectionally connected to the external power grid 4, and when the test operation of the test bench 1 consumes too much power, and the sum of the power provided by the photovoltaic power generation device 2 and the energy storage device is still insufficient to support the test operation, the external power grid 4 can be used to provide power.

[0062] The energy storage module 3 is also bidirectionally connected to the external power grid 4, and based on the bidirectional power connection, the energy storage module 3 can also deliver the stored electric energy to the external power grid 4, and in the case that the weather is bad and the photovoltaic power generation device 2 generates little power, the energy storage module 3 can also charge the valley electricity of the external power grid 4 (the valley electricity generally refers to the time period with low electricity consumption at night, and the price of the valley electricity is low).

[0063] Optionally, the control device 5 can be unidirectionally connected to one of the photovoltaic power generation device 2, the energy storage module 3, and the external power grid 4, or can be unidirectionally connected to multiple modules respectively, as long as the power connection can supply power to the control device 5.

[0064] It should be noted that, taking the factory as a steam turbine factory and the product equipment produced by the factory as a steam turbine as an example, the test run of the test bench on the steam turbine is in turn in the stage of increasing speed and in the stage of increasing load. In the stage of increasing speed, the test run consumes electric energy, and in the stage of increasing load, the test run outputs electric energy. The ideal state of the low-carbon factory power system provided in this embodiment is that the control module controls the test run amount of the test bench 1 based on the received information, so that the test run of the test bench 1 in the stage of increasing speed just consumes the electric energy provided by the photovoltaic power generation device 2, but if the electric energy provided by the photovoltaic power generation device 2 cannot meet the electric energy required by the test run in the stage of increasing speed, the electric energy stored in the energy storage module 3 can be supplemented. For example, the control device 5 can obtain the current power generation amount of the photovoltaic power generation device 2, and it is assumed that the current power generation amount of the photovoltaic power generation device 2 is 1000kW·h, and the maximum storage capacity of the energy storage module 3 is 500kW·h. Therefore, the test run amount of the test bench 1 can be controlled, so that the electric energy consumed by the current test run in the stage of increasing speed is 1000kW·h. In this way, the test bench in the stage of increasing speed just consumes the electric energy provided by the photovoltaic power generation device 2. However, if the electric energy consumed by the test run in the stage of increasing speed is greater than 1000kW·h, for example, 1500kW·h, the electric energy provided by the photovoltaic power generation device cannot meet the electric energy required by the test run in the stage of increasing speed, and therefore, the energy storage module 3 can supplement 500kW·h of electric energy. The test run generates electric energy in the stage of increasing load, and it is assumed that the electric energy generated by the test run in the stage of increasing load is 500kW·h, and therefore, the 500kW·h of electric energy is transmitted to the energy storage module 3.

[0065] In the stage of increasing speed of the test run, the energy storage module 3 discharges 500kW·h of electric energy, and the electric energy consumption of the test run of the test bench 1 just equals the sum of the power generation amount of the photovoltaic power generation device 2 and the discharge amount of the energy storage module 3. In the stage of increasing load of the test run, the energy storage module 3 charges 500kW·h of electric energy. In this way, the electric energy provided by the photovoltaic power generation device 2 is just consumed by the test run of the test bench 1, and there is no surplus electric energy, so that the factory power system meets the green and low-carbon requirements.

[0066] In summary, by using the low-carbon factory power system provided in this application, the control device 5 can obtain the power generation amount of the photovoltaic power generation device 2 at the current time, and the test run is arranged according to the power generation amount of the photovoltaic power generation device 2, so that the intelligent operation of the factory power system is realized, and the electric energy provided by the photovoltaic power generation device 2 is just consumed by the test run of the test bench 1, thereby improving the energy utilization efficiency of the factory power system. In this embodiment, the photovoltaic power generation device 2 converts light energy into electric energy to provide the electric energy required by the test run, and the conversion of light energy into electric energy reduces carbon emissions, which can play a low-carbon and environmentally friendly role, so that the factory power system is more green and low-carbon.

[0067] An embodiment of the present application further provides a possible implementation of a low-carbon factory power system, Figure 2 Fig. 2 is a structural schematic diagram of a low-carbon factory power system according to an embodiment of the present application; and Figure 2 As shown in the possible implementation, the low-carbon factory power system provided by the above embodiment can further include a load device 6.

[0068] The load device 6 provided by the embodiment can be unidirectionally connected with the test bench 1. When the test operation of the test bench 1 cannot consume all the electric energy provided by the photovoltaic power generation device 2, and the electric energy stored in the energy storage module 3 reaches the upper limit of the storage, and the test bench itself outputs load in an extreme case, the test bench 1 can further deliver the remaining electric energy to the load device 6, and the load device 6 can consume the remaining electric energy, for example, by driving an air compressor to compress air into an air tank to provide stable compressed air for the production process of the factory, thereby improving the utilization efficiency of the electric energy.

[0069] The load device 6 is further bidirectionally connected with the control device 5. Based on the communication connection, the control device 5 can control the connection and disconnection of the circuit between the load device 6 and the test bench 1, and can also receive the information sent by the load device 6 to the control device 5, which can include the current power consumption of the load device 6 or other parameters of the load device 6.

[0070] In the embodiment, the load device 6 is arranged. When there is remaining electric energy in the factory power system, the remaining electric energy is consumed by the load device 6, which can further improve the utilization rate of the electric energy in the factory power system, and make the factory power system more green and low-carbon.

[0071] An embodiment of the present application further provides a possible implementation of a low-carbon factory power system, Figure 3 Fig. 2 is a structural schematic diagram of a low-carbon factory power system according to an embodiment of the present application; and Figure 3 As shown in the possible implementation, the low-carbon factory power system provided by the above embodiment can further include a load device 6.

[0072] For example, the test bench 1 in the above embodiment can be used for the test running operation of the steam turbine produced by the factory, and the production equipment 7 in the present embodiment can be used for the production of the steam turbine. Since the production equipment 7 also consumes electric energy when producing the steam turbine, the production equipment 7 can be unidirectionally connected to the photovoltaic power generation equipment 2, the external power grid 4 and the energy storage module 3, the photovoltaic power generation equipment 2 can provide electric energy for the production equipment 7, and when the electric energy provided by the photovoltaic power generation equipment 2 is insufficient to support the production operation of the production equipment 7, the control device 5 can also control the energy storage module 3 and the external power grid 4 to deliver electric energy to the production equipment 7. It should be noted that when the electric energy in the energy storage module 3 is insufficient, the electric energy in the external power grid 4 is used.

[0073] The production equipment 7 can also be bidirectionally connected to the control device 5, based on the communication connection, the control device 5 can control the production operation of the production equipment 7, and can also receive the information sent by the production equipment 7 to the control device 5, which may, for example, include the production operation progress or other information of the production equipment 7.

[0074] By setting the production equipment 7 and connecting the production equipment 7 to the factory power system, the power supply of the production equipment 7 is realized, and the production equipment 7 is bidirectionally connected to the control device 5, the control device 5 can control the production equipment 7, and can also receive the information sent by the production equipment 7 to the control device 5, based on the information, the production operation of the production equipment 7 can be controlled.

[0075] An embodiment of the present application also provides a possible implementation of the test bench 1. In the possible implementation, the test bench 1 provided by the above embodiment can include a plurality of test bench positions, and the plurality of test bench positions correspond to a plurality of different power levels respectively, so as to simultaneously perform the test running operation on the steam turbines and / or gas turbines of the plurality of power levels respectively.

[0076] For example, the test bench 1 is used for the test running operation of the steam turbine and / or gas turbine produced by the production equipment 7. However, due to different production requirements, the power levels of the produced steam turbines and gas turbines are also different, and if only a single power level test bench is set, the test running operation of the steam turbines and gas turbines of multiple power levels cannot be met. Therefore, the test bench provided by the above embodiment can include a plurality of test bench positions, and the plurality of test bench positions correspond to a plurality of different power levels respectively, so as to perform the test running operation on the steam turbines and / or gas turbines of the plurality of power levels respectively. The specific power value can be set according to actual requirements, which is not limited herein. It should be noted that the test bench can only perform the test running operation on the steam turbine or the gas turbine, or can simultaneously perform the test running operation on the steam turbine or the gas turbine.

[0077] By setting multiple test benches of different power levels, different power level steam turbines and gas turbines can be tested, so that the test bench 1 has more comprehensive functions.

[0078] An embodiment of the present application also provides an intelligent control method of a low-carbon factory power system, which is applied to the control device 5 provided in the above embodiment. Figure 4 The flowchart of the control method of the low-carbon factory power system provided in an embodiment of the present application is shown in FIG. 4. Figure 4 The intelligent control method comprises the following steps.

[0079] S401, using a preset power load prediction algorithm to perform time series prediction to obtain a predicted power load of the production equipment in a preset future time period.

[0080] In this embodiment, the predicted power load of the production equipment in the preset future time period can be obtained by using a preset power load prediction algorithm to perform time series prediction according to the production plan of the production equipment in the preset future time period and the historical power load corresponding to the historical production plan. The preset future time period is a time length set according to actual needs (for example, it can be one week in the future), which is not limited herein.

[0081] Specifically, the historical production plan and the historical power load corresponding to the historical production plan can be used to train the preset power load prediction algorithm to obtain a trained power load prediction algorithm. The trained power load prediction algorithm can obtain the predicted power load of the production equipment in the preset future time period according to the production plan of the production equipment in the preset future time period. The power load prediction algorithm may, for example, be a LSTM algorithm based on deep learning, but this does not mean that the LSTM algorithm can only be used in this embodiment. The power load prediction algorithm can also be other types of algorithms, as long as it can obtain the predicted power load of the production equipment in the preset future time period according to the production plan of the production equipment in the preset future time period. The specific type of algorithm is not limited in this embodiment.

[0082] Taking the deep learning LSTM algorithm as an example, the factory historical power load can be denoted as L(t), and the LSTM algorithm is trained using L(t) to obtain a trained LSTM algorithm. When the predicted power load of the production equipment in the preset future time period needs to be predicted, the production plan of the preset future time period is denoted as M(t), where t is time. The trained LSTM algorithm is used for intelligent prediction, and the output is the predicted power load L(t+7) of the production equipment in the preset future time period, L(t+7)=f1(L(t), M(t)), where f1 is a function of L, which is a LSTM neural network function trained by deep learning.

[0083] S402, using a preset power generation load prediction algorithm to perform time series prediction to predict a first predicted power generation load of the photovoltaic power generation device 2 in a preset future time period.

[0084] After obtaining the predicted power consumption load of the production equipment in the preset future time period according to step S401, a preset power generation load prediction algorithm can also be used to train the power generation load prediction algorithm according to the historical power generation load of the photovoltaic power generation device in the low-carbon factory power system and the weather forecast corresponding to the historical power generation load, to obtain a trained power generation load prediction algorithm. The trained power generation load prediction algorithm can predict the predicted power generation load of the photovoltaic power generation device in the preset future time period, i.e. the first predicted power generation load, according to the weather forecast in the preset future time period.

[0085] Taking the preset power generation load prediction algorithm as an example, the historical power generation load is P(t), and the LSTM algorithm is trained to obtain the trained LSTM algorithm. When the first predicted power generation load of the photovoltaic power generation device in the preset future time period needs to be predicted, only the weather forecast in the preset future time period needs to be input, and the trained LSTM algorithm is used for intelligent prediction. The output is the first predicted power generation load Px(t+7) of the photovoltaic power generation device in the preset future time period.

[0086] S403, obtaining the predicted energy storage load in the preset future time period according to the predicted power consumption load and the first predicted power generation load.

[0087] After obtaining the predicted power consumption load of the production equipment according to step S401 and obtaining the first predicted power generation load according to step S402, the first predicted power generation load is subtracted from the predicted power consumption load of the production equipment, and the predicted energy storage load in the preset future time period is obtained.

[0088] Taking the first predicted power generation load as Px(t+7) and the predicted power consumption load as L(t+7) as an example, the predicted energy storage load Pc(t+7)=D*Px(t+7)-E*L(t+7)+F, wherein D and E are weighting coefficients, and F is a bias.

[0089] S404, generating a predicted test vehicle plan in the preset future time period according to the predicted energy storage load.

[0090] After obtaining the predicted energy storage load in the preset future time period according to step S403, a predicted test vehicle plan in the preset future time period can be generated according to the predicted energy storage load, so that the predicted test vehicle plan is executed in the preset future time period to consume the predicted energy storage load.

[0091] For example, if the predicted energy storage load is 500 kW·h, the pre-test plan can be to perform an empty load speed-up test on a 500 kW·h turbine, and the pre-test plan is to consume 500 kW·h of electricity in the future time period. In the pre-set future time period, the pre-test plan can consume the predicted energy storage load.

[0092] S405, optimizing the pre-test plan according to the first predicted power generation load and the predicted energy storage load.

[0093] After obtaining the pre-test plan according to step S404, the genetic algorithm can be used to optimize the pre-test plan according to the first predicted power generation load and the predicted energy storage load, and an optimized pre-test plan can be obtained.

[0094] S406, controlling the test bench to perform test operation in the pre-set future time period according to the optimized pre-test plan.

[0095] After obtaining the optimized pre-test plan according to step S405, the test bench can be controlled to perform test operation in the pre-set future time period according to the optimized pre-test plan.

[0096] The intelligent control method of the low-carbon factory power system provided by the embodiment uses a pre-set algorithm to obtain the predicted power consumption of the production equipment in the pre-set future time period and the first predicted power generation load of the photovoltaic power generation equipment in the pre-set future time period, and calculates the predicted energy storage load according to the predicted power consumption and the first predicted power generation load. The predicted energy storage load can be a discharge load, i.e. the power consumption of the test product equipment matched by the test bench for performing test operation, or a charging load, i.e. the power generation of the test product equipment matched by the test bench for performing test operation. Therefore, the pre-test plan is generated according to the predicted energy storage load, so that the pre-test plan can consume the power provided by the photovoltaic power generation equipment and the test product equipment in the load-up stage, thereby improving the energy utilization efficiency of the low-carbon factory power system.

[0097] An embodiment of the present application also provides an optimization method for a production plan, Figure 5 The flowchart of the optimization method for the production plan provided by the embodiment of the present application is shown in Figure 5 The optimization method comprises:

[0098] S501, optimizing the production plan according to the first predicted power generation load.

[0099] After obtaining the first predicted power generation load according to step S402, the genetic algorithm can be used to optimize the production plan according to the first predicted power generation load, and an optimized production plan can be obtained.

[0100] S502, control the production equipment to perform the production operation in the preset future time period according to the optimized production plan.

[0101] After the optimized production plan is obtained according to step S501, the production equipment can be controlled to perform the production operation in the preset future time period according to the optimized production plan.

[0102] In this embodiment, the production plan is optimized by the first predicted power generation load, the accuracy of the production plan is improved, and the production equipment is controlled to perform the production operation in the preset future time period by using the optimized production plan, the authenticity of the production operation is improved.

[0103] An embodiment of the present application also provides a method for optimizing the obtained power generation load, Figure 6 The flowchart of the method for optimizing the obtained power generation load provided by an embodiment of the present application is shown in Figure 6 As shown in the figure, before the predicted energy storage load in the preset future time period is obtained according to the predicted power consumption load and the first predicted power generation load in step S403, the following steps can also be included:

[0104] S601, according to the weather forecast in the preset future time period, the second predicted power generation load of the photovoltaic power generation equipment in the preset future time period is obtained by using the photovoltaic physical model information corresponding to the photovoltaic power generation equipment for simulation prediction.

[0105] When the first predicted power generation load of the photovoltaic power generation equipment is obtained according to S402, the photovoltaic physical model information corresponding to the photovoltaic power generation equipment can also be obtained, and the photovoltaic power generation equipment is simulated and modeled by using the PVsyst software to obtain the simulation prediction model of the photovoltaic power generation equipment. Based on the weather forecast in the preset future time period, the simulation prediction model can simulate and predict the power output by the photovoltaic power generation equipment, obtain the simulated photovoltaic power generation load, and the obtained simulated photovoltaic power generation load is the second predicted power generation load Ps(t+7).

[0106] S602, according to the second predicted power generation load and the first predicted power generation load, the target predicted power generation load of the photovoltaic power generation equipment in the preset future time period is obtained.

[0107] After the first predicted power generation load Px(t+7) is obtained according to step S402, and the second predicted power generation load Ps(t+7) is obtained according to step S601, the target predicted power generation load of the photovoltaic power generation equipment in the preset future time period is obtained according to the second predicted power generation load and the first predicted power generation load. For example, the target predicted power generation load Pz(t+7)=A*Ps(t+7)+B*Px(t+7))+C, wherein A and B are weighting coefficients, and C is a bias.

[0108] Then, in step S403, the predicted energy storage load of the preset future time period is obtained according to the predicted power consumption load and the first predicted power generation load, which can include:

[0109] According to the predicted power consumption load L(t+7) and the target predicted power generation load Pz(t+7), the predicted energy storage load Pc(t+7) of the preset future time period is obtained, where Pc(t+7)=D*Pz(t+7)-E*L(t+7)+F, D and E are weighting coefficients, and F is a bias.

[0110] In this embodiment, the target predicted power generation load of the photovoltaic power generation device in the preset future time period is obtained according to the second predicted power generation load and the first predicted power generation load. The target predicted power generation load is more accurate than the first predicted power generation load, so that the target predicted power generation load is used to obtain the predicted energy storage load, which improves the accuracy of the obtained predicted energy storage load compared with directly using the first predicted power generation load to obtain the predicted energy storage load.

[0111] An embodiment of the present application also provides an evaluation method for a low-carbon factory power system, Figure 7 The flowchart of the evaluation method for the low-carbon factory power system provided by an embodiment of the present application is shown in Figure 7 The method includes:

[0112] S701, obtaining actual power corresponding to at least one key evaluation index of the low-carbon factory power system.

[0113] The key evaluation index is an index that can be used to judge the performance of the low-carbon factory power system. After determining the type of the key evaluation index, the numerical value of the actual power corresponding to the key evaluation index is obtained.

[0114] The key evaluation index may, for example, include the total power consumption Pt of the low-carbon factory power system, the rated power Pw1 of the produced steam turbine, the rated power Pw2 of the produced gas turbine, the equivalent carbon emission amount Ct, the total power generation amount Pz of the photovoltaic power generation device, the photovoltaic power generation amount Pz1 consumed inside the factory, the total power generation amount Pr of the test bench, the steam turbine power generation amount Prs, the gas turbine power generation amount Prg, the test bench power generation amount Pr1 consumed inside the factory, etc. The calculation method of the equivalent carbon emission amount Ct is as follows:

[0115] For example, the carbon emission amount of external power grid power supply is 762 g / kW·h, the carbon emission amount of factory photovoltaic power generation is 0 g / kW·h, the carbon emission amount of factory test steam turbine power generation is 800 g / kW·h, and the carbon emission amount of factory test gas turbine power generation is 400 g / kW·h, then the equivalent carbon emission amount Ct=(Pt-Pz1-Pr1)*762+Pz1*0+Prs*800+Prg*400.

[0116] S702, calculate the index parameters of each key evaluation index according to the actual power corresponding to each key evaluation index respectively.

[0117] According to the actual power corresponding to each key evaluation index obtained in step S701, the index parameters of each key evaluation index can be calculated respectively.

[0118] The index parameters may, for example, include unit output power energy consumption intensity Edu, unit output carbon emission intensity Cdu, photovoltaic consumption ratio PVr, test drive consumption ratio Tr, and the like. Among them, , , , In an ideal state, 1, 1, that is, the photovoltaic power generation capacity is completely consumed, and the power generation capacity in the test drive stage is also completely consumed.

[0119] When the actual power corresponding to the key evaluation index is obtained according to step S701, the index parameters of each key evaluation index can be calculated respectively.

[0120] In this embodiment, according to the actual power corresponding to each key evaluation index, the index parameters of each key evaluation index can be calculated respectively. The calculated index parameters can be used to judge the performance of the low-carbon factory power system, improve the evaluation mechanism of the low-carbon factory power system, and can improve the low-carbon factory power system according to the judgment result, so that the function of the low-carbon factory power system is more perfect.

[0121] An embodiment of the present application also provides an updating method of a preset algorithm. In a possible implementation example, after the index parameters of each key evaluation index are calculated, the electricity load prediction algorithm and / or the power generation load prediction algorithm can be updated according to the index parameters of each key evaluation index.

[0122] In this embodiment, the electricity load prediction algorithm and / or the power generation load prediction algorithm is updated according to the index parameters of each key evaluation index. The electricity load of the production equipment and the power generation load of the photovoltaic power generation equipment are predicted by using the updated algorithm, which can make the prediction result more accurate and improve the accuracy of the algorithm.

[0123] Figure 8 The structural schematic diagram of the computer device provided by an embodiment of the present application is shown in Figure 8As shown, the control device in the above embodiment can be, for example, a power flow brain platform computer device of an energy power equipment factory, which comprises a processor 801, a storage medium 802, and a bus 803, the storage medium stores processor-executable program instructions, an intelligent operation algorithm model, and a power flow operation history database, the intelligent operation algorithm model can be trained according to the power flow operation history database, the trained intelligent operation algorithm model can be used for power flow data prediction (the power flow data can be, for example, the predicted power consumption load, the first predicted power generation load, and the second predicted power generation load in the above embodiment), when the computer device is running, the processor and the storage medium communicate through the bus, and the processor executes the program instructions to perform the steps of the control method of the factory power system provided in the above embodiment.

[0124] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other manners. For example, the apparatus embodiments described above are only schematic. For example, the division of the units is only a logical function division. There can be another division manner for the actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between the units can be indirect couplings or communication connections through some interfaces, devices or units, and can be electrical, mechanical or in other forms.

[0125] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0126] In addition, each functional unit in the various embodiments of the present application can be integrated in one processing unit, or each unit can be a physically independent unit, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of hardware plus software function unit.

[0127] The integrated unit implemented in the form of the software function unit can be stored in a computer readable storage medium. The software function unit is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute part of steps of the method described in various embodiments of the present application. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media capable of storing program codes.

[0128] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A low-carbon factory power system, characterized in that, The factory's power system includes: a test bench, photovoltaic power generation equipment, energy storage modules, an external power grid, and control equipment; The test bench is unidirectionally electrically connected to the photovoltaic power generation equipment; the test bench is also bidirectionally electrically connected to the energy storage module; the photovoltaic power generation equipment is unidirectionally electrically connected to both the energy storage module and the external power grid; the test bench is also unidirectionally electrically connected to the external power grid; the energy storage module is also bidirectionally electrically connected to the external power grid. The control equipment is bidirectionally connected to the test bench, the photovoltaic power generation equipment, the energy storage module, and the external power grid. The control device is used to perform time-series prediction based on the production plan of the production equipment in the low-carbon factory power system in a preset future time period and the historical power load corresponding to the historical production plan, and to obtain the predicted power load of the production equipment in the preset future time period. Based on the historical power generation load of the photovoltaic power generation equipment in the low-carbon factory power system, a preset power generation load prediction algorithm is used to perform time-series prediction, predicting the first predicted power generation load of the photovoltaic power generation equipment in the preset future time period. Based on the predicted electricity load and the first predicted power generation load, the predicted energy storage load for the preset future time period is obtained; Based on the predicted energy storage load, a pre-test vehicle plan for the preset future time period is generated; The pre-test vehicle plan is optimized based on the first predicted power generation load and the predicted energy storage load. According to the optimized pre-test vehicle plan, the test stand is controlled to perform test operations within the preset future time period.

2. The low-carbon factory power system according to claim 1, characterized in that, The factory power system also includes: load devices; The load device is unidirectionally electrically connected to the test bench; the load device is also bidirectionally communicatively connected to the control device.

3. The low-carbon factory power system according to claim 1, characterized in that, The factory power system also includes: production equipment; The production equipment is also unidirectionally connected to the photovoltaic power generation equipment, the external power grid, and the energy storage module.

4. The low-carbon factory power system according to claim 1, characterized in that, The test stand includes multiple test positions, each corresponding to a different power level, for conducting test operations on the steam turbine or gas turbine of the respective power level.

5. The low-carbon factory power system according to claim 1, characterized in that, The control device is also used for: The production plan is optimized based on the first predicted power generation load. According to the optimized production plan, the production equipment is controlled to perform production operations within the preset future time period.

6. The low-carbon factory power system according to claim 1, characterized in that, Before obtaining the predicted energy storage load for the preset future time period based on the predicted electricity load and the first predicted power generation load, the control device is further configured to: Based on the weather forecast for the preset future time period, the photovoltaic physical model information corresponding to the photovoltaic power generation equipment is used for simulation and prediction to obtain the second predicted power generation load of the photovoltaic power generation equipment within the preset future time period; Based on the second predicted power generation load and the first predicted power generation load, the target predicted power generation load of the photovoltaic power generation equipment within the preset future time period is obtained; The step of obtaining the predicted energy storage load for the preset future time period based on the predicted electricity load and the first predicted power generation load includes: Based on the predicted electricity load and the target predicted power generation load, the predicted energy storage load for the preset future time period is obtained.

7. The low-carbon factory power system according to claim 1, characterized in that, The control device is also used for: Obtain the actual electricity consumption corresponding to at least one key evaluation indicator of the low-carbon factory power system; Based on the actual electricity consumption corresponding to each key evaluation indicator, the indicator parameters for each key evaluation indicator are calculated respectively.

8. The low-carbon factory power system according to claim 7, characterized in that, The control device is also used for: The electricity load prediction algorithm and / or power generation load prediction algorithm are updated based on the index parameters of each key evaluation indicator.

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