Central intelligent dispatching method and system for distributed energy in smart communities

Abstract

The present invention discloses a central intelligent dispatching method and system for distributed energy in a smart community, which belongs to the field of energy dispatching technology, and includes: step one, dividing the smart community into multiple power consumption blocks according to the power consumption plan, and configuring a sub-energy storage unit for each power consumption block; step two, dividing the power consumption time into multiple power consumption time periods, and allocating expected power to the sub-energy storage units of each power consumption block in each power consumption time period; step three, judging whether the allocated expected power is normal, and generating a dispatching instruction when it is judged to be abnormal; step four, dispatching the power in the energy storage module and the sub-energy storage unit according to the generated dispatching instruction. The present invention combines the current power consumption status value and the historical power consumption status value for comprehensive analysis, and can more accurately judge the power consumption required by each power consumption block, thereby dynamically dispatching electric energy, and ensuring the reasonable allocation and utilization of electric energy in the smart community.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy dispatching, and specifically relates to a central intelligent dispatching method and system for distributed energy in a smart community. Background Art

[0002] Smart community is a community development model that uses modern information technology and intelligent systems to improve community management efficiency, service quality and residents' quality of life. With the acceleration of urbanization, the rapid development of science and technology, and the continuous improvement of residents' quality of life, the development of smart communities has become more and more extensive.

[0003] When smart communities manage and dispatch distributed energy, they generally dispatch electricity based on the electricity demand of each electricity consumption area in the community. When dispatching electricity, the amount of electricity to be dispatched is generally allocated in advance. However, in actual use, due to the uncertainty of electricity consumption in different areas, if a fixed allocation is performed, it is easy to cause unbalanced electricity distribution, thus affecting the normal operation of the smart community. Summary of the invention

[0004] The purpose of the present invention is to provide a central intelligent scheduling method and system for distributed energy in a smart community, so as to solve the problems faced in the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A central intelligent dispatching method for distributed energy in a smart community, the dispatching method comprising:

[0007] Step 1: Divide the smart community into multiple power consumption blocks according to the power consumption plan, and configure a sub-energy storage unit for each power consumption block;

[0008] Step 2: Divide the electricity consumption time into multiple electricity consumption time periods, and the energy storage module allocates the estimated power to the sub-energy storage units of each electricity consumption block in each electricity consumption time period;

[0009] Step 3: Collect the power consumption data of each power consumption sector in real time, and conduct a comprehensive analysis based on historical data to determine whether the estimated power consumption is normal. If it is abnormal, generate a dispatch instruction;

[0010] Step 4: Dispatch the power in the energy storage module and the sub-energy storage unit according to the generated dispatch instruction.

[0011] Furthermore, the method for determining whether the allocated estimated power is normal in step 3 is:

[0012] Get the daily electricity consumption QH in the current time period in the historical database i ;

[0013] So through the formula The power consumption evaluation value F is obtained;

[0014] The obtained power consumption evaluation value F is compared with the preset standard power consumption evaluation value interval [F th1 , F th2 ] for comparison;

[0015] When F∈[F th1 , F th2 ], it is judged that the estimated power allocated in this time period is normal;

[0016] Otherwise, it is determined that the estimated amount of electricity to be allocated during the time period is abnormal, and a dispatch instruction is generated;

[0017] Among them, QR is the current power consumption status value, a1 and a2 are proportional coefficients, i∈[1,n], and n is the total number of historical days.

[0018] Furthermore, the method for obtaining the current power consumption status value QR is:

[0019] Get the time-varying curve Q of the electricity consumption of the electricity consumption block in the previous time period of the current time period N (t);

[0020] By formula Obtain the current power consumption value QR;

[0021] Among them, Q o (t) is the time-varying curve of the preset standard power consumption in the previous time period, t1 is the start time of the previous time period, t2 is the end time of the previous time period, β is the judgment coefficient, and m is the total number of times the power consumption was collected in the previous time period, Q>E Q is the number of times the power consumption is greater than the average power consumption in the collected times. max is the maximum power consumption collected in the previous time period, m Q<E Q is the number of times the power consumption is less than the average power consumption in the collected times. min is the minimum power consumption collected in the previous time period,

[0022] Furthermore, the scheduling instructions include increase instructions and decrease instructions:

[0023] When F∈(F th2 , +∞), an increase instruction is generated, and the electric energy in the energy storage module is dispatched to the sub-energy storage unit;

[0024] When F∈(-∞,F th1), a reduction instruction is generated, and the electric energy in the sub-energy storage unit is dispatched to the energy storage module.

[0025] Furthermore, the method for scheduling the power in the energy storage module and the sub-energy storage unit according to the scheduling instruction in step 4 is:

[0026] When the increase instruction is generated, the formula Dispatch the electric energy in the energy storage module to the sub-energy storage unit Q add Electricity;

[0027] When a reduction instruction is generated, the formula The electric energy in the sub-storage unit is dispatched to the energy storage module Q sub Electricity;

[0028] Among them, μ is the conversion coefficient, T is the ambient temperature detected in this time period, T0 is the preset standard temperature reference value, S is the number of devices consuming electricity in the electricity sector in this time period, S0 is the preset reference value of the number of electrical devices, and v1, v2, w1, and w2 are proportional coefficients.

[0029] A central intelligent dispatching system for distributed energy in a smart community, the system is applicable to the central intelligent dispatching method for distributed energy in a smart community, and the system includes:

[0030] An energy storage module, wherein the energy storage module is used to store the electric energy required by the smart community;

[0031] Multiple sub-energy storage units are connected to the energy storage module, and each of the sub-energy storage units provides electric energy for each power consumption block of the smart community;

[0032] An electricity consumption data collection module, which is used to obtain electricity consumption data generated by each electricity consumption block;

[0033] A data analysis module, which is used to conduct a comprehensive analysis based on the acquired power consumption data combined with the historical power consumption data, thereby generating a power consumption evaluation value, and judging whether the estimated power allocated by the sub-energy storage units of each power consumption block is normal based on the power consumption evaluation value, and generating a dispatch instruction when it is abnormal;

[0034] A scheduling module is used to schedule the electric energy of each sub-energy storage unit according to the generated scheduling instruction.

[0035] Furthermore, a prediction unit is provided in the energy storage module, and the prediction unit predicts the amount of electricity generated on the day according to the temperature change and the light change on the day.

[0036] Furthermore, the prediction unit performs prediction in the following manner:

[0037] Get the temperature change curve T of the day e (t) and the light intensity variation curve Lx(t);

[0038] By formula The predicted generated electricity QA is obtained;

[0039] Among them, g is the conversion coefficient, d is the number of photovoltaic panels, t a is the illumination start time, t b The end time of illumination.

[0040] Beneficial effects of the present invention:

[0041] The present invention divides the smart community into multiple power consumption blocks according to the power consumption plan, configures a sub-energy storage unit for each power consumption block, and distinguishes multiple power consumption time periods according to the power consumption time, and in each power consumption time period, the energy storage module allocates the estimated power to the sub-energy storage unit, so that the power can be allocated more reasonably, thereby reducing the waste of power; at the same time, the power consumption data of each power consumption block is collected in real time, and a comprehensive analysis is performed in combination with historical data to determine whether the allocated estimated power is normal. When it is determined to be abnormal, a scheduling instruction is generated to schedule the power in the energy storage module and the sub-energy storage unit, so that the power can be allocated more reasonably according to the real-time power consumption of each power consumption block, and the phenomenon of more power being allocated to the power consumption block with less power consumption and less power being allocated to the power consumption block with more power consumption is reduced, thereby ensuring the timely and reasonable allocation of power, thereby ensuring the normal operation of the entire smart community.

[0042] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0044] Figure 1 is a flow chart of the method of the present invention;

[0045] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] In one embodiment, a central intelligent dispatching method for distributed energy in a smart community is disclosed, such as Figure 1 As shown, the scheduling method mainly includes the following steps:

[0048] Step 1: Divide the smart community into multiple power consumption blocks according to the power consumption plan, and configure a sub-energy storage unit for each power consumption block;

[0049] Step 2: Divide the electricity consumption time into multiple electricity consumption time periods, and the energy storage module allocates the estimated power to the sub-energy storage units of each electricity consumption block in each electricity consumption time period;

[0050] Step 3: Collect the power consumption data of each power consumption sector in real time, and conduct a comprehensive analysis based on historical data to determine whether the estimated power consumption is normal. If it is abnormal, generate a dispatch instruction;

[0051] Step 4: Dispatch the power in the energy storage module and the sub-energy storage unit according to the generated dispatch instruction.

[0052] Through the above technical scheme, the present application divides the smart community into multiple power consumption blocks according to the power consumption plan, and configures a sub-energy storage unit for each power consumption block, and distinguishes multiple power consumption time periods according to the power consumption time, and in each power consumption time period, the energy storage module allocates the estimated power to the sub-energy storage unit, so that the power can be allocated more reasonably, thereby reducing the waste of power; at the same time, the power consumption data of each power consumption block is collected in real time, and a comprehensive analysis is performed in combination with historical data to determine whether the allocated estimated power is normal. When it is determined to be abnormal, a scheduling instruction is generated to schedule the power in the energy storage module and the sub-energy storage unit, so that the power can be allocated more reasonably according to the real-time power consumption of each power consumption block, and the phenomenon of allocating more power to the power consumption block with less power consumption and less power to the power consumption block with more power consumption is reduced, thereby ensuring the timely and reasonable allocation of power, thereby ensuring the normal operation of the entire smart community.

[0053] As an implementation mode of the present invention, the method for determining whether the allocated estimated power is normal in step 3 is:

[0054] Get the daily electricity consumption QH in the current time period in the historical database i ;

[0055] So through the formula The power consumption evaluation value F is obtained;

[0056] The obtained power consumption evaluation value F is compared with the preset standard power consumption evaluation value interval [F th1 , F th2 ] for comparison;

[0057] When F∈[F th1 , F th2 ], it is judged that the estimated power allocated in this time period is normal;

[0058] Otherwise, it is determined that the estimated amount of electricity to be allocated during the time period is abnormal, and a dispatch instruction is generated;

[0059] Among them, QR is the current power consumption value, a1 and a2 are proportional coefficients, i∈[1,n], n is the total number of historical days;

[0060] The method for obtaining the current power consumption value QR is:

[0061] Get the time-varying curve Q of the electricity consumption of the electricity consumption block in the previous time period of the current time period N (t);

[0062] By formula Obtain the current power consumption value QR;

[0063] Among them, Q O (t) is the time-varying curve of the preset standard power consumption in the previous time period, t1 is the start time of the previous time period, t2 is the end time of the previous time period, β is the judgment coefficient, and m is the total number of times the power consumption was collected in the previous time period, Q>E Q is the number of times the power consumption is greater than the average power consumption in the collected times. max is the maximum power consumption collected in the previous time period, m Q<E Q is the number of times the power consumption is less than the average power consumption in the collected times. min is the minimum power consumption collected in the previous time period,

[0064] Through the above technical solution, this embodiment provides a method for determining whether the allocated estimated power is normal. First, according to the historical power consumption of each power consumption block, the estimated power is allocated to each power consumption block. Since the daily power consumption is uncertain, in order to ensure a more reasonable allocation and utilization of electric energy, the current power consumption status value is first obtained. The method for obtaining the current power consumption status value QR is: obtain the power consumption change curve Q of the power consumption block in the previous time period of the current time period over time N (t), then by the formula The current power consumption value QR is obtained, where formula It shows the difference between the power consumption of the power consumption section and the standard power consumption in the previous time period. When its value is greater than 0, it means that more power is consumed at this time. When its value is less than 0, it means that less power is consumed at this time. At this time when At this time From the formula It can be seen that the higher the proportion of the number of times the power consumption is greater than the average power consumption in the total number of times collected in this time period, the higher the maximum power consumption Q collected in this time period. max The greater the difference between the standard average value, the more electricity is needed. It can be seen that the higher the proportion of the number of times the power consumption is less than the average power consumption in the total number of times collected in the time period, the greater the difference between the minimum power consumption collected in the time period and the standard average value, indicating that less power is needed. Therefore, through the formula Get the current power consumption value QR, and then use the formula to get The historical electricity consumption during this period is calculated by the formula The power consumption evaluation value F is obtained. When the value is larger, it means that more power is needed, and when the value is smaller, it means that less power is needed. Therefore, the obtained power consumption evaluation value F is compared with the preset standard power consumption evaluation value interval [F th1 , F th2 ] to compare, when F∈[F th1 , F th2 ], it means that the obtained power consumption judgment value is within the preset normal range, and the estimated power allocated in this time period is normal. Otherwise, the estimated power allocated in this time period is abnormal, and the power needs to be dispatched accordingly to ensure normal operation, and then a dispatch instruction is generated. In this way, we can derive the current power consumption status value based on the real-time power consumption situation, and then conduct a comprehensive analysis based on the current power consumption status value and the historical power consumption status value to more accurately determine the power consumption required by each power consumption sector, so as to dynamically dispatch electric energy and ensure the reasonable allocation and utilization of electric energy.

[0065] In the above technical solution, the proportional coefficients a1 and a2, the standard power consumption evaluation value range [F th1 , F th2 ] can be determined based on experience, and the standard power consumption curve Q O(t) can be formulated based on historical electricity consumption, while the start time t1, end time t2 of the time period and the total number of times m of electricity consumption collected within the time period can be determined artificially based on actual conditions, which will not be described in detail here.

[0066] As an implementation mode of the present invention, the scheduling instruction includes an increase instruction and a decrease instruction:

[0067] When F∈(F th2 , +∞), an increase instruction is generated, and the electric energy in the energy storage module is dispatched to the sub-energy storage unit. At this time, the formula Dispatch the electric energy in the energy storage module to the sub-energy storage unit Q add Electricity;

[0068] When F∈(-∞,F th1 ), a reduction instruction is generated, and the electric energy in the sub-energy storage unit is dispatched to the energy storage module. At this time, the formula The electric energy in the sub-storage unit is dispatched to the energy storage module Q sub Electricity;

[0069] Among them, μ is the conversion coefficient, T is the ambient temperature detected in this time period, T0 is the preset standard temperature reference value, S is the number of devices consuming electricity in the electricity sector in this time period, S0 is the preset reference value of the number of electrical devices, and v1, v2, w1, and w2 are proportional coefficients.

[0070] Through the above technical solution, this embodiment provides a specific method for scheduling the power in the energy storage module and the sub-energy storage unit according to the generated scheduling instruction, and the scheduling instruction includes an increase instruction and a decrease instruction. When F∈(F th2 , +∞), it means that the power consumption evaluation value is too large, indicating that the power consumption needs to increase. The power in the sub-energy storage unit is insufficient, and an increase instruction is generated. At this time, the power in the energy storage module is dispatched to the sub-energy storage unit, and the formula is used to calculate the power consumption. Dispatch the electric energy in the energy storage module to the sub-energy storage unit Q add The amount of electricity required is not only related to the electricity assessment value, but also to other factors. For example, the more devices that consume electricity in this time period, the more electricity is required. For example, when the ambient temperature is too high or too low, the amount of electricity required will also increase. Therefore, taking these factors into consideration, it can be seen from the formula that the more devices that consume electricity in this time period, or the greater the difference between the ambient temperature and the standard temperature in this time period, the more electricity is required. Then, the amount of electricity Q that needs to be dispatched from the energy storage module to the sub-energy storage unit. addThe more; similarly when F∈(-∞, F th1 ), it means that the power consumption evaluation value is too small, indicating that the power consumption block does not need to use too much power, and a reduction instruction is generated. At this time, the power in the sub-energy storage unit is dispatched to the energy storage module to supply other required sub-energy storage units, and the formula is used to calculate the power consumption of the sub-energy storage unit. The electric energy in the sub-storage unit is dispatched to the energy storage module Q sub From the formula, we can see that when the power consumption evaluation value is smaller, the required power is smaller, and the more power can be dispatched out; when the difference between the ambient temperature and the standard temperature is smaller, or the number of devices using power in this time period is smaller, the more power can be dispatched out. In this way, we can conduct a comprehensive analysis based on the power consumption evaluation value obtained, combined with the ambient temperature of each power consumption block and the number of power consumption devices, so that when it is determined that the allocated estimated power is abnormal, the power can be accurately dispatched to ensure that the power is reasonably allocated and utilized.

[0071] In the above technical scheme, the proportional coefficients v1, v2, w1, and w2 can be determined based on experience, the ambient temperature T can be obtained through the corresponding temperature sensor, the number of electrical equipment S can be determined based on the power consumption of each device, and the preset reference value S0 of the number of electrical equipment, the preset standard temperature reference value T0, and the conversion coefficient μ can be formulated based on historical data combined with empirical data, which will not be described in detail here.

[0072] In one embodiment, a central intelligent dispatching system for distributed energy in a smart community is also disclosed. Figure 2 As shown, the system is applicable to the above-mentioned central intelligent dispatching method for distributed energy in a smart community, and the system includes:

[0073] Energy storage module, which is used to store the electric energy required by the smart community;

[0074] Multiple sub-energy storage units are connected to the energy storage module, and each sub-energy storage unit provides electricity for each power consumption section of the smart community;

[0075] The electricity consumption data collection module is used to obtain the electricity consumption data generated by each electricity consumption block;

[0076] Data analysis module: The data analysis module is used to conduct a comprehensive analysis based on the acquired power consumption data combined with the historical power consumption data, thereby generating a power consumption evaluation value, and judging whether the estimated power allocated by the sub-energy storage units of each power consumption block is normal based on the power consumption evaluation value. If it is abnormal, a dispatch instruction is generated;

[0077] A dispatching module, which dispatches the electric energy of each sub-energy storage unit according to the generated dispatching instructions;

[0078] The energy storage module is also provided with a prediction unit, which predicts the amount of electricity generated on the day based on the temperature and light changes of the day. The prediction method of the prediction unit is as follows:

[0079] Get the temperature change curve T of the day e (t) and the light intensity variation curve Lx(t);

[0080] By formula The predicted generated electricity QA is obtained;

[0081] Among them, g is the conversion coefficient, d is the number of photovoltaic panels, t a is the illumination start time, t b The end time of illumination.

[0082] Through the above technical solution, this embodiment provides a central intelligent dispatching system for distributed energy in a smart community, which includes: an energy storage module, multiple sub-energy storage units, an electricity consumption data acquisition module, a data analysis module and a dispatching module, so as to realize the above central intelligent dispatching method for distributed energy in a smart community, wherein a prediction unit is also provided in the energy storage module, and the prediction unit predicts the amount of electricity generated on the day according to the temperature change and the light change on the day, so that the amount of electricity that needs to be purchased from the power grid can be predicted according to the electricity generated by the photovoltaic panels on the day, so as to facilitate the relevant personnel to manage the purchase of electricity; and the method for the prediction by the measurement unit is: first obtain the temperature change curve T of the day e (t) and the light intensity variation curve Lx(t), and then through the formula The predicted generated electricity Q is obtained A Generally speaking, the greater the light intensity, the more electricity is generated, and the efficiency of photovoltaic panels decreases as the temperature rises. Similarly, the longer the light time and the more photovoltaic panels there are, the more electricity they generate. Therefore, through the formula The predicted generated electricity Q is obtained A In this way, the amount of electricity generated by photovoltaic panels can be predicted based on a comprehensive analysis of the day's sunshine duration, changes in light intensity, and temperature changes, so that managers can purchase electricity from the grid accordingly, reducing electricity cost output without affecting the normal operation of the smart community.

[0083] In the above technical solution, the illumination start time t a and the end time t b It can be determined based on the conditions of the day. The temperature and light intensity of the day can be obtained through corresponding sensors, and the conversion coefficient can be determined based on relevant industry standards combined with practical experience, which will not be described in detail here.

[0084] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A central intelligent dispatching method for distributed energy in smart communities, characterized in that: The scheduling method comprises: Step 1: Divide the smart community into multiple power consumption blocks according to the power consumption plan, and configure a sub-energy storage unit for each power consumption block; Step 2: Divide the electricity consumption time into multiple electricity consumption time periods, and the energy storage module allocates the estimated power to the sub-energy storage units of each electricity consumption block in each electricity consumption time period; Step 3: Collect the power consumption data of each power consumption sector in real time, and conduct a comprehensive analysis based on historical data to determine whether the estimated power consumption is normal. If it is abnormal, generate a dispatch instruction; Step 4: Dispatching the power in the energy storage module and the sub-energy storage unit according to the generated dispatching instruction; The method for determining whether the estimated power consumption allocated in step 3 is normal is to obtain the daily power consumption in the current time period from the historical database. ; So through the formula Get the power consumption evaluation value ; The power consumption evaluation value obtained The preset standard power consumption evaluation value range Make a comparison; when When , it is judged that the estimated power allocated in this time period is normal; Otherwise, it is determined that the estimated amount of electricity allocated during the time period is abnormal, and a dispatch instruction is generated; in, is the current power usage value, as well as is the proportionality coefficient, , is the total number of historical days; The current power usage value The method of obtaining is: obtain the time-varying curve of the electricity consumption of the electricity consumption block in the previous time period of the current time period ; By formula Get the current power consumption value ; in, It is the time-varying curve of the preset standard power consumption in the previous time period. is the start time of the previous time period, The end time of the previous time period. is the judgment coefficient, and , is the total number of times electricity consumption was collected in the previous time period. The number of times the power consumption is greater than the average power consumption among the collected times, is the maximum power consumption collected in the previous time period, The number of times the power consumption is less than the average power consumption among the collected times, is the minimum power consumption collected in the previous time period, E is the average power consumption, and .

2. The central intelligent dispatching method for distributed energy in smart communities according to claim 1 is characterized in that: The scheduling instructions include increase instructions and decrease instructions: when When , an increase instruction is generated, and the electric energy in the energy storage module is dispatched to the sub-energy storage unit; when When , a reduction instruction is generated, and the electric energy in the sub-energy storage unit is dispatched to the energy storage module.

3. The central intelligent dispatching method for distributed energy in smart communities according to claim 2 is characterized in that: The method for scheduling the power in the energy storage module and the sub-energy storage unit according to the scheduling instruction in step 4 is: When the increase instruction is generated, the formula Dispatch the electric energy in the energy storage module to the sub-energy storage unit Power; When a reduction instruction is generated, the formula Dispatch the electric energy in the sub-storage unit to the energy storage module Power; in, is the conversion coefficient, is the ambient temperature detected during this time period, is the preset standard temperature reference value, is the number of devices that consume electricity in the electricity consumption sector during this time period. is the preset reference value of the number of electrical equipment. is the proportionality coefficient.

4. The central intelligent dispatching system for distributed energy in smart communities is characterized by: The system is applicable to the central intelligent dispatching method for distributed energy in a smart community according to any one of claims 1 to 3, and the system comprises: An energy storage module, wherein the energy storage module is used to store the electric energy required by the smart community; Multiple sub-energy storage units are connected to the energy storage module, and each of the sub-energy storage units provides electric energy for each power consumption block of the smart community; An electricity consumption data collection module, which is used to obtain electricity consumption data generated by each electricity consumption block; A data analysis module, which is used to conduct a comprehensive analysis based on the acquired power consumption data combined with the historical power consumption data, thereby generating a power consumption evaluation value, and judging whether the estimated power allocated by the sub-energy storage units of each power consumption block is normal based on the power consumption evaluation value, and generating a dispatch instruction when it is abnormal; A scheduling module is used to schedule the electric energy of each sub-energy storage unit according to the generated scheduling instruction.

5. The central intelligent dispatching system for distributed energy in smart communities according to claim 4 is characterized in that: The energy storage module is also provided with a prediction unit, which predicts the amount of electricity generated on the day according to the temperature change and light change on the day.

6. The central intelligent dispatching system for distributed energy in smart communities according to claim 5 is characterized in that: The prediction method of the prediction unit is: Get the temperature change curve of the day And the light intensity variation curve over time ; By formula Calculate the predicted power generation ; in, is the conversion factor, is the number of photovoltaic panels, is the illumination start time, The end time of illumination.

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