Street lamp energy-saving management system based on big data analysis

Abstract

The invention discloses a street lamp energy-saving management system based on big data analysis, and the system comprises a collection end which is used for collecting the flow information and illumination information of a road corresponding to a street lamp, storing the flow information and the illumination information, and transmitting the flow information and the illumination information to a processing end for illumination energy-saving processing; the processing end is used for receiving the flow information and the illumination information, generating corresponding required illumination, transmitting the required illumination to the monitoring end, and performing energy-saving processing on the street lamp so as to adjust the real-time mains supply consumption of the street lamp; and the monitoring end is used for receiving the required illumination value transmitted by the processing end, obtaining the actual illumination on the road surface, and comparing the required illumination data with the actual illumination. However, repeated switching on and off of the street lamp easily leads to unfixed lighting time, and actual urban lighting requirements are affected.

Description

Technical Field

[0001] The present invention relates to the technical field of street lamps, and in particular to a street lamp energy-saving management system based on big data analysis. Background Art

[0002] Street lamps are an important means of urban lighting projects. All regions regard the construction of urban night lighting as an important means to change the appearance of the city and improve the investment environment. However, the resulting electricity bills and maintenance expenses are also very alarming. The invention patent with application number CN201210562813.0 discloses a street lamp energy-saving management system and a street lamp energy-saving control method. The switch box reads the switch strategy stored locally and supports single-lamp single control in both switch control and dimming control modes; energy-saving control can be combined with daylighting.

[0003] Although this management system has the above advantages when in use, it still has certain disadvantages. It reduces the actual power consumption of street lamps by calculating the switching of street lamps and controlling the lighting time of street lamps. However, repeated switching will lead to inconsistent lighting time, affecting the actual urban lighting needs. Therefore, it is necessary to solve the shortcomings of the existing technology. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a street lamp energy-saving management system based on big data analysis, which solves the problem that when the existing street lamp energy-saving management system is used, energy saving is achieved by repeatedly switching street lamps on and off to reduce power consumption, but the repeated switching of street lamps easily leads to unstable lighting time, affecting the actual urban lighting needs.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A street lamp energy-saving management system based on big data analysis, comprising:

[0006] The collection end is used to collect the traffic information and lighting information on the road corresponding to the street lamp, and then store the traffic information and lighting information and transmit them to the processing end for lighting energy saving processing;

[0007] The processing end is used to receive traffic information and light information, generate corresponding required illumination and transmit it to the monitoring end, and perform energy-saving processing on the street lamps to adjust the real-time mains power consumption of the street lamps;

[0008] The monitoring end is used to receive the required illuminance value transmitted by the processing end, and obtain the actual illuminance on the road surface. By comparing the required illuminance data with the actual illuminance, the illuminance of the road surface is monitored and an abnormal signal is generated;

[0009] The energy storage end obtains the lighting information inside the collection end, and stores and distributes the electricity that can be provided by natural light illumination.

[0010] Preferably, the traffic information includes the flow of people and vehicles when the street lamps are illuminated, and the lighting information includes the natural light illumination at the corresponding position of the street lamp and its corresponding lighting duration.

[0011] Preferably, the specific processing method of mains power consumption is:

[0012] The obtained pedestrian and vehicle flows are marked as flow data lj, and the illumination duration Sj corresponding to the flow data lj is obtained, where j = 1, 2, 3, ..., m. A scatter plot is formed with the value of the flow data lj as the vertical axis and the value of j as the horizontal axis. The scatter points corresponding to the flow data lj are fitted to obtain the linear fitting formula and fitting data Nj. Then, according to Get the deviation from the mean A, and then use the linear fitting formula to get the fitting data N for m+1 days m+1 , and according to N m+1 +A=l m+1 , obtain the flow data of the day lm+1, and use the same processing method as the flow data lj to obtain the day's sunshine duration S m+1 ;

[0013] Through P4=P1-P2-P3, the power supply output power P4 required to be provided by the mains is obtained.

[0014] Preferably, the specific monitoring method is:

[0015] Obtain the required illuminance value and actual illuminance value of the road surface, and make a judgment based on the required illuminance data ≦ actual illuminance value;

[0016] If satisfied, a normal monitoring signal is generated without any processing;

[0017] If it is not satisfied, an abnormal illumination signal is generated and secondary monitoring is performed.

[0018] Preferably, the specific method of secondary monitoring is:

[0019] Obtain an abnormal illumination signal, increase the value of the power output power P4, obtain the actual illumination of the road surface again, and compare it with the required illumination value again;

[0020] If satisfied, no action is taken;

[0021] If the conditions are still not met, an abnormal propagation signal is generated and sent to the management terminal to remind municipal personnel to inspect the street lights and trim the greenery on the road surface.

[0022] Preferably, the specific energy storage method is:

[0023] The street lamp is marked as Di, where i = 1, 2, 3, ..., n, indicating that a total of n street lamps are obtained for power distribution, and then the natural light illumination and lighting duration corresponding to the street lamp Di are obtained, and then the parameters of the photovoltaic panel corresponding to the street lamp Di are obtained to obtain the power generation Qi corresponding to the street lamp Di, and the storage capacity Q of the battery corresponding to the street lamp Di is obtained.

[0024] The judgment is made based on Qi-Q≧0. If it is not satisfied, the electricity generated by the photovoltaic panel is directly stored in the battery.

[0025] If it is met, the excess power will be allocated.

[0026] Preferably, the specific distribution method of electricity is:

[0027] The distance between two street lamps Di is calculated, and the corresponding power loss coefficient Wi is obtained, where i = 1, 2, 3, ..., n-1, indicating that there are n-1 power loss coefficients in total, Wn-1 is the power loss coefficient corresponding to the two street lamps Di with the longest distance, and Wn-1 is the maximum value of the power loss coefficient, and W1 is the minimum value of the power loss coefficient;

[0028] The power generation Qi corresponding to Qi-Q≧0 is marked as the surplus power Bi, and the power generation corresponding to Qi-Q<0 is marked as the difference power Ci;

[0029] According to Bi*Wi=Ci, if it is satisfied, the corresponding remaining power Bi is transmitted to the storage battery corresponding to the difference power Ci for storage;

[0030] If not, the remaining power Bi will be redistributed.

[0031] Preferably, the specific method of secondary distribution is:

[0032] According to Wi*a+Ci*b=E, where E is the weight value corresponding to the differential charge Ci, and a and b are both preset weight coefficients,

[0033] When distributing the maximum value in the power generation Qi, obtain the power difference Ci with the largest corresponding weight value, and then transfer it to the battery corresponding to the power difference Ci for storage. If the battery can be fully charged, the remaining power will be redistributed in the same way. If the battery cannot be fully charged, the battery will be fully charged by redistributing the remaining power.

[0034] Beneficial Effects

[0035] The present invention provides a street lamp energy-saving management system based on big data analysis. Compared with the prior art, it has the following beneficial effects:

[0036] (1) By utilizing natural light to enhance the illumination of street lamps and providing power output through photovoltaic power generation, the actual consumption of municipal electricity by street lamps can be reduced, thereby achieving energy-saving effects when using street lamps.

[0037] (2) By monitoring the actual illumination of the road surface and comparing it with the required illumination of the road surface, the street lighting can be monitored to avoid affecting the lighting demand and avoid the problem of power loss caused by abnormal street lighting.

[0038] (3) The amount of photovoltaic power that can be obtained is calculated by measuring the natural light intensity in the area corresponding to the street lamp and the parameters of the photovoltaic panel. The distribution and storage of photovoltaic power is achieved by counting the battery reserves of the street lamps in the area, maximizing the acquisition of photovoltaic power to save the street lamp's demand for municipal electricity and reduce the actual energy consumption of the street lamp. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a system block diagram of the energy-saving management system of the present invention. DETAILED DESCRIPTION

[0040] 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.

[0041] See also Figure 1 The present invention provides a street lamp energy-saving management system based on big data analysis:

[0042] As the first embodiment of the present application, it specifically includes:

[0043] The collection end is used to collect the pedestrian and vehicle flow when the street lamps are corresponding to the road lighting, and to collect the natural light illumination and the corresponding lighting duration in the area corresponding to the street lamps. The collected pedestrian and vehicle flow, natural light illumination and the corresponding lighting duration are then stored and transmitted to the processing end for lighting energy-saving processing.

[0044] The processing end is used to receive the pedestrian and vehicle flow, natural light illumination and corresponding illumination duration transmitted by the collection end and perform illumination energy-saving processing to adjust the real-time mains power consumption of street lamps; the specific processing method is as follows:

[0045] The obtained pedestrian and vehicle flows are marked as flow data lj, and the illumination duration Sj corresponding to the flow data lj is obtained, (the illumination duration SJ represents the duration between the generation and the end of the flow data lj, that is, the duration between the start of street lighting and the absence of pedestrians and vehicles), wherein j = 1, 2, 3, ..., m, wherein m is a positive integer, representing that a total of m days of pedestrian and vehicle flows are obtained, and lm is the flow data corresponding to the previous day, a scatter plot is formed with the value of the flow data lj as the vertical axis and the value of j as the horizontal axis, and the scatter points corresponding to the flow data lj are fitted to obtain a linear fitting formula and fitting data Nj, wherein the flow data lj and the fitting data Nj are in one-to-one correspondence, and then according to Get the deviation from the mean A, and then use the linear fitting formula to get the fitting data N for m+1 days m+1 , and according to N m+1 +A=l m+1 , obtain the flow data of the day lm+1, and use the same processing method as the flow data lj to obtain the day's sunshine duration S m+1 ;

[0046] Through P4=P1-P2-P3, the power supply output power P4 required to be provided by the mains is obtained, and the power of the mains is distributed and output according to the power supply output power P4.

[0047] As the second embodiment of the present application, it specifically includes:

[0048] The monitoring end is used to receive the required illumination value transmitted by the processing end and collect the actual illumination of the road surface to monitor the output illumination of the street lamp;

[0049] The specific monitoring methods are:

[0050] Obtain the required illuminance value and actual illuminance value of the road surface, and make a judgment based on the required illuminance data ≦ actual illuminance value;

[0051] If satisfied, a normal monitoring signal is generated without any processing;

[0052] If it is not satisfied, an abnormal illumination signal is generated and secondary monitoring is performed;

[0053] The specific methods of secondary monitoring are:

[0054] Obtain an abnormal illumination signal, increase the value of the power output power P4, obtain the actual illumination of the road surface again, and compare it with the required illumination value again;

[0055] If satisfied, no action is taken;

[0056] If the conditions are still not met, an abnormal propagation signal is generated and sent to the management terminal to remind municipal personnel to inspect the street lights and trim the greenery on the road surface.

[0057] As the third embodiment of the present application, it specifically includes:

[0058] The energy storage end obtains the natural light illumination and corresponding illumination duration stored in the collection end, and stores and distributes the power generated by the natural light illumination;

[0059] The specific energy storage methods are:

[0060] The street lamp is marked as Di, where i = 1, 2, 3, ..., n, indicating that a total of n street lamps are obtained for power distribution, and then the natural light illumination and lighting duration corresponding to the street lamp Di are obtained, and then the parameters of the photovoltaic panel corresponding to the street lamp Di are obtained to obtain the power generation Qi corresponding to the street lamp Di, and the storage capacity Q of the battery corresponding to the street lamp Di is obtained.

[0061] The judgment is made based on Qi-Q≧0. If it is not satisfied, the electricity generated by the photovoltaic panel is directly stored in the battery.

[0062] If it is satisfied, the excess power is allocated:

[0063] The specific distribution of electricity is as follows:

[0064] The distance between two street lamps Di is calculated, and the corresponding power loss coefficient Wi is obtained, where i = 1, 2, 3, ..., n-1, indicating that there are n-1 power loss coefficients in total, Wn-1 is the power loss coefficient corresponding to the two street lamps Di with the longest distance, and Wn-1 is the maximum value of the power loss coefficient, and W1 is the minimum value of the power loss coefficient;

[0065] The power generation Qi corresponding to Qi-Q≧0 is marked as the surplus power Bi, and the power generation corresponding to Qi-Q<0 is marked as the difference power Ci;

[0066] According to Bi*Wi=Ci, if it is satisfied, the corresponding remaining power Bi is transmitted to the storage battery corresponding to the difference power Ci for storage;

[0067] If not, the remaining power Bi is redistributed;

[0068] The specific method of secondary distribution is:

[0069] According to Wi*a+Ci*b=E, where E is the weight value corresponding to the differential charge Ci, and a and b are both preset weight coefficients,

[0070] When distributing the maximum value in the power generation Qi, obtain the power difference Ci with the largest corresponding weight value, and then transfer it to the battery corresponding to the power difference Ci for storage. If the battery can be fully charged, the remaining power will be redistributed in the same way. If the battery cannot be fully charged, the battery will be fully charged by redistributing the remaining power.

[0071] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A street lamp energy-saving management system based on big data analysis, characterized in that: include: The collection end is used to collect the traffic information and lighting information on the road corresponding to the street lamp, and then store the traffic information and lighting information and transmit them to the processing end for lighting energy saving processing; The processing end is used to receive traffic information and light information, generate corresponding required illumination and transmit it to the monitoring end, and perform energy-saving processing on the street lamps to adjust the real-time mains power consumption of the street lamps; The monitoring end is used to receive the required illuminance value transmitted by the processing end, and obtain the actual illuminance on the road surface. By comparing the required illuminance data with the actual illuminance, the illuminance of the road surface is monitored and an abnormal signal is generated; The energy storage end obtains the lighting information inside the collection end, and stores and distributes the electricity that can be provided by natural light illumination.

2. According to claim 1, a street lamp energy-saving management system based on big data analysis is characterized in that: Traffic information includes the flow of people and vehicles when street lamps are illuminated, and lighting information includes the natural light illumination at the corresponding position of the street lamp and its corresponding lighting duration.

3. According to the street lamp energy-saving management system based on big data analysis as claimed in claim 1, it is characterized by: Specific treatment methods for mains electricity consumption: The obtained pedestrian and vehicle flows are marked as flow data lj, and the illumination duration Sj corresponding to the flow data lj is obtained, where j = 1, 2, 3, ..., m. A scatter plot is formed with the value of the flow data lj as the vertical axis and the value of j as the horizontal axis. The scatter points corresponding to the flow data lj are fitted to obtain the linear fitting formula and fitting data Nj. Then, according to Get the deviation from the mean A, and then use the linear fitting formula to get the fitting data N for m+1 days m+1 , and according to N m+1 +A=l m+1 , obtain the flow data of the day lm+1, and use the same processing method as the flow data lj to obtain the day's sunshine duration S m+1 ; Through P4=P1-P2-P3, the power supply output power P4 required to be provided by the mains is obtained.

4. According to claim 1, a street lamp energy-saving management system based on big data analysis is characterized in that: The specific monitoring methods are: Obtain the required illuminance value and actual illuminance value of the road surface, and make a judgment based on the required illuminance data ≦ actual illuminance value; If satisfied, a normal monitoring signal is generated without any processing; If it is not satisfied, an abnormal illumination signal is generated and secondary monitoring is performed.

5. The street lamp energy-saving management system based on big data analysis according to claim 4 is characterized in that: The specific methods of secondary monitoring are: Obtain an abnormal illumination signal, increase the value of the power output power P4, obtain the actual illumination of the road surface again, and compare it with the required illumination value again; If satisfied, no action is taken; If the conditions are still not met, an abnormal propagation signal is generated and sent to the management terminal to remind municipal personnel to inspect the street lights and trim the greenery on the road surface.

6. The street lamp energy-saving management system based on big data analysis according to claim 1 is characterized in that: The specific energy storage methods are: The street lamp is marked as Di, where i = 1, 2, 3, ..., n, indicating that a total of n street lamps are obtained for power distribution, and then the natural light illumination and lighting duration corresponding to the street lamp Di are obtained, and then the parameters of the photovoltaic panel corresponding to the street lamp Di are obtained to obtain the power generation Qi corresponding to the street lamp Di, and the storage capacity Q of the battery corresponding to the street lamp Di is obtained. The judgment is made based on Qi-Q≧0. If it is not satisfied, the electricity generated by the photovoltaic panel is directly stored in the battery. If it is met, the excess power will be allocated.

7. The street lamp energy-saving management system based on big data analysis according to claim 6 is characterized by: The specific distribution of electricity is as follows: The distance between two street lamps Di is calculated, and the corresponding power loss coefficient Wi is obtained, where i = 1, 2, 3, ..., n-1, indicating that there are n-1 power loss coefficients in total, Wn-1 is the power loss coefficient corresponding to the two street lamps Di with the longest distance, and Wn-1 is the maximum value of the power loss coefficient, and W1 is the minimum value of the power loss coefficient; The power generation Qi corresponding to Qi-Q≧0 is marked as the surplus power Bi, and the power generation corresponding to Qi-Q<0 is marked as the difference power Ci; According to Bi*Wi=Ci, if it is satisfied, the corresponding remaining power Bi is transmitted to the storage battery corresponding to the difference power Ci for storage; If not, the remaining power Bi will be redistributed.

8. The street lamp energy-saving management system based on big data analysis according to claim 7 is characterized in that: The specific method of secondary distribution is: According to Wi*a+Ci*b=E, where E is the weight value corresponding to the differential charge Ci, and a and b are both preset weight coefficients, When distributing the maximum value in the power generation Qi, obtain the power difference Ci with the largest corresponding weight value, and then transfer it to the battery corresponding to the power difference Ci for storage. If the battery can be fully charged, the remaining power will be redistributed in the same way. If the battery cannot be fully charged, the battery will be fully charged by redistributing the remaining power.

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