Power distribution network technology loss reduction effect influence analysis method, system and equipment

Abstract

The invention provides a power distribution network technology loss reduction effect influence analysis method, system and equipment, and the method comprises the steps: analyzing the historical data of a transformer area, and obtaining the time distribution, fluctuation rule and seasonal change of an electric heating load; predicting the theoretical active power supply quantity, the active power sale quantity and the heavy overload time of the transformer area according to the real-time operation data and the environment data of the power distribution network in combination with the time distribution, the fluctuation rule and the seasonal change of the electric heating load; calculating key indexes based on the theoretical active power supply quantity and the active power sale quantity of the transformer area and the active power supply quantity and the active power sale quantity in the same period in the historical data; determining a technical loss reduction scheme based on the key indexes, and obtaining update parameters after the technical loss reduction scheme is implemented; and calculating a financial net present value based on the updated parameter, and determining a technical loss reduction effect according to the financial net present value. According to the method, the electric heating load characteristics are considered, the effectiveness of the loss reduction strategy is accurately evaluated, and a scientific basis is provided for further optimizing the strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network, and in particular to a method, system and device for analyzing the impact of distribution network technology loss reduction effectiveness. Background Art

[0002] As the terminal link of the power system, the distribution network is an important part connecting the transmission network and the end users, and plays the role of distributing electric energy. In this process, due to the physical characteristics and operating conditions of equipment such as cables, transformers, switches, and wires, a certain amount of energy loss will occur. Especially after considering the load characteristics of electric heating, the load distribution and operating efficiency of the distribution network will be affected, making the loss reduction work more complicated. As a major heating method, the load characteristics of electric heating have obvious time and periodicity. In winter, due to the increase in heating demand, the electric heating load will increase significantly, bringing greater pressure to the distribution network. At the same time, the volatility and uncertainty of the electric heating load also bring challenges to the stable operation and loss reduction of the distribution network.

[0003] In this context, the reduction of distribution network technology losses has become a research focus. By optimizing the grid structure, improving equipment design, and increasing the efficiency of power transmission, the energy loss of the system can be effectively reduced. At the same time, the application of technologies such as intelligent monitoring, scheduling, and management also provides strong support for the reduction of distribution network losses. However, the existing distribution network technology loss reduction methods often do not fully consider the impact of electric heating load characteristics.

[0004] There is insufficient analysis of the impact of technical loss reduction on the existing distribution network when considering the characteristics of electric heating loads.

[0005] First, existing loss reduction analysis methods for distribution networks often fail to fully consider the particularity of electric heating loads. Electric heating loads have their own unique time characteristics and periodic changes. For example, during the winter heating period, the electric heating load will increase significantly, which will have a significant impact on the stability and efficiency of the distribution network. Therefore, if the changes in electric heating loads cannot be accurately analyzed and predicted, it will be difficult to develop an effective loss reduction strategy.

[0006] Second, existing distribution network loss reduction strategies often lack targeted optimization of electric heating load characteristics. Traditional loss reduction methods may focus more on line design, equipment updates, etc., without fully considering the impact of electric heating loads on the distribution network. This may lead to poor loss reduction effects and may even exacerbate line losses in some cases.

[0007] Third, the existing methods for analyzing the effectiveness of distribution network loss reduction are insufficient in terms of data analysis and processing capabilities. Due to the complexity and diversity of electric heating load data, more advanced data analysis and processing technologies are needed to extract useful information and provide a scientific basis for the formulation of loss reduction strategies. However, existing analysis methods often fail to meet this demand, resulting in a lack of sufficient data support for the formulation of loss reduction strategies.

[0008] The technical solutions that are most similar to the distribution network technical loss reduction effectiveness analysis method considering the load characteristics of electric heating may include the following:

[0009] 1) Distribution network loss reduction method based on intelligent optimization algorithm: This method uses intelligent optimization algorithms (such as genetic algorithms, particle swarm optimization algorithms, etc.) to optimize the operating parameters and structure of the distribution network to reduce power loss. By comprehensively considering factors such as load characteristics, equipment parameters and line layout, the intelligent optimization algorithm can find the optimal distribution network operation plan to achieve the purpose of loss reduction.

[0010] 2) Dynamic loss reduction strategy of distribution network based on load forecasting: This method uses advanced load forecasting technology to accurately predict the load changes of the distribution network, and dynamically adjusts the operation mode and equipment configuration of the distribution network according to the forecast results. By responding to changes in load characteristics in real time, the power loss of the distribution network can be effectively reduced.

[0011] 3) Distribution network loss reduction optimization method based on big data analysis: Using big data analysis technology, the operation data of the distribution network is deeply mined and analyzed to reveal the correlation between load characteristics and power loss. Based on these rules, more accurate loss reduction strategies can be formulated, and the operation performance of the distribution network can be continuously optimized through real-time monitoring and adjustment.

[0012] These technical solutions all take into account the impact of load characteristics on distribution network losses and use advanced technical means to optimize the operation of the distribution network to achieve the purpose of reducing losses. However, there are several major disadvantages:

[0013] First, the characteristics of electric heating loads are not adequately considered. At present, many distribution network loss reduction technical solutions do not fully consider the unique characteristics of electric heating loads, such as large load fluctuations and obvious seasonality. As a result, in actual operation, the loss reduction effect may not be ideal, and even the loss may increase.

[0014] Second, data analysis and processing capabilities are limited. Existing technologies often rely on traditional data analysis methods, which are difficult to effectively process large-scale, highly complex electric heating load data. This makes it impossible to accurately capture the changing patterns of electric heating loads, and thus it is impossible to formulate more accurate loss reduction strategies.

[0015] Third, the loss reduction strategy lacks specificity and flexibility. Due to the lack of understanding of the characteristics of electric heating loads in existing technologies, the loss reduction strategies developed are often too general and lack specificity and flexibility. As a result, in actual applications, the loss reduction strategy may not be able to adapt to the changes in electric heating loads, resulting in poor loss reduction effects.

[0016] Fourth, the level of intelligence is not high. Existing technologies are still insufficient in the intelligent management and monitoring of distribution networks, making it difficult to achieve real-time, accurate monitoring and dispatching of distribution networks. This results in the distribution network being unable to effectively cope with load pressure during peak hours of electric heating loads, thereby increasing the risk of line losses.

[0017] Fifth, the speed of technology update and iteration is slow: the distribution network loss reduction technology involves the cross-integration of knowledge in multiple fields and disciplines, and the speed of technology update and iteration is relatively slow. With the rapid development of the power industry and the continuous changes in load characteristics, existing technologies may not be able to adapt to new demands and challenges in a timely manner, resulting in limited loss reduction effects.

[0018] In summary, the existing technology still has many shortcomings in reducing the loss of distribution network technology considering the characteristics of electric heating load, which needs further research and improvement. Summary of the invention

[0019] In order to solve the problem that the existing distribution network is insufficient in analyzing the impact of technical loss reduction when considering the characteristics of electric heating load, the present invention proposes a method for analyzing the impact of technical loss reduction in distribution network, including:

[0020] Analyze the historical data of the substation to obtain the time distribution, fluctuation pattern and seasonal changes of the electric heating load;

[0021] The theoretical active power supply, active power sales and heavy overload time of the substation are predicted based on the real-time operation data and environmental data of the distribution network combined with the time distribution, fluctuation law and seasonal changes of the electric heating load;

[0022] Calculate key indicators based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data;

[0023] Determine a technical loss reduction plan based on the key indicators, and obtain updated parameters after implementing the technical loss reduction plan;

[0024] The financial net present value is calculated based on the updated parameters, and the technical loss reduction effect is determined by the financial net present value.

[0025] Preferably, the key indicators are calculated based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data, including:

[0026] The theoretical power loss is obtained by subtracting the active power sales from the theoretical active power supply.

[0027] The theoretical line loss rate is obtained from the ratio of the theoretical power loss to the active power supply;

[0028] Subtract the active power sales from the active power supply in the same period to get the power loss in the same period.

[0029] The line loss rate in the same period is obtained by the ratio of the power loss in the same period to the active power supply;

[0030] Subtract the line loss rate of the same period from the theoretical line loss rate to obtain the line loss rate difference;

[0031] The difference between the theoretical power loss and the power loss during the same period is used to obtain the power loss deviation value.

[0032] The power supply deviation is obtained by subtracting the active power supply in the same period from the theoretical active power supply.

[0033] The proportion of total heavy overload time is calculated from the heavy overload time;

[0034] Among them, the key indicators include: line loss rate difference, power loss deviation value, power supply deviation and overload time ratio.

[0035] Preferably, determining a technical loss reduction solution based on the key indicators includes:

[0036] When the line loss rate difference in the key indicator is greater than the set threshold, a line transformation technology loss reduction plan is implemented;

[0037] When the power supply deviation value in the key indicator is less than the set threshold, the low voltage transformation technology loss reduction plan is implemented;

[0038] When the total proportion of heavy overload time in key indicators is greater than the set threshold, a network transformation technology loss reduction plan is implemented.

[0039] Preferably, the calculating of the financial net present value based on the updated parameters and determining the technical loss reduction effectiveness by the financial net present value comprises:

[0040] The cost of selling the old equipment is obtained by updating the new equipment cost, labor cost, original value of the old equipment, estimated service life of the old equipment, and estimated service life of the old equipment in the updated parameters;

[0041] The financial net present value is obtained based on the cost of selling old equipment, the cost of new equipment, labor costs, calculation years, average electricity purchase price and discount rate combined with the financial net present value calculation formula.

[0042] Preferably, the old equipment selling cost is calculated as follows:

[0043]

[0044] In the formula, I 0 Cost of selling old equipment, C 0 is the original value of the old equipment, C f is the estimated net residual value of the old equipment, n 1 is the estimated service life of the old equipment, n 2 Estimated age of the old equipment.

[0045] Preferably, the financial net present value is calculated as follows:

[0046]

[0047] Where NPV is the net present value, I o Cost of selling old equipment, C s is the cost of new equipment, C p For labor costs, For the first year of electricity saving, C e is the average electricity purchase price, C w is the annual operation and maintenance cost increase fee, i is the discount rate, To save electricity in the second year, The electricity saved in the nth year, where n is the number of years.

[0048] Preferably, the determining of the technical loss reduction effectiveness by the financial net present value includes:

[0049] If the financial net present value is not less than zero, the profit rate of the technological transformation loss reduction plan is not lower than the discount rate of the investment opportunity cost, and the technological transformation loss reduction plan has a good loss reduction effect; otherwise, the technological transformation loss reduction plan has a poor loss reduction effect.

[0050] On the other hand, the present invention also discloses a distribution network technology loss reduction effect impact analysis system, comprising:

[0051] Data analysis module, used to analyze historical data of the substation to obtain the time distribution, fluctuation pattern and seasonal changes of electric heating load;

[0052] A prediction module, used to predict the theoretical active power supply, active power sales and heavy overload time of the substation based on the time distribution, fluctuation law and seasonal changes of the electric heating load;

[0053] An indicator calculation module, used to calculate key indicators based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data;

[0054] A loss reduction scheme implementation module, used to determine a technical loss reduction scheme based on the key indicators and obtain updated parameters after the technical loss reduction scheme is implemented;

[0055] The effectiveness analysis module is used to calculate the financial net present value based on the updated parameters, and determine the technical loss reduction effectiveness from the financial net present value.

[0056] Preferably, the indicator calculation module is specifically used for:

[0057] The theoretical power loss is obtained by subtracting the active power sales from the theoretical active power supply.

[0058] The theoretical line loss rate is obtained from the ratio of the theoretical power loss to the active power supply;

[0059] Subtract the active power sales from the active power supply in the same period to get the power loss in the same period.

[0060] The line loss rate in the same period is obtained by the ratio of the power loss in the same period to the active power supply;

[0061] Subtract the line loss rate of the same period from the theoretical line loss rate to obtain the line loss rate difference;

[0062] The difference between the theoretical power loss and the power loss during the same period is used to obtain the power loss deviation value.

[0063] The power supply deviation is obtained by subtracting the active power supply in the same period from the theoretical active power supply.

[0064] The proportion of total heavy overload time is calculated from the heavy overload time;

[0065] Among them, the key indicators include: line loss rate difference, power loss deviation value, power supply deviation and overload time ratio.

[0066] Preferably, the implementation steps of determining the technical loss reduction scheme based on the key indicators in the loss reduction scheme implementation module include:

[0067] When the line loss rate difference in the key indicator is greater than the set threshold, a line transformation technology loss reduction plan is implemented;

[0068] When the power supply deviation value in the key indicator is less than the set threshold, the low voltage transformation technology loss reduction plan is implemented;

[0069] When the total proportion of heavy overload time in key indicators is greater than the set threshold, a network transformation technology loss reduction plan is implemented.

[0070] Preferably, the effectiveness analysis module includes:

[0071] The calculation submodule is used to obtain the cost of selling the old equipment by combining the cost of the new equipment, the labor cost, the original value of the old equipment, the estimated service life of the old equipment, and the estimated service life of the old equipment in the update parameters; and obtain the financial net present value based on the cost of selling the old equipment, the cost of the new equipment, the labor cost, the calculation life, the average power purchase price and the discount rate in combination with the financial net present value calculation formula;

[0072] The evaluation submodule is used to: if the financial net present value is not less than zero, the profit rate of the transformation technology loss reduction plan is not lower than the discount rate of the investment opportunity cost, and the transformation technology loss reduction plan has a good loss reduction effect; otherwise, the transformation technology loss reduction plan has a poor loss reduction effect.

[0073] The cost of selling old equipment is calculated as follows:

[0074]

[0075] In the formula, I 0 Cost of selling old equipment, C 0 is the original value of the old equipment, C f is the estimated net residual value of the old equipment, n 1 is the estimated service life of the old equipment, n 2 Estimated age of the old equipment.

[0076] Preferably, the financial net present value is calculated as follows:

[0077]

[0078] Where NPV is the net present value, I o Cost of selling old equipment, C s is the cost of new equipment, C p For labor costs, For the first year of electricity saving, C e is the average electricity purchase price, C w is the annual operation and maintenance cost increase fee, i is the discount rate, To save electricity in the second year, The electricity saved in the nth year, where n is the number of years.

[0079] In another aspect, the present application further provides an electronic device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus;

[0080] The memory is used to store one or more programs;

[0081] When the one or more programs are executed by the at least one processor, a distribution network technology loss reduction effectiveness impact analysis method as described above is implemented.

[0082] On the other hand, the present application also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed, a distribution network technology loss reduction effectiveness impact analysis method as described above is implemented.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] The present invention provides a method for analyzing the impact of technical loss reduction effectiveness of distribution network, including: analyzing historical data of the substation to obtain the time distribution, fluctuation law and seasonal changes of electric heating load; predicting the theoretical active power supply, active power sales and heavy overload time of the substation by combining the real-time operation data and environmental data of the distribution network with the time distribution, fluctuation law and seasonal changes of the electric heating load; calculating key indicators based on the theoretical active power supply, active power sales and active power supply and active power sales in the historical data of the substation during the same period; determining the technical loss reduction plan based on the key indicators, and obtaining the updated parameters after implementing the technical loss reduction plan; calculating the financial net present value based on the updated parameters, and determining the technical loss reduction effectiveness by the financial net present value. This method takes into account the characteristics of electric heating load, not only accurately evaluates the effectiveness of the loss reduction strategy, but also provides a scientific basis for further optimizing the strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] Figure 1 A flow chart of a method for analyzing the impact of power distribution network technology loss reduction effect of the present invention;

[0086] Figure 2 It is an overall flow chart of a method for analyzing the impact of power distribution network technology loss reduction effect of the present invention;

[0087] Figure 3 A flow chart of power prediction of the present invention;

[0088] Figure 4 A typical daily load curve diagram of electric heating load in an embodiment of the present invention;

[0089] Figure 5 A typical annual load curve diagram of electric heating in an embodiment of the present invention;

[0090] Figure 6 The figure is a schematic diagram of the structure of an electronic device of the present invention. DETAILED DESCRIPTION

[0091] The purpose of the present invention is to provide a method for analyzing the impact of distribution network technology loss reduction effectiveness, aiming to solve the problem that the existing technology does not take into account the load characteristics of electric heating in terms of distribution network loss reduction, and to improve the operating efficiency and loss reduction effect of the distribution network. By deeply analyzing the load characteristics of electric heating, including its time distribution, fluctuation patterns, seasonal changes, etc., targeted distribution network loss reduction strategies are formulated. These strategies may include optimizing line design, updating high-efficiency energy-saving equipment, implementing load balancing control, etc., aiming to reduce line losses caused by factors such as resistance and overload. The present invention mainly proposes an effective loss reduction effectiveness analysis method, which collects and analyzes real-time operating data of the distribution network to quantitatively evaluate the implementation effect of the loss reduction strategy; this method can not only help us accurately understand the effectiveness of the loss reduction strategy, but also provide a scientific basis for further optimizing the strategy.

[0092] In order to better understand the present invention, the content of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0093] Embodiment 1:

[0094] A method for analyzing the impact of distribution network technology loss reduction effect, such as Figure 1 As shown, including:

[0095] Step S1: Analyze the historical data of the substation to obtain the time distribution, fluctuation pattern and seasonal changes of the electric heating load;

[0096] Step S2: predicting the theoretical active power supply, active power sales and heavy overload time of the substation based on the real-time operation data and environmental data of the distribution network combined with the time distribution, fluctuation law and seasonal changes of the electric heating load;

[0097] Step S3: Calculate key indicators based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data;

[0098] Step S4: determining a technical loss reduction plan based on the key indicators, and obtaining updated parameters after implementing the technical loss reduction plan;

[0099] Step S5: Calculate the financial net present value based on the updated parameters, and determine the technical loss reduction effect by the financial net present value.

[0100] The method of the present invention can be used to analyze the loss reduction effect of distribution network technology by considering the load characteristics of electric heating, so as to formulate a more effective loss reduction strategy and improve the operation efficiency and economic benefits of the distribution network. At the same time, this method also provides an important reference for the planning, design and operation management of the distribution network.

[0101] Combine the following Figure 2 The technical solution of the method of the present invention is introduced in detail:

[0102] Step S1: Analyze the historical data of the substation to obtain the time distribution, fluctuation pattern and seasonal changes of the electric heating load, including:

[0103] (1) Data Collection

[0104] By collecting and analyzing historical data, we can understand the time distribution, fluctuation patterns, and seasonal changes of electric heating loads. At the same time, we need to ensure the accuracy, completeness, and real-time nature of the data, which will help us more accurately grasp the characteristics of electric heating loads and the operation patterns of distribution networks, and provide a scientific basis for formulating effective loss reduction strategies. The data that needs to be collected include but are not limited to:

[0105] Electric heating load data: real-time operating data of electric heating equipment, including power, energy consumption, switch status, etc.; historical data of electric heating load, including daily, weekly, monthly and annual load change curves; seasonal change data of electric heating load, in order to analyze the characteristics and patterns of load in different seasons.

[0106] Distribution network operation data: real-time operation data of the distribution network, including electrical parameters such as voltage, current, and power factor; line loss data of the distribution network, including total loss, branch loss, etc.; equipment operation data of the distribution network, such as the operating status and energy consumption of transformers, switches, lines, etc.

[0107] Meteorological and environmental data: Meteorological data such as temperature, humidity, and wind speed are used to analyze the impact of meteorological conditions on electric heating loads and distribution network operations; environmental data such as regional energy policies and electricity price policies are used to evaluate their impact on electric heating load characteristics and distribution network loss reduction strategies.

[0108] Economic data: Economic data such as electricity prices and fuel prices, which are used to analyze the impact of economic factors on electric heating loads and distribution network operating costs; data such as distribution network investment and operation and maintenance costs, which are used to evaluate the economic benefits of loss reduction strategies.

[0109] Other relevant data: user electricity usage behavior data, such as electricity usage habits, electricity usage time periods, etc., to understand the impact of user electricity usage behavior on the characteristics of electric heating loads; historical fault records, maintenance records and other data, used to analyze the reliability and stability of the distribution network.

[0110] (2) Regional analysis of electric heating

[0111] The areas in China with electric heating are mainly concentrated in the following areas:

[0112] Cold areas in the north: such as Inner Mongolia and Northeast China, where the winter temperature is extremely low, traditional heating methods may not be able to meet the heating needs. Therefore, electric heating, as an efficient and environmentally friendly heating method, has been widely used in these areas. In particular, in the context of the country's promotion of clean heating in the north in winter and coal-to-electricity conversion, electric heating equipment has been vigorously promoted in these areas.

[0113] Regions rich in renewable energy resources: Electric heating has been fully utilized in regions rich in renewable energy resources, such as Xinjiang, Gansu, Hebei, Liaoning, Jilin, and Heilongjiang. These regions use surplus wind power during low seasons for electric heating and promote electric heating facilities with heat storage functions to promote the consumption of renewable energy electricity.

[0114] Urban and rural areas: Not only do residents in northern cities use electric heating, but rural users in some southern cities also choose electric heating for its comfort and environmental protection. Especially in some rural areas in the south with higher living standards, electric heating has become an important way to improve living conditions.

[0115] In addition, due to the characteristics of high intelligence, good safety of water and electricity separation, and maintenance-free, electric heating has also been widely used in some places with special heating needs, such as hospitals, schools, office buildings, etc. In general, the areas with electric heating in China are mainly concentrated in the cold northern regions, areas rich in renewable energy resources, and rural areas of some southern cities. With the continuous advancement of technology and the improvement of environmental awareness, the application scope of electric heating will be further expanded.

[0116] Step S2: predicting the theoretical active power supply, active power sales and heavy overload time of the substation area based on the real-time operation data and environmental data of the distribution network combined with the time distribution, fluctuation law and seasonal changes of the electric heating load, including:

[0117] Based on the real-time operation data of the distribution network, combined with the time distribution, fluctuation pattern and seasonal changes of the electric heating load introduced in step S1, the theoretical active power supply, active power sales and heavy overload time of the substation are predicted.

[0118] Step S2 specifically includes:

[0119] Load characteristics analysis and power forecast:

[0120] 1) Electricity consumption type and power consumption forecast analysis

[0121] Total regional load: mainly includes electricity for agricultural irrigation, residential electricity, and major users; among which the main load for residential electricity is residential lighting and electric heating.

[0122] Rural residents' lighting load and developed agricultural irrigation wells' electricity load; these two types of electricity load are the main load types in the current rural areas. The electricity consumption of this part of the load has certain rules and maintains a relatively stable growth trend every year. The average annual growth rate of the load can be found based on the historical annual load growth, which can be used as a reference value for the electricity forecast from 2020 to 2025. The recommended electricity forecast method is the trend extrapolation method (natural growth method).

[0123] Electric heating load: This part of the load is the main type of electricity load growth in the future, which will cause a second impact on the grid structure and volume of the existing power grid. Since the implementation of electric heating, township government agencies and rural individual households have begun to actively and spontaneously apply for installation. However, for the region, the form of electricity consumption for electric heating is still not optimistic. When the equipment in the substation is transformed, such equipment needs to be differentiated for load assessment to avoid unreasonable planning. The main reason is in the electricity price policy: At present, the people have reported the demand for electric heating, and after purchasing electric heating equipment, after a month of all-day heating trial, the parity electricity price is 0.254 yuan / kWh, and the monthly electricity fee is about 1,500 yuan. Compared with coal-fired, the cost is much higher, and the user's boiler is shut down; local coal resources: from the perspective of mineral resources, the region is rich in coal resources. Compared with other states, coal is produced and used by itself, saving transportation costs, so the price of coal is low, and residents generally tend to adopt coal-fired heating. Ideas for forecasting electric heating electricity consumption: The first step is to investigate typical user indicators; the second step is to implement the scale in typical villages, accumulate the current status and registration, and through visits, adjust the saturation scale to a certain extent; the third step is to carry out differentiated electric heating electricity consumption forecasts based on village types.

[0124] New agricultural irrigation load: According to the recent land development and water conservancy project plans of relevant government departments such as the Land and Resources Bureau and the Water Conservancy Bureau, grasp the direction of the channels and the irrigable areas covered. According to the newly added land conditions and different irrigation forms, calculate different types of load demands. Ideas for well irrigation power forecasting: The first step is to understand the existing cultivated land area of ​​each village; the second step is to understand the government's future cultivated land development plan; the third step is to analyze the irrigation type and the level of irrigation forecast line loss; the fourth step is to carry out irrigation power forecasting. Through the above analysis, the power forecasting process is condensed as follows: Figure 3 shown.

[0125] When considering well irrigation load and electric heating load, judging from the load characteristic curves of the two loads, the two loads will not overlap, that is: well irrigation occurs in May, June and July, and electric heating occurs in October, November, December, January, February and March. There is a certain time difference between the two. Therefore, when the loads are added together, the values ​​of the two should be compared and a choice should be made.

[0126] 2) Analysis of load characteristic curve of power load type

[0127] Based on the data of power load, time and season in a certain place, the load curve is completed, and the typical daily load curve of electric heating load is obtained through analysis. Figure 4 As shown, the horizontal axis is time, in hours, from the origin of the coordinate system, it is 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, ..., 24, the vertical axis is the quantity, from the origin, it is 0, 180, 185, 190, 195, 200, 205, 210, and the typical annual load curve of electric heating is as follows Figure 5As shown, the horizontal axis is the month, starting from the origin, it is January, February, March, April, ..., December, and the vertical axis is the quantity, starting from the origin, the quantity values ​​are -50, 0, 50, 100, 150, 200, 250.

[0128] Through the implementation of the present invention, the loss reduction effect of the distribution network can be significantly improved when considering the characteristics of electric heating loads, line losses can be reduced, and power supply efficiency and quality can be improved. This not only helps to reduce energy waste and reduce operating costs, but also helps to improve the stability and reliability of the power system and contribute to the sustainable development of the power industry.

[0129] In the figure above, the daily load curve is relatively flat. The temperature rises at noon and the load is relatively reduced, but the peak-to-valley difference is within 60%, maintaining a relatively high level of electricity consumption. In the annual load characteristic curve, May, June, August, and September are non-heating seasons, and the electric heating load is 0. In other months, electricity consumption remains at a high level without obvious fluctuations. In addition to the emerging load of electric heating, other traditional load types include:

[0130] Residential, three-phase power, well irrigation load. The load curves are not listed one by one. The curve characteristics can be summarized as follows: Residential life: The daily load presents two peaks, located at 12 noon and 9 pm respectively. The two times are the rest time after get off work, and the concentrated power consumption period of household appliances such as lighting and air conditioning. The annual load mostly occurs in summer and winter. Without considering electric heating, it is the cooling and heating of air conditioning.

[0131] Three-phase power: There is no obvious pattern in daily load and annual load, and the curve is highly affected by the user's electricity consumption.

[0132] Agricultural well irrigation: The daily load is similar to that of three-phase power electricity. In the annual load curve, the electricity load is mainly in May, June and July, which are the concentrated months for irrigation. There is a certain time difference with the electric heating load.

[0133] 3) Typical user survey and typical village analysis

[0134] Research and analysis of cultivated land conditions: A certain area was selected for research and analysis, and it was found that the cultivated land area of ​​a village was 2,100 mu, the current well irrigation capacity was about 350kVA, and the equipment full load rate was controlled between 70% and 80%. After calculation, the average load was 100kW per 800 mu, and the unit cultivated land index was 8 mu / kW. This was used as the unit irrigation index for cultivated land in each village from 2023 to 2025.

[0135] Survey on typical users of electric heating: The survey on electric heating adopts the form of home visits. The selected object is: Wang Moumou, electric heating is used all day, the heating equipment range is adjustable, the adjustment range is 50-65-80 degrees Celsius, there are 4 rooms, and the actual heating area is about 120km2. Under normal circumstances, the set temperature is 50 degrees Celsius, the room temperature is average, and the radiator is slightly hot. There is no insulation facility in the house, and the temperature difference between indoor and outdoor is about 45 degrees Celsius. Through the user's visit, it is learned that the rated power of the electrode hot water boiler is 16kW. The optimal heating area is 100km2. The user's heating demand coefficient is selected as 0.4, that is, the residential electric boiler electric heating index is 6kW / household (6kW / 100m2). This index can be used for the promotion index of other villages that have not been clearly reported. For users who have already reported, it can be comprehensively considered according to the actual reporting situation.

[0136] Survey of rural bulk users - agricultural equipment: rural bulk users are basically three-phase power electricity, the type of electricity used is agricultural motors, and the electrical equipment includes: grass crusher, corn crusher, etc. Users use it randomly according to the actual needs of their own livestock scale, and electricity is generated throughout the year. The overall scale of electricity is small, the maximum utilization hours are low, and it is crushed for many days at a time. The survey object is: Ma Moumou, the user has 2 three-phase equipment, namely corn crusher and grass powder machine, with nominal capacities of 15kW and 5kW respectively, and the rated power of electrical equipment is 20kW in total. The annual electricity consumption is 422.4kWh, the power of electrical equipment is 20kW in total, the demand coefficient is selected as 0.6, the annual maximum utilization hours are 182h, and the electricity consumption time is short. Through the above analysis and survey of typical users, 12kW can be selected for the three-phase power indicator for household agricultural use.

[0137] Residential electricity consumption: There is a certain diversity in residential electrical appliances, but most of them are the following: refrigerators, washing machines, televisions, air conditioners, lights, etc. The common power consumption parameters of the equipment are shown in the following table.

[0138] Household Appliance Power Survey Table

[0139] Serial number Classification Power(W) 1 television 60-110 2 refrigerator 90-200 3 washing machine 120-130 4 lamp 3-45 5 air conditioner 1200-1500

[0140] The middle value is selected as the average power consumption level. The equipment parameters are as follows:

[0141] Household appliances power selection table

[0142]

[0143] After accumulating all kinds of electrical equipment, the maximum load of each household with all electrical equipment turned on is 1.63kW, and after considering the simultaneous rate of 0.8, the maximum load is 1.3kW. The residential electricity consumption index is 1.3kW, which is used as a typical residential electricity consumption index.

[0144] Step S3: Calculate key indicators based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data, including:

[0145] The theoretical power loss is obtained by subtracting the active power sales from the theoretical active power supply.

[0146] The theoretical line loss rate is obtained from the ratio of the theoretical power loss to the active power supply;

[0147] Subtract the active power sales from the active power supply in the same period to get the power loss in the same period.

[0148] The line loss rate in the same period is obtained by the ratio of the power loss in the same period to the active power supply;

[0149] Subtract the line loss rate of the same period from the theoretical line loss rate to obtain the line loss rate difference;

[0150] The difference between the theoretical power loss and the power loss during the same period is used to obtain the power loss deviation value.

[0151] The power supply deviation is obtained by subtracting the active power supply in the same period from the theoretical active power supply.

[0152] The proportion of total heavy overload time is calculated from the heavy overload time;

[0153] Among them, the key indicators include: line loss rate difference, power loss deviation value, power supply deviation and overload time ratio.

[0154] Step S3 specifically includes:

[0155] Principles for calculating theoretical line loss: Theoretical line loss is calculated using the phase-separated equal resistance method, assuming that the shape of the load curve of each load node is the same as that of the head end, the power factor of each load node is equal to that of the head end, and the impact of voltage drop along the line on power loss is ignored.

[0156] Data required for calculation: active power of distribution transformer and active power of the distribution line head end.

[0157] Loss calculation:

[0158]

[0159] Where, ΔA is the power loss of the distribution network, ΔA 0 Fixed losses in the distribution network, I av(0) Average current at the head end of the distribution network, k 2 Square value of load curve shape factor, R eq Variable loss equivalent resistor, T calculation time.

[0160] Line equivalent resistance:

[0161]

[0162] In the formula, R eqL is the equivalent resistance of the distribution network conductor, Ω, ∑A a is the total active power of all load nodes in the distribution network, kWh, R i is the resistance of the i-th line segment, Ω, A (i) is the total active power of the load nodes transmitted through the i-th line segment, kWh, m is the number of distribution line segments, and i is the discount rate.

[0163] Average current:

[0164]

[0165] In the formula, I av(i) is the average current, I av(0) is the average current at the head end of the distribution line, A.

[0166] The equivalent resistance method is currently widely used in the theoretical calculation of line losses in 0.4kV distribution networks due to its simple calculation and clear principle.

[0167] Step S4: Determine a technical loss reduction plan based on the key indicators, and obtain updated parameters after implementing the technical loss reduction plan, including:

[0168] When the line loss rate difference in the key indicator is greater than the set threshold, a line transformation technology loss reduction plan is implemented;

[0169] When the power supply deviation value in the key indicator is less than the set threshold, the low voltage transformation technology loss reduction plan is implemented;

[0170] When the total time proportion of heavy overload in key indicators is greater than the set threshold, a network transformation technology loss reduction plan is implemented;

[0171] Implement the technical loss reduction plan and obtain updated parameters after the implementation of the technical loss reduction plan.

[0172] The technical loss reduction scheme in step S4 is as follows:

[0173] Theoretical line loss calculation and loss reduction transformation technical principles:

[0174] Principles for solving the heavy overload problem: if the overload time accounts for less than 0.05% and the total heavy overload time accounts for less than 0.20%, network modification is not considered for the time being; if the overload time accounts for more than 0.05% and the total heavy overload time accounts for between 0.2-0.5%, consider using a high overload rate transformer to solve the problem; if the total heavy overload time accounts for more than 0.5%, consider the order of batch modification in combination with the development trend of the substation area; for some areas where the overload time is less than 0.5%, consider including them in the project together with the underground pole and line project in the core scenic area.

[0175] Principles for solving low voltage problems: if the number of low voltage occurrences throughout the year is less than or equal to 3 times, it will not be included in the renovation plan for the time being; low voltage caused by three-phase imbalance can be solved by adjusting the load through operation and maintenance, and will not be included in the renovation plan for the time being; because the power supply radius is greater than 800 meters, causing low voltage for more than 5 users, it will be included in the renovation plan; because low voltage occurs more than 3 times throughout the year and the load rate is too high (above 80%), resulting in low voltage, it will be included in the renovation plan; if there are other problems at the same time, combined with the overall evaluation, it will be considered to be included in the renovation plan.

[0176] Principles for the construction and renovation of 10kV lines: The loss reduction measures for this substation include the extension of 10kV lines. Therefore, it is recommended that insulated conductors should be used for the construction and renovation of 10kV overhead lines in towns, forest areas, key scenic spots, severely polluted areas, areas with many fish ponds, and those crossing high-voltage line sections.

[0177] Principles for the construction and renovation of distribution transformers: Distribution transformers should be configured according to the principle of "dense points and short radius", and should be as close to the load center as possible. Three-phase distribution transformers should be used first. Three-phase pole-mounted distribution transformers: 100kVA, 200kVA, 400kVA. Box-type distribution transformers: 400kVA, 500kVA, 630kVA. Newly installed and replaced distribution transformers should use energy-saving distribution transformers above S13. The number of low-voltage distribution lines of pole-mounted distribution transformers is generally considered to be 2-3. C and D power supply areas: 200 and 400kVA three-phase pole-mounted distribution transformers are recommended.

[0178] Step S5: Calculating the financial net present value based on the updated parameters, and determining the technical loss reduction effect from the financial net present value, including:

[0179] The cost of selling the old equipment is obtained by updating the new equipment cost, labor cost, original value of the old equipment, estimated service life of the old equipment, and estimated service life of the old equipment in the updated parameters;

[0180] The financial net present value is obtained based on the cost of selling old equipment, the cost of new equipment, labor costs, calculation years, average electricity purchase price and discount rate combined with the financial net present value calculation formula.

[0181] Furthermore, the cost of selling the old equipment is calculated as follows:

[0182]

[0183] In the formula, I 0 Cost of selling old equipment, C 0 is the original value of the old equipment, C f is the estimated net residual value of the old equipment, n 1 is the estimated service life of the old equipment, n 2 Estimated age of the old equipment.

[0184] Furthermore, the financial net present value is calculated as follows:

[0185]

[0186] In the formula, NPV is the net present value, I o Cost of selling old equipment, C s is the cost of new equipment, C p For labor costs, For the first year of electricity saving, C e is the average electricity purchase price, C w is the annual operation and maintenance cost increase fee, i is the discount rate, To save electricity in the second year, The electricity saved in the nth year, where n is the number of years.

[0187] Furthermore, the technical loss reduction effectiveness is determined by the financial net present value, including:

[0188] If the financial net present value is not less than zero, the profit rate of the technological transformation loss reduction plan is not lower than the discount rate of the investment opportunity cost, and the technological transformation loss reduction plan has a good loss reduction effect; otherwise, the technological transformation loss reduction plan has a poor loss reduction effect.

[0189] Step S5 specifically includes:

[0190] Technical and economic estimation and analysis:

[0191] Analysis of three-phase optimization cost: The three-phase optimization cost price is derived based on basic data and field surveys. The low-voltage users connected to a single substation will undergo load shedding or three-phase four-wire transformation to achieve optimal three-phase load balance. The transformation cost for each substation is estimated at RMB 2,000.

[0192] Cost analysis of typical overhead / cable lines: Based on basic data and field surveys, a cost price list of typical overhead / cable lines is drawn up as the basis for subsequent calculation of loss reduction results.

[0193] Typical transformer cost analysis: Based on basic data and field surveys, a typical transformer cost price list is drawn up as the basis for subsequent loss reduction calculations.

[0194] Cost analysis of reactive power compensation devices: Based on basic data and field surveys, a cost price list of reactive power compensation devices is drawn up, including labor and construction costs, equipment and material costs, unit construction cost, annual operation and maintenance cost increase, etc., which serves as the basis for calculating subsequent loss reduction results.

[0195] Financial Net Present Value Calculation:

[0196] Financial net present value (NPV): It refers to the cumulative present value of the net cash flow in each year of the calculation period discounted to the construction starting year (base year) according to the benchmark rate of return or the set discount rate of the department or industry of the proposed project. It is an auxiliary indicator of economic evaluation. When the financial net present value is greater than or equal to zero, it indicates that the project's profitability is not lower than the discount rate of the investment opportunity cost, and the project is considered acceptable. When the financial net present value is negative, the project is financially infeasible. When selecting project plans with equal investment amounts, the plan with a larger financial net present value should be selected; when the investment amounts of the plans are not equal, the financial net present value rate can be used to compare the plans. The calculation method of financial net present value is as follows: Formula 1:

[0197]

[0198] Formula 2:

[0199]

[0200] Formula 3:

[0201]

[0202] The variables required for calculation include:

[0203]

[0204]

[0205] Loss reduction effectiveness evaluation and effect feedback

[0206] Evaluation of loss reduction effectiveness: Calculate key indicators before and after the implementation of loss reduction measures, such as line loss rate, power factor, load rate, etc.; compare the data before and after the implementation of loss reduction measures, analyze the loss reduction effect, and determine which measures are more effective in reducing losses.

[0207] Feedback and adjustment: Feedback the loss reduction effectiveness analysis results to relevant departments and personnel to understand the effectiveness of the implementation measures. According to the loss reduction effectiveness analysis results, make necessary adjustments and optimizations to the loss reduction measures to improve the loss reduction effect.

[0208] Example 2

[0209] Take a certain area as an example:

[0210] The theoretical line loss is calculated by the phase-separated equal resistance method. In the theoretical daily line loss, the active power supply is 2504.4536 kWh, the active power sales is 2295.16 kWh, the loss is 209.29353 kWh, and the theoretical line loss rate is 8.3569%; in the daily line loss of the same period, the power supply is 2520.6000 kWh, the active power sales is 2295.1600 kWh, the loss is 225.4400 kWh, and the line loss rate is 8.9439% in the same period. According to the comparative analysis of the theoretical line loss and the line loss in the same period, the deviation of active power supply is 16.2 kWh; the deviation of active power sales is 0 kWh; the deviation of loss is 16.2 kWh; the deviation of the two rates is 0.6; the line loss in the substation area mainly exists in the line segment loss, and the meter loss is a fixed loss that cannot be eliminated. Therefore, the line segment loss is mainly analyzed. There are 48 low-voltage line segments in the four groups of public transformers in Sunjia Village, 192 Chibei Line, all of which are overhead line segments, most of which are model 2*JKLGYJ-150 / LGJ-120. From June 22 to July 20, 2023, the power supply and sales of this area ranged from 1784 kWh to 2769 kWh, and the load fluctuation curve was relatively smooth. The line loss rate during the same period fluctuated smoothly between 7.4% and 10.5%, and the line loss was basically maintained at around 8.3%, with long-term high-loss operation. On the one hand, based on the comparison of double-rate deviations (line loss rate deviation 0.6), power supply deviation (power deviation rate 0.643%), and loss power deviation (deviation 16.2kwh), it was found that the overall deviation of this area was small; on the other hand, based on the analysis of the theoretical daily line loss and the daily line loss curve during the same period, it was found that this area has been operating at high losses for a long time, and is a true high-loss area. After analyzing the 40 line segments in this substation, it was concluded that "the small diameter of the outgoing lines in the substation is the main reason for the high losses in this substation."

[0211] In view of the high loss of this area, according to the grid transformation idea, considering the load characteristics of electric heating, the impact of the distribution network technology loss reduction effect analysis and the impact of input-output, the five sections of the outlet of the area were upgraded and transformed as follows. According to the loss reduction effect calculation of the transformation plan, the new equipment material cost is 200,400 yuan, the labor cost is 570,550 yuan, and the annual operation and maintenance cost increase is 21,300 yuan. With 15 years as the calculation period, the annual load growth rate is 3%, the discount rate is 5%, and the comprehensive electricity price is 0.45 yuan / kWh. The annual electricity saving is 25102.5600 kWh, and the old equipment is sold for 16,510 yuan. Among the economic benefits, the annual electricity saving benefit is 112,960 yuan, the financial net present value is 65,200 yuan, the input-output ratio is 0.5484, and the cumulative CO2 emission reduction is 343,611.3 kg.

[0212] This invention method provides a more accurate and effective solution for reducing the loss of distribution network technology by comprehensively considering the characteristics of electric heating load, and has significant invention effects and practical application value. The invention effects are mainly reflected in the following aspects:

[0213] First, by deeply analyzing the load characteristics of electric heating, this method can more accurately grasp the impact of electric heating on the distribution network. This helps to formulate a more practical distribution network loss reduction strategy, thereby significantly improving the operating efficiency and loss reduction effect of the distribution network.

[0214] Second, the method helps to realize intelligent management and monitoring of the distribution network. By collecting and analyzing the operation data of the distribution network in real time, the method can timely discover and solve potential problems, reduce line losses, and improve the reliability and stability of power supply.

[0215] Third, the implementation of this method can also help reduce the operation and maintenance costs of the distribution network. By optimizing the structure and equipment of the distribution network and reducing the loss during the power transmission process, it can not only reduce energy waste, but also reduce the frequency of equipment maintenance and replacement, thereby reducing operation and maintenance costs.

[0216] Fourth, the promotion and application of this method will help promote the development of distribution network technology loss reduction and improve the overall operation level of the power system. By continuously improving and optimizing the loss reduction strategy, the energy efficiency and environmental protection performance of the distribution network can be further improved, contributing to the sustainable development of the power industry.

[0217] The present invention includes a detailed design and process of the measurement method, covering key steps such as the algorithm process and calculation rules. The present invention proposes a method for analyzing the impact of distribution network technology loss reduction effectiveness. This method deeply analyzes the characteristics of electric heating loads, uses an optimized financial net present value calculation method, assists in formulating targeted loss reduction strategies, and uses advanced data analysis and processing technology to evaluate loss reduction effectiveness. Through this method, the line loss of the distribution network can be more effectively reduced, the power supply efficiency and quality can be improved, and contributions can be made to the sustainable development of the power industry. It also provides new ideas and means for the optimized operation of the power system.

[0218] Example 3

[0219] The present invention based on the same inventive concept also provides a distribution network technology loss reduction effect impact analysis system, comprising:

[0220] Data analysis module, used to analyze historical data of the substation to obtain the time distribution, fluctuation pattern and seasonal changes of electric heating load;

[0221] A prediction module, used to predict the theoretical active power supply, active power sales and heavy overload time of the substation based on the time distribution, fluctuation law and seasonal changes of the electric heating load;

[0222] An indicator calculation module, used to calculate key indicators based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data;

[0223] A loss reduction scheme implementation module, used to determine a technical loss reduction scheme based on the key indicators and obtain updated parameters after the technical loss reduction scheme is implemented;

[0224] The effectiveness analysis module is used to calculate the financial net present value based on the updated parameters, and determine the technical loss reduction effectiveness from the financial net present value.

[0225] Preferably, the indicator calculation module is specifically used for:

[0226] The theoretical power loss is obtained by subtracting the active power sales from the theoretical active power supply.

[0227] The theoretical line loss rate is obtained from the ratio of the theoretical power loss to the active power supply;

[0228] Subtract the active power sales from the active power supply in the same period to get the power loss in the same period.

[0229] The line loss rate in the same period is obtained by the ratio of the power loss in the same period to the active power supply;

[0230] Subtract the line loss rate of the same period from the theoretical line loss rate to obtain the line loss rate difference;

[0231] The difference between the theoretical power loss and the power loss during the same period is used to obtain the power loss deviation value.

[0232] The power supply deviation is obtained by subtracting the active power supply in the same period from the theoretical active power supply.

[0233] The proportion of total heavy overload time is calculated from the heavy overload time;

[0234] Among them, the key indicators include: line loss rate difference, power loss deviation value, power supply deviation and overload time ratio.

[0235] Preferably, the implementation steps of determining the technical loss reduction scheme based on the key indicators in the loss reduction scheme implementation module include:

[0236] When the line loss rate difference in the key indicator is greater than the set threshold, a line transformation technology loss reduction plan is implemented;

[0237] When the power supply deviation value in the key indicator is less than the set threshold, the low voltage transformation technology loss reduction plan is implemented;

[0238] When the total proportion of heavy overload time in key indicators is greater than the set threshold, a network transformation technology loss reduction plan is implemented.

[0239] Preferably, the effectiveness analysis module includes:

[0240] The calculation submodule is used to obtain the cost of selling the old equipment by combining the cost of the new equipment, the labor cost, the original value of the old equipment, the estimated service life of the old equipment, and the estimated service life of the old equipment in the update parameters; and obtain the financial net present value based on the cost of selling the old equipment, the cost of the new equipment, the labor cost, the calculation life, the average power purchase price and the discount rate in combination with the financial net present value calculation formula;

[0241] The evaluation submodule is used to: if the financial net present value is not less than zero, the profit rate of the transformation technology loss reduction plan is not lower than the discount rate of the investment opportunity cost, and the transformation technology loss reduction plan has a good loss reduction effect; otherwise, the transformation technology loss reduction plan has a poor loss reduction effect.

[0242] The cost of selling old equipment is calculated as follows:

[0243]

[0244] In the formula, I 0 Cost of selling old equipment, C 0 is the original value of the old equipment, C f is the estimated net residual value of the old equipment, n 1 is the estimated service life of the old equipment, n 2 Estimated age of the old equipment.

[0245] Preferably, the financial net present value is calculated as follows:

[0246]

[0247] In the formula, NPV is the net present value, I o Cost of selling old equipment, C s is the cost of new equipment, C p For labor costs, For the first year of electricity saving, C e is the average electricity purchase price, C w is the annual operation and maintenance cost increase fee, i is the discount rate, To save electricity in the second year, The electricity saved in the nth year, where n is the number of years.

[0248] Example 4

[0249] like Figure 6 As shown, the present invention also provides an electronic device, which may be a computer device, a single-chip device, an intelligent mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, the processor, and the transceiver component are connected via a bus; the memory may be used to store an execution program, and an exemplary execution program may include instructions; the processor is used to execute the instructions stored in the memory. The memory may also be used to store data, which may be called and / or modified when the instructions are executed.

[0250] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in a storage medium to implement the corresponding method flow or corresponding functions, so as to realize the steps of a distribution network technology loss reduction effectiveness impact analysis method in the above-mentioned embodiment.

[0251] Example 5

[0252] Based on the same inventive concept, the present invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory), which is a memory device in an electronic device for storing programs and data. It can be understood that the storage medium here can include both built-in storage media in electronic devices and, of course, extended storage media supported by electronic devices. The storage medium provides a storage space that stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more execution programs (including program codes). It should be noted that the storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor loads and executes one or more instructions stored in the storage medium, which can implement the steps of a distribution network technology loss reduction effect impact analysis method in the above embodiment.

[0253] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0254] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0255] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0256] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0257] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A method for analyzing the impact of distribution network technology loss reduction, characterized in that: include: Analyze the historical data of the substation to obtain the time distribution, fluctuation pattern and seasonal changes of the electric heating load; The theoretical active power supply, active power sales and heavy overload time of the substation are predicted based on the real-time operation data and environmental data of the distribution network combined with the time distribution, fluctuation law and seasonal changes of the electric heating load; Calculate key indicators based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data; Determine a technical loss reduction plan based on the key indicators, and obtain updated parameters after implementing the technical loss reduction plan; The financial net present value is calculated based on the updated parameters, and the technical loss reduction effect is determined by the financial net present value.

2. The method according to claim 1, characterized in that The key indicators calculated based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data include: The theoretical power loss is obtained by subtracting the active power sales from the theoretical active power supply. The theoretical line loss rate is obtained from the ratio of the theoretical power loss to the active power supply; Subtract the active power sales from the active power supply in the same period to get the power loss in the same period. The line loss rate in the same period is obtained by the ratio of the power loss in the same period to the active power supply; Subtract the line loss rate of the same period from the theoretical line loss rate to obtain the line loss rate difference; The difference between the theoretical power loss and the power loss during the same period is used to obtain the power loss deviation value. The power supply deviation is obtained by subtracting the active power supply in the same period from the theoretical active power supply. The proportion of total heavy overload time is calculated from the heavy overload time; Among them, the key indicators include: line loss rate difference, power loss deviation value, power supply deviation and overload time ratio.

3. The method according to claim 1, characterized in that Determining a technical loss reduction solution based on the key indicators includes: When the line loss rate difference in the key indicator is greater than the set threshold, a line transformation technology loss reduction plan is implemented; When the power supply deviation value in the key indicator is less than the set threshold, the low voltage transformation technology loss reduction plan is implemented; When the total proportion of heavy overload time in key indicators is greater than the set threshold, a network transformation technology loss reduction plan is implemented.

4. The method according to claim 1, characterized in that The calculating of the financial net present value based on the updated parameters and determining the technical loss reduction effect by the financial net present value includes: The cost of selling the old equipment is obtained by updating the new equipment cost, labor cost, original value of the old equipment, estimated service life of the old equipment, and estimated service life of the old equipment in the updated parameters; The financial net present value is obtained based on the cost of selling old equipment, the cost of new equipment, labor costs, calculation years, average electricity purchase price and discount rate combined with the financial net present value calculation formula.

5. The method according to claim 1, characterized in that The cost of selling old equipment is calculated as follows: In the formula, I0 is the cost of selling the old equipment, C0 is the original value of the old equipment, and C f is the estimated net residual value of the old equipment, n1 is the estimated useful life of the old equipment, and n2 is the estimated used life of the old equipment.

6. The method according to claim 4, characterized in that The financial net present value is calculated as follows: In the formula, NPV is the net present value, I o Cost of selling old equipment, C s is the cost of new equipment, C p For labor costs, For the first year of electricity saving, C e is the average electricity purchase price, C w is the annual operation and maintenance cost increase fee, i is the discount rate, To save electricity in the second year, The electricity saved in the nth year, where n is the number of years.

7. The method according to claim 1, characterized in that The determination of the technical loss reduction effect by the financial net present value includes: If the financial net present value is not less than zero, the profit rate of the technological transformation loss reduction plan is not lower than the discount rate of the investment opportunity cost, and the technological transformation loss reduction plan has a good loss reduction effect; otherwise, the technological transformation loss reduction plan has a poor loss reduction effect.

8. A distribution network technology loss reduction effect analysis system, characterized in that: include: Data analysis module, used to analyze historical data of the substation to obtain the time distribution, fluctuation pattern and seasonal changes of electric heating load; A prediction module, used to predict the theoretical active power supply, active power sales and heavy overload time of the substation based on the time distribution, fluctuation law and seasonal changes of the electric heating load; An indicator calculation module, used to calculate key indicators based on the theoretical active power supply and active power sales of the substation area and the active power supply and active power sales of the same period in historical data; A loss reduction scheme implementation module, used to determine a technical loss reduction scheme based on the key indicators and obtain updated parameters after the technical loss reduction scheme is implemented; The effectiveness analysis module is used to calculate the financial net present value based on the updated parameters, and determine the technical loss reduction effectiveness from the financial net present value.

9. The system according to claim 8, characterized in that The indicator calculation module is specifically used for: The theoretical power loss is obtained by subtracting the active power sales from the theoretical active power supply. The theoretical line loss rate is obtained from the ratio of the theoretical power loss to the active power supply; Subtract the active power sales from the active power supply in the same period to get the power loss in the same period. The line loss rate in the same period is obtained by the ratio of the power loss in the same period to the active power supply; Subtract the line loss rate of the same period from the theoretical line loss rate to obtain the line loss rate difference; The difference between the theoretical power loss and the power loss during the same period is used to obtain the power loss deviation value. The power supply deviation is obtained by subtracting the active power supply in the same period from the theoretical active power supply. The proportion of total heavy overload time is calculated from the heavy overload time; Among them, the key indicators include: line loss rate difference, power loss deviation value, power supply deviation and overload time ratio.

10. An electronic device, characterized in that: include: at least one processor and memory; The memory and the processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a distribution network technology loss reduction effectiveness impact analysis method as described in any one of claims 1 to 7 is implemented.

11. A readable storage medium, characterized in that: An execution program is stored thereon, and when the execution program is executed, a distribution network technology loss reduction effectiveness impact analysis method as described in any one of claims 1 to 7 is implemented.

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