Method for measuring influence of energy storage charging and discharging on actual maximum demand of total incoming line

Abstract

The application discloses a kind of methods for metering the influence of energy storage charge-discharge on total line actual maximum demand, which through several energy storage access electric meter cooperate an energy storage demand influence electric meter, real-time metering the real-time demand of each energy storage system per unit time and the real-time demand of total line per unit time after energy storage system intervention, then according to the unique algorithm finally calculated by the application, the influence value of energy storage system intervention on total line actual maximum demand, positive value is positive influence, negative value is negative influence. Thus, the user can very intuitively know the increase and decrease of basic electricity charge and transformer reserve capacity caused by energy storage charge-discharge after installing energy storage, so that the user can take corresponding hedging measures. At the same time, the energy storage investor can also use the application as the identity of third-party independent accounting to measure the demand reduction or increase value caused by energy storage power station after intervention, to facilitate and user to carry out income settlement, achieves the effect of win-win.

Description

Technical Field

[0001] This invention relates to the field of electricity metering technology, and specifically to a method for measuring the impact of electricity on industrial and commercial energy storage. Background Technology

[0002] With the rapid development of new energy technologies, energy storage technology has been increasingly widely applied. 2023 was particularly significant, dubbed the "Year Zero" for industrial and commercial energy storage in China, with several provinces experiencing a surge in such applications. However, the installation of energy storage alters the electricity demand of users (such as factories) through charging and discharging (i.e., changing the original electricity load curve). This poses a challenge for most users on a demand-based two-part electricity billing system. They worry about whether installing energy storage will increase their basic electricity costs (the basic electricity cost is calculated by multiplying the actual maximum demand for the month by the local demand-based electricity price) and whether it will reduce the storage capacity of existing transformers. Similarly, energy storage investors need a metering system to independently measure the demand reduction or increase caused by the intervention of the energy storage power station, facilitating revenue settlement with users. Currently, however, no solution exists that can achieve this functionality independently. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method for measuring the impact of energy storage charging and discharging on the actual maximum demand of the total incoming line, which has a more accurate and synchronized metering process, more independent and reliable data, and a more intuitive representation of the impact on actual electricity.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a method for measuring the impact of energy storage charging and discharging on the actual maximum demand of the total incoming line, the hardware involved in the method including several smart meters and a cloud platform, characterized in that: the implementation process is carried out according to the following steps:

[0005] (1) Install one of the smart meters as a communication host at the main power line of the user to form a storage demand impact meter; use the remaining smart meters as downstream storage demand meters of each energy storage system and connect them one by one with each energy storage system to connect N energy storage systems to form N energy storage access meters, and each energy storage access meter is connected to the energy demand impact meter respectively.

[0006] (2) The energy storage demand affects the real-time demand of the main power line collected by the meter and the real-time demand D1, D2...Dn of each energy storage access meter. Then, the monthly actual maximum demand MDx caused by energy storage charging and discharging is calculated and the value is displayed.

[0007] The calculation process is as follows:

[0008] 1) Obtain the real-time demand Da of the total incoming line per unit time after the energy storage system is connected by the energy storage demand-affected meter, and obtain the real-time demand D1, D2...Dn of each energy storage system per unit time by the energy storage access meter;

[0009] 2) The electricity meter automatically calculates the real-time demand Db of the total incoming line per unit time before the energy storage system is deployed, based on the energy storage demand.

[0010] Db = (Da - D1 - D2 - ... - Dn)

[0011] 3) The actual maximum demand MDa of the total incoming line after the energy storage system is connected is calculated by comparing the electricity meter readings based on the energy storage demand effect using the following formula:

[0012] MDa = Max(Da1,Da2,…,Dan)

[0013] 4) The actual maximum demand (MDb) of the total incoming line before the energy storage system is implemented is calculated using the following formula based on the energy storage demand impact meter:

[0014] MDb = Max(Db1, Db2, ..., Dbn)

[0015] 5) Finally, the impact of the energy storage system on the actual maximum demand of the total incoming line is calculated using the following formula: positive values ​​indicate a positive impact, and negative values ​​indicate a negative impact:

[0016] MDx = MDb - MDa

[0017] (3) Upload the calculated real-time demand value of the main power line before the energy storage intervention and the real-time demand data after the energy storage intervention collected by the energy storage demand-affected meter to the cloud platform, and form two sets of curves for comparison in the cloud platform to facilitate users to view the curves and verify the data.

[0018] (4) When the actual maximum demand impact value MDx is less than the set value, an alarm signal is issued to remind the user that the energy storage charging will increase the total electricity demand and intervention is required.

[0019] The energy storage demand-affecting meter connects to each energy storage access meter via an RS485 communication interface and collects the real-time demand of each energy storage access meter. The RS485 communication interface also enables the energy storage demand-affecting meter to automatically and periodically synchronize with each energy storage access meter to ensure clock synchronization and keep the demand data collected by each energy storage access meter consistent on the time axis.

[0020] Preferably, the unit time is measured in minutes, using a slip-count metering method, with one value per minute, marked on a time axis. Depending on the actual number of days, the demand value is recorded as 1 to 40,320 for 28 days, 1 to 43,200 for 30 days, or 1 to 44,640 for 31 days in a month, while keeping the time unit consistent between the energy storage demand-affected meter and the energy storage access meter.

[0021] This invention uses several energy storage access meters (sub-meters) in conjunction with a single energy storage demand impact meter (main meter) to measure the real-time demand of each energy storage system per unit time and the real-time demand of the total incoming line per unit time after the energy storage system's intervention. Then, based on a unique algorithm proposed by this invention, it ultimately calculates the impact value of the energy storage system's intervention on the actual maximum demand of the total incoming line. Positive values ​​indicate a positive impact, while negative values ​​indicate a negative impact. This allows users to intuitively understand the increase or decrease in their basic electricity costs and transformer reserve capacity caused by energy storage charging and discharging after installation, enabling them to take appropriate hedging measures. Simultaneously, energy storage investors can use this invention as an independent third-party accountant to measure the decrease or increase in demand caused by the intervention of the energy storage power station, facilitating revenue settlement with users and achieving a win-win situation. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the layout of the electricity meter according to the present invention. Detailed Implementation

[0023] In this embodiment, as Figure 1 As shown, the method for measuring the impact of energy storage charging and discharging on the actual maximum demand of the total incoming line involves hardware including several smart meters and a cloud platform. Both the smart meters and the cloud platform are existing technologies. For example, the smart meters can be DTZ341 / DSZ331 0.5S / 0.2S class smart meters. The implementation process is as follows:

[0024] (1) Install one of the smart meters as a communication host at the main power line of the user to form a storage demand impact meter; use the remaining smart meters as downstream storage demand meters of each energy storage system and connect them one by one with each energy storage system to connect N energy storage systems to form N energy storage access meters, and each energy storage access meter is connected to the energy demand impact meter respectively.

[0025] (2) The energy storage demand affects the real-time demand of the main power line collected by the meter and the real-time demand D1, D2...Dn of each energy storage access meter. Then, the monthly actual maximum demand MDx caused by energy storage charging and discharging is calculated and the value is displayed.

[0026] The calculation process is as follows:

[0027] 1) Obtain the real-time demand Da of the total incoming line per unit time after the energy storage system is connected by the energy storage demand-affected meter, and obtain the real-time demand D1, D2...Dn of each energy storage system per unit time by the energy storage access meter;

[0028] 2) The electricity meter automatically calculates the real-time demand Db of the total incoming line per unit time before the energy storage system is deployed, based on the energy storage demand.

[0029] Db = (Da - D1 - D2 - ... - Dn) - the first value

[0030] The second value of (Da-D1-D2-……-Dn)

[0031] ...

[0032] 3) The actual maximum demand MDa of the total incoming line after the energy storage system is connected is calculated by comparing the electricity meter readings based on the energy storage demand effect using the following formula:

[0033] MDa = Max(Da1,Da2,…,Dan)

[0034] 4) The actual maximum demand (MDb) of the total incoming line before the energy storage system is implemented is calculated using the following formula based on the energy storage demand impact meter:

[0035] MDb = Max(Db1, Db2, ..., Dbn)

[0036] 5) Finally, the impact of the energy storage system on the actual maximum demand of the total incoming line is calculated using the following formula: positive values ​​indicate a positive impact, and negative values ​​indicate a negative impact:

[0037] MDx = MDb - MDa

[0038] (3) Upload the calculated real-time demand value of the main power line before the energy storage intervention and the real-time demand data after the energy storage intervention collected by the energy storage demand-affected meter to the cloud platform, and form two sets of curves for comparison in the cloud platform to facilitate users to view the curves and verify the data.

[0039] (4) When the actual maximum demand impact value MDx is less than the set value, an alarm signal is issued to remind the user that the energy storage charging will increase the total electricity demand and intervention is required.

[0040] The energy storage demand-affecting meter connects to each energy storage access meter via an RS485 communication interface and collects the real-time demand of each energy storage access meter. The RS485 communication interface also enables the energy storage demand-affecting meter to automatically and periodically synchronize with each energy storage access meter to ensure clock synchronization and keep the demand data collected by each energy storage access meter consistent on the time axis.

[0041] The aforementioned unit time is measured in minutes, using a slip-rate metering method, with one value per minute, marked on a time axis. Depending on the actual number of days, a month may record 1-40320 demand values ​​for 28 days, 1-43200 for 30 days, or 1-44640 for 31 days, ensuring consistency between the time units of the energy storage demand impact meter and the energy storage access meter. Both the energy storage demand impact meter and the energy storage access meter use kW as the unit of measurement, and the calculation process also uses kW as the unit.

[0042] The specific calculation process is illustrated in Tables 1 and 2 below.

[0043] Table 1 shows the positive impacts of energy storage on total demand.

[0044] Example 1: Positive impact of energy storage on total demand

[0045]

[0046] As shown in Table 1, the factory's total electricity demand during the 1-12 minute time period decreased from 1800kW before the intervention to 1500kW after the intervention due to the discharge of energy storage. Energy storage plays a positive role in reducing the factory's demand. Taking Zhejiang Province's 2023 policy as an example, this month it will save the factory 300kW * 48 yuan / month / kW = 14400 yuan in basic electricity costs.

[0047] Table 2 shows the negative impacts of energy storage intervention on total demand.

[0048]

[0049] As shown in Table 2, the factory's total electricity demand during the 1-12 minute time period increased from 1300kW before the intervention of energy storage to 1500kW after the intervention due to the charging effect of energy storage. Therefore, energy storage has a negative effect on reducing the factory's demand. Taking Zhejiang Province's 2023 policy as an example, the factory will need to pay an additional 200kW * 48 yuan / month / kW = 9600 yuan in basic electricity fees this month.

[0050] The present invention has been described in detail above. The above description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made in accordance with the scope of this application should still fall within the scope of the present invention.

Claims

1. A method for measuring the impact of energy storage charging and discharging on the actual maximum demand of the total incoming line, the method involving hardware including several smart meters and a cloud platform, characterized in that: The implementation process is carried out in the following steps: (1) Install one of the smart meters as a communication host at the main power line of the user to form a storage demand impact meter; use the remaining smart meters as downstream storage demand meters of each energy storage system and connect them one by one with each energy storage system to connect N energy storage systems to form N energy storage access meters, and each energy storage access meter is connected to the energy demand impact meter respectively. (2) The energy storage demand affects the real-time demand of the main power line collected by the meter and the real-time demand D1, D2...Dn of each energy storage access meter. Then, the monthly actual maximum demand MDx caused by energy storage charging and discharging is calculated and the value is displayed. The calculation process is as follows: 1) Obtain the real-time demand Da of the total incoming line per unit time after the energy storage system is connected by the energy storage demand-affected meter, and obtain the real-time demand D1, D2...Dn of each energy storage system per unit time by the energy storage access meter; 2) The electricity meter automatically calculates the real-time demand Db of the total incoming line per unit time before the energy storage system is deployed, based on the energy storage demand. Db = (Da - D1 - D2 - ... - Dn) 3) The actual maximum demand MDa of the total incoming line after the energy storage system is connected is calculated by comparing the electricity meter readings based on the energy storage demand effect using the following formula: MDa = Max(Da1,Da2,…,Dan) 4) The actual maximum demand (MDb) of the total incoming line before the energy storage system is implemented is calculated using the following formula based on the energy storage demand impact meter: MDb = Max(Db1, Db2, ..., Dbn) 5) Finally, the impact of the energy storage system on the actual maximum demand of the total incoming line is calculated using the following formula: positive values ​​indicate a positive impact, and negative values ​​indicate a negative impact: MDx = MDb - MDa (3) Upload the calculated real-time demand value of the main power line before the energy storage intervention and the real-time demand data after the energy storage intervention collected by the energy storage demand-affected meter to the cloud platform, and form two sets of curves for comparison in the cloud platform to facilitate users to view the curves and verify the data. (4) When the actual maximum demand impact value MDx is less than the set value, an alarm signal is issued to remind the user that the energy storage charging will increase the total electricity demand and intervention is required.

2. The method for measuring the impact of energy storage charging and discharging on the actual maximum demand of the total incoming line according to claim 1, characterized in that: The energy storage demand impact meter connects to each energy storage access meter via an RS485 communication interface and collects the real-time demand of each energy storage access meter. The RS485 communication interface also enables the energy storage demand impact meter to automatically and periodically synchronize with each energy storage access meter to ensure clock synchronization and keep the demand data collected by each energy storage access meter consistent on the time axis.

3. The method for measuring the impact of energy storage charging and discharging on the actual maximum demand of the total incoming line according to claim 1, characterized in that: The unit of time is measured in minutes, with one value per minute, and marked on a time axis. Depending on the actual number of days, the demand value is recorded as 1 to 40,320 for 28 days, 1 to 43,200 for 30 days, or 1 to 44,640 for 31 days in a month, and the time unit of the energy storage demand-affected meter and the energy storage access meter are kept consistent.

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