A method and system for calculating a minimum capacity lease price of energy storage charging and discharging control

Abstract

The application discloses a kind of energy storage charge-discharge control method and system for calculating minimum capacity lease price, applied to energy storage charge-discharge optimization control technical field.Through receiving system real-time electricity price information from power transaction platform, with the maximum energy storage power station income as target, the charge / discharge period and charge / discharge power of energy storage battery within day are calculated, the charge-discharge control time sequence of energy storage battery is generated, the day-ahead charge-discharge plan of energy storage battery is formed, and the optimization control of energy storage battery charge-discharge is realized;Energy storage cost parameters are received from energy storage power station operation platform, the daily average investment and operation cost in the investment return period of energy storage power station are calculated, combined with the maximum market income of energy storage day, the minimum capacity lease price of energy storage day considering investment return rate is calculated, and the reasonable return of energy storage power station investment is realized.The application is easy to operate, can guarantee the charge-discharge control under the operation income of energy storage power station, and realizes reasonable investment return.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage charging and discharging optimization control, and more particularly to a method and system for calculating the minimum capacity leasing price of energy storage charging and discharging. BACKGROUND

[0002] One of the core features of the new power system is that new energy represented by wind power and photovoltaic power will become the main power source in the green energy transformation. The output of new energy is constrained by weather conditions and has significant intermittency, volatility and anti-peaking characteristics. Under the new situation of achieving the "double carbon" target and building a new power system, the proportion of new energy is growing rapidly, the share of thermal power is gradually being replaced, the system peak-valley difference is expanding, and the power supply and demand contradiction is intensifying, increasing the difficulty of system power balance and seriously affecting the new energy consumption and power supply capacity of the system in special periods. Energy storage is a device that converts electrical energy into other forms of energy through devices or physical media and releases it in the form of electrical energy based on future application needs. Energy storage has both power supply and load functions, with characteristics such as rapid response, precise control and bidirectional regulation, and has great flexibility in grid peak shaving and backup. In the operation of the new power system, energy storage participates in system dispatching as an adjustable resource, promotes new energy consumption, and optimizes the configuration of power generation and power consumption resources. When the system power generation cannot meet the load demand, energy storage participates in system dispatching as a power source, plays a peak role, and relieves the pressure of grid peak shaving. By flexibly and timely changing the identity of energy storage as a power source / consumer, it effectively provides services to balance power supply and demand, ensures the safe and stable operation of the system, significantly reduces system power supply costs, and promotes new energy consumption in terms of environmental and economic benefits. With the development of the electricity market and the improvement of the energy storage policy system, the necessity of energy storage with bidirectional regulation capacity participating in the electricity market and ancillary service market is further enhanced, and the market revenue optimization problem of energy storage can be realized through energy storage charging and discharging optimization control, and the investment return problem of operators can also be implemented through capacity leasing prices.

[0003] Therefore, the present application proposes a method and system for calculating the minimum capacity leasing price of energy storage charging and discharging to solve the problems existing in the prior art, which is a problem that needs to be solved by those skilled in the art. SUMMARY

[0004] Therefore, the application provides a method and system for calculating the minimum capacity leasing price of energy storage charging and discharging control, which receives system real-time electricity price information from a power trading platform, calculates the charging / discharging period and charging / discharging power of the energy storage battery within a day to generate the charging and discharging control time sequence of the energy storage battery, forms the day-ahead charging and discharging plan of the energy storage battery, and realizes the optimized control of the charging and discharging of the energy storage battery; receives the energy storage cost parameters from the energy storage power station operation platform, calculates the daily average investment and operation cost of the energy storage power station within the investment return period, combines the maximum daily market income of the energy storage, calculates the minimum daily capacity leasing price of the energy storage considering the investment return rate, and realizes the reasonable return on investment of the energy storage power station.

[0005] In order to achieve the above-mentioned purpose, the application provides the following technical scheme:

[0006] A method for calculating the minimum capacity leasing price of energy storage charging and discharging control comprises the following steps:

[0007] S1, the energy storage charging and discharging control ring receives the real-time clearing electricity price of the spot market every τ minutes within the system operation day from the power trading platform Deep peak regulation compensation price And emergency short-term peak regulation compensation price

[0008] S2, read the energy storage physical parameters including the initial state of charge through the battery management system Charging and discharging efficiency η, maximum charging power Maximum discharging power Maximum state of charge Minimum state of charge

[0009] S3, combine the charging and discharging power constraint and the state of charge constraint of the energy storage power station, calculate the charging / discharging period and charging / discharging power of the energy storage battery within a day to generate the charging and discharging control time sequence {P1, ···, P t ,···,P 1440 / τ} of the energy storage battery, form the day-ahead charging and discharging plan of the energy storage battery, and control the optimized charging and discharging of the energy storage battery;

[0010] S4, the energy storage capacity leasing pricing ring receives the energy storage cost parameters including the unit capacity investment construction cost, the unit capacity annual operation and maintenance cost, the unit capacity replacement cost, the unit capacity loss cost, the energy storage battery cycle life and the energy storage power station investment return period from the energy storage power station operation platform; in the energy storage capacity leasing pricing ring, the daily average investment and operation cost of the energy storage power station within the investment return period is calculated in combination with the discount rate of funds;

[0011] S5. Receive the maximum daily market revenue of energy storage through the energy storage charging and discharging control loop, combine it with the average daily investment and operating costs, calculate the minimum daily capacity leasing price of energy storage considering the rate of return on investment, use it as the minimum bid for energy storage power stations to participate in the capacity leasing market, and output it to the capacity leasing trading module of the power trading platform to achieve a reasonable return on investment for energy storage power stations.

[0012] Optionally, in S3, with the goal of maximizing the revenue of the energy storage power station, the daily charging / discharging periods and charging / discharging power of the energy storage battery are calculated using the following formula:

[0013]

[0014] In the formula, τ minutes is a scheduling cycle; F d Indicates daily market revenue for energy storage; μ dis,t μ represents the state of charge of energy storage during time period t. ch,t This indicates the discharge state of the energy storage during time period t; These represent the real-time clearing electricity price, deep peak-shaving compensation price, and emergency short-term peak-shaving compensation price in the spot market during time period t, respectively. These represent the discharge power allocated in the spot market and the short-term emergency peak-shaving ancillary service market during the energy storage discharge period t, respectively. These represent the success rates of the energy storage discharge period t in the spot market and the short-term emergency peak-shaving ancillary service market, respectively. These represent the charging power allocated in the spot market and the deep peak-shaving ancillary service market during the energy storage charging period t, respectively. η represents the winning bid rate of energy storage charging period t in the spot market and deep peak shaving ancillary service market, respectively; η represents the energy storage charging and discharging efficiency.

[0015] Optionally, in S4, within the energy storage capacity leasing pricing loop, the average daily investment and operating costs during the investment payback period of the energy storage power station are calculated using the following formula:

[0016]

[0017] In the formula, n represents the investment payback period for the energy storage power station; t d t cy These represent the daily cycle count and cycle life of the energy storage battery, respectively. These represent the unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, and unit capacity loss cost of an energy storage power station, respectively; E N Indicates the rated capacity of the energy storage battery; E loss represents the daily power loss of the energy storage power station; r represents the discount rate.

[0018] Optionally, in S5, the maximum daily market revenue of energy storage is received through the energy storage charge and discharge control loop, and the minimum daily capacity rental price of energy storage is calculated using the following formula:

[0019]

[0020] In the formula, This indicates the minimum daily capacity rental price for an energy storage power station; P N C represents the rated power of the energy storage battery. d This represents the average daily investment and operating cost of an energy storage power station, maxF. d This represents the maximum daily market revenue under optimal control of the charging and discharging of an energy storage power station.

[0021] Optionally, an energy storage charging and discharging control system for calculating the minimum capacity rental price, using the above-mentioned energy storage charging and discharging control method for calculating the minimum capacity rental price, includes a price information receiving module, a physical parameter receiving module, an operating status verification module, a cost parameter acquisition module, and a capacity rental price calculation module connected in sequence.

[0022] Electricity price information receiving module: The energy storage charging and discharging control loop receives the real-time cleared electricity price from the spot market every τ minutes during the system's operating day from the power trading platform. Deep peak shaving compensation price Emergency short-term peak shaving compensation price

[0023] Physical parameter receiving module: Reads energy storage physical parameters, including initial state of charge, through the battery management system. Charge / discharge efficiency η, maximum charging power Maximum discharge power Maximum state of charge Minimum state of charge

[0024] Operational Status Verification Module: Combining the charging and discharging power constraints and state of charge constraints of the energy storage power station, and aiming to maximize the revenue of the energy storage power station, this module calculates the charging / discharging periods and charging / discharging power of the energy storage battery during the day, generating the energy storage battery charging and discharging control time series {P1,···,P t ,···,P 1440 / τ This generates a day-ahead charge / discharge plan for the energy storage battery and optimizes and controls the charge / discharge process.

[0025] Cost parameter acquisition module: The energy storage capacity leasing pricing loop receives energy storage cost parameters from the energy storage power station operation platform, including unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, unit capacity loss cost, energy storage battery cycle life, and energy storage power station investment payback period; combined with the discount rate, the daily average investment and operating costs of the energy storage power station during the investment payback period are calculated in the energy storage capacity leasing pricing loop;

[0026] The capacity leasing price calculation module receives the maximum daily market revenue of energy storage through the energy storage charging and discharging control loop. Combined with the average daily investment and operating costs, it calculates the minimum daily capacity leasing price of energy storage, taking into account the rate of return on investment. This price serves as the minimum bid for energy storage power stations to participate in the capacity leasing market and is output to the capacity leasing trading module of the power trading platform to achieve a reasonable return on investment for energy storage power stations.

[0027] Optionally, it also includes an optimal revenue calculation unit that receives real-time electricity price information, considers battery state of charge and charging / discharging power constraints, and calculates the daily market revenue of the energy storage power station to obtain the charging period t and charging power that maximize the revenue of the energy storage power station. Discharge duration t and discharge power The data is sent to the operation status verification module to perform over-limit verification of the energy storage power station's operation status, and the maximum revenue value is sent to the capacity leasing price calculation module.

[0028] Optionally, it also includes a cycle count calculation module and a power loss calculation module, which receive the charging / discharging period and charging / discharging power output by the optimal profit calculation unit, calculate the daily cycle count and daily power loss of energy storage respectively, and output them to the daily average cost calculation unit.

[0029] Optionally, it also includes a daily average cost calculation unit, which receives the energy storage power station cost parameters, daily cycle count and daily power loss, and calculates the daily investment and construction cost, daily operation and maintenance cost, daily battery replacement cost and daily charge and discharge loss cost of the energy storage power station by taking into account the discount rate. All costs are added together to obtain the daily average investment and operation cost of the energy storage power station, which is then sent to the capacity leasing price calculation module.

[0030] As can be seen from the above technical solution, compared with the prior art, the present invention discloses an energy storage charging and discharging control circuit for calculating the minimum capacity leasing price, the beneficial effects of which are:

[0031] By receiving real-time electricity price information from the power trading platform, and aiming to maximize the profitability of the energy storage power station, the system calculates the daily charging / discharging periods and power of the energy storage batteries, generating a charging / discharging control time series and forming a daily charging / discharging plan for the energy storage batteries, thus achieving optimized charging / discharging control. The system also receives energy storage cost parameters from the energy storage power station operation platform, calculates the average daily investment and operating costs during the investment payback period, and, combined with the maximum daily market revenue of the energy storage, calculates the minimum daily capacity rental price considering the rate of return on investment, achieving a reasonable return on investment for the energy storage power station. This invention features easy operation, ensures charging / discharging control while maintaining the operational profitability of the energy storage power station, and achieves a reasonable return on investment. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0033] Figure 1 A flowchart of a method for calculating the minimum capacity rental price of energy storage charging and discharging control provided by the present invention;

[0034] Figure 2 A system structure diagram of an energy storage charging and discharging control system for calculating the minimum capacity rental price provided by the present invention;

[0035] Figure 3 The energy storage charging and discharging control circuit diagram provided by the present invention;

[0036] Figure 4 The real-time electricity price information graph provided by this invention;

[0037] Figure 5 The present invention provides a time series diagram for the charging and discharging control of an energy storage battery. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] See Figure 1 As shown, this invention discloses a method for calculating the minimum capacity rental price of energy storage charging and discharging control, comprising the following steps:

[0040] S1, the energy storage charging and discharging control loop receives the real-time cleared electricity price from the spot market every τ minutes during the system's operation day from the power trading platform. Deep peak shaving compensation price Emergency short-term peak shaving compensation price

[0041] S2. Read the energy storage physical parameters, including the initial state of charge, through the battery management system. Charge / discharge efficiency η, maximum charging power Maximum discharge power Maximum state of charge Minimum state of charge

[0042] S3. Combining the charging / discharging power constraints and state of charge constraints of the energy storage power station, and with the goal of maximizing the revenue of the energy storage power station, calculate the charging / discharging periods and charging / discharging power of the energy storage battery during the day, and generate the charging / discharging control time series {P1,···,P} of the energy storage battery. t ,···,P 1440 / τ This generates a day-ahead charge / discharge plan for the energy storage battery and optimizes and controls the charge / discharge process.

[0043] S4. The energy storage capacity leasing pricing loop receives energy storage cost parameters from the energy storage power station operation platform, including unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, unit capacity loss cost, energy storage battery cycle life, and energy storage power station investment payback period; combined with the discount rate, the daily average investment and operating costs of the energy storage power station during the investment payback period are calculated in the energy storage capacity leasing pricing loop.

[0044] S5. Receive the maximum daily market revenue of energy storage through the energy storage charging and discharging control loop, combine it with the average daily investment and operating costs, calculate the minimum daily capacity leasing price of energy storage considering the rate of return on investment, use it as the minimum bid for energy storage power stations to participate in the capacity leasing market, and output it to the capacity leasing trading module of the power trading platform to achieve a reasonable return on investment for energy storage power stations.

[0045] Furthermore, S3 aims to maximize the revenue of the energy storage power station by calculating the daily charging / discharging periods and charging / discharging power of the energy storage battery. The formula is as follows:

[0046]

[0047] In the formula, τ minutes is a scheduling cycle; F d Indicates daily market revenue for energy storage; μ dis,t μ represents the state of charge of energy storage during time period t. ch,t This indicates the discharge state of the energy storage during time period t; These represent the real-time clearing electricity price, deep peak-shaving compensation price, and emergency short-term peak-shaving compensation price in the spot market during time period t, respectively. These represent the discharge power allocated in the spot market and the short-term emergency peak-shaving ancillary service market during the energy storage discharge period t, respectively. These represent the success rates of the energy storage discharge period t in the spot market and the short-term emergency peak-shaving ancillary service market, respectively. These represent the charging power allocated in the spot market and the deep peak-shaving ancillary service market during the energy storage charging period t, respectively. η represents the winning bid rate of energy storage charging period t in the spot market and deep peak shaving ancillary service market, respectively; η represents the energy storage charging and discharging efficiency.

[0048] Furthermore, in S4, within the energy storage capacity leasing pricing loop, the average daily investment and operating costs during the investment payback period of the energy storage power station are calculated using the following formula:

[0049]

[0050] In the formula, n represents the investment payback period for the energy storage power station; t d t cy These represent the daily cycle count and cycle life of the energy storage battery, respectively. These represent the unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, and unit capacity loss cost of an energy storage power station, respectively; E N Indicates the rated capacity of the energy storage battery; E loss represents the daily power loss of the energy storage power station; r represents the discount rate.

[0051] Furthermore, in S5, the maximum daily market revenue of energy storage is received through the energy storage charge and discharge control loop, and the minimum daily capacity rental price of energy storage is calculated based on the return on investment. The formula is as follows:

[0052]

[0053] In the formula, This indicates the minimum daily capacity rental price for an energy storage power station; P N C represents the rated power of the energy storage battery. d This represents the average daily investment and operating cost of an energy storage power station, maxF. d This represents the maximum daily market revenue under optimal control of the charging and discharging of an energy storage power station.

[0054] Further, see Figure 2As shown, an energy storage charging and discharging control system for calculating the minimum capacity rental price applies the above-mentioned energy storage charging and discharging control method for calculating the minimum capacity rental price, including a price information receiving module, a physical parameter receiving module, an operating status verification module, a cost parameter acquisition module, and a capacity rental price calculation module connected in sequence.

[0055] Electricity price information receiving module: The energy storage charging and discharging control loop receives the real-time cleared electricity price from the spot market every τ minutes during the system's operating day from the power trading platform. Deep peak shaving compensation price Emergency short-term peak shaving compensation price

[0056] Physical parameter receiving module: Reads energy storage physical parameters, including initial state of charge, through the battery management system. Charge / discharge efficiency η, maximum charging power Maximum discharge power Maximum state of charge Minimum state of charge

[0057] Operational Status Verification Module: Combining the charging and discharging power constraints and state of charge constraints of the energy storage power station, and aiming to maximize the revenue of the energy storage power station, this module calculates the charging / discharging periods and charging / discharging power of the energy storage battery during the day, generating the energy storage battery charging and discharging control time series {P1,···,P t ,···,P 1440 / τ This generates a day-ahead charge / discharge plan for the energy storage battery and optimizes and controls the charge / discharge process.

[0058] Cost parameter acquisition module: The energy storage capacity leasing pricing loop receives energy storage cost parameters from the energy storage power station operation platform, including unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, unit capacity loss cost, energy storage battery cycle life, and energy storage power station investment payback period; combined with the discount rate, the daily average investment and operating costs of the energy storage power station during the investment payback period are calculated in the energy storage capacity leasing pricing loop;

[0059] The capacity leasing price calculation module receives the maximum daily market revenue of energy storage through the energy storage charging and discharging control loop. Combined with the average daily investment and operating costs, it calculates the minimum daily capacity leasing price of energy storage, taking into account the rate of return on investment. This price serves as the minimum bid for energy storage power stations to participate in the capacity leasing market and is output to the capacity leasing trading module of the power trading platform to achieve a reasonable return on investment for energy storage power stations.

[0060] Furthermore, it also includes an optimal revenue calculation unit that receives real-time electricity price information, considers battery state of charge and charging / discharging power constraints, and calculates the daily market revenue of the energy storage power station to obtain the charging period t and charging power that maximize the revenue of the energy storage power station. Discharge duration t and discharge power

[0061] The data is sent to the operation status verification module to perform over-limit verification of the energy storage power station's operation status, and the maximum revenue value is sent to the capacity leasing price calculation module.

[0062] Furthermore, it also includes a cycle count calculation module and a power loss calculation module, which receive the charging / discharging period and charging / discharging power output by the optimal profit calculation unit, calculate the daily cycle count and daily power loss of energy storage respectively, and output them to the daily average cost calculation unit.

[0063] Furthermore, it also includes a daily average cost calculation unit, which receives the energy storage power station's cost parameters, daily cycle count, and daily power loss. Taking into account the discount rate, it calculates the daily investment and construction cost, daily operation and maintenance cost, daily battery replacement cost, and daily charge and discharge loss cost of the energy storage power station. All costs are added together to obtain the daily average investment and operating cost of the energy storage power station, which is then sent to the capacity leasing price calculation module.

[0064] See Figure 3 As shown, this invention receives real-time electricity price information from the power trading platform, calculates the daily charging / discharging periods and power of the energy storage battery with the goal of maximizing the revenue of the energy storage power station, generates a charging / discharging control time series for the energy storage battery, and forms a daily charging / discharging plan for the energy storage battery, thereby achieving optimized charging and discharging control of the energy storage battery; it also receives energy storage cost parameters from the energy storage power station operation platform, calculates the average daily investment and operating costs of the energy storage power station during the investment payback period, and, combined with the maximum daily market revenue of the energy storage, calculates the minimum daily capacity rental price of the energy storage considering the rate of return on investment, thereby achieving a reasonable return on investment for the energy storage power station.

[0065] In a specific application example, the specific implementation steps of this invention are as follows:

[0066] The energy storage power station is designed to include a 100 MW / 200 MW lithium iron phosphate electrochemical energy storage system.

[0067] This embodiment selects a typical system operating day for real-time scenario calculation. First, this circuit receives the real-time clearing price of the spot market every 60 minutes during the system operating day from the power trading platform. Deep compensation price Emergency short-term peak shaving compensation price For real-time electricity price information, please refer to [link / reference]. Figure 4 As shown, real-time electricity price information is output to the optimal revenue calculation unit to calculate the optimal market revenue of energy storage on a given day.

[0068] The physical parameter receiving module receives energy storage physical parameters from the battery management system, including initial state of charge, charge / discharge efficiency, maximum charge / discharge power, and maximum and minimum state of charge. These physical parameters are then sent to the operation status verification module to perform over-limit verification of the energy storage power station's operation status. The parameters received by the physical parameter receiving module are shown in Table 1.

[0069] Table 1 Energy Storage Physical Parameters

[0070] The cost parameter acquisition module receives energy storage cost parameters from the energy storage power station operation platform, including unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, unit capacity loss cost, energy storage battery cycle life, and energy storage power station investment payback period. It then sends these energy storage cost parameters to the daily average cost calculation unit to calculate the daily average investment and operating costs of the energy storage power station. The energy storage cost parameters acquired by the cost parameter acquisition module are shown in Table 2.

[0071] Parameter Value Initial SOC state 10％ Battery efficiency / % 80％ Maximum charging power / MW 10 Maximum discharging power / MW 10 Maximum SOC state 90％ Minimum SOC state 10％

[0072] Table 2 Energy Storage Cost Parameters

[0073] Parameter Value Unit capacity construction cost / yuan / Wh 2 Unit capacity annual operation and maintenance cost / ten thousand yuan 27.5 Unit capacity replacement cost / yuan / Wh 0.9 Unit capacity loss cost / yuan / Wh 350 Battery cycle life / times 5000 Energy storage power station investment payback period 10 Annual operation of power station / times 330 Capital discount rate 5％

[0074] The optimal revenue calculation unit receives real-time electricity price information, considers battery state of charge and charging / discharging power constraints, and calculates the daily market revenue of the energy storage power station to obtain the charging period and charging power, and the discharging period and discharging power that maximize the revenue of the energy storage power station. This information is then sent to the operation status verification module to perform over-limit verification of the energy storage power station's operation status, and the maximum revenue value is sent to the capacity leasing price calculation module. The optimal revenue calculation unit calculates the following: the first charging period is 3:00–5:00 with a charging power of 10MW; the first discharging period is 10:00–12:00 with a discharging power of 8MW; the second charging period is 13:00–15:00 with a charging power of 10MW; the second discharging period is 21:00–23:00 with a discharging power of 8MW. The calculated maximum daily market revenue for the energy storage is 12,736 yuan.

[0075] The operation status verification module receives the charging / discharging time period and charging / discharging power of the energy storage power station, and performs over-limit verification of the operation status of the energy storage power station. The constraints include two parts:

[0076] (1) Charge and discharge power constraints

[0077]

[0078] In the formula, These represent the maximum charging and discharging power of the energy storage, respectively. These represent the actual charging and discharging power of the energy storage at time t, respectively.

[0079] (2) SOC state constraints

[0080]

[0081] In the formula, These represent the maximum and minimum states of charge of energy storage, respectively. This represents the actual state of charge of the stored energy at time t.

[0082] The charge / discharge control time series generation unit, based on the charging / discharging periods and power of the energy storage battery obtained from the optimal benefit calculation unit, assembles the charge / discharge control time series of the energy storage battery, forming a day-ahead charge / discharge plan for the energy storage battery. This achieves optimized charge / discharge control of the energy storage battery. The charge / discharge control time series generated by the charge / discharge control time series generation unit can be found in [link to relevant documentation]. Figure 5 As shown.

[0083] The cycle count calculation module and the power loss calculation module receive the charging / discharging periods and their charging / discharging power output from the optimal profit calculation unit, respectively calculate the daily cycle count and daily power loss of energy storage, and output them to the daily average cost calculation unit. The daily cycle count calculated by the cycle count calculation module is 2, and the daily power loss calculated by the power loss calculation module is 3.2MWh.

[0084] The daily average cost calculation unit receives cost parameters, daily cycle count, and daily power loss from the energy storage power station. Considering the discount rate, it calculates the daily investment and construction cost, daily operation and maintenance cost, daily battery replacement cost, and daily charge / discharge loss cost. All costs are summed to obtain the daily average investment and operating cost of the energy storage power station, which is then sent to the capacity leasing price calculation module. The daily average cost calculation unit calculates the daily average investment and operating cost of the energy storage power station to be 14,180 yuan.

[0085] The capacity leasing price calculation module receives the maximum daily market revenue and average daily investment and operating costs of the energy storage power station, calculates the minimum daily capacity leasing price required to consider the return on investment of the energy storage power station, and outputs this price as the minimum bid for the energy storage power station to participate in the capacity leasing market. This output is then sent to the capacity leasing trading module of the power trading platform to achieve a reasonable return on energy storage investment. The minimum capacity leasing price calculated by the capacity leasing price calculation module is 144 yuan / MW / day.

[0086] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0087] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling the charging and discharging of energy storage for calculating the minimum capacity rental price, characterized in that, Includes the following steps: S1, the energy storage charging and discharging control loop receives daily system operation data from the power trading platform. Real-time clearing electricity price in the spot market (minutes) Deep peak shaving compensation price Emergency short-term peak shaving compensation price ; S2. Read the energy storage physical parameters, including the initial state of charge, through the battery management system. Charge and discharge efficiency Maximum charging power Maximum discharge power Maximum state of charge Minimum state of charge ; S3. Combining the charging / discharging power constraints and state of charge constraints of the energy storage power station, and with the goal of maximizing the revenue of the energy storage power station, calculate the charging / discharging periods and charging / discharging power of the energy storage battery during the day, and generate the charging / discharging control time series of the energy storage battery. This generates a day-ahead charge and discharge plan for the energy storage battery, and optimizes and controls the charge and discharge of the energy storage battery. S4. The energy storage capacity leasing pricing loop receives energy storage cost parameters from the energy storage power station operation platform, including unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, unit capacity loss cost, energy storage battery cycle life, and energy storage power station investment payback period; combined with the discount rate, the daily average investment and operating costs of the energy storage power station during the investment payback period are calculated in the energy storage capacity leasing pricing loop. S5. Receive the maximum daily market revenue of energy storage through the energy storage charging and discharging control loop, combine it with the average daily investment and operating costs, calculate the minimum daily capacity leasing price of energy storage considering the rate of return on investment, use it as the minimum bid for energy storage power stations to participate in the capacity leasing market, and output it to the capacity leasing trading module of the power trading platform to achieve a reasonable return on investment for energy storage power stations. S3 aims to maximize the revenue of the energy storage power station, calculating the daily charging / discharging periods and charging / discharging power of the energy storage battery using the following formula: In the formula, with A scheduling cycle is one minute. Indicates daily market revenue for energy storage; Indicates the time period of energy storage The charging status, Indicates the time period of energy storage The discharge state; , , They represent The real-time clearing price of electricity in the spot market during specific periods, the deep peak-shaving compensation price, and the emergency short-term peak-shaving compensation price; , These represent the energy storage discharge periods. The discharge power allocated in the spot market and the short-term emergency peak-shaving ancillary service market , These represent the energy storage discharge periods. The success rate of bids allocated in the spot market and the short-term emergency peak-shaving ancillary services market; , These represent the energy storage charging periods. The charging power allocated in the spot market and the deep peak shaving ancillary service market , These represent the energy storage charging periods. The success rate allocated in the spot market and the deep peak-shaving ancillary services market; This indicates the energy storage charging and discharging efficiency.

2. The energy storage charging and discharging control method for calculating the minimum capacity leasing price according to claim 1, characterized in that, In S4, within the energy storage capacity leasing pricing loop, the average daily investment and operating costs during the investment payback period of the energy storage power station are calculated using the following formula: In the formula, Indicates the investment payback period for energy storage power stations; , These represent the daily cycle count and cycle life of the energy storage battery, respectively. , , , These represent the unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, and unit capacity loss cost of an energy storage power station, respectively. Indicates the rated capacity of the energy storage battery; This indicates the daily power loss of the energy storage power station; This represents the discount rate.

3. The energy storage charging and discharging control method for calculating the minimum capacity leasing price according to claim 1, characterized in that, In S5, the maximum daily market revenue of energy storage is received through the energy storage charging and discharging control loop. The minimum daily capacity rental price of energy storage is used to calculate the return on investment. The formula is as follows: In the formula, This indicates the minimum daily capacity rental price for an energy storage power station; This indicates the rated power of the energy storage battery. This indicates the average daily investment and operating cost of an energy storage power station. This represents the maximum daily market revenue under optimal control of the charging and discharging of an energy storage power station.

4. A storage charging and discharging control system for calculating the minimum capacity rental price, characterized in that... An energy storage charging and discharging control method for calculating the minimum capacity leasing price according to any one of claims 1-3 includes a price information receiving module, a physical parameter receiving module, an operating status verification module, a cost parameter acquisition module, and a capacity leasing price calculation module connected in sequence. Electricity price information receiving module: The energy storage charging and discharging control loop receives daily electricity price information from the power trading platform. Real-time clearing electricity price in the spot market (minutes) Deep peak shaving compensation price Emergency short-term peak shaving compensation price ; Physical parameter receiving module: Reads energy storage physical parameters, including initial state of charge, through the battery management system. Charge and discharge efficiency Maximum charging power Maximum discharge power Maximum state of charge Minimum state of charge ; Operational status verification module: Combining the charging and discharging power constraints and state of charge constraints of the energy storage power station, and with the goal of maximizing the revenue of the energy storage power station, it calculates the charging / discharging periods and charging / discharging power of the energy storage battery during the day, and generates the charging and discharging control time series of the energy storage battery. This generates a day-ahead charge and discharge plan for the energy storage battery, and optimizes and controls the charge and discharge of the energy storage battery. Cost parameter acquisition module: The energy storage capacity leasing pricing loop receives energy storage cost parameters from the energy storage power station operation platform, including unit capacity investment and construction cost, unit capacity annual operation and maintenance cost, unit capacity replacement cost, unit capacity loss cost, energy storage battery cycle life, and energy storage power station investment payback period; combined with the discount rate, the daily average investment and operating costs of the energy storage power station during the investment payback period are calculated in the energy storage capacity leasing pricing loop; The capacity leasing price calculation module receives the maximum daily market revenue of energy storage through the energy storage charging and discharging control loop. Combined with the average daily investment and operating costs, it calculates the minimum daily capacity leasing price of energy storage, taking into account the rate of return on investment. This price serves as the minimum bid for energy storage power stations to participate in the capacity leasing market and is output to the capacity leasing trading module of the power trading platform to achieve a reasonable return on investment for energy storage power stations.

5. A storage charging and discharging control system for calculating the minimum capacity rental price according to claim 4, characterized in that: It also includes an optimal revenue calculation unit that receives real-time electricity price information, considers battery state of charge and charging / discharging power constraints, and calculates the daily market revenue optimization of the energy storage power station to obtain the charging period that maximizes the revenue of the energy storage power station. and charging power Discharge period and discharge power The data is sent to the operation status verification module to perform over-limit verification of the energy storage power station's operation status, and the maximum revenue value is sent to the capacity leasing price calculation module.

6. A storage charging and discharging control system for calculating the minimum capacity rental price according to claim 5, characterized in that: It also includes a cycle count calculation module and a power loss calculation module, which receive the charging / discharging period and charging / discharging power output by the optimal profit calculation unit, calculate the daily cycle count and daily power loss of energy storage respectively, and output them to the daily average cost calculation unit.

7. A storage charging and discharging control system for calculating the minimum capacity rental price according to claim 6, characterized in that: It also includes a daily average cost calculation unit, which receives the energy storage power station's cost parameters, daily cycle count, and daily power loss. Taking into account the discount rate, it calculates the daily investment and construction cost, daily operation and maintenance cost, daily battery replacement cost, and daily charge and discharge loss cost of the energy storage power station. All costs are added together to obtain the daily average investment and operating cost of the energy storage power station, which is then sent to the capacity leasing price calculation module.

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