User side energy storage optimization configuration method and system based on electricity price difference

Abstract

According to the user side energy storage optimization configuration method and system based on the electricity price difference, the maximum value and the second maximum value of the electricity price difference in each day are obtained based on the time-of-use electricity price, the time period corresponding to the maximum value of the electricity price difference serves as the first charging and discharging time period of energy storage, and the time period corresponding to the second maximum value of the electricity price difference serves as the second charging and discharging time period of energy storage; optimizing energy storage daily charging and discharging control logic in the determined first charging and discharging time period and the determined second charging and discharging time period; based on the law of conservation of energy, an energy storage operation model and operation constraint conditions are established according to the operation parameters of the energy storage system; based on the optimized energy storage daily charging and discharging control logic, on the basis of an energy storage operation model and operation constraint conditions, establishing a user side energy storage configuration optimization objective function; and in combination with the construction constraint condition of each project, solving the user-side energy storage configuration optimization objective function to obtain the optimal configuration of user-side energy storage. According to the invention, optimal configuration of user side energy storage under maximization of technical economic benefits is realized.

Description

Technical Field

[0001] The present invention relates to an energy storage optimization configuration method, and in particular to a user-side energy storage optimization configuration method and system based on electricity price difference. Background Art

[0002] With the rapid development of power energy storage, energy storage has been widely used in power supply side, grid side, independent microgrid and other scenarios. User-side energy storage represented by industrial and commercial users is expected to become the next hot energy storage application scenario under the stimulation of the following points: 1) The time-of-use electricity price policy continues to deepen, and the peak-valley price difference is further widened; 2) The demand response market is gradually maturing, and the profit channels are increasing; 3) In recent years, there have been power restrictions or insufficient power supply, and industrial and commercial users have begun to pay attention to their own risk resistance; 4) Distributed rooftop photovoltaic installations are gradually popularized, and energy storage is expected to be used in conjunction. However, the configuration of user-side energy storage not only needs to consider meeting its functional needs, but also needs to combine its profit model to pursue the maximization of investment returns.

[0003] Prior art 1 (CN111049171A) aims to maximize the net economic benefits of energy storage, including the benefits brought by reducing network losses after accessing energy storage, the benefits brought by energy storage through electricity price difference arbitrage, and the total cost of energy storage during the planning period, and establishes the comprehensive benefit objective function of the distribution network, and obtains the optimal dynamic configuration of energy storage under the constraints of distribution network operation, energy storage operation capacity, and energy storage charge state. Prior art 2 (CN115759623A) divides the electricity price period according to the clustering of load power curves, and constructs a two-layer optimization model of energy storage and electricity price according to the period division results. The upper optimization model aims to maximize the total benefits of the energy storage power station, and the lower optimization model aims to minimize the loss cost of energy storage. Considering various short-term operation constraints of the energy storage power station, the particle swarm optimization algorithm is used to solve the electricity price and electricity volume; then, the daily load curve of the energy storage power station is analyzed before and after the implementation of the time-of-use electricity price in the summer, winter, spring (autumn) seasons. Then, different energy storage peak and valley electricity price differences are set for one of the seasons, and the output changes of energy storage in specific periods are analyzed. Prior art 3 (CN109583704A) uses eight parameters, namely, the unit price of energy storage, the difference between the peak and valley electricity prices at the project location, the average power consumption per unit time, energy storage efficiency, the duration of each period, the number of cycles of peak and flat peak, the number of days of peak periods, and the number of cycles of charging batteries, to establish a formula to obtain the annual maximum profit, energy storage equipment price, profit payback time, and total profit of the energy storage system in a certain place, thereby achieving the purpose of simply calculating the energy storage income and investment payback period. Prior art only considers the economic benefits that can be brought by time-of-use electricity prices, but does not consider the optimization of the charging and discharging period and the optimization of the charging and discharging control strategy under time-of-use electricity prices. The energy storage configuration capacity obtained cannot take into account the health of energy storage and is difficult to meet the technical requirements for extending the life. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention provides a method and system for optimizing the configuration of user-side energy storage based on electricity price difference, which comprehensively considers the energy storage operation demand and the economic feasibility of the project, first determines the energy storage charging and discharging period based on the time-of-use electricity price, considers the battery cell temperature, battery health and profit maximization during the charging and discharging period, optimizes the energy storage charging and discharging control logic, establishes the user-side energy storage configuration optimization objective function based on the optimized control logic, and jointly solves the energy storage operation constraints and construction constraints to obtain the optimal configuration of the user-side energy storage.

[0005] The present invention adopts the following technical solution.

[0006] The present invention proposes a user-side energy storage optimization configuration method based on electricity price difference, comprising:

[0007] Step 1: Based on the time-of-use electricity price, the maximum and second largest values ​​of the daily electricity price difference are obtained, and the time period corresponding to the maximum value of the electricity price difference is used as the first charging and discharging time period of the energy storage, and the time period corresponding to the second largest value of the electricity price difference is used as the second charging and discharging time period of the energy storage;

[0008] Step 2, optimizing the daily charge and discharge control logic of the energy storage during the determined first and second charge and discharge periods;

[0009] Step 3: Based on the law of conservation of energy and according to the operating parameters of the energy storage system, establish an energy storage operation model and operating constraints;

[0010] Step 4: Based on the optimized energy storage daily charge and discharge control logic, the energy storage operation model and operation constraints, establish the user-side energy storage configuration optimization objective function;

[0011] Step 5: Combine the construction constraints of each project to solve the user-side energy storage configuration optimization objective function and obtain the optimal configuration of the user-side energy storage.

[0012] Preferably, based on the time-of-use electricity price, the maximum and second largest values ​​of the daily electricity price difference are obtained by the following relationship:

[0013]

[0014] In the formula,

[0015] ΔP1 represents the maximum value of the daily electricity price difference,

[0016] ΔP2 represents the second largest daily electricity price difference.

[0017] p f is the peak-time electricity price,

[0018] p g is the off-peak electricity price,

[0019] p p This is the normal electricity price.

[0020] Preferably, based on the time-of-use electricity price, the maximum value of the daily electricity price difference is the peak-valley period electricity price difference, the period corresponding to the peak period electricity price is used as the first discharge period, and the period corresponding to the valley period electricity price is used as the first charging period;

[0021] The second largest daily price difference is the maximum value of the difference between the peak-time price and the normal-time price or the difference between the normal-time price and the valley-time price.

[0022] When the second largest value is the difference between the peak-period electricity price and the normal-period electricity price, the period corresponding to the peak-period electricity price is used as the second discharge period, and the period corresponding to the normal-period electricity price is used as the second charging period;

[0023] When the second largest value is the difference between the normal period electricity price and the valley period electricity price, the period corresponding to the normal period electricity price is used as the second discharge period, and the period corresponding to the valley period electricity price is used as the second charging period.

[0024] Preferably, the optimization of the daily charging and discharging control logic of the energy storage includes:

[0025] When the length of any charge / discharge period is not greater than the first period threshold, low-power discharge / charging is implemented, wherein the first period threshold is the time required for full charge or full discharge at low power, and the low power is 80% of the rated charging power.

[0026] Preferably, the optimization of the daily charging and discharging control logic of the energy storage includes: when the interval time between the charging and discharging periods is not greater than the second period threshold, charging ends half an hour in advance and discharging starts half an hour later, wherein the second period threshold is 1 hour.

[0027] Preferably, the optimization of the energy storage daily charge and discharge control logic includes: in the second charge and discharge period, controlling the energy storage charging power to be no greater than the difference between the maximum demand for charging this month and the load power.

[0028] Preferably, energy storage health constraints are introduced into the energy storage operation model as follows:

[0029] W bat.Ni =W bat.N0 ·SOH i

[0030] In the formula,

[0031] W bat.Ni Indicates the remaining capacity of the energy storage system in year i, unit: kWh,

[0032] W bat.N0 Indicates the initial rated capacity of the energy storage system, unit: kWh,

[0033] SOH i Represents the remaining life coefficient of the energy storage system in the i-th year.

[0034] Preferably, the user-side energy storage configuration optimization objective function is as follows:

[0035]

[0036] In the formula,

[0037] L npv Represents the net present value of the energy storage project over its entire life cycle,

[0038] L bess (i) represents the energy storage operation income in the i-th year, i = 1, 2, ..., I, I represents the operation years,

[0039] C om Represents the annual operation and maintenance cost of the project,

[0040] L rv represents the depreciation of the project,

[0041] C ini represents the initial investment cost of the project,

[0042] r represents the project discount rate expected by the investor.

[0043] Preferably, the energy storage operation benefit is expressed as follows:

[0044]

[0045] In the formula,

[0046] ΔP1 represents the maximum value of the daily electricity price difference,

[0047] ΔP2 represents the second largest daily electricity price difference.

[0048] W bat.Ni Indicates the remaining capacity of the energy storage system in year i, unit: kWh,

[0049] d represents the annual operating days, which is considered to be 300 to 350 days. The number of cycles in 10 years does not exceed the number of cycles in the energy storage life.

[0050] Preferably, the construction constraints include: load power constraints of electricity users, which ensure that the load power consumption during peak / peak electricity price periods is the upper limit of the energy storage discharge power.

[0051] Preferably, the construction constraints include: the maximum allowable grid-connected power of the main transformer is the upper limit of the sum of the energy storage discharge power and the maximum power load power during the noon flat electricity price period.

[0052] The present invention also proposes a user-side energy storage optimization configuration system based on electricity price difference, including: an energy storage charging and discharging control optimization module, an energy storage configuration optimization module;

[0053] The energy storage charge and discharge control optimization module is used to obtain the maximum and second maximum values ​​of the daily electricity price difference based on the time-of-use electricity price, and use the time period corresponding to the maximum value of the electricity price difference as the first charge and discharge period of the energy storage, and the time period corresponding to the second maximum value of the electricity price difference as the second charge and discharge period of the energy storage; optimize the daily charge and discharge control logic of the energy storage in the determined first and second charge and discharge periods;

[0054] The energy storage configuration optimization module is used to establish the energy storage operation model and operation constraints based on the law of conservation of energy and the operating parameters of the energy storage system; based on the optimized energy storage daily charging and discharging control logic, on the basis of the energy storage operation model and operation constraints, establish the user-side energy storage configuration optimization objective function; combined with the construction constraints of each project, solve the user-side energy storage configuration optimization objective function to obtain the optimal configuration of the user-side energy storage.

[0055] The beneficial effect of the present invention is that, compared with the prior art, the present invention obtains the maximum and second largest values ​​of the daily electricity price difference based on the time-of-use electricity price according to the user-side energy storage operation mode and the current revenue status, thereby determining the energy storage charging and discharging period, and considering the battery cell temperature, battery health and profit maximization during the charging and discharging period, and optimizing the energy storage charging and discharging control logic, which can not only ensure the efficiency and life of the energy storage system, but also ensure that the peak period corresponding to the second largest value of the electricity price difference is longer and the discharge conditions are better to achieve maximum revenue, thereby truly implementing the maximization of technical and economic benefits.

[0056] When constructing the energy storage operation model, the present invention comprehensively considers parameters such as energy storage self-consumption, charging and discharging efficiency, charging and discharging time, and power constraints of energy storage operation, and especially introduces the energy storage health coefficient to more practically and comprehensively reflect the characteristics of the energy storage system.

[0057] The present invention comprehensively considers the energy storage operation requirements and investment benefits, establishes a user-side energy storage optimization configuration model for the entire life cycle, and also introduces specific construction parameters of each project to obtain the optimal configuration of user-side energy storage. It takes into account a wider range of dimensions, can meet the needs of multiple parties, and has obvious advantages and convenience. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flow chart of a user-side energy storage optimization configuration method and system based on electricity price difference proposed by the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0060] The present invention proposes a user-side energy storage optimization configuration method based on electricity price difference, such as Figure 1 As shown, including:

[0061] Step 1: Based on the time-of-use electricity price, the maximum and second maximum values ​​of the daily electricity price difference are obtained, and the time period corresponding to the maximum value of the electricity price difference is used as the first charging and discharging period of the energy storage, and the time period corresponding to the second maximum value of the electricity price difference is used as the second charging and discharging period of the energy storage.

[0062] In the embodiment of the present invention, by analyzing the typical business model of user-side energy storage, the revenue source of energy storage operation is determined, an electricity price difference traction strategy is formulated according to the time-of-use electricity price characteristics, and an energy storage charging and discharging control strategy under the electricity price difference traction of two charges and two discharges per day is established.

[0063] Specifically, user-side energy storage has a variety of potential commercial application models, including but not limited to: peak-valley arbitrage models based on time-of-use electricity prices, models that optimize load characteristics to reduce demand electricity charges, models that cooperate with household-side photovoltaics to reduce peaks and fill valleys, models based on aggregators participating in demand response models, models that participate in the electricity spot market, and emergency power supply models during power outages.

[0064] Among them, the peak-valley arbitrage model based on time-of-use electricity prices refers to the industrial and commercial user-side energy storage that charges during valley periods or normal periods when electricity prices are lower, and discharges during peak periods or peak periods when electricity prices are higher, thereby reducing the company's electricity costs by time-shifting electricity.

[0065] The mode of optimizing load characteristics to reduce demand charges refers to a mode in which the load curve fluctuates greatly and has obvious peaks. At this time, the demand charge is relatively large. Energy storage is used to charge during periods of low load and discharge during periods of peak load to "smooth out the peak and fill the valley" of the load, thereby reducing the demand charge.

[0066] The aggregator-based demand response model refers to participating in grid demand response by aggregating user-side flexible resources, thereby obtaining service revenue. According to the policy, user-side energy storage obtains subsidy income by participating in local demand-side response.

[0067] Participating in the electricity spot market model refers to energy storage conducting electricity spot market transactions. Currently, Shandong's electricity spot market is relatively good.

[0068] The emergency power supply mode during power outages and power restrictions refers to the use of user-side energy storage as an emergency backup power supply for the enterprise to prevent the loss of important loads during power restrictions or sudden power outages, which may cause serious economic losses. It is of great significance in the context of "dual control of energy consumption".

[0069] Among them, the peak-valley arbitrage model based on time-of-use electricity prices has the main, stable and extensive benefits. All provinces and cities have released their own agency electricity prices. Among them, the number of regions with a peak-valley price difference of more than 0.7 yuan / kWh is 17. In areas where energy storage can achieve two charging and discharging operations throughout the day, the sum of the two charging and discharging electricity price differences exceeds 1.2 yuan / kWh in about 13 areas, providing better conditions for user-side energy storage benefits.

[0070] Without considering the peak electricity price, the time-of-use electricity price model P(t) is expressed as:

[0071]

[0072] In the formula,

[0073] t is time,

[0074] p f is the peak-time electricity price,

[0075] t f1 ,t f2 are the initial time and end time of the peak electricity price respectively.

[0076] p g is the off-peak electricity price,

[0077] t g1 ,t g2 are the initial and end times of valley electricity prices,

[0078] p p The electricity price during normal times is

[0079] Others is the time corresponding to the normal period electricity price.

[0080] The peak-valley arbitrage model based on time-of-use electricity prices is the main source of economic benefits for user-side energy storage. Its principle is to charge at a low price and discharge at a high price, thereby obtaining electricity price difference benefits. Therefore, in the method proposed by the present invention, the electricity price difference throughout the day is calculated and compared based on the time-of-use electricity prices in various places.

[0081] Specifically, considering the energy storage life and time-of-use electricity price characteristics, the user-side energy storage is charged and discharged twice a day, and the two larger electricity price differences in a day are taken as the traction target. Therefore, the electricity price difference model is expressed as:

[0082]

[0083] In the formula,

[0084] ΔP1 represents the maximum value of the daily electricity price difference,

[0085] ΔP2 represents the second largest daily electricity price difference.

[0086] Except for special areas that can obtain two peak-valley electricity price differences, other areas can only achieve one peak-valley electricity price difference. The electricity price characteristics of most areas throughout the day are as follows: early morning valley, morning flat, morning peak, noon flat, afternoon or evening peak. Therefore, normally there are two charging and discharging times, one peak and one peak flat. Therefore, according to formula (2), the maximum and second largest values ​​of the daily electricity price difference are determined, and the daily charging and discharging time period of the energy storage is determined in combination with the time period corresponding to formula (1). In a non-limiting preferred embodiment, the power plan curve for daily charging and discharging of the energy storage is formulated based on the traction of the electricity price difference. The starting time of the lower electricity price is the starting time of the energy storage charging, and the ending time of the lower electricity price is the ending time of the energy storage charging. The starting time of the higher electricity price is the starting time of the energy storage discharging, and the ending time of the higher electricity price is the ending time of the energy storage discharging.

[0087] Specifically, the daily charge and discharge control period of energy storage includes the first charge and discharge period and the second charge and discharge period. Based on the time-of-use electricity price, the maximum value of the daily electricity price difference is the peak-valley period electricity price difference. The period corresponding to the peak period electricity price is the first discharge period, and the period corresponding to the valley period electricity price is the first charging period; the second largest value of the daily electricity price difference is the maximum value of the difference between the peak period electricity price and the normal period electricity price or the difference between the normal period electricity price and the valley period electricity price; when the second largest value is the difference between the peak period electricity price and the normal period electricity price, the period corresponding to the peak period electricity price is the second discharge period, and the period corresponding to the normal period electricity price is the second charging period; when the second largest value is the difference between the normal period electricity price and the valley period electricity price, the period corresponding to the normal period electricity price is the second discharge period, and the period corresponding to the valley period electricity price is the second charging period. Generally, the peak period is longer in the second charge and discharge period, and the discharge conditions are better.

[0088] Step 2, optimizing the daily charge and discharge control logic of the energy storage according to the determined first and second charge and discharge periods, including: when the length of any charge and discharge period is not greater than the first period threshold, low-power discharge / charging is implemented, wherein the first period threshold is the time required for full charge or full discharge at low power, and the low power is 80% of the rated charging power; when the interval time of the charge and discharge period is not greater than the second period threshold, charging ends half an hour in advance and discharging starts half an hour later, wherein the second period threshold is 1h; in the second charge and discharge period, the energy storage charging power is controlled not to be greater than the difference between the maximum demand for charging this month and the load power.

[0089] Specifically, the adverse effects of battery cell temperature on the efficiency and life of the energy storage system are specially considered, and the control logic of daily charging and discharging of the energy storage is optimized according to the following conditions:

[0090] 1) Buffering and slow-release optimization control: When the length of any charging and discharging period is not greater than the first period threshold, low-power discharge / charging is implemented, where the first period threshold is the time required for full charging or full discharging at low power, and the low power is 80% of the rated charging power. Implementing buffering and slow-release optimization control can also ensure that the system is fully charged and discharged, but avoids the over-temperature caused by rapid charging and discharging.

[0091] 2) Static transition optimization control: When the interval time between the charging and discharging periods is not greater than the threshold of the second period, the charging ends half an hour in advance and the discharging starts half an hour later. The threshold of the second period is 1 hour. Static transition optimization control is implemented to allow energy storage to rest for 1 hour to facilitate energy storage and heat dissipation.

[0092] Furthermore, in order to maximize profits, under the condition of a certain cycle life, the user-side energy storage adopts a full charge and discharge control strategy, that is, the SOC is considered as 100%. In particular, considering the characteristics of the time period corresponding to the second largest value of the electricity price difference, that is, the short period at noon, high-power charging is required. If the user's basic electricity fee adopts the demand electricity fee, the control logic can be further optimized so that the energy storage charging power is not greater than the difference between the maximum demand for charging this month and the current load power, that is, the user's demand electricity fee will not be increased.

[0093] P bat.c ≤P base.max -P load (3)

[0094] In the formula,

[0095] P bat.c Indicates the energy storage charging power,

[0096] P base.max Indicates the maximum amount of energy storage users need to charge this month.

[0097] P load Indicates load power.

[0098] Step 3: Based on the law of conservation of energy and the operating parameters of the energy storage system, establish the energy storage operation model and operation constraints.

[0099] Furthermore, in step 3, based on the law of conservation of energy, an energy storage operation model is established by taking into account energy storage self-consumption, charging and discharging efficiency, charging and discharging time, power constraints of energy storage operation, and energy storage health.

[0100] There are many types of electric energy storage, the most common ones are mechanical energy storage and electrochemical energy storage. Mechanical energy storage equipment includes pumped storage, flywheel energy storage, etc. Mechanical energy storage can be modeled from the perspective of its dynamics; electrochemical energy storage equipment includes lithium-ion battery energy storage, super container energy storage, etc. Electrochemical energy storage can be modeled from the perspective of its electrochemical reaction. Energy storage equipment is modeled based on the law of conservation of energy. Taking lithium battery energy storage as an example, its energy conservation of charging and discharging in the Δt time period, where the charging process satisfies equation (4a) and the discharging process satisfies equation (4b):

[0101]

[0102]

[0103] In the formula,

[0104] is the remaining energy storage capacity (SOC) after charging and discharging.

[0105] is the stored energy capacity (SOC) before charging and discharging,

[0106] δ bat is the self-discharge rate of lithium battery,

[0107] is the charging power of the lithium battery, unit: kW,

[0108] is the discharge power of the lithium battery, unit: kW,

[0109] W bat.N is the rated capacity of energy storage, unit: kWh,

[0110] η bat.c For charging efficiency,

[0111] η bat.d is the discharge efficiency,

[0112] Δt is the duration of the charge and discharge period, unit: h.

[0113] During the operation of energy storage, the operating constraints include electricity constraints and power constraints, as shown in equations (5), (6), and (7).

[0114]

[0115]

[0116]

[0117] In the formula,

[0118] S bat , are the lower and upper limits of energy storage SOC respectively,

[0119] They are the maximum allowable charging power and maximum allowable discharging power of the energy storage system, unit: kW.

[0120] In particular, as the energy storage operation time goes by, the battery life will decay year by year. Therefore, the storage health (SOH) constraint is introduced into the model to indicate the degree of battery capacity decay, as shown in formula (8).

[0121] W bat.Ni =W bat.N0 ·SOH i (8)

[0122] In the formula,

[0123] W bat.Ni Indicates the remaining capacity of the energy storage system in year i, unit: kWh,

[0124] W bat.N0 Indicates the initial rated capacity of the energy storage system, unit: kWh,

[0125] SOH i Represents the remaining life coefficient of the energy storage system in the i-th year.

[0126] Step 4: Based on the optimized daily charging and discharging control logic of energy storage, on the basis of energy storage operation model and operation constraints, with the goal of maximizing the net present value of the project's entire life cycle, while taking into account operation and maintenance costs and project depreciation, establish the user-side energy storage configuration optimization objective function.

[0127] Energy storage configuration optimization is the basis for efficient and economical operation of energy storage systems. Based on the optimized daily charge and discharge control logic of energy storage, the benefits and costs are coordinated, the expectations of investors for capital returns are considered, the net present value of the project life cycle is maximized, and the operation and maintenance costs and project depreciation are considered. The user-side energy storage configuration optimization objective function is established as follows:

[0128]

[0129] In the formula,

[0130] L npv represents the net present value of the energy storage project over its entire life cycle,

[0131] L bess (i) represents the energy storage operation income in the i-th year, i = 1, 2, ..., I, I represents the operation years, I = 10,

[0132] C om Represents the annual operation and maintenance cost of the project,

[0133] L rv represents the depreciation of the project,

[0134] C ini represents the initial investment cost of the project,

[0135] r represents the project discount rate expected by the investor, which is generally 8%. Please refer to the internal requirements of the investor for specific details.

[0136] Furthermore, the operating income of energy storage is driven by the price difference of electricity, that is, during the life cycle, the more discharge during the period of higher electricity price, the greater the income. Since there are at least two higher price differences in time-of-use electricity prices, energy storage can generally be charged and discharged twice a day, with the time period corresponding to the maximum and second largest price difference as the time basis, guiding users to discharge energy storage under the time basis to maximize the operating income. The operating income of energy storage is expressed as follows:

[0137]

[0138] In the formula,

[0139] d represents the annual operating days, which is considered to be 300 to 350 days. The number of cycles in 10 years does not exceed the number of cycles in the energy storage life.

[0140] Furthermore, the initial investment cost of the energy storage project is proportional to the scale of energy storage, as shown below:

[0141]

[0142] In the formula,

[0143] k epc Indicates the EPC unit price per watt-hour of energy storage.

[0144] Furthermore, the operation and maintenance of energy storage projects mainly includes power station management, planned equipment maintenance, early warning processing, etc. during operation. The operation and maintenance costs of energy storage on the user side vary greatly, which is mainly affected by the scale and is basically proportional to the energy storage capacity, as shown below:

[0145]

[0146] In the formula, k om Represents the unit price of operation and maintenance per kilowatt-hour of energy storage, assumed to remain unchanged every year.

[0147] Furthermore, at the end of the project life cycle, there is still a certain residual value, mainly the disposal of equipment, which is generally proportional to the initial investment, as shown below:

[0148] L rv =r rv C ini (13)

[0149] In the formula,

[0150] r rv is the project depreciation rate, taking into account a one-time depreciation at the end of its life.

[0151] Furthermore, in view of the electricity price difference traction strategy, the time-of-use electricity price period rules, and the typical application of lithium battery energy storage, the user-side energy storage system is configured for 2 hours, as shown below:

[0152]

[0153] In the formula,

[0154] P bat Indicates the energy storage power, that is, the energy storage PCS configuration.

[0155] Step 5: Combine the construction constraints of each project to solve the user-side energy storage configuration optimization model.

[0156] Specifically, the user-side energy storage configuration optimization model is taken as the optimization target, and the main conditions such as the load power of the power user, the capacity of the main transformer and the land available for energy storage construction are taken as the construction constraints. The user-side energy storage configuration optimization model is solved to obtain the optimal configuration of the user-side energy storage.

[0157] The configuration of energy storage capacity on the user side is mainly constrained by the load power of the power user, the capacity of the main transformer and the land available for energy storage construction.

[0158] 1) The user-side energy storage revenue comes from discharge during peak / peak electricity price periods. Therefore, the ideal situation is that all energy storage power can be discharged during this period. However, a peak period in most areas is only 2 hours. Therefore, the load power consumption during the peak / peak electricity price period is the upper limit of the energy storage discharge power. The constraints are expressed as follows:

[0159] st0 <P bat <P loadmin (15)

[0160] In the formula,

[0161] P bat Indicates the energy storage PCS configuration,

[0162] P loadmin Indicates the minimum power load power during peak / peak electricity price period.

[0163] 2) Users implement a two-part electricity price system and the basic electricity fee adopts a capacity-based electricity fee. In order to avoid the main transformer overload problem caused by energy storage charging, it is particularly pointed out that in most areas, the normal time period at noon is only 2 hours, and the charging time is very tight. Therefore, it is necessary to charge at the maximum power of the energy storage PCS. At this time, it is necessary to ensure that the main transformer is not overloaded during this period. The constraints are expressed as follows:

[0164] sPbat +P load.p <P b (16)

[0165] In the formula,

[0166] P load.p It indicates the maximum power load during the noon flat electricity price period.

[0167] P b Indicates the maximum allowable grid-connected power of the main transformer.

[0168] 3) User-side enterprises generally have limited land use, so the construction land situation also needs to be considered when planning energy storage. However, due to different energy storage solutions, the land occupation cannot be quantitatively evaluated. Only a qualitative description is given here, and this needs to be considered during specific configuration.

[0169] Combined with the specific data of the actual project, equations (9), (15), and (16) are jointly solved to obtain the optimal configuration of user-side energy storage.

[0170] The present invention also proposes a user-side energy storage optimization configuration system based on electricity price difference, including: an energy storage charging and discharging control optimization module, an energy storage configuration optimization module;

[0171] The energy storage charge and discharge control optimization module is used to obtain the maximum and second maximum values ​​of the daily electricity price difference based on the time-of-use electricity price, and use the time period corresponding to the maximum value of the electricity price difference as the first charge and discharge period of the energy storage, and the time period corresponding to the second maximum value of the electricity price difference as the second charge and discharge period of the energy storage; optimize the daily charge and discharge control logic of the energy storage in the determined first and second charge and discharge periods;

[0172] The energy storage configuration optimization module is used to establish the energy storage operation model and operation constraints based on the law of conservation of energy and the operating parameters of the energy storage system; based on the optimized energy storage daily charging and discharging control logic, on the basis of the energy storage operation model and operation constraints, establish the user-side energy storage configuration optimization objective function; combined with the construction constraints of each project, solve the user-side energy storage configuration optimization objective function to obtain the optimal configuration of the user-side energy storage.

[0173] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0174] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0175] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0176] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing configuration of user-side energy storage based on electricity price difference, characterized in that: include: Step 1: Based on the time-of-use electricity price, the maximum and second largest values ​​of the daily electricity price difference are obtained, and the time period corresponding to the maximum value of the electricity price difference is used as the first charging and discharging time period of the energy storage, and the time period corresponding to the second largest value of the electricity price difference is used as the second charging and discharging time period of the energy storage; Step 2, optimizing the daily charge and discharge control logic of the energy storage during the determined first and second charge and discharge periods; Step 3: Based on the law of conservation of energy and according to the operating parameters of the energy storage system, establish an energy storage operation model and operating constraints; Step 4: Based on the optimized energy storage daily charge and discharge control logic, the energy storage operation model and operation constraints, establish the user-side energy storage configuration optimization objective function; Step 5: Combine the construction constraints of each project to solve the user-side energy storage configuration optimization objective function and obtain the optimal configuration of the user-side energy storage.

2. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: Based on the time-of-use electricity price, the maximum and second largest values ​​of the daily electricity price difference are obtained using the following relationship: In the formula, ΔP1 represents the maximum value of the daily electricity price difference, ΔP2 represents the second largest daily electricity price difference. p f is the peak-time electricity price, p g is the off-peak electricity price, p p This is the normal electricity price.

3. The user-side energy storage optimization configuration method based on electricity price difference according to claim 2 is characterized in that: Based on the time-of-use electricity price, the maximum value of the daily electricity price difference is the peak-valley price difference. The period corresponding to the peak period electricity price is used as the first discharge period, and the period corresponding to the valley period electricity price is used as the first charging period. The second largest daily price difference is the maximum value of the difference between the peak-time price and the normal-time price or the difference between the normal-time price and the valley-time price. When the second largest value is the difference between the peak-period electricity price and the normal-period electricity price, the period corresponding to the peak-period electricity price is used as the second discharge period, and the period corresponding to the normal-period electricity price is used as the second charging period; When the second largest value is the difference between the normal period electricity price and the valley period electricity price, the period corresponding to the normal period electricity price is used as the second discharge period, and the period corresponding to the valley period electricity price is used as the second charging period.

4. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: The optimization of the daily charging and discharging control logic of energy storage includes: When the length of any charge / discharge period is not greater than the first period threshold, low-power discharge / charging is implemented, wherein the first period threshold is the time required for full charge or full discharge at low power, and the low power is 80% of the rated charging power.

5. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: The optimization of the daily charging and discharging control logic of energy storage includes: when the interval time between the charging and discharging periods is not greater than the second period threshold, charging ends half an hour in advance and discharging starts half an hour later, where the second period threshold is 1 hour.

6. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: The optimization of the daily charging and discharging control logic of the energy storage includes: in the second charging and discharging period, controlling the energy storage charging power to be no greater than the difference between the maximum charging demand of this month and the load power.

7. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: The energy storage health constraint is introduced into the energy storage operation model as follows: W bat.Ni =W bat.N0 ·SOH i In the formula, W bat.Ni Indicates the remaining capacity of the energy storage system in year i, unit: kWh, W bat.N0 Indicates the initial rated capacity of the energy storage system, unit: kWh, SOH i Represents the remaining life coefficient of the energy storage system in the i-th year.

8. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: The optimization objective function of the user-side energy storage configuration is as follows: In the formula, L npv represents the net present value of the energy storage project over its entire life cycle, L bess (i) represents the energy storage operation income in the i-th year, i = 1, 2, ..., I, I represents the operation years, C om Represents the annual operation and maintenance cost of the project, L rv represents the depreciation of the project, C ini represents the initial investment cost of the project, r represents the project discount rate expected by the investor.

9. The user-side energy storage optimization configuration method based on electricity price difference according to claim 8 is characterized in that: The benefits of energy storage operation are as follows: In the formula, ΔP1 represents the maximum value of the daily electricity price difference, ΔP2 represents the second largest daily electricity price difference. W bat.Ni Indicates the remaining capacity of the energy storage system in year i, unit: kWh, d represents the annual operating days, which is considered to be 300 to 350 days. The number of cycles in 10 years does not exceed the number of cycles in the energy storage life.

10. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: Construction constraints include: load power constraints of electricity users, and the load power consumption during peak / peak electricity price periods is the upper limit of the energy storage discharge power.

11. The user-side energy storage optimization configuration method based on electricity price difference according to claim 1 is characterized in that: Construction constraints include: the maximum allowable grid-connected power of the main transformer is the upper limit of the sum of the energy storage discharge power and the maximum power load power during the noon flat electricity price period.

12. A user-side energy storage optimization configuration system based on electricity price difference, used to implement the method according to any one of claims 1 to 11, characterized in that: The system includes: energy storage charging and discharging control optimization module, energy storage configuration optimization module; The energy storage charge and discharge control optimization module is used to obtain the maximum and second maximum values ​​of the daily electricity price difference based on the time-of-use electricity price, and use the time period corresponding to the maximum value of the electricity price difference as the first charge and discharge period of the energy storage, and the time period corresponding to the second maximum value of the electricity price difference as the second charge and discharge period of the energy storage; optimize the daily charge and discharge control logic of the energy storage in the determined first and second charge and discharge periods; The energy storage configuration optimization module is used to establish the energy storage operation model and operation constraints based on the law of conservation of energy and the operating parameters of the energy storage system; based on the optimized energy storage daily charging and discharging control logic, on the basis of the energy storage operation model and operation constraints, establish the user-side energy storage configuration optimization objective function; combined with the construction constraints of each project, solve the user-side energy storage configuration optimization objective function to obtain the optimal configuration of the user-side energy storage.

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