A method for generating a coordinated operation strategy for a user-side energy storage system

Abstract

The present invention provides a method for generating a coordinated operation strategy for a user-side energy storage system. Based on the equipment cost model and the equipment operation revenue model of the energy storage system, under the existing market price mechanism, based on the principle of preferentially selecting to obtain high revenue, the economy of the energy storage system participating in obtaining different revenues is compared. According to the sequence of the energy storage system participating in delaying grid upgrade and transformation revenue, improving power supply reliability revenue, participating in the electricity energy market revenue, and participating in the ancillary service market revenue, the operating power and duration of the energy storage at time t are determined, and finally the operating conditions of the energy storage system for each hour of each day are determined.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy storage system operation, and particularly relates to a method for generating a coordinated operation strategy of a user-side energy storage system. Background Art

[0002] To cope with the dual pressures of energy crisis and environmental pollution, a large number of clean power sources such as wind power and photovoltaic power, as well as re-electrification devices such as electric vehicles and electric heating, are connected to the power grid, resulting in a significant increase in the grid's reserve demand, peak-valley difference, and peak shaving pressure. Due to the excellent regulation performance of the energy storage system (ES), as a new technology, its participation in system peak shaving has received increasing attention. At present, the energy storage system can be centrally configured on the power source side or in the high-voltage power grid, or can be connected to the distribution network in a distributed form. The distributed access of the energy storage system can suppress the load nearby, can more effectively reduce the investment in power sources and the power grid, improve the system operation performance, and enhance the operation economy.

[0003] For user-side energy storage, if, under the market mechanism, the operation of the energy storage system is optimized to maximize the energy storage configuration benefit, it can not only promote the healthy development of the user side, but also promote the application of user-side ES.

[0004] At present, domestic and foreign scholars have conducted in-depth research on the optimal operation of energy storage systems and the benefits they can obtain. The research shows that: the benefits obtained by configuring an energy storage system are closely related to the investment subject, equipment capacity, market mechanism, and operation strategy. Since power grid enterprises cannot participate in peak shaving, the main purpose of configuring an energy storage system is to suppress the fluctuations of the power source and load, so as to reduce network losses, reduce the peak-valley difference of the load, and delay the upgrade and transformation. An energy storage system is configured on the medium-voltage feeder to cope with the impact of a large number of distributed photovoltaics built by users. This method comprehensively considers benefits such as reliability, loss reduction, delay of upgrade and transformation, and environment, and takes the optimal economy as the goal to establish an ES optimal configuration model considering the operation strategy. The results show that: based on the variable operation strategy, the energy storage system can obtain the maximum benefit in the game between reliability and economy. To cope with the volatility risk brought by distributed grid connection, the operation of the energy storage system is optimized with the goal of minimizing the risk cost of insufficient system flexibility, taking into account multiple costs such as energy storage investment, energy storage charge and discharge cost, switch operation cost, on-load tap-changer tap adjustment cost, and insufficient flexibility risk, and configuring the capacity and location of the energy storage. The above research all takes the power grid company as the energy storage investment subject, and through optimizing the energy storage operation, solves various negative impacts brought by the grid connection of distributed power sources to further improve the performance of the distribution network.

[0005] On the other hand, users' investment in energy storage pays more attention to obtaining benefits from the market. Photovoltaic-storage combined system investors can obtain benefits such as reducing power generation losses and high selling price with low charging cost through the coordinated operation of photovoltaics and energy storage. The amount of benefits is related to the on-grid price of photovoltaics, time-of-use electricity price of the distribution network, charging and discharging costs of energy storage, government subsidies, and local load. Although the configuration of photovoltaics and energy storage may reduce network losses at this time, third parties cannot obtain this part of the benefits. Based on the two-part time-of-use electricity price, the rated power and capacity of the user-side energy storage are configured with the goal of the net benefit within the entire life cycle of the energy storage system, comprehensively considering the reduction in electricity charges, price arbitrage of high selling price with low charging cost, reduced transformer costs, and the recovery value of energy storage. It can be seen that energy storage systems with third parties as the investment entity mostly pay more attention to the comprehensive benefits of energy storage operation.

[0006] To sum up, whether it is the distribution network or the user side investing in energy storage, both emphasize the importance of the operation strategy for the achievable efficiency of energy storage and adopt two-layer optimization to maximize the operation benefits through the operation optimization of the lower layer. Since the acquisition of various benefits is related to the load and electricity price at different time scales of year, day, and hour, and different benefits should have strategy priorities, while the existing research on the lower-layer operation optimization only aims at the optimal daily operation benefits and cannot achieve global coordinated optimization at different time scales. Summary of the Invention

[0007] Therefore, for the user-side energy storage system, the present invention proposes a method for generating a coordinated operation strategy for the user-side energy storage system, which solves the problem that the existing research on operation strategies cannot achieve global coordinated optimization at different time scales. The method includes: establishing an equipment cost model of the energy storage system and an equipment operation benefit model of the energy storage system. The equipment cost model of the energy storage system includes an investment and construction cost model of the energy storage system and a charge-discharge loss cost model considering the cycle life of the energy storage system. The equipment operation benefit model of the energy storage system includes a benefit model for delaying grid upgrade and transformation, a benefit model for improving power supply reliability, a benefit model for the electricity energy market, and a benefit model for the ancillary service market. For a specific power grid, under the condition of certain load characteristics, adequacy, and external price mechanism, its optimal operation strategy is clear. Based on this, the sizes of the ES capacity A1 for delaying grid upgrade and transformation, the ES capacity A2 for improving power supply reliability, and the ES capacity A3 for participating in market benefit allocation are obtained through optimal configuration, and the load characteristics P1 and P2 corresponding to A1 and A2 can be deduced. Based on the equipment cost model of the energy storage system and the equipment operation benefit model of the energy storage system, under the existing market price mechanism, based on the principle of preferentially selecting to obtain high benefits, compare the economy of the energy storage system participating in obtaining different benefits, and determine the operating power and duration of the energy storage at time t in the order of the energy storage system participating in the benefit of delaying grid upgrade and transformation, the benefit of improving power supply reliability, the benefit of participating in the electricity energy market, and the benefit of participating in the ancillary service market, and finally determine the operation of the energy storage system for each hour of each day.

[0008] Furthermore, the investment and construction cost model of the energy storage system is expressed by Equations (1) and (2)

[0009] C inv =-(A·c cons +ESP·c cyber ) (1)

[0010] A=A1+A2+A3 (2)

[0011] Wherein, A is the total configured capacity of the energy storage system (ES), A1, A2, and A3 are the ES capacities configured for delaying grid upgrade and transformation, improving power supply reliability, and participating in market revenue respectively, ESP is the rated total power of the ES, C inv is the investment and construction cost of the energy storage system, c cons is the unit construction cost of the energy storage system, c cyber is the unit software configuration cost of the energy storage system;

[0012] Furthermore, the charge and discharge loss cost model considering the cycle life of the energy storage system is expressed by Equation (3),

[0013]

[0014] Wherein, C m is the charge and discharge loss cost, N anu is the total number of days in a year, N t is the number of time periods in a day, k is the power loss coefficient, Δt is the time interval, P ES (n,j) is the scheduling power of the ES in the jth time period on the nth day, θ is the aging coefficient, ndc is the number of charge and discharge times completed by the ES, N dcm is the cycle life of the ES.

[0015] Furthermore, according to the peak load reduction height ΔP peak an ES revenue model for delaying grid upgrade and transformation is established, expressed as:

[0016]

[0017]

[0018]

[0019]

[0020] Wherein, R upd is the revenue for delaying grid upgrade and transformation, c sub is the construction cost of the unit power substation and line, ΔT delay is the number of years of grid construction delay, λ is the peak shaving rate achieved by configuring the ES, τ is the annual growth rate of the peak load, Pm The maximum peak load before configuring the energy storage system is P max (n) is the peak load value on the nth day, and N anu is the total number of days in a year.

[0021] Furthermore, to obtain the benefit of delaying the grid upgrade and transformation, the following constraints need to be satisfied:

[0022] Capacity constraint: At the starting time t of discharging on the nth day 1S (n), the remaining capacity of the A1 capacity ES should be greater than or equal to the ES capacity required for peak shaving on the nth day;

[0023] Discharge constraint: When the daily load is higher than P1, the A1 capacity ES should output with the difference between the current load and P1, as shown in Equation (14). At other times, the output of the A1 capacity ES for delaying the grid upgrade and transformation is 0.

[0024] P 1ES (n,t) = max(0, P load (n,t) - P1) (8)

[0025] In the formula, P 1ES (n,t) is the output of the A1 capacity ES at time t on the nth day;

[0026] Charge constraint: During the valley period after discharging, the ES can be charged according to the total rated power ESP. The charging time required to reduce the load on the nth day to P1 is as shown in Equation (15);

[0027] tch1(n) = A1(n) / (ESP·η) (9)

[0028] In the formula, tch1(n) is the charging time required for the A1 capacity ES to participate in delaying the grid upgrade and transformation on the nth day, ESP is the total rated power of the energy storage, and η is the charge-discharge efficiency.

[0029] Furthermore, the mathematical model for the A2 capacity ES to obtain the benefit of improving power supply reliability within one year is:

[0030]

[0031] p d (n) = t2(n) / 24 (11)

[0032] t2(n) = min(t fault (d),t d (n)) (12)

[0033]

[0034] P rel,d ((n,t) = min(ESP2, max(0, Pload (n,t)-P cap,d )) (14)

[0035]

[0036] Wherein, R rel is the revenue for improving power supply reliability, p d (n) is the probability that the failure of device d on the nth day actually affects the system, f d is the failure probability of the dth device, ΔS rel (n,d) is the ES capacity used to restore the lost power load when the dth device fails on the nth day, c loss is the power outage loss per unit user, t2(n) is the duration of the failure impact on the nth day, t fault (d) is the failure time of device d, t d (n) is the duration when the load on the nth day is higher than P cap,d , P rel,d (n,t) is the output power of the ES when the dth device fails at time t on the nth day, P cap,d is the power supply capacity of the system when the dth transformer fails, P T,j is the power supply capacity of the jth transformer, N s is the number of substations with connections, α k is the load rate of the kth substation, P S,k is the total power supply capacity of the kth substation.

[0037] Furthermore, the constraint condition for obtaining the revenue for improving reliability is: when the daily maximum load is greater than P2, once a system failure occurs, the energy storage system outputs power according to the current power shortage load.

[0038] Furthermore, the revenue that the energy storage system can obtain by participating in the electricity energy market includes low-price storage and high-price generation arbitrage and reduced capacity electricity charges. The mathematical model of the revenue within one year is:

[0039]

[0040] Wherein, R pm is the revenue of the energy storage system participating in the electricity energy market, R1 is the low-price storage and high-price generation arbitrage of the ES, and R2 is the reduced capacity electricity charge of the ES;

[0041] The low-price storage and high-price generation arbitrage R1 on the nth day can be calculated according to Equation (30):

[0042]

[0043] Wherein, R1(n) is the low-price storage and high-price generation arbitrage revenue, SP is the peak-time electricity price for selling electricity, BV is the valley-time electricity price for purchasing electricity, and η is the charge-discharge efficiency;

[0044] The monthly capacity electricity charge R2 that can be reduced by ES in a year is as follows:

[0045]

[0046]

[0047]

[0048]

[0049] P' load (n, :) = P load (n, :) - M'(n) (22)

[0050] Where a is the basic electricity charge payable for every 1 kW of maximum load, M j and M' j are respectively the maximum demand loads of the user before and after the low storage and high discharge of the energy storage system in the j-th month (the maximum value of the average load every 30 minutes per month), t start and t end are respectively the start and end times of the peak period, E espm (n) is the capacity of the energy storage system that can participate in the electricity energy market on the n-th day, P load and M'(n) are respectively the load levels before and after the low storage and high discharge of ES, P' load (n, t) is the reduced load peak value on the n-th day after the low storage and high discharge of ES.

[0051] Furthermore, obtaining the revenue from the electricity energy market needs to satisfy the following constraints:

[0052] Electricity energy market electricity price constraint: On the premise of being in the peak period, if the sum of the monthly electricity sales revenue and the capacity electricity charge unit price is greater than the sum of the monthly charging cost and the charge-discharge loss cost, then ES can discharge, and the discharge power is as follows,

[0053]

[0054] Where P 3ES (n, t) is the output of ES participating in the electricity energy market at time t on the n-th day, t 3S (n) and t 3E (n) are respectively the start and end times of the discharge of the ES with a capacity of E espm (n) participating in the electricity energy market;

[0055] Charging constraint: In the valley period after the end of the peak period, ES can charge according to the rated power ESP. The charging time required for the ES participating in the electricity energy market on the n-th day is as shown in Equation (37),

[0056] tch3(n) = E espm(n)·DOD / (ESP·η) (24)

[0057] Where tch3(n) is E espm (n) Capacity: The charging time required for ES after participating in the electric energy market on day n.

[0058] Furthermore, the benefits of energy storage systems participating in the ancillary services market are primarily derived through bilateral transactions, followed by market bidding, and finally through centralized dispatch. Assuming bilateral negotiations are the transaction method, with the power and duration of the energy storage system output stipulated in a contract, the potential benefits of the energy storage system participating in the ancillary services market over a year are calculated as follows:

[0059]

[0060] P 3ES (n,t)=min(P demand (n,t),ESP aux (n,t)) (26)

[0061]

[0062] Where R aux To participate in the ancillary services market revenue, N anu is the total number of days in a year, N t is the number of time periods in a day, P 3ES (n,t) is the discharge power of ES participating in the ancillary service market at time t on day n, Δt is the time interval, r aux is the unit power peak regulation price, R ch (n) is the charging cost required to participate in the ancillary service market on day n, ESP aux (n, t) is the output power of ES when participating in the ancillary service market at time t on day n. ESP1, ESP2, and ESP3 are the rated powers of energy storage systems with capacities A1, A2, and A3, respectively. 1S (n) and t 1E (n) are the start and end time of discharge of A1 capacity ES participating in delaying grid upgrade and transformation.

[0063] Furthermore, obtaining revenue from the ancillary services market requires satisfying the following constraints:

[0064] Ancillary service market price constraint: If the ancillary service market unit price is greater than the sum of the charging cost and the charging and discharging loss cost (Equation (3)), the ES can discharge, and the discharge power is shown in Equation (39);

[0065]

[0066] Charging constraints: During off-peak hours, the ES can be charged according to the rated power ESP;

[0067] Discharge duration constraint: Only ESs with a sustainable discharge time greater than 4 hours are admitted to the ancillary service market.

[0068] Furthermore, if P2 ≥ P1, the ES not only participates in delaying the grid upgrade but also ensures an improvement in power supply reliability; if P2 < P1, since the benefit of delaying the grid upgrade and transformation is the best, an ES with capacity A1 is configured to reduce the load to P1 to ensure obtaining this benefit first; at the same time, an ES with capacity A2 is configured to ensure power supply reliability within the load range of P1 and P2; in addition, an ES with capacity A3 is configured to obtain market benefits.

[0069] Furthermore, assume P2 < P1, and the maximum daily net load P max (n) is higher than P1. The ES with capacity A1 obtains the benefit UPD of delaying the grid upgrade and transformation and the benefit PM of the electricity energy market under the discharge constraint and the electricity price constraint of the electricity energy market, obtains the ancillary peaking benefit AM under the capacity constraint and the electricity price constraint of the ancillary service market, and obtains the reliability improvement benefit REL; the ES with capacity A2 obtains the reliability improvement benefit REL; the remaining capacity ESs of A3 and A1 obtain market benefits. According to the priority of the benefit size, they choose to participate in the electricity energy market during peak hours and obtain the benefit PM of the electricity energy market under the electricity price constraint of the electricity energy market. During off-peak hours, they can obtain the benefit AM of the ancillary service market under the electricity price constraint of the ancillary service market.

[0070] Furthermore, assume P2 < P1, and the maximum daily net load P max (n) is higher than P2 but not higher than P1. The ES with capacity A2 obtains the reliability improvement benefit for power supply; the ESs with capacity A1 + A3 obtain market benefits according to the priority of the benefit size under the electricity price constraint of the electricity energy market.

[0071] Furthermore, assume P2 < P1, and the maximum daily net load P max (n) is not higher than P2. The ESs with capacity A1 + A2 + A3 obtain market benefits according to the priority of the benefit size under the electricity price constraint of the market. Description of the drawings

[0072] Figure 1 is the annual continuous load curve of a single-peak load;

[0073] Figure 2 is the schematic diagram of the benefit of the ES participating in delaying the grid upgrade and transformation;

[0074] Figure 3 is the schematic diagram of the benefit of the ESs with capacity A1 + A2 + A3 participating in the electricity energy market;

[0075] Figure 4 is the schematic diagram of the constraint conditions on the delay day and the operation of the ES (Pmax(n) > P1);

[0076] Figure 5 It is an operation strategy diagram based on the load curve;

[0077] Figure 6 It is the distribution network structure of the energy storage system equipment area in the example of the present invention. Detailed implementation manners

[0078] The embodiments will be described in detail below with reference to the accompanying drawings.

[0079] The benefits obtained by configuring an energy storage system on the user side mainly include delaying the grid upgrade and transformation, improving the power supply reliability, and market benefits. The market benefits consist of the electricity energy market benefits and the ancillary service market benefits. However, these benefits are often not all achievable at the same time, and different optimal operation strategies are applicable to different load scenarios.

[0080] Taking the industrial park of the incremental distribution system as an example, large users usually have the characteristics of large load, irregular peak-valley distribution, and being greatly affected by the industrial type. The following several typical load curves are common: triple-peak type, double-peak type, single-peak type, stable type, and peak-shaving type. Taking the single-peak type load as an example, its annual continuous load curve is as Figure 1 shown. When the load is higher than P1, the load peak is large and the electricity quantity is small, and the utilization rate of the equipment invested in by the grid is relatively low. If this part of the load is reduced by using the ES, good benefits of delaying the grid upgrade and transformation will be achieved; when the load is greater than P2, the grid operation margin is small. Once equipment failures and maintenance occur, load shedding may occur. If part of the grid equipment and network investment are replaced by energy storage, better benefits of improving the power supply reliability will be generated in areas with slow load growth, scarce land resources, and high land prices; in addition, energy storage can also be configured to participate in market transactions to obtain electricity energy market benefits and ancillary service market benefits.

[0081] Establishing the cost model of the energy storage system and the benefit models for various uses

[0082] Since different benefits involved in the operation of the energy storage system can sometimes be obtained simultaneously, but in some cases they cannot, this is closely related to the load characteristics and the external market price mechanism. Assuming that energy storage systems with capacities of A1, A2, and A3 are configured respectively for delaying the grid upgrade and transformation, improving the power supply reliability, and participating in the market benefits, the relevant costs and benefits are analyzed.

[0083] 1. The equipment cost model of the energy storage system considering charge and discharge losses

[0084] In this paper, taking lithium iron phosphate energy storage as an example, the cost model of the ES and the benefit models for various uses are established, and the economy of the ES per unit capacity obtaining different benefits is compared and analyzed to support the formulation of subsequent operation strategies.

[0085] (1) The investment and construction cost model

[0086] The investment and construction cost of the energy storage system includes hardware cost and software cost. The hardware cost refers to the cost required to equip batteries with a certain capacity, and the software cost refers to the cost of the power conversion system (PCS), battery management system (BMS), and other equipment for system monitoring and control. The investment cost is shown in the following formula:

[0087] C inv =-(A·c cons +ESP·c cyber ) (29)

[0088] A=A1+A2+A3 (30)

[0089] In the formula, A is the total capacity of ES configuration, A1, A2, and A3 are the capacities of ES configured for delaying grid upgrade and transformation, improving power supply reliability, and participating in market revenue respectively, ESP is the rated total power of ES, C inv is the investment and construction cost of the energy storage system, c cons is the unit construction cost of the energy storage system, c cyber is the unit software configuration cost of the energy storage system.

[0090] (2) Charge and discharge loss cost model considering the cycle life of the energy storage system

[0091] From the perspective of electrochemistry, during the cyclic use of lithium ions, due to the loss of active lithium ions, side reactions on the electrode surface, etc., the performance of the battery will decline slowly. Therefore, the operation of the energy storage system will generate charge and discharge loss costs, and the mathematical model of the charge and discharge loss costs is shown in formula (3). It can be seen that the charge and discharge loss costs of ES increase with the increase of the number of charge and discharge cycles, and the initial charge and discharge loss costs are the same as the power loss coefficient.

[0092]

[0093] In the formula, C m is the charge and discharge loss cost, N anu is the total number of days in a year, N t is the number of time periods in a day, k is the power loss coefficient, Δt is the time interval, P ES (n,j) is the scheduling power of ES in the jth time period of the nth day, θ is the aging coefficient, ndc is the number of charge and discharge cycles completed by ES, N dcm is the cycle life of ES.

[0094] The ES cycle life varies at different depths of discharge (DOD). By fitting the relationship among the lithium battery cycle life, DOD, and battery capacity, it can be found that the greater the DOD, the faster the energy storage system capacity decays. The cycle life when the battery capacity decays to 80% is the maximum charge-discharge cycle life of the energy storage system.

[0095] 2. Operating Strategy and Revenue Analysis of Energy Storage System Equipment

[0096] (1) Revenue Model for Delaying Grid Upgrading and Transformation

[0097] To obtain the revenue from delaying grid upgrading and transformation, it is necessary to ensure that the ES has sufficient capacity A1 to continuously discharge during the periods when the daily load is greater than P1 throughout the year, reducing the annual maximum load to P1. The energy storage system capacity A1 and the rated power ESP1 can be obtained according to equations (4) - (7).

[0098]

[0099]

[0100]

[0101]

[0102] In the formula, A1(n) is the energy storage system capacity required to reduce the load to P1 on the nth day, P load (n,t) is the load at time t on the nth day, N anu is the total number of days in a year, DOD is the ES discharge depth, ESP1 is the rated discharge power of the ES with capacity A1, ΔP peak (n) is the difference between the daily maximum load and P1 on the nth day, P max (n) is the peak load value on the nth day.

[0103] t 1S (n) and t 1E (n) are the abscissas of the intersection points of the daily load curve and P1, that is, the start and end times of the discharge of the ES with capacity A1 participating in delaying the grid upgrading and transformation on the nth day, as Figure 2 shown. If the daily load on the nth day shows a bimodal characteristic, that is, there are m pairs (m > 1) of intersection points between the daily load curve and P1, then there are also m pairs of ES discharge start and end times, which are t 1S1 (n) and t 1E1 (n), …, t 1Sm (n) and t 1Em (n). The corresponding energy storage system capacities under the constraints of each discharge start and end time are A 1,1 , …, A 1,m . At this time, it is necessary to verify between A 1,k and A1,k+1 The charging capacity of the energy storage system during the valley period between them, that is, during the valley period from the end of the discharge time of A 1,k to the start of the discharge time of A 1,k+1 whether the energy storage system can be charged to the capacity required by A 1,k+1 during the valley period before the start of the discharge time. If this check is satisfied, A1(n) is as shown in Equation (8); otherwise, P1 should be increased and the start and end times of ES discharge and the corresponding required energy storage system capacity should be re-determined until the check is satisfied.

[0104]

[0105] The magnitude of the benefit of delaying grid upgrade and transformation is related to the height of the actually reduced peak load. Figure 2 In, ΔP peak (n) is the height of the load reduced by the ES with A1 capacity on the nth day, as shown in Equation (7). Then, the height of the peak load reduction ΔP peak achievable by the energy storage system with A1 capacity participating in delaying grid upgrade and transformation is the maximum value of ΔP peak (n) over all days of the year, as shown in Equation (9).

[0106]

[0107] Based on the height of the peak load reduction ΔP peak An income model for ES to delay grid upgrade and transformation is established, which can be expressed as:

[0108]

[0109]

[0110]

[0111]

[0112] In the formula, R upd is the income from delaying grid upgrade and transformation, c sub is the construction cost of the substation and line per unit power, ΔT delay is the number of years of grid construction delay, λ is the peak shaving rate achieved by configuring ES, τ is the annual growth rate of the peak load, and P m is the maximum peak load before configuring the energy storage system. [[ID=�4]]

[0113] To obtain the income from delaying grid upgrade and transformation, the following constraints must also be satisfied:

[0114] Capacity constraint: At the start time of discharge t 1S (n) on the nth day, the remaining capacity of the ES with A1 capacity should be greater than or equal to the ES capacity required for peak shaving on the nth day.

[0115] Discharge constraint: When the daily load is higher than P1, the A1 capacity ES needs to output power according to the difference between the current load and P1, as shown in Equation (14). At other times, the output power of the A1 capacity ES for delaying the grid upgrade and transformation is 0.

[0116] P 1ES (n,t) = max(0, P load (n,t) - P1) (42)

[0117] In the formula, P 1ES (n,t) is the output power of the A1 capacity ES at time t on the nth day.

[0118] Charging constraint: During the valley period after discharge, the ES can be charged according to the total rated power ESP. The charging time required to reduce the load on the nth day to P1 is as shown in Equation (15).

[0119] tch1(n) = A1(n) / (ESP·η) (43)

[0120] In the formula, tch1(n) is the charging time required for the A1 capacity ES to participate in delaying the grid upgrade and transformation on the nth day, ESP is the total rated power of the energy storage, and η is the charge-discharge efficiency.

[0121] (2) Improved power supply reliability revenue model

[0122] Configuring the A2 capacity energy storage system is to use the energy storage system to discharge and reduce load shedding when the load is greater than P2 and the system adequacy is insufficient, so as to obtain the revenue of improved power supply reliability. This revenue can be measured according to the reduction of the annual power supply shortage and the user's unit power outage loss. To ensure the power supply to the load in case of a fault and considering the duration of the fault impact, the relationship between the rated power ESP2 of the ES, A2, and P2 is as follows:

[0123]

[0124]

[0125]

[0126] Taking into account the in-station transformer failure and the in-station and inter-station power transfer, the revenue of improved power supply reliability is calculated based on the equipment failure probability, the actual probability of affecting the system, the reduced power supply shortage, and the user's power outage loss. Then the mathematical model for the A2 capacity ES to obtain the revenue of improved power supply reliability within one year is as follows:

[0127]

[0128] p d (n) = t2(n) / 24 (48)

[0129] t2(n) = min(t fault (d), t d (n)) (49)

[0130]

[0131] P rel,d (n, t) = min(ESP2, max(0, P load (n, t) - P cap,d )) (51)

[0132]

[0133] Wherein, R rel is the revenue for improving power supply reliability, p d (n) is the probability that the failure of equipment d on the nth day actually affects the system, f d is the failure probability of the dth equipment, ΔS rel (n, d) is the ES capacity used to restore the lost load when the dth equipment fails on the nth day, c loss is the power outage loss per unit user, t2(n) is the duration of the fault impact on the nth day, t fault (d) is the fault time of equipment d, t d (n) is the duration when the load on the nth day is higher than P cap,d , P rel,d (n, t) is the output power of ES when the dth equipment fails at time t on the nth day, P cap,d is the power supply capacity of the system when the dth transformer fails, P T,j is the power supply capacity of the jth transformer, N s is the number of substations with connections, α k is the load factor of the kth substation, P S,k is the total power supply capacity of the kth substation.

[0134] The constraint condition for obtaining the revenue of improving reliability is: when the maximum load on the day is greater than P2, once a system failure occurs, the energy storage system outputs power according to the current shortage of supply load.

[0135] (3) Electricity energy market revenue model

[0136] The benefits of ES participating in the electricity energy market specifically include the transactions between the user side and users (discharge benefits) and the power grid (charging costs). According to the regulations, a maximum price limit management is implemented for the actual distribution price charged for the incremental distribution network, that is, the sum of the distribution price of the distribution network borne by the user and the transmission and distribution price of the upper-level power grid shall not be higher than the current provincial power grid transmission and distribution price corresponding to the user's direct connection to the same voltage level. For the settlement between it and the power grid, the two-part electricity price method commonly used by industrial users is selected in this invention, which includes electricity charge and capacity charge, and the capacity charge is charged according to the monthly maximum load. Assuming that the power supply of the distribution network preferentially schedules the energy storage system, when ES with A3 capacity participates in the electricity energy market, the rated power ESP3 is as follows:

[0137]

[0138] ΔP dpeak (n) = P max (n) - P3(n) (54)

[0139]

[0140] In the formula, ΔP dpeak (n) is the height of peak shaving of ES with A3 capacity on the nth day, P max (n) is the peak load value on the nth day, P3(n) is the load level after peak shaving that can be achieved on the nth day, and Δt is the time interval.

[0141] Since the electricity consumption remains unchanged after configuring the energy storage system, the electricity charge remains unchanged. Therefore, the benefits that the energy storage system can obtain by participating in the electricity energy market include low-energy storage and high-discharge arbitrage and reduced capacity charge. The mathematical model of the benefits within one year is as follows:

[0142]

[0143] In the formula, R pm is the benefit of the energy storage system participating in the electricity energy market, R1 is the low-energy storage and high-discharge arbitrage of ES, and R2 is the reduced capacity charge of ES.

[0144] From the perspective of operation economy, taking P1 > P2 as an example for illustration: when the daily maximum load is higher than P1, the remaining capacity of A1 should be considered for ES participating in the electricity energy market; when the daily maximum load is lower than P1, the capacity of the energy storage system for ES participating in the electricity energy market should consider the full capacity of A1; when the daily maximum load is lower than P2, the full capacities of A1 and A2 should be considered for ES participating in the electricity energy market. The schematic diagram is as Figure 3 shown. In the figure, t 3S (n) and t 3E (n) are the abscissas of the intersection points of the daily load curve and P3(n), that is, the start and end times of discharging for ES participating in the electricity energy market on the nth day. From Figure 3It can be seen that when the daily maximum load is lower than P1, A1, A2, and A3 can all participate in the electricity energy market, discharge during peak hours to obtain low storage and high generation arbitrage, and at the same time achieve the reduction of peak load and obtain the reduced capacity electricity fee income. The three shaded parts are the schematic diagrams of the capacity of the A1, A2, and A3 energy storage systems participating in the electricity energy market, and M(n) and M’(n) are the load levels before and after the energy storage system participates in the electricity energy market discharge, respectively. And for A3, the peak shaving height P dpeak (n) is the power value required for the A3 capacity energy storage system on the nth day.

[0145]

[0146] In the formula, E espm (n) is the ES capacity that can participate in the electricity energy market on the nth day.

[0147] When the daily maximum load P max (n) is greater than P1, the A1(n) capacity energy storage is used to delay the grid upgrade and transformation. Considering that the peak load generally appears during peak hours, the A1(n) capacity ES can also obtain low storage and high generation arbitrage. The low storage and high generation arbitrage R1 on the nth day can be calculated according to Equation (30):

[0148]

[0149] In the formula, R1(n) is the low storage and high generation arbitrage income, SP is the peak-hour electricity price for selling electricity, BV is the valley-hour electricity price for purchasing electricity, and η is the charge-discharge efficiency.

[0150] In addition, by participating in the electricity energy market with low storage and high generation, the energy storage system can also reduce the peak-valley difference of the system daily load, thereby reducing the monthly capacity electricity fee. The monthly capacity electricity fee R2 that can be reduced by the ES in a year is as follows:

[0151]

[0152]

[0153]

[0154]

[0155] P' load (n,:) = P load (n,:) - M'(n) (63)

[0156] In the formula, a is the basic electricity fee payable for every 1 kW of maximum load, M j and M' j are the maximum demand loads of the user before and after low storage and high generation of the energy storage system in the jth month (the maximum value of the average load every 30 minutes per month), respectively, tstart and t end are the start and end times of the peak time respectively, E espm (n) is the capacity of the energy storage system that can participate in the electricity energy market on the nth day, P load and M'(n) are the load levels before and after the ES low storage and high discharge respectively, P' load (n, t) is the reduced peak load value on the nth day after the ES low storage and high discharge.

[0157] To obtain the revenue from the electricity energy market, the following constraints need to be met:

[0158] Electricity price constraint in the electricity energy market: On the premise of being in the peak time period, if the sum of the monthly electricity sales revenue and the unit price of capacity electricity charge is greater than the sum of the monthly charging cost and the charge-discharge loss cost, then the ES can discharge, and the discharge power is as follows.

[0159]

[0160] In the formula, P 3ES (n, t) is the output of the ES participating in the electricity energy market at time t on the nth day, t 3S (n) and t 3E (n) are respectively the start and end times of the discharge of the ES with a capacity of E espm (n) participating in the electricity energy market.

[0161] Charging constraint: During the valley time period after the end of the peak time period, the ES can charge according to the rated power ESP. The charging time required for the ES participating in the electricity energy market on the nth day is as shown in Equation (37).

[0162] tch3(n) = E espm (n)·DOD / (ESP·η) (65)

[0163] In the formula, tch3(n) is the charging time required for the ES with a capacity of E espm (n) after participating in the electricity energy market on the nth day.

[0164] (4) Ancillary service market revenue model

[0165] The revenue obtained by the ES participating in the ancillary service market is related to the market peak shaving demand, the cleared electricity quantity and the cleared price of the ES participating in peak shaving, and should be calculated according to the actual contribution of the energy storage to participating in the ancillary service. The system peak shaving demand P demand is the difference between the net load in the market area and the minimum net load on that day. According to the regulations, for the energy storage system to participate in the ancillary service market, bilateral transactions are preferred first, followed by market bidding, and finally unified dispatching. Assuming that the trading method is bilateral negotiation, the power and duration of the output of the energy storage system are agreed in the form of a contract, and assuming that the smaller value is taken between the available output size of the energy storage system and the ancillary service demand, the calculation of the revenue that the energy storage system can obtain in one year by participating in the ancillary service market is as follows:

[0166]

[0167] P 3ES P(n,t) = min(P demand (n,t), ESP aux (n,t)) (67)

[0168]

[0169] In the formula, R aux is the revenue from participating in the ancillary service market, N anu is the total number of days in a year, N t is the number of time periods in a day, P 3ES (n,t) is the discharging power of the ES participating in the ancillary service market at time t on the nth day, Δt is the time interval, r aux is the peaking price per unit power, R ch (n) is the charging cost required for the ES to participate in the ancillary service market on the nth day, ESP aux (n,t) is the available output power of the ES participating in the ancillary service market at time t on the nth day, ESP1, ESP2, and ESP3 are the rated powers of the energy storages with capacities A1, A2, and A3 respectively, t 1S (n) and t 1E (n) are the start and end times of discharging of the ES with capacity A1 participating in delaying the grid upgrade and transformation respectively.

[0170] To obtain the revenue from the ancillary service market, the following constraints need to be satisfied:

[0171] Ancillary service market electricity price constraint: If the unit price in the ancillary service market is greater than the sum of the charging cost and the charge-discharge loss cost (Equation (3)), the ES can discharge, and the discharging power is as shown in Equation (39).

[0172]

[0173] Charging constraint: Due to the ancillary service market, charging is not allowed during the system peak load period. Therefore, the ES can only charge at the rated power ESP during the non-peak period.

[0174] Discharging duration constraint: Only ESs with a sustainable discharging time greater than 4 hours are admitted to the ancillary service market.

[0175] Intelligent generation method for operation strategy based on load characteristics

[0176] According to the ES operation revenue model mentioned above, compare the economics of ES participating in obtaining different revenues under the existing market price mechanism. Since the relationship between the size of the revenue obtained and the ES capacity is not completely linear (such as the revenue from delaying grid upgrade and transformation), generally speaking, it can be considered that the size of the revenue obtained is proportional to the ES capacity. Then, considering the discharge benefit, charging cost, and charge-discharge loss cost, through calculation, the economics of ES with unit capacity participating in various revenues are ranked from high to low as follows: the revenue from delaying grid upgrade and transformation is 631 yuan / kWh, the revenue from improving power supply reliability is 32 yuan / kWh, the revenue from the electricity energy market is 9 yuan / kWh, and the revenue from ancillary peak regulation is -0.3 yuan / kWh.

[0177] ES operation should first ensure obtaining higher revenues. Due to the difference in grid adequacy, the size relationship between P1 and P2 is uncertain. If P2 ≥ P1, then ES not only participates in delaying grid upgrade but also ensures the improvement of power supply reliability. If P2 < P1, since the benefit of delaying grid upgrade and transformation is the best, configure ES with capacity A1 to reduce the load to P1 to first ensure obtaining this revenue; at the same time, configure ES with capacity A2 to ensure power supply reliability within the load range of P1 and P2; in addition, configure ES with capacity A3 to obtain market revenue. The total ES capacity A is the sum of A1, A2, and A3, and the rated total power ESP is the sum of ESP1, ESP2, and ESP3. For a specific power grid, under the conditions of its own load characteristics, adequacy, and external price mechanism being certain, its optimal operation strategy should be clear. Based on this, the sizes of A1, A2, and A3 can be obtained through optimal configuration, and the corresponding load characteristics P1 and P2 corresponding to A1 and A2 can be deduced.

[0178] According to the order of revenue size, considering that multiple revenues can be obtained simultaneously or separately during ES operation, taking P2 < P1 as an example, considering the access of distributed power sources, based on the net load curve, the matching situation between source-load characteristics and operation strategies is as follows:

[0179] (1) When the daily maximum net load P max (n) is higher than P1

[0180] At this time, it is a delaying day. ES with capacity A1 can obtain the revenue UPD from delaying grid upgrade and transformation and the revenue PM from the electricity energy market under the discharge constraint and the electricity energy market price constraint; obtain the revenue AM from ancillary peak regulation under the capacity constraint and the ancillary service market price constraint; and can also obtain the revenue REL from improving reliability. ES with capacity A2 obtains the revenue REL from improving power supply reliability. ES with capacity A3 and the remaining capacity of A1 obtain market revenue. According to the priority of revenue size, during peak hours, choose to participate in the electricity energy market and obtain the revenue PM from the electricity energy market under the electricity energy market price constraint; during off-peak hours, it can obtain the revenue AM from the ancillary service market under the constraint of the ancillary service market price. The operating power P of ES at time t on the nth day ES(n, t) is as shown in Equation (42). The charging time required after the end of peak-time discharge is tch(n), which is the sum of the discharge times of the A1 capacity ES and the A3 capacity ES, as shown in the following equation.

[0181] P ES (n, t) = P 1ES (n, t) + P 3ES (n, t) (70)

[0182] tch(n) = tch1(n) + tch3(n) (71)

[0183] Then the operation strategy of ES on the nth day is as Figure 4 shown. Figure 4 Among them, t start and t end are the start and end times of the peak time respectively, t 1S (n) and t 1E (n) are the start and end times of discharge when the A1 capacity ES participates in delaying the grid upgrade and transformation respectively, t 3S (n) and t 3E (n) are the start and end times of discharge when the E espm (n) capacity ES participates in the electricity energy market respectively, t C (n - 1) is the moment when the charging of the (n - 1)th day is completed within the nth day, tch(n) is the charging time required after the end of peak-time discharge, M'(n) is the maximum load on the nth day after the ES stores at low level and discharges at high level, and A1(n) is the energy storage system capacity required to reduce the load to P1 on the nth day.

[0184] Analyze the situation of ES participating in the ancillary service market in each time period on the nth day: If Equation (44) is satisfied, it indicates that the discharge amount generated when ES participates in the ancillary service market at t can be charged after the charging of the (n - 1)th day is completed and before the start of the peak time on the nth day or after the charging of the nth day is completed and before the end of the nth day, that is, it meets the capacity constraints of delaying the grid upgrade and transformation and the electricity energy market, then ES can output power according to Equation (39), otherwise, P 3ES (n, t) is 0;

[0185]

[0186] taux(n, t) = ΔE aux (n, t) / (η · ESP) (73)

[0187]

[0188] ΔE aux (n, t) ≤ E espm (n) (75)

[0189] In the formula, t startand t end are the start and end times of the peak time respectively, Δt is the time interval, t aux (n, t) is the charging time required after participating in the ancillary service market at time t on the nth day, ΔE aux (n, t) is the cumulative discharged energy of the ES participating in the ancillary service at time t on the nth day, t C (n - 1) is the moment when the charging on the (n - 1)th day is completed within the nth day. If the charging is completed on the (n - 1)th day, then t C (n - 1) is 0.

[0190] Initialize the marker of the number of ancillary service discharge times Δn aux to 0. When the inequality (47) is not satisfied, it indicates that the ES has reached the maximum depth of discharge DOD. Then the ES needs to charge at ESP for a duration of tch3(n) (as shown in equation (37)), generating a charging cost. At this time, make Δn aux = Δn aux + 1, modify the left boundary of k in equation (74) based on the new full - charge moment and clear ΔE aux (n, t) and continue to analyze the revenue that the ES can obtain by participating in the ancillary service market. The time when the constraint shown in inequality (44) is not satisfied is t over , and calculate the discharge cost of participating in the ancillary service market on the nth day according to equation (48).

[0191] R ch (n) = (Δn aux ·E espm (n)+ΔE aux (n, t over - 1))·BV / η (76)

[0192] In the formula, Δn aux is the marker of the number of ancillary service discharge times, ΔE aux (n, t) is the cumulative discharged energy of the ES participating in the ancillary service at time t on the nth day, BV is the off - peak electricity price for purchasing electricity, and η is the charge - discharge efficiency.

[0193] The charging constraint specifically means that the energy storage discharge capacity within the nth day can be charged to full charge during the off - peak electricity price period for purchasing electricity from the end of the peak time t end to the start of discharge on the (n + 1)th day. Let the set of the time period from the end of discharge on the nth day to the start of discharge on the (n + 1)th day be T d , and the set of the off - peak electricity price period for purchasing electricity be T BV , then the charging constraint can be expressed as equation (49).

[0194]

[0195] (2) When the maximum net load P max (n) on the current day is higher than P2 but not higher than P1

[0196] This is the reliability day. The A2-capacity ES obtains the benefit of improved power supply reliability; the A1+A3-capacity ES obtains the market benefit according to the priority of the benefit size under the constraint of the electricity energy market price. The capacity constraint and charging constraint at this time are similar to those on the delay day.

[0197] (3) The maximum net load P on the day max (n) When it is not higher than P2

[0198] This is the market day. The A1+A2+A3-capacity ES obtains the market benefit according to the priority of the benefit size under the constraint of the market price. The capacity constraint and charging constraint at this time are still similar to those on the delay day.

[0199] According to the analysis of the operation strategies of the above three types of days, under the conditions of the given original load, market price mechanism, the capacities of the A1, A2, and A3 energy storage systems, and the depth of discharge DOD, the charge and discharge strategies of the ES can be formulated. The operation strategy based on the load characteristics is as Figure 5 shown. As can be seen from Figure 5 , by judging whether it is the peak time / before the start of the peak time / after the start of the peak time, whether it is the discharge time for obtaining the benefit of the electricity energy market (i.e., whether the load is higher than M’(n)), whether the capacity constraint is met when participating in the ancillary service market, and whether it is economical to participate in the electricity energy market / ancillary service market, etc., based on the principle of preferentially selecting to obtain high benefits, that is, giving priority to ensuring participation in delaying the grid upgrade and transformation, secondly improving power supply reliability, then the electricity energy market, and finally the ancillary service market, the operating power and duration of the energy storage system at time t are determined, and finally the operating conditions of the energy storage system for each hour of each day are determined.

[0200] The method of the present invention will be described below through a specific example. It is set that the incremental distribution system area includes 3 interconnected substations, and it is expected to configure energy storage system equipment in substation S1, as shown in Figure 6 . The load rates of substation S2 and substation S3 are 65% and 70% respectively. The peak-valley electricity price mechanism is adopted for purchasing electricity from the superior power grid and supplying electricity within the incremental distribution system. The peak-valley periods are: peak 08:00 - 20:00, valley 20:00 - 08:00. The peak-valley electricity prices for purchasing electricity from the superior power grid are 1.1372 yuan / kWh and 0.3639 yuan / kWh respectively, and the corresponding peak-valley electricity prices for supplying electricity within the system are 0.9176 yuan / kWh and 0.2443 yuan / kWh respectively. The benchmark rate of return i0 is taken as 8%.

[0201] Control group

[0202] Since the highest proportion of the load that cannot be transferred is only 2%, considering the economy of configuration, energy storage is not configured separately to improve power supply reliability, so A2 is 0. And because the current ES operation does not satisfy Equation (47) and no auxiliary peak shaving benefits can be obtained, relying only on obtaining revenue from the electricity energy market, the investment cost cannot be recovered, so A3 is set to 0.

[0203] Table 1 ES Optimization Configuration Scheme

[0204]

[0205]

[0206] Based on the energy storage configuration scheme shown in Table 1, on the premise of adopting the coordinated operation strategy for the user-side energy storage system proposed by the present invention, the costs and revenues of the energy storage system are shown in Table 2.

[0207] Table 2 ES Cost and Revenue Situation

[0208]

[0209] It can be seen that by reducing the annual peak load, A1 can obtain a revenue of 21,700 yuan for delaying grid upgrade and transformation during the peak load period of the whole year, and can also participate in the electricity energy market, with the net present value of the electricity energy market revenue reaching 364,600 yuan. At the same time, if a system failure occurs, A1 can also participate in fault recovery during non-peak shaving periods and obtain revenue for improving reliability. However, since the system's inter-station transfer capacity reaches 2.85 MVA, when the system fails, it is not necessary to dispatch energy storage, and fault recovery can be achieved relying on inter-station transfer, so A1 does not obtain this revenue.

[0210] Therefore, the method for generating the coordinated operation strategy for the user-side energy storage system proposed by the present invention can achieve good economy. With the future decline in the construction cost of the energy storage system and the improvement of the economy of the energy storage system participating in the auxiliary service market, the energy storage capacity A2 configured to improve power supply reliability and the energy storage system capacity A3 configured to participate in the market will no longer be 0, and the economy of the energy storage system adopting this operation strategy will be more prominent.

[0211] This embodiment is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for generating a coordinated operation strategy of a user-side energy storage system, characterized in that: An equipment cost model of the energy storage system and an equipment operation revenue model of the energy storage system are established. The equipment cost model of the energy storage system includes an investment and construction cost model of the energy storage system and a charge-discharge loss cost model considering the cycle life of the energy storage system. The equipment operation revenue model of the energy storage system includes a revenue model for delaying grid upgrade and transformation, a revenue model for improving power supply reliability, a revenue model for the electricity energy market, and a revenue model for the ancillary service market. For a specific power grid, under certain conditions of its own load characteristics, adequacy, and external price mechanism, its optimal operation strategy is clear. Based on this, the sizes of the ES capacity A1 for delaying grid upgrade and transformation, the ES capacity A2 for improving power supply reliability, and the ES capacity A3 for participating in market revenue allocation are obtained through optimal configuration, and the load characteristics P1 and P2 corresponding to A1 and A2 can be deduced inversely. Based on the equipment cost model of the energy storage system and the equipment operation revenue model of the energy storage system, under the existing market price mechanism, based on the principle of preferentially selecting to obtain high revenue, the economy of the energy storage system participating in obtaining different revenues is compared. According to the sequence of the energy storage system participating in the revenue for delaying grid upgrade and transformation, the revenue for improving power supply reliability, the revenue for participating in the electricity energy market, and the revenue for participating in the ancillary service market, the energy storage operation power and duration at time t are determined, and finally the operation conditions of the energy storage system for each hour of each day are determined; The investment and construction cost model of the energy storage system is represented by equations (1) and (2) C inv = -(A·c cons + ESP·c cyber ) (1) A = A1 + A2 + A3 (2) Wherein, A is the total configured capacity of the energy storage system (ES), A1, A2, and A3 are the ES capacities configured for delaying grid upgrade and transformation, improving power supply reliability, and participating in market revenue respectively, ESP is the rated total power of the ES, C inv is the investment and construction cost of the energy storage system, c cons is the unit construction cost of the energy storage system, c cyber is the unit software configuration cost of the energy storage system; The charge-discharge loss cost model considering the cycle life of the energy storage system is represented by equation (3), Where C m is the charge-discharge loss cost, N anu is the total number of days in a year, N t is the number of time periods in a day, k is the power loss coefficient, Δt is the time interval, P ES (n,j) is the scheduling power of the ES in the j-th time period of the n-th day, θ is the aging coefficient, ndc is the number of charge-discharge cycles completed by the ES, N dcm is the cycle life of the ES; According to the peak load reduction height ΔP peak An ES delay power grid upgrade benefit model is established and expressed as: Wherein, R upd is the benefit of delaying the grid upgrade, c sub is the construction cost of the substation and line per unit power, ΔT delay is the number of years of delaying the grid construction, λ is the peak shaving rate achieved by configuring the ES, τ is the annual growth rate of the peak load, P m is the maximum peak load before configuring the energy storage system, P max (n) is the peak load value on the nth day, N anu is the total number of days in a year; To obtain the revenue for delaying grid upgrade and transformation, the following constraints need to be satisfied: Capacity constraint: At the starting time t 1S (n) of the nth day, the remaining capacity ES of A1 needs to be greater than or equal to the ES capacity required for peak shaving on the nth day; Discharge constraint: When the daily load is higher than P1, the ES with capacity A1 needs to output power with the difference between the current load and P1, and at other times, the output power of the ES with capacity A1 for delaying grid upgrade and transformation is 0. P 1ES (n,t) = max(0, P load (n,t) - P1) (14) where P 1ES (n, t) is the output of the A1 capacity ES at time t on the nth day; P load (n, t) is the load at time t on the nth day, and P1 refers to reducing the annual maximum load to the P1 value by discharging the ES. Charge constraint: During the valley period after discharge, the ES can be charged according to the total rated power ESP. tch1(n) = A1(n) / (ESP·η) (15) In the formula, tch1(n) is the charging time required for the ES with capacity A1 to participate in delaying grid upgrade and transformation on the nth day, ESP is the total rated power of the energy storage, and η is the charge-discharge efficiency.

2. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 1, wherein: The mathematical model for the ES with capacity A2 to obtain the revenue for improving power supply reliability within one year is: p d (n) = t2(n) / 24 (20) t2(n) = min(t fault (d), t d (n)) (21) P rel,d (n,t) = min(ESP2, max(0, P load (n,t) - P cap,d )) (23) where, R rel is the revenue for improving power supply reliability, p d (n) is the probability of the actual impact on the system when equipment d fails on the nth day, f d is the failure probability of the dth equipment, ΔS rel (n, d) is the ES capacity used to restore the lost power load when the dth equipment fails on the nth day, c loss is the power outage loss per unit user, t2(n) is the duration of the failure impact on the nth day, t fault (d) is the failure time of equipment d, t d (n) is the duration when the load on the nth day is higher than P cap,d , P rel,d (n, t) is the output power of the ES when the dth equipment fails at time t on the nth day, P cap,d is the power supply capacity of the system when the dth transformer fails, P T,j is the power supply capacity of the jth transformer, N s is the number of substations with connections, α k is the load rate of the kth substation, P S,k is the total power supply capacity of the kth substation; DOD is the depth of discharge of the ES.

3. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 2, characterized in that: The constraint condition for obtaining the revenue for improving reliability is: When the daily maximum load is greater than P2, once the system fails, the energy storage system outputs power according to the current unsupplied load size.

4. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 1, wherein: The revenues that the energy storage system can obtain by participating in the electricity energy market include low-storage and high-discharge arbitrage and reduced capacity electricity charges: Wherein, R pm is the revenue of the energy storage system participating in the electricity energy market, R1 is the arbitrage of the ES's low storage and high generation, and R2 is the reduced capacity electricity charge of the ES; The low-storage and high-discharge arbitrage R1 on the nth day can be calculated according to the following formula: In the formula, R1(n) is the low-storage and high-discharge arbitrage revenue, SP is the peak-time electricity price for selling electricity, BV is the valley-time electricity price for purchasing electricity, and η is the charge-discharge efficiency; P2 is the load value when the load is greater than this value and the system adequacy is insufficient, and the energy storage system is used to discharge to reduce load curtailment to obtain the revenue for improving power supply reliability. The monthly capacity electricity charges R2 that the ES can reduce in a year are: P′ load (n,t) = P load (n,t) - M'(n) (35) Where a is the basic electricity charge payable for each 1 kW of maximum load, M j and M' j are respectively the maximum demand loads of the user before and after the low storage and high generation of the energy storage system in the j-th month (the maximum value of the average load every 30 minutes per month), t start and t end are respectively the start and end times of the peak period, E espm (n) is the capacity of the energy storage system that can participate in the electricity energy market on the n-th day, P load and M'(n) are respectively the load levels before and after the low storage and high generation of the ES, P′ load (n, t) is the reduced peak load value on the n-th day after the low storage and high generation of the ES.

5. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 4, wherein: The following constraints need to be satisfied to obtain the revenue for the electricity energy market: Electric energy market electricity price constraint: On the premise of being in the peak time period, if the sum of the monthly electricity sales revenue and the unit price of capacity electricity fee is greater than the sum of the monthly charging cost and the charge-discharge loss cost, then the ES can discharge, and the discharge power is as follows. Where, P 3ES (n, t) is the output participating in the electricity energy market ES at time t on the nth day, and t 3S (n) and t 3E (n) are respectively the start and end times of discharging of the ES with a capacity of E espm (n) participating in the electricity energy market; Charging constraint: During the valley time period after the peak time period ends, the ES can charge according to the rated power ESP. The charging time required for the ES participating in the electric energy market on the nth day is tch3(n) = E espm (n)·DOD / (ESP·η) (37) Where, tch3(n) is the charging time required for E espm (n) capacity ES after participating in the electricity energy market on the nth day, and DOD is the discharge depth of ES.

6. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 1, wherein: The revenue of the energy storage system participating in the ancillary service market gives priority to bilateral transactions, followed by market bidding, and finally unified dispatching. Assuming that the trading method is bilateral negotiation, the power and duration of the energy storage system output are agreed in the form of a contract. Then the calculation of the revenue that the energy storage system can obtain by participating in the ancillary service market within one year is as follows: P 3ES (n,t) = min(P demand (n,t), ESP aux (n,t)) (39) Wherein, R aux is the revenue from participating in the ancillary service market, N anu is the total number of days in a year, N t is the number of time periods in a day, P 3ES (n, t) is the discharging power of the ES participating in the ancillary service market at the nth day and the tth hour, Δt is the time interval, r aux is the peaking price per unit power, R ch (n) is the charging cost required for the ES to participate in the ancillary service market on the nth day, ESP aux (n, t) is the output power of the ES participating in the ancillary service market at the nth day and the tth hour. ESP1, ESP2, and ESP3 are the rated powers of the A1, A2, and A3 capacity energy storage systems respectively, t 1S (n) and t 1E (n) are the starting and ending times of discharging for the A1 capacity ES participating in delaying the grid upgrade and transformation respectively.

7. A method for generating a coordinated operation strategy of a user-side energy storage system according to claim 6, characterized in that: To obtain the revenue from the ancillary service market, the following constraints need to be met: Ancillary service market electricity price constraint: If the unit price of the ancillary service market is greater than the sum of the charging cost and the charge-discharge loss cost (Equation (3)), then the ES can discharge. where r aux is the unit power peak shaving price, BV is the electricity price during the off-peak period of power purchase, k is the power loss coefficient, θ is the aging coefficient, ndc is the number of charge and discharge cycles completed by the ES, and N dcm is the cycle life of the ES; Charging constraint: During non-peak time periods, the ES can charge according to the rated power ESP. Discharge duration constraint: Only ES with a sustainable discharge time greater than 4 hours is admitted to the ancillary service market.

8. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 1, wherein: If P2≥P1, then while the ES participates in delaying the grid upgrade, it also ensures the improvement of power supply reliability; if P2<P1, since the benefit of delaying the grid upgrade and transformation is the best, an ES with a capacity of A1 is configured to reduce the load to P1 to ensure obtaining this revenue first; at the same time, an ES with a capacity of A2 is configured to ensure the power supply reliability within the load range of P1 and P2; in addition, an ES with a capacity of A3 is configured to obtain market revenue.

9. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 1, wherein: Assume P2 < P1, and the daily maximum net load P max (n) When it is higher than P1, the A1 capacity ES obtains the benefit of delaying grid upgrade UPD and the power energy market benefit PM under the discharge constraint and the power energy market price constraint, obtains the auxiliary peak regulation benefit AM under the capacity constraint and the auxiliary service market price constraint, and obtains the reliability improvement benefit REL; the A2 capacity ES obtains the reliability improvement benefit REL of power supply; the A3 and the remaining capacity ES of A1 obtain market benefits. According to the priority of the benefit size, they choose to participate in the power energy market during peak hours and obtain the power energy market benefit PM under the power energy market price constraint. During off-peak hours, they can obtain the auxiliary service market benefit AM under the constraint of the auxiliary service market price.

10. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 1, characterized in that: Assume P2 < P1, and the daily maximum net load P max (n) When it is higher than P2 but not higher than P1, the A2-capacity ES obtains the benefit of improved power supply reliability; the A1+A3-capacity ES obtains the market benefit according to the priority of the benefit size under the constraint of the electricity energy market price.

11. The method for generating a coordinated operation strategy of a user-side energy storage system according to claim 1, characterized in that: Assume P2 < P1, and when the daily maximum net load P max (n) is not higher than P2, the A1+A2+A3 capacity ES obtains market revenue according to the priority of revenue size under the constraint of market electricity price.

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