Shared energy storage optimization configuration method and system based on load quasi-linear demand response

Abstract

The invention discloses a shared energy storage optimal configuration method and system based on load quasi-linear demand response, and belongs to a new energy grid-connected control technology. According to the method, firstly, a user side shared energy storage operation mode is constructed, then a directrix forming mode based on a performance incentive mechanism and an incentive subsidy strategy are provided, the common value of micro-grid users and shared energy storage is fully excavated, and the difficulty of guiding the users to change a power consumption mode is simplified. The limitation that users with weak rigid load and decision-making ability are poor in friendly degree and are not favorable for attracting massive users to participate is made up. Further, a user side shared energy storage configuration model taking the social welfare optimization of maximization of the remaining sum of shared energy storage operators and energy storage users as a target is constructed, the model considers two links of planning and operation, and the operation link is priced according to substitution benefits of each market member to other market members; and properties such as social welfare maximization, excitation compatibility and individual rationality are met.

Description

Technical Field

[0001] The present invention belongs to new energy grid-connected control technology, and specifically relates to a shared energy storage optimization configuration method and system based on load quasi-linear demand response. Background Art

[0002] With the development of distributed energy and multiple loads, the intermittent generation of renewable energy and the surge in controllable loads, how to make full use of these renewable energy sources and coordinate and match the flexible loads on the user side has become a major challenge facing current research. Using demand response plans to stimulate the potential of flexible loads to improve operating technology and economy is one of the current research hotspots.

[0003] There are currently two incentive methods for demand response. Among them, price-based demand response is a user-involuntary adjustment method. For example, under the premise of establishing a numerical relationship between carbon emissions and photovoltaic power generation, the concept of discount factor is introduced, so that prosumers can obtain lower discount prices at different times by actively participating in demand response. It also includes a dynamic pricing scheme for allocable electricity prices designed through linear regression to maximize the profits of microgrid load users. However, the above method is not friendly to users with rigid loads and weak decision-making ability, which is not conducive to attracting massive users to participate, and can only be applied to small-scale systems. Incentive demand response mainly compares the load data when the user does not participate in demand response with the user's actual load curve to evaluate the user's contribution to demand response.

[0004] "Optimal Configuration of Photovoltaic Microgrid Energy Storage Considering Demand Response and Source-Load Uncertainty" considers the capacity optimization configuration problem of grid-connected photovoltaic microgrid energy storage system with demand response, establishes a load guidance mechanism based on load dispatch priority, and then proposes a storage planning configuration strategy considering demand response guidance. "Impact of renewable energy integration on a novel method for pricing incentive payments of incentive-based demand response program" proposes a method for pricing incentive payments for incentive-based demand response programs through a social welfare maximization framework, which ensures the interests of all participants. However, the above method requires the dispatch center to calculate the load baseline for each user, which puts huge pressure on communication and calculation. Therefore, it is urgent to study incentive methods for large-scale and standardized demand response.

[0005] Although demand response improves the flexibility of energy management, its behavior is difficult to predict, exacerbating the mismatch between supply and demand on the demand side. The operating mechanism of shared energy storage to meet the needs of multiple users not only has the advantages of energy storage to improve the reliability and economy of load power consumption, but also can activate the scheduling space of limited flexible resources in the system, improve resource utilization and improve system reliability.

[0006] With the above advantages, shared energy storage has been widely studied. The "Cooperative Control Strategy for Multiple Loads in Substations Based on Shared Energy Storage" proposes a cooperative control strategy for multiple loads in substations based on shared energy storage. The user side optimizes the load scheduling within the day according to the shared energy storage price and time-of-use electricity price combined with its own needs. The substation side coordinates the scheduling by adjusting the shared energy storage price and the user's flexible load. Aiming at the equilibrium state of the supply and demand flow in the point-to-point market model of residential shared energy storage units, the "Peer-to-peer transactive mechanism for residential shared energy storage" proposes a service pricing and load scheduling method. However, shared operation requires a fair and efficient resource allocation mechanism to balance the interests of multiple subjects. Effective means of benefit distribution is a necessary way to configure energy storage systems more economically.

[0007] In the power market environment, real information such as the investment and construction and operation and maintenance costs of energy storage systems and the energy consumption costs of energy storage users are not easily disclosed to the public, which leads to information asymmetry among market members. In mechanism design theory, the Vickrey-Clarke-Groves (VCG) mechanism is a mechanism design method that encourages market members to disclose real information. The above method can guide market members to report real information and achieve fair distribution of payments to each market member. Summary of the invention

[0008] Purpose of the invention: Under the goal of building a new power system, in order to promote the coordinated operation of flexible resources, the present invention provides a shared energy storage optimization configuration method and system based on load quasi-linear demand response, so as to give full play to the demand response capability of the load side.

[0009] Technical solution: A shared energy storage optimization configuration method based on load quasi-linear demand response, the method includes building a user-side shared energy storage operation mode, in which the user meets the power demand through the equipped wind and solar power generation, purchases electricity from the shared energy storage and purchases electricity from the power grid; the power consumption is achieved by consuming the own load and selling the surplus power to the shared energy storage; the shared energy storage refers to charging, purchasing electricity from the power grid, purchasing surplus wind and solar power from users; discharging, selling electricity to users to provide power services;

[0010] The method includes the following steps for optimizing the configuration of shared energy storage:

[0011] (1) Based on the tracking accuracy of the actual load curve and the load criterion, participants with outstanding performance will be given a tiered reward;

[0012] Let the base incentive price be p m , the benefit of user i after participating in quasi-linear demand response is defined as:

[0013] I CDL,i =p m ·P D ·ε i

[0014] Among them, P D is the total adjustable power declared by the user the day before, ε i It is a similarity index used to describe the similarity between the actual load form of the user and the adjustment target;

[0015] (2) A shared energy storage configuration model based on maximizing social welfare is constructed. The shared energy storage configuration takes into account the economic efficiency of both investment and operation, which are composed of the user's benefits and the cost of shared energy storage, respectively. The overall objective function is to maximize social welfare, which can be expressed as:

[0016] W all =max(I user -C ses )

[0017] In the formula, user benefit I user and the shared energy storage cost C ess The maximization of the difference corresponds to social welfare W all Optimal;

[0018] (3) Establish a VCG-based resource allocation mechanism to encourage investors and builders of shared energy storage to report their true operation and maintenance costs during operation, and at the same time encourage users of energy storage charging and discharging services to report their energy consumption truthfully, including:

[0019] (3.1) Phase I: The value of market members is reflected in the substitution benefits for other members and the contribution to the overall benefits of the system. The value of shared energy storage is expressed as the change in the total social welfare of the market before and after participating in the market. Similarly, the value of a user's load is also measured by the change in the total social welfare of the market before and after participating in the market.

[0020] make For the social welfare of all members when they participate in the system market, Excluding the social welfare of the new market for shared energy storage systems, the payment for shared energy storage is expressed as:

[0021]

[0022] make The social welfare of the new system market without user load i is:

[0023]

[0024] (3.2) Phase II: Considering the operating costs and income of shared energy storage and users to calculate the initial benefits, and calculating the initial investment cost of the shared energy storage power station, the income redistribution factor is introduced to redistribute the initial cost, thereby obtaining the final benefits of users and shared energy storage. The specific expression is as follows:

[0025]

[0026] In the formula, To share the benefits of energy storage systems; Payment for user i; β is the income redistribution factor.

[0027] Furthermore, the similarity ε used in step (1) to describe the actual load form of the user and the regulation target i The calculation is as follows:

[0028]

[0029] Where: d i Used to describe the Euclidean distance between the actual load line and the load directrix; ε 0 The similarity standard value for determining whether to obtain demand response rewards; represents the actual load form of user i's flexible load, represents the non-adjustable load of user i in period t, is the total adjustable power declared by the i-th user the day before; is the normalized load line shape, and the specific calculation is as follows:

[0030]

[0031] in is the total load at time t; in addition, the load criterion has the following constraints:

[0032]

[0033] In the formula, To purchase electricity, is the actual output of new energy in period t, is the predicted value of wind and solar power generation in the system during period t, The maximum amount of electricity purchased.

[0034] Furthermore, considering the similarity ε defined iis a piecewise function. If the similarity does not reach the set threshold, the final problem will be transformed into a linear programming problem. Once the similarity reaches or exceeds the threshold, the variable C needs to be introduced for calculation:

[0035]

[0036] The d in the formula is converted into the form of the second norm, and the new variable C is used to replace the corresponding item of the objective function in the benefit of user i after participating in the quasi-linear demand response. The above formula is converted into an inequality form and added as a constraint condition, thereby obtaining a new expression of the optimization problem:

[0037] I CDL,i =p m P D -C

[0038]

[0039] Furthermore, step (2) includes constructing a user benefit model and a shared energy storage cost model, as follows:

[0040] (2.1) User benefit model, whose objective function is:

[0041]

[0042] The total user benefit is composed of the demand response benefit of each user, the reduced penalty cost of power abandonment, the reduced cost of purchasing electricity from the grid, and the benefit of selling abandoned electricity to shared energy storage. ab1 Penalty fees for power abandonment, and They represent the amount of power abandoned by the i-th user without energy storage and with energy storage in period t respectively; and They represent the amount of electricity purchased by the i-th user without energy storage and with energy storage in period t respectively; ab2 The price of electricity sold for abandoned power, is the amount of abandoned electricity sold by the i-th user in period t;

[0043] In terms of user collaborative operation, it is possible to avoid simultaneous power abandonment and power purchase from the grid, power balance, new energy power usage range, charging and discharging power range, avoid simultaneous charging and discharging, and only purchase power from the grid. The constraints are as follows:

[0044]

[0045]

[0046] Where: and are the load and the output of renewable energy of the i-th user in period t respectively; and The status bits representing the user's power abandonment and power purchase are Boolean variables. If the demand is greater than the supply, the user needs to purchase electricity, otherwise the user abandons electricity. and They represent the charging and discharging amount of the i-th user in period t respectively; The upper limit of the renewable energy output of the i-th user in period t; is the maximum charging and discharging power of the i-th user; and The status bits representing user charging and discharging are 0-1 variables respectively;

[0047] (2.2) Shared energy storage cost model, whose objective function is:

[0048]

[0049] The total cost of shared energy storage consists of the cost of purchasing abandoned electricity from users, the cost of purchasing electricity from the grid, and the operation and maintenance costs. N is the amount of electricity purchased from the grid by the shared energy storage during period t; om The daily operation and maintenance rate for shared energy storage; and They represent the charging and discharging amounts of the shared energy storage in period t respectively;

[0050] During the coordinated operation of users and shared energy storage power stations, the general constraints that need to be ensured are as follows:

[0051]

[0052] In the formula, It represents the total charging amount including the charging from the user side by the shared energy storage and the electricity purchased from the grid; is the maximum charging and discharging power of the shared energy storage; and Respectively represent the status bits of shared energy storage charging and discharging; is the capacity state of the shared energy storage in period t; η is the charging and discharging efficiency of the shared energy storage; and They respectively represent the upper and lower limits of the shared energy storage capacity.

[0053] Based on the implementation of the above method, the present invention also provides a shared energy storage optimization configuration system based on load quasi-linear demand response, the system includes a memory, a processor and a computer program stored in the memory, the processor executes the computer program to implement the above-mentioned shared energy storage optimization configuration method based on load quasi-linear demand response.

[0054] A computer-readable storage medium stores a computer program / instruction thereon. When the computer program / instruction is executed by a processor, a method for optimizing the configuration of shared energy storage based on load quasi-linear demand response is implemented.

[0055] Beneficial effects: The essential features and significant effects of the present invention include:

[0056] (1) Based on the spatiotemporal complementary characteristics of energy consumption of multiple types of energy storage users, the basic framework of the user-side shared energy storage operation mode is proposed to achieve economical energy supply and efficient electricity consumption.

[0057] (2) A performance-based incentive mechanism-based criterion formation method and incentive subsidy strategy are proposed to fully tap the common value of microgrid users and shared energy storage and simplify the difficulty of guiding users to change their power consumption patterns. This makes up for the limitations of rigid loads and weak decision-making ability, which are not user-friendly and are not conducive to attracting massive user participation.

[0058] (3) A user-side shared energy storage configuration model is constructed with the goal of maximizing the sum of the surplus of shared energy storage operators and energy storage users. The model takes into account both planning and operation. The operation stage prices the market members according to the substitution benefits of other market members, satisfying the properties of social welfare maximization, incentive compatibility, and individual rationality. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is the user-side shared energy storage operation framework diagram;

[0060] Figure 2 This is the wind and solar output diagram of each industrial user in the embodiment;

[0061] Figure 3 is the load curve of each industrial user in the embodiment;

[0062] Figure 4 It is the optimal configuration capacity curve of energy storage under the quasi-linear demand response of each industrial user;

[0063] Figure 5 It is the load adjustment comparison curve before and after the user participates in demand response (CDL, CBL);

[0064] Figure 6 It is the load standard line and the load curve of each industrial user (energy storage participation);

[0065] Figure 7 It is the user charging and discharging power and the shared energy storage SOC state curve;

[0066] Figure 8 It is a comparison chart of adjustable loads with or without energy storage participating in the user shaping capacity adjustment;

[0067] Fig. 9 It is a sensitivity analysis of price factors on the optimal configuration size of shared energy storage;

[0068] Fig.10 It is the optimal configuration capacity curve of energy storage under different user participation conditions;

[0069] Fig.11 It is the income and expenditure situation of each entity under different benefit distribution plans. DETAILED DESCRIPTION

[0070] To illustrate the technical solution provided by the present invention in detail, a further introduction is given below in conjunction with the accompanying drawings.

[0071] This embodiment takes the example of a centralized shared energy storage and three energy storage users with self-equipped new energy power generation equipment in the region to verify the proposed configuration strategy and conduct a quantitative analysis of the impact of factors such as price, load type, and allocation plan on the configuration results.

[0072] 1. User-side shared energy storage operation model

[0073] The user-side centralized shared energy storage operation model framework is as follows: Figure 1 As shown, there are two types of operating entities, namely users and shared energy storage operators;

[0074] The internal energy supply relationship of each operating entity is as follows:

[0075] 1) Users: meet electricity demand through equipped wind and solar power generation, purchasing electricity from shared energy storage and purchasing electricity from the power grid; realize electricity consumption by consuming their own load and selling surplus electricity to shared energy storage.

[0076] 2) Shared energy storage: Charging, purchasing electricity from the grid and purchasing surplus wind and solar power from users; discharging, selling electricity to users and providing electricity services.

[0077] 2. Formation of incentive load line

[0078] Taking into account the response performance compensation in the frequency regulation incentive measures, the regional power grid will give tiered rewards to participants with outstanding performance based on the tracking accuracy of the actual load curve and the load directive.

[0079] Let the base incentive price be p m , the benefit of user i after participating in quasi-linear demand response is defined as:

[0080] I CDL,i =p m ·P D ·ε i (1)

[0081] Among them, P Dis the total adjustable power declared by the user the day before, ε i It is a similarity index used to describe the similarity between the actual load form of the user and the adjustment target. The specific calculation is as follows:

[0082]

[0083] Where: d i Used to describe the Euclidean distance between the actual load line and the load directrix; ε 0 The similarity standard value for determining whether or not to obtain demand response rewards. represents the actual load form of user i's flexible load, represents the non-adjustable load of user i in period t, is the total adjustable electricity declared by the i-th user the day before. is the normalized load line shape, and the specific calculation is as follows:

[0084]

[0085] in is the total load at time t; in addition, the load criterion has the following constraints:

[0086]

[0087] The node power balance constraint in formula (5) abandons the traditional supply-demand balance equation constraint form and adopts a new expression of "adjustable" balancing "unadjustable", where To purchase electricity, is the actual output of renewable energy in period t. Formula (6) emphasizes that the load standard is to adjust the form of the original load rather than increase or decrease the overall power consumption; Formula (7) constrains the user's online purchase of electricity and the upper limit of renewable energy output, where is the predicted value of wind and solar power generation in the system during period t, The maximum amount of electricity purchased.

[0088] Considering the similarity ε defined i It is a piecewise function, so if the similarity does not reach the set threshold, the final problem will be transformed into a linear programming problem; once the similarity reaches or exceeds the threshold, the variable C needs to be introduced for further analysis:

[0089]

[0090] The d in the formula is converted into the form of the two norm. The new variable C is used to replace the corresponding terms of the objective function in formula (1), and formula (8) is converted into an inequality form and added as a constraint condition, thereby obtaining a new expression of the optimization problem:

[0091]

[0092] 3. Construct a shared energy storage configuration model based on maximizing social welfare

[0093] The configuration of shared energy storage takes into account the economic efficiency of both investment and operation, which are composed of the user's benefits and the cost of shared energy storage respectively. The overall objective function is to maximize social welfare:

[0094] W all =max(I user -C ses ) (10)

[0095] In the formula, user benefit I user and the shared energy storage cost C ess The maximization of the difference corresponds to social welfare W all Best.

[0096] 3.1 User Benefit Model

[0097] As the user subject in the proposed social model, its objective function is:

[0098]

[0099] In the formula: the total user benefit is composed of the demand response benefits of each user, the reduced penalty cost of power abandonment, the reduced cost of purchasing electricity from the grid, and the benefits of selling abandoned electricity to shared energy storage. ab1 Penalty fees for power abandonment, and They represent the amount of power abandoned by the i-th user without energy storage and with energy storage in period t respectively; and They represent the amount of electricity purchased by the i-th user without energy storage and with energy storage in period t respectively; ab2 The price of electricity sold for abandoned power, It is the abandoned electricity sold by the i-th user in period t (the electricity charged into the shared energy storage).

[0100] In terms of user collaborative operation, there are constraints such as avoiding simultaneous power abandonment and purchasing power from the grid, power balance, new energy power usage range, charging and discharging power range, avoiding simultaneous charging and discharging, and only purchasing power from the grid. The constraints are as follows:

[0101]

[0102]

[0103] Where: and are the load and the output of renewable energy of the i-th user in period t respectively; and The status bits representing the user's power abandonment and power purchase are Boolean variables. If the demand is greater than the supply, the user needs to purchase electricity, otherwise the user abandons electricity. and They represent the charging and discharging amount of the i-th user in period t respectively; is the upper limit of the renewable energy output of the i-th user in period t. Constraint (17) includes balance constraints, renewable energy output constraints, constraints to avoid simultaneous charging and discharging of users, and constraints on purchasing electricity. is the maximum charging and discharging power of the i-th user; and The status bits representing user charging and discharging are 0-1 variables.

[0104] 3.2 Shared Energy Storage Cost Model

[0105] As the shared energy storage subject in the proposed social model, its objective function is:

[0106]

[0107] In the formula: The total cost of shared energy storage is composed of the cost of purchasing abandoned electricity from users (user charging), the cost of purchasing electricity from the power grid, and the operation and maintenance cost. N is the amount of electricity purchased from the grid by the shared energy storage during period t; om The daily operation and maintenance rate for shared energy storage; and They represent the charging and discharging amounts of the shared energy storage in period t respectively.

[0108] During the coordinated operation of users and shared energy storage power stations, the conventional constraints that need to be ensured are as described in formula (18):

[0109]

[0110] The formula includes power balance constraints, upper and lower limit constraints on charging and discharging power, and constraints to prevent simultaneous charging and discharging. It represents the total charging amount including the charging from the user side by the shared energy storage and the electricity purchased from the grid; is the maximum charging and discharging power of the shared energy storage; and Respectively represent the status bits of shared energy storage charging and discharging; is the capacity state of the shared energy storage in period t; η is the charging and discharging efficiency of the shared energy storage; and They respectively represent the upper and lower limits of the shared energy storage capacity.

[0111] 4 VCG-based resource allocation mechanism

[0112] In order to encourage the investors and builders of shared energy storage to report their real operation and maintenance costs during the operation process, and to encourage users of energy storage charging and discharging services to report their energy consumption truthfully, this section proposes a resource allocation mechanism based on VCG.

[0113] 4.1 The first phase of benefit distribution based on VCG mechanism

[0114] The value of market members is reflected in the substitution benefits for other members and the contribution to the overall benefits of the system. The value of shared energy storage is expressed as the change in the total social welfare of the market before and after participating in the market; similarly, the value of a user's load is also measured by the change in the total social welfare of the market before and after participating in the market.

[0115] make For the social welfare of all members when they participate in the system market, is the social welfare of the new market without the shared energy storage system. The payment for shared energy storage is expressed as:

[0116]

[0117] make is the social welfare of the new system market that does not include user load i. Then under the VCG mechanism proposed in the present invention, the payment obtained by user i is:

[0118]

[0119] 4.2 Second stage of benefit distribution based on VCG mechanism

[0120] It is necessary not only to consider the operating costs and income of shared energy storage and users to calculate the initial benefits, but also to calculate the initial investment cost of the shared energy storage power station. Therefore, it is necessary to introduce a benefit redistribution factor to redistribute the initial cost, so as to obtain the final benefits of users and shared energy storage. The specific expression is as follows:

[0121]

[0122] In the formula, To share the benefits of energy storage systems; is the payment of user i; β is the profit redistribution factor.

[0123] The rapid development of microgrid systems has led to the emergence of distributed power generation resources on the user side. In order to encourage users to consume more new energy, a shared energy storage system is introduced to cooperate with the user's controllable load. In order to verify the effectiveness of the proposed configuration strategy and benefit distribution model, three industrial users and one shared energy storage in the same area are selected for case analysis. The system parameters of the example are shown in Table 1. The wind and solar output, total load and non-adjustable load of each industrial user are shown in Table 1. Figure 2 , Figure 3 As shown in Table 2, the time-of-use electricity price on the grid side within a day.

[0124] Table 1 Basic parameters

[0125]

[0126] Table 2 Time-of-use electricity price on the grid side

[0127]

[0128] Analysis of energy storage configuration results: Figure 4 As shown in the figure, when all users participate in demand response and use shared energy storage, the social welfare reaches 41,297.71 yuan per day, and the final optimized capacity is 3,400 kWh.

[0129] 5.2.2 Quasi-linear demand response strategy

[0130] The microgrid operator publishes the load standard line based on the adjustable load information and the predicted output of new energy. After receiving the load standard line, the user will actively adjust the power consumption mode, strive to improve the similarity index with the load standard line, so as to obtain more incentive benefits. The standard line demand response proposed by the present invention is compared with the baseline type.

[0131] like Figure 5 The first column of curves is a comparison of the load curves before and after each user participates in the quasi-linear (CDL) demand response after the microgrid system in the region announces the load quasi-linear; the second column of curves is a comparison of the curves before and after the user participates in the baseline (CBL) demand response according to his own elastic load coefficient; the third column of curves is a comparison of the load curve shape after each user participates in the two demand responses and is normalized with the load quasi-linear announced by the microgrid system. It can be seen that the quasi-linear demand response proposed in the present invention has caused a significant change in the user load. Compared with the baseline demand response, the quasi-linear demand response achieves better tracking of the load quasi-linear, and the load shaping effect is more obvious.

[0132] Based on the quasi-linear demand response proposed by the present invention, the changes in user loads are analyzed: the load power adjusted by user 1 and user 3 is relatively high, and that of user 2 is relatively low. According to the analysis of the adjustable load reporting of each user in the original data of the example, user 3 reports the most adjustable load, followed by user 1, and user 2 reports the least, which is also consistent with Figure 4 The load adjustment of each user after participating in demand response is consistent.

[0133] 5.2.3 Shared energy storage participates in user shaping capacity adjustment

[0134] In order to improve the energy efficiency of users in the entire regional microgrid system, this section introduces the process of shared energy storage participating in the user load shaping capacity adjustment. After the shared energy storage participated in the adjustment, the three users in the regional microgrid system changed their electricity usage habits by increasing the energy storage charging and discharging behavior, thereby shaping their own load curves. The similarity between user 1 and user 3 changed from less than 70% to 74.96% and 70.69%, respectively. Figure 6 .

[0135] As shown in Table 3, after the introduction of shared energy storage to participate in the demand response of industrial users, the similarity of the load curves of the three users all reached above the threshold and obtained incentive benefits. According to the data comparison before and after the shared energy storage participated in the load shaping capacity adjustment of users, the electricity purchase cost and power abandonment cost of each user decreased after using shared energy storage. Among them, the net expenditure of user 1 decreased by 10,949.42 yuan, the net expenditure of user 2 decreased by 503.51 yuan, and the net expenditure of user 3 decreased by 8,933.77 yuan.

[0136] Table 3 Comparison of expenditures of shared energy storage participating in user demand response

[0137]

[0138]

[0139] Figure 7 The figure shows the daily charging and discharging of shared energy storage when participating in the user shaping capacity adjustment. It can be seen from the figure that user 1 has a greater demand for charging and discharging during the 12:00-17:00 and 18:00-20:00 periods, user 2 has a greater demand for discharging during the 10:00-12:00 period, and user 3 has a smaller demand for charging and discharging during the entire period. This is related to the fact that the photovoltaic power generation equipment equipped by user 1 generates excess power during the noon and afternoon periods, and the wind power generation equipment equipped by user 2 cannot meet its load demand during the morning period.

[0140] Figure 8 The adjustable load reported by each user to the regional power grid system before and after using shared energy storage. From the comparison of the three sub-graphs, it can be seen that user 1 has the largest increase in adjustable load under the shared energy storage participating in the shaping capacity adjustment, followed by user 3, and user 2 has the smallest increase. This is because the load curve similarity of user 1 before the shared energy storage participates in the shaping capacity adjustment is the lowest among the three, and the gap from the threshold is the largest, so user 1 needs to report more adjustable loads and use shared energy storage to assist in adjusting its shaping capacity, while user 2 has the least use of shared energy storage. Since the load curve similarity of user 3 before the shared energy storage participates in the shaping capacity adjustment is very small from the threshold, it only needs to report a small amount of adjustable load and use shared energy storage to assist in adjusting its shaping capacity to achieve the purpose of obtaining incentive benefits.

[0141] Analysis of revenue distribution results: As shown in Table 4, based on the core logic of the VCG profit distribution mechanism, it can be calculated that user 1 has the greatest contribution to this microgrid system and the highest revenue after using energy storage services for demand response. Therefore, user 1 also pays the most, accounting for 98.75% of the expenditure at the user level. This allocation plan also redistributes the initial revenue by introducing a redistribution factor to shorten the investment payback period. The final calculated investment payback period for shared energy storage is about 5.32 years.

[0142] Table 4. Results of shared energy storage and user payment allocation

[0143]

[0144] Price factors: Considering the price factors as uncertain factors, the sensitivity of the benchmark incentive unit price, the power abandonment penalty unit price and the energy storage operation and maintenance cost to the configuration results of the shared energy storage capacity is analyzed. Taking the price parameters in Table 3 as the benchmark, the configuration scheme of shared energy storage is explored when the above prices change from -0.4% to 0.4%. The results are shown in Fig. 9 .

[0145] according to Fig. 9 , it can be observed that among the three uncertain factors, the power abandonment penalty unit price and energy storage operation and maintenance costs have a more significant impact on the final operating cost of shared energy storage. In addition, since shared energy storage power stations serve different users, the fluctuations in the benchmark incentive unit price, power abandonment penalty unit price, and energy storage operation and maintenance costs may have different degrees of impact on the scale of shared energy storage configuration. Therefore, from the perspective of the optimal configuration size of shared energy storage power stations, more attention should be paid to the impact of the power abandonment penalty unit price and energy storage operation and maintenance costs on its configuration results, and less attention should be paid to the benchmark incentive unit price.

[0146] A sensitivity analysis is conducted on the size of the shared energy storage capacity configuration based on the different proportions of user loads participating in quasi-linear demand response. The specific analysis scenario is: in the three cases where the regional microgrid system only contains user 1 and user 2, only contains user 1 and user 3, and only contains user 2 and user 3, the corresponding shared energy storage final configuration results or changes in social welfare are compared.

[0147] like Fig.10 As shown, the following results are obtained:

[0148] (1) When all users participate in demand response and use shared energy storage, the social welfare reaches 41,297.71 yuan per day, and the final optimized capacity is 3,400 kWh;

[0149] (2) The social welfare of the new system without user 2 is inferior to the first case, and the optimal capacity is 3200 kWh;

[0150] (3) The social welfare of the new system without user 3 is inferior to the second case, and the optimal capacity is 2000 kWh;

[0151] (4) The social welfare of the new system without user 1 is inferior to the third case, and the optimal capacity is 200 kWh. It can be seen that for user 1, who is equipped with photovoltaic power generation equipment and has the most obvious load shaping before and after participating in quasi-linear demand response, it has a greater contribution to the improvement of social welfare and has a more significant impact on the size of shared energy storage configuration. 5.3.3 Allocation scheme factors

[0152] The profit distribution scheme based on Shapley value is compared with the profit distribution scheme based on VCG proposed in the present invention, and the length of the payback period of the corresponding shared energy storage configuration is analyzed.

[0153] according to Fig.11 As shown, it is easy to see that:

[0154] (1) Compared with the VCG phase 1 solution, the Shapley value-based solution only highlights the marginal contribution of user 1, causing user 1 to spend relatively more on shared energy storage under this benefit distribution scheme. Under this scheme, the payback period of shared energy storage is 7.97 years.

[0155] (2) The benefit distribution plan of the VCG I phase did not take into account the initial investment cost of shared energy storage, but only reorganized the income and expenditure of each user entity in the microgrid system. Under this plan, the payback period of shared energy storage is 7.98 years;

[0156] The profit distribution plan for the VCG II phase takes the initial investment cost of shared energy storage into account. User 1 has the highest contribution and should bear more payment costs. Under this plan, the payback period of shared energy storage is 5.32 years.

[0157] This paper proposes a shared energy storage configuration method that considers the quasi-linear demand response on the user side. The two operation processes of the centralized shared energy storage system and cost sharing are analyzed, and the following conclusions can be drawn:

[0158] 1) Based on the concept of load quasi-line, a quasi-line demand response strategy is given, and a quasi-line formation model and incentive subsidy strategy based on performance incentive mechanism are proposed, so that energy storage system users can jointly discover value and maximize benefits. Compared with baseline demand response, quasi-line demand response achieves better load tracking and has a more obvious load shaping effect.

[0159] 2) In order to motivate users to participate in quasi-linear demand response, a performance-based incentive mechanism is adopted to provide income subsidies. With the participation of shared energy storage, the user similarity based on quasi-linear demand response increased by 8.59% and 0.99% respectively, effectively improving the system's ability to absorb new energy.

[0160] 3) A VCG-based market clearing mechanism is proposed to meet the incentive requirements of individual rationality, incentive compatibility and social welfare maximization in market clearing, and shorten the payback period of the shared energy storage system by 33.33%. User 1's net expenditure is reduced by 143%, user 2's net expenditure is reduced by 35%, and user 3's net expenditure is reduced by 304%.

Claims

1. A method for optimizing the configuration of shared energy storage based on quasi-linear load demand response, characterized in that: The method includes constructing a user-side shared energy storage operation mode; in this mode, the user meets the power demand through the equipped wind and solar power generation, purchases electricity from the shared energy storage and purchases electricity from the power grid; and realizes power consumption by consuming the load by itself and selling the surplus electricity to the shared energy storage; the shared energy storage refers to charging, purchasing electricity from the power grid and purchasing surplus wind and solar power generation from users; Discharging electricity and selling electricity to users to provide electricity services; The method includes the following steps for optimizing the configuration of shared energy storage: (1) Based on the tracking accuracy of the actual load curve and the load criterion, participants with outstanding performance will be given a tiered reward system, specifically: Let the base incentive price be p m , the benefit of user i after participating in quasi-linear demand response is defined as: I CDL,i =p m ·P D ·ε i Among them, P D is the total adjustable power declared by the user the day before, ε i It is a similarity index, which is used to describe the similarity between the actual load form of the user and the regulation target; (2) A shared energy storage configuration model based on maximizing social welfare is constructed. The shared energy storage configuration takes into account the economic efficiency of both investment and operation, which are composed of the user's benefits and the cost of shared energy storage, respectively. The overall objective function is to maximize social welfare, which can be expressed as: W all =max(I user -C ses ) In the formula, user benefit I user and the shared energy storage cost C ess The maximization of the difference corresponds to social welfare W all Optimal; (3) Establish a VCG-based resource allocation mechanism to encourage shared energy storage investors to report their true operation and maintenance costs during operation, and at the same time encourage users of energy storage charging and discharging services to report their energy consumption truthfully. This mechanism includes the following two stages: (3.1) Phase I: The value of market members is reflected in the substitution benefits for other members and the contribution to the overall benefits of the power system. The value of shared energy storage is reflected in the change in the total social welfare of the market before and after participating in the market. The value of a user's load is also measured by the change in the total social welfare of the market before and after participating in the market. make For the social welfare of all members when they participate in the system market, Excluding the social welfare of the new market for shared energy storage systems, the payment for shared energy storage is expressed as: make The social welfare of the new system market without user load i is: (3.2) Phase II: Considering the operating costs and income of shared energy storage and users to calculate the initial benefits, and calculate the initial investment cost of the shared energy storage power station, introduce the benefit redistribution factor to redistribute the initial cost, and thus obtain the final benefits of users and shared energy storage, which is expressed as follows: In the formula, To share the benefits of energy storage systems; Payment for user i; β is the income redistribution factor.

2. The shared energy storage optimization configuration method based on load quasi-linear demand response according to claim 1 is characterized in that: The similarity ε used in step (1) to describe the actual load form of the user and the regulation target i The calculation is as follows: Where: d i It is used to describe the Euclidean distance between the actual load line and the load standard line; ε0 is the similarity standard value for determining whether or not to obtain demand response rewards; represents the actual load form of user i's flexible load, represents the non-adjustable load of user i in period t, P D i is the total adjustable power declared by the i-th user the day before; is the normalized load line shape, and the specific calculation is as follows: in is the total load at time t; in addition, the load criterion has the following constraints: In the formula, For the amount of electricity purchased, is the actual output of new energy in period t, is the predicted value of wind and solar power generation in the system during period t, The maximum amount of electricity purchased.

3. The shared energy storage optimization configuration method based on load quasi-linear demand response according to claim 1 or 2 is characterized in that: Considering the similarity ε defined i is a piecewise function. If the similarity does not reach the set threshold, the final problem will be transformed into a linear programming problem. Once the similarity reaches or exceeds the threshold, the variable C needs to be introduced for calculation: The d in the formula is converted into the form of the second norm, and the new variable C is used to replace the corresponding item of the objective function in the benefit of user i after participating in the quasi-linear demand response. The above formula is converted into an inequality form and added as a constraint condition, thereby obtaining a new expression of the optimization problem: I CDL,i =p m P D -C 4. The shared energy storage optimization configuration method based on load quasi-linear demand response according to claim 1 or 2, characterized in that: Step (2) includes constructing a user benefit model and a shared energy storage cost model, as follows: (2.1) User benefit model, whose objective function is: The total user benefit is composed of the demand response benefit of each user, the reduced penalty cost of power abandonment, the reduced cost of purchasing electricity from the grid, and the benefit of selling abandoned electricity to shared energy storage. ab1 Penalty fees for power abandonment, and They represent the amount of power abandoned by the i-th user without energy storage and with energy storage in period t respectively; and P g t ,i They represent the amount of electricity purchased by the i-th user without energy storage and with energy storage in period t respectively; ab2 The price of electricity sold for abandoned power, is the amount of abandoned electricity sold by the i-th user in period t; In terms of user collaborative operation, it is possible to avoid simultaneous power abandonment and power purchase from the grid, power balance, new energy power usage range, charging and discharging power range, avoid simultaneous charging and discharging, and only purchase power from the grid. The constraints are as follows: Where: and are the load and the output of renewable energy of the i-th user in period t respectively; and The status bits representing the user's power abandonment and power purchase are Boolean variables. If the demand is greater than the supply, the user needs to purchase electricity, otherwise the user abandons electricity. and They represent the charging and discharging amount of the i-th user in period t respectively; The upper limit of the renewable energy output of the i-th user in period t; is the maximum charging and discharging power of the i-th user; and The status bits representing user charging and discharging are 0-1 variables respectively; (2.2) Shared energy storage cost model, whose objective function is: The total cost of shared energy storage consists of the cost of purchasing abandoned electricity from users, the cost of purchasing electricity from the grid, and the operation and maintenance costs. N is the amount of electricity purchased from the grid by the shared energy storage during period t; om The daily operation and maintenance rate for shared energy storage; and They represent the charging and discharging amounts of the shared energy storage in period t respectively; During the coordinated operation of users and shared energy storage power stations, the general constraints that need to be ensured are as follows: In the formula, It represents the total charging amount including the charging from the user side by the shared energy storage and the electricity purchased from the grid; is the maximum charging and discharging power of the shared energy storage; and Respectively represent the status bits of shared energy storage charging and discharging; is the capacity state of the shared energy storage in period t; η is the charging and discharging efficiency of the shared energy storage; and They respectively represent the upper and lower limits of the shared energy storage capacity.

5. A shared energy storage optimization configuration method system based on load quasi-linear demand response, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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