Multi-scene energy storage value evaluation method and device, equipment and storage medium

Abstract

The invention relates to the technical field of novel energy storage, and discloses a multi-scene energy storage value evaluation method, device and equipment and a storage medium, and the method comprises the steps: determining a to-be-evaluated target scene, and constructing a multi-scene energy storage value evaluation system; different target scenes in the multi-scene energy storage value evaluation system correspond to different evaluation indexes; the types of the evaluation indexes comprise direct earnings and indirect earnings; obtaining the direct income of the energy storage power station in the target scene and the indirect income of the energy storage power station in other scenes except the target scene; and obtaining the energy storage value corresponding to the target scene based on the weight coefficient corresponding to the target scene, the direct income and the indirect income of each other scene. According to the scheme, automatic value evaluation of multi-scene energy storage is realized, and the values of multiple scenes are considered at the same time; and the efficiency and accuracy of value evaluation of multi-scene energy storage are improved.

Description

Technical Field

[0001] The present invention relates to the field of novel energy storage technologies, and in particular to a multi-scenario energy storage value assessment method, device, equipment and storage medium. Background Art

[0002] As the world pays more and more attention to clean energy and sustainable development, new power systems are gradually replacing traditional energy supply models. In this transformation process, energy storage technology, as one of the core supporting technologies, plays a vital role.

[0003] With the transformation of the global energy structure and the rapid development of renewable energy, new power systems are gradually replacing traditional energy supply models. In this transformation, energy storage technology plays a vital role in the new power system with its unique advantages. Energy storage plays multiple roles in the power system, including stabilizing grid operation, shaving peak loads and filling valleys, and improving system safety. Adding energy storage to the power system generally does not cause a reduction in the value of the original system, so the system value can be evaluated by the superposition of multiple application values, but the evaluation of its value requires artificial consideration of multiple factors, the evaluation is difficult, and the evaluation process is very complicated.

[0004] Therefore, in the power system, there is an urgent need for a value assessment method to determine the power system after adding energy storage. Summary of the invention

[0005] In view of this, the present invention provides a multi-scenario energy storage value assessment method, device, equipment and storage medium, which can improve the value assessment efficiency and accuracy of the power system after adding energy storage.

[0006] In a first aspect, the present invention provides a multi-scenario energy storage value assessment method, the method comprising:

[0007] Construct a multi-scenario energy storage value evaluation system and determine the target scenario to be evaluated; the target scenario includes independent energy storage, thermal power side, photovoltaic / wind power side, user side and grid side; the energy storage on different sides in the multi-scenario energy storage value evaluation system has different evaluation indicators; the types of evaluation indicators include direct benefits and indirect benefits;

[0008] Obtain the evaluation indicators of the energy storage power station on each side of the target scenario;

[0009] Based on the weight coefficients corresponding to the various evaluation indicators, the direct benefits, and the indirect benefits, the energy storage value corresponding to the target scenario is obtained.

[0010] In a possible implementation, before obtaining the energy storage value corresponding to the target scenario based on the weight coefficients corresponding to the evaluation indicators, the direct benefits, and the indirect benefits, the method further includes:

[0011] Constructing a judgment matrix according to the direct benefits and the indirect benefits;

[0012] The entropy weight of each evaluation index is calculated, and the weight coefficient of each evaluation index is generated by the least square method.

[0013] In a possible implementation, the method further includes:

[0014] The maximum value and the minimum value of each evaluation index are used as the positive ideal solution and the negative ideal solution, and the grey correlation degree corresponding to the target scene is calculated; the grey correlation degree includes a positive correlation coefficient and a negative correlation coefficient;

[0015] Calculating the positive Euclidean distance and the negative Euclidean distance between each evaluation index and the positive ideal solution and the negative ideal solution;

[0016] Determine the relative closeness of the grey relational analysis according to the positive relational coefficient and the negative relational coefficient;

[0017] Determining the relative closeness of the Euclidean distance according to the positive Euclidean distance and the negative Euclidean distance;

[0018] The comprehensive value of the energy storage solution for the target scenario is calculated based on the closeness of the Euclidean distance and the closeness of the grey relational analysis.

[0019] In a possible implementation, for independent energy storage in a target scenario, obtaining evaluation indicators of the energy storage power station on each side of the target scenario includes:

[0020] Determine the peak and valley benefits of energy storage based on the real-time peak and valley time-of-use electricity prices of the power grid and the efficiency of the energy storage system;

[0021] Determine the emergency power support benefit based on the emergency power support times, wherein the emergency power support times are the times of stable load shedding by the energy storage power station within a specified time;

[0022] Determine the frequency regulation capacity compensation income based on the allocated capacity;

[0023] Obtaining backup service income; the backup service income is the benefit value obtained by assisting other scenarios when the energy storage power station is in a backup state;

[0024] Based on the energy storage peak-valley income, the emergency power support income, the deployment capacity compensation income and the backup service income, the direct income of the independent energy storage power station is obtained.

[0025] In a possible implementation, for the thermal power side in the target scenario, obtaining the evaluation index of the energy storage power station on each side of the target scenario includes:

[0026] Determine the frequency regulation capacity compensation income based on the allocated capacity;

[0027] Based on the speed of the thermal power unit, the difference in coal consumption before and after the energy storage power station participates in the deployment is calculated, and the total coal consumption reduction benefit is obtained through the difference in coal consumption;

[0028] Based on the compensation income for the deployment capacity and the income from the reduction in total coal consumption, direct income of the energy storage power station under the energy storage on the thermal power side is obtained.

[0029] In a possible implementation, for the photovoltaic / wind power side in the target scenario, the evaluation index of the energy storage power station on each side of the target scenario is obtained, including:

[0030] Obtaining a target off-grid capacity; the target off-grid capacity is used to indicate the number of times the total off-grid capacity of the photovoltaic / wind turbine generator set exceeds a specified proportion of the installed capacity;

[0031] Determining the benefit of reducing off-line traffic based on the target off-line traffic volume;

[0032] Based on the real-time active power of the photovoltaic / wind power station after energy storage configuration, the time-limited period scheduling plan processing and the time-limited period, determine the benefits of reducing the light / wind limit period;

[0033] Obtain the grid-connected electricity revenue based on the increased annual grid-connected electricity revenue and the number of days per month when wind power / PV output cannot meet the dispatch plan power;

[0034] Based on the reduction of off-grid benefits, the reduction of limited light / wind time benefits, and the acquisition of grid-connected electricity benefits, direct benefits of the energy storage power station under the photovoltaic / wind power side energy storage are generated.

[0035] In a possible implementation, for the power grid side in the target scenario, obtaining the evaluation index of the energy storage power station on each side of the target scenario includes:

[0036] Obtain the power change of the system at each moment, the active power of the section after the energy storage charging and discharging power, the load demand in the section, the power output, the energy storage charging and discharging power, the network loss and the line flow limit value;

[0037] Obtaining system congestion cost based on the power change, section active power after energy storage charging and discharging power, load demand in section, power supply output, energy storage charging and discharging power, network loss and line flow limit value;

[0038] When obtaining grid-side energy storage, the grid loss amount and grid loss rate reduced by the grid system, and obtaining grid loss reduction benefits based on the grid loss amount and grid loss rate;

[0039] Based on the system congestion cost and the benefits of reducing network losses, the direct benefits of the energy storage power station in the target scenario are obtained.

[0040] In a possible implementation, for the user side in the target scenario, obtaining the evaluation index of the energy storage power station on each side of the target scenario includes:

[0041] Determine the first planned capacity of the transformer when there is no energy storage, the second planned capacity of the transformer when there is energy storage, and the maximum calculated load of the user when the energy storage is erroneous;

[0042] Determine the capacity of a dedicated transformer based on the first planned capacity, the second planned capacity, and the maximum calculated load of the user;

[0043] Based on the dedicated transformer capacity, the transformer capacity benefits are reduced;

[0044] Determine the peak and valley benefits of energy storage based on the real-time peak and valley time-of-use electricity prices of the power grid and the efficiency of the energy storage system;

[0045] Based on the transformer capacity benefit and the energy storage peak-valley benefit, the direct benefit of the energy storage power station for user-side energy storage is obtained.

[0046] In a third aspect, the present invention provides a computer device, which includes a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the above-mentioned multi-scenario energy storage value assessment method by executing the computer instructions.

[0047] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the above-mentioned multi-scenario energy storage value assessment method.

[0048] In a fifth aspect, the present invention provides a computer program product, including computer instructions, which are used to enable a computer to execute the above-mentioned multi-scenario energy storage value assessment method.

[0049] The technical solution provided by this application may have the following beneficial effects:

[0050] When a power system is deployed with an energy storage power station, a multi-scenario energy storage value assessment system can be first constructed, and the target scenario in which the energy storage power station is deployed can be obtained, and the various evaluation indicators of the energy storage power station in the target scenario in terms of independent energy storage, thermal power side, photovoltaic / wind power side, user side, and grid side can be determined. Finally, the energy storage value of the target scenario can be determined by calculating the weight coefficients of different evaluation indicators, as well as the direct and indirect benefits in the evaluation indicators. The above scheme constructs a multi-scenario energy storage value assessment system, taking into account that energy storage power stations have different evaluation indicators in different scenarios, and assigning different weights to different evaluation indicators, and obtaining the final energy storage value by weighting, providing an automated value assessment method for multi-scenario energy storage, while taking into account the value of multiple scenarios, and improving the efficiency and accuracy of the value assessment of multi-scenario energy storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 It is a structural diagram of a comprehensive power value evaluation system according to an exemplary embodiment.

[0053] Figure 2 It is a method flow chart of a multi-scenario energy storage value assessment method according to an exemplary embodiment.

[0054] Figure 3 It is a method flow chart of another multi-scenario energy storage value assessment method according to an exemplary embodiment.

[0055] Figure 4 A flowchart for implementing comprehensive value evaluation of energy storage involved in an embodiment of the present application is shown.

[0056] Figure 5 It is a structural schematic diagram of a multi-scenario energy storage value assessment device provided in an embodiment of the present application.

[0057] Figure 6 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0059] In the description of the embodiments of the present application, the term "corresponding" may indicate a direct or indirect correspondence between two items, or an association relationship between the two items, or a relationship between indication and being indicated, configuration and being configured, and the like.

[0060] Figure 1 FIG. 1 is a schematic diagram showing a structure of a comprehensive power value evaluation system according to an exemplary embodiment. Figure 1 As shown, the engineering design system includes a target terminal 101 and a target server 102 .

[0061] Optionally, the target terminal may be a computer device with high-performance processing capabilities, such as a PC (personal computer), a mobile terminal, or a tablet computer.

[0062] The target terminal can be installed with power comprehensive value evaluation software, which can obtain the distribution and specific parameters of each unit of the target power system. For example, the target power system includes the thermal power side, wind power / photovoltaic side, grid side, and user side. At this time, the power comprehensive value evaluation software saves the distribution of each side (such as the number of generator sets) and related parameters of each side (such as the power generation power, efficiency, loss, etc. of the generator sets).

[0063] Optionally, the power comprehensive value evaluation software can also obtain the actual working status of the target power system in the historical time period from the target server 102. The target server can be a server corresponding to the target power system, and there are corresponding control devices on each side of the target power system. The control device can record the data of the working status of this side and upload it to the target server for storage.

[0064] Optionally, the above-mentioned server can be a server cluster or a distributed system composed of multiple physical servers, or it can be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, as well as big data and artificial intelligence platforms and other technical computing services.

[0065] Optionally, the system may further include a management device, which is used to manage the system (such as managing the connection status between each module and the server, etc.), and the management device is connected to the server via a communication network. Optionally, the communication network is a wired network or a wireless network.

[0066] Optionally, the above-mentioned wireless network or wired network uses standard communication technology and / or protocol. The network is usually the Internet, but it can also be any other network, including but not limited to any combination of local area network, metropolitan area network, wide area network, mobile, limited or wireless network, private network or virtual private network. In some embodiments, the technology and / or format including hypertext markup language, extensible markup language, etc. are used to represent the data exchanged through the network. In addition, conventional encryption technologies such as secure socket layer, transport layer security, virtual private network, Internet protocol security, etc. can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technology can also be used to replace or supplement the above-mentioned data communication technology.

[0067] Since the system value of energy storage refers to the sum of the values ​​realized by energy storage in the various links of power system generation / transmission / transformation / distribution / use, that is, the quantifiable direct value and indirect value that can be realized by installed energy storage under the current electricity price and relevant policies on power auxiliary services, the direct value of energy storage refers to the value realized by energy storage participating in specific applications, and the indirect value refers to the additional value generated on the basis of realizing the direct value.

[0068] The judgment from the perspective of the whole society is a general evaluation standard, but it is not the only standard to determine whether to build an energy storage power station. In a special development stage, the evaluation indicators of other stakeholders should be given more attention. For example, when the installed capacity of electricity is insufficient, the economic evaluation weight of traditional power generation enterprises and renewable energy power generation units should be increased; when energy consumption is too high and the primary energy for power generation is insufficient, the evaluation weight of fuel consumption should be increased; when the resources of power transmission and distribution related equipment are tight, the weight of delaying the upgrade of the power system in the evaluation indicators of power grid companies should be increased. Therefore, it is necessary to propose an evaluation criterion that comprehensively weighs the gains and losses of different stakeholders and makes decisions on the construction and operation of specific energy storage power station projects.

[0069] In order to solve the above problems, the present application provides a multi-scenario energy storage value assessment method. Figure 2 is a method flow chart of a multi-scenario energy storage value assessment method according to an exemplary embodiment. The method is executed by a computer device, which may be as follows Figure 1 The target terminal 110 in the multi-scenario energy storage value assessment system is shown. Figure 2 As shown, the multi-scenario energy storage value assessment method may include the following steps:

[0070] Step 201, construct a multi-scenario energy storage value assessment system and determine the target scenario to be assessed.

[0071] In the embodiment of the present application, the target scenario includes independent energy storage, thermal power side, photovoltaic / wind power side, user side and grid side; the energy storage on different sides in the multi-scenario energy storage value assessment system has different evaluation indicators; the types of evaluation indicators include direct benefits and indirect benefits.

[0072] Step 202: Obtain evaluation indicators of the energy storage power station on each side of the target scenario.

[0073] Specifically, the direct benefits of the energy storage power station on each side of the target scenario and the indirect benefits on each side of the target scenario are obtained.

[0074] When an energy storage power station is set up in the power system, it can directly generate value in the target scenario (such as the thermal power side). However, since there is a certain connection between the various sides in the power system, setting up an energy storage power station on one side will also reduce the losses on other sides, thereby having certain indirect benefits.

[0075] Step 203, based on the weight coefficients corresponding to the various evaluation indicators, the direct benefits and the indirect benefits, the energy storage value corresponding to the target scenario is obtained.

[0076] In summary, when a power system is deployed with an energy storage power station, a multi-scenario energy storage value assessment system can be first constructed, and the target scenario in which the energy storage power station is deployed can be obtained, and the various evaluation indicators of the energy storage power station in the target scenario in terms of independent energy storage, thermal power side, photovoltaic / wind power side, user side, and grid side can be determined. Finally, the energy storage value of the target scenario can be determined by calculating the weight coefficients of different evaluation indicators, as well as the direct and indirect benefits in the evaluation indicators. The above scheme constructs a multi-scenario energy storage value assessment system, taking into account that energy storage power stations have different evaluation indicators in different scenarios, and assigning different weights to different evaluation indicators, and obtaining the final energy storage value by weighting, providing an automated value assessment method for multi-scenario energy storage, while taking into account the value of multiple scenarios, and improving the efficiency and accuracy of the value assessment of multi-scenario energy storage.

[0077] Specifically, based on the embodiment shown in 2, the embodiment of the present application provides another multi-scenario energy storage value assessment method. Figure 3 is a method flow chart of another multi-scenario energy storage value assessment method according to an exemplary embodiment. The method is executed by a computer device, which may be as follows Figure 1 The target terminal 110 in the multi-scenario energy storage value assessment system is shown. Figure 3As shown, the multi-scenario energy storage value assessment method may include the following steps:

[0078] Step 301, construct a multi-scenario energy storage value evaluation system and determine the target scenario to be evaluated.

[0079] In the embodiment of the present application, the target scenario has independent energy storage, thermal power side, photovoltaic / wind power side, user side and grid side.

[0080] Step 302: Obtain evaluation indicators of the energy storage power station on each side of the target scenario.

[0081] The types of evaluation indicators include direct benefits and indirect benefits.

[0082] Specifically, when the target scenario is independent energy storage, direct benefits can be obtained in the following ways:

[0083] Determine the peak and valley benefits of energy storage based on the real-time peak and valley time-of-use electricity prices of the power grid and the efficiency of the energy storage system;

[0084] Determine the emergency power support benefit based on the emergency power support times, wherein the emergency power support times are the times of stable load shedding by the energy storage power station within a specified time;

[0085] Determine the frequency regulation capacity compensation income based on the allocated capacity;

[0086] Obtaining backup service income; the backup service income is the benefit value obtained by assisting other scenarios when the energy storage power station is in a backup state;

[0087] Based on the energy storage peak-valley income, the emergency power support income, the deployment capacity compensation income and the backup service income, the direct income of the independent energy storage power station is obtained.

[0088] In the embodiment of the present application, independent energy storage refers to a new type of energy storage power station that is invested and constructed by social capital, directly connected to the public power grid, directly signs a grid connection dispatching agreement with the power dispatching agency as an independent market entity, accepts unified dispatching by the power dispatching agency, and serves the operation of the power system.

[0089] Including electrochemistry, compressed air, flywheel, gravity, supercapacitor, etc. Independent energy storage power stations can obtain income by participating in the electricity spot market and the electricity auxiliary service market. The charging and discharging electricity prices and auxiliary service fees are implemented in accordance with relevant market prices and rules. Among the independent energy storage power stations on the grid side, the independent energy storage power stations that improve the system regulation capability are mainly deployed in areas where the grid regulation capability is weak and new energy is difficult to absorb due to transmission obstruction; the independent energy storage power stations that guarantee peak power demand are mainly deployed in areas where the power demand of load centers is growing rapidly and the power supply capacity is insufficient at peak times.

[0090] At this time, the values ​​generated for the energy storage side itself, the power generation side, the grid side, the user side and the social side are shown in Table 1.

[0091]

[0092] Table 1. Comprehensive value assessment index system for third-party entities investing in energy storage

[0093] First, the direct benefits (that is, direct value) of independent energy storage can be calculated. The direct benefits include:

[0094] 1) Peak-valley arbitrage (i.e. the peak-valley income of energy storage mentioned above)

[0095] The calculation formula for energy storage peak-valley arbitrage profit is:

[0096] R e =(η dis P t dis -P t cha )q e Δt (3-1)

[0097] In the formula, R e To obtain arbitrage benefits for energy storage according to the peak and valley of the power grid, q e is the real-time peak-valley time-of-use electricity price of the power grid, P t cha Charging power for energy storage system, P t dis is the discharge power of the energy storage system, η dis is the discharge efficiency of the energy storage system, and Δt is the time interval.

[0098] 2) Direct income from emergency power support (i.e. the above-mentioned emergency power support income)

[0099] DC blocking will lead to active power imbalance, and the UHV AC / DC system will take stabilization measures. During this period, the receiving-end power grid has a power shortage and a continuous low-voltage state. The load pressure at the receiving end is reduced by shedding the load, and the receiving-end voltage is raised. At the same time, the power shortage causes the receiving-end power grid frequency to decrease, the rotor of the generator set accelerates, and the rotational inertia power is provided. The power shortage and frequency changes of the system are shown in formula (3-2). It can be seen from formula (3-2) that the frequency deviation of the system at a certain moment is linearly related to the power shortage. Changing the system power shortage can change the system frequency deviation.

[0100]

[0101] In the formula, ΔP t is the power shortage of the system at time t; ΔP loss P is the active power lost by the system due to DC blocking when the distributed energy storage system is not put into use;Mj is the moment of inertia power of the jth generator set when the distributed energy storage system is not put into use; c is the number of generator sets connected to the grid; P Lj is the power of the jth load that can be cut after DC blocking; m is the number of loads that can be cut; Δf t / f is the frequency deviation of the system at time t; P is the total active power of the system; ρ is the rotating reserve coefficient of the power grid; K g K is the frequency static characteristic coefficient of the generator set; f is the load frequency static characteristic coefficient.

[0102] If a distributed energy storage system is put into use, after the stabilization measures are implemented, the emergency power support command is issued to the energy storage unit, and the distributed energy storage system is adjusted. The power shortage and frequency changes of the receiving power grid after the distributed energy storage system is put into use are shown in formula (3-3). It can be seen from formula (3-3) that after the distributed energy storage system is put into use, the power shortage of the receiving power grid is reduced, the frequency deviation is reduced, and the frequency stability is improved.

[0103]

[0104] Where: P M'j P is the moment of inertia power of the jth generator set after the distributed energy storage system is put into use; battery,dc,i P is the active power provided by the energy storage system i to increase the UHV DC operating power after DC blocking; battery,i is the backup power of energy storage system i. In the UHV AC / DC hybrid operation system, the dynamic characteristics of the DC transmission line, such as voltage and power, are mainly determined by the strength of the connected AC system. The investment of distributed energy storage system improves the frequency stability of the receiving power grid and enhances the strength of the AC power grid, thereby improving the operating power of the UHV DC line.

[0105] Since grid load shedding and emergency support of energy storage systems can effectively reduce the peak flow of the line, and the load shedding power and energy storage system power support of the same capacity have similar effects, this study provides compensation according to the stable load shedding service fee. The stable load shedding service fee is divided into capacity fee and usage fee. Referring to the "Implementation Rules for the Management of Electric Power Auxiliary Services in the Southern Region", for the stable load shedding service entities that meet the requirements, the stable load shedding capacity fee will be compensated at a rate of 0.1 (10,000 yuan / year / MW) starting from the month after the transmission test is qualified. For power users who are unable to provide stable load shedding auxiliary services due to maintenance and other conditions, the stable load shedding compensation fee for the corresponding period will be deducted. The compensation standard for the stable load shedding usage fee is 1,500 (yuan / MWh) each time.

[0106] 3) Direct income from frequency regulation compensation (i.e., compensation income from capacity allocation)

[0107] Energy storage power stations that provide auxiliary services to third parties temporarily participate in the frequency regulation market in accordance with the standards of conventional units, using the method of "capacity compensation + mileage compensation". The frequency regulation benefits of energy storage power stations are:

[0108] R tp =W C +W M (3-4)

[0109] In the formula, R tp The frequency modulation compensation income; W C is the capacity compensation income; W M Compensate for mileage income.

[0110] Capacity compensation is based on the energy storage frequency regulation capacity quota compensation, and the calculation method is:

[0111] W C =P AGC ×C C (3-5)

[0112] Where: P AGC C is the adjustable capacity of the energy storage automatic generation control AGC (Automatic Generation Control), which is the difference between the upper and lower limits of the adjustable capacity of the energy storage that can be put into AGC operation (MW); C is the frequency regulation capacity compensation price (yuan / MW·month).

[0113] The regulation rate of the AGC command issued to the energy storage device should be the power increase and decrease rate required by the power grid during the period, and the upper and lower limits of the energy storage AGC command regulation are the rated charge and discharge power of the energy storage. At present, the minimum unit of the AGC service frequency regulation mileage price is 0.1 yuan / MW, and the declared price range is temporarily set at 6-15 yuan / MW. The AGC service regulation capacity compensation standard is 60 yuan / MW.

[0114] Mileage compensation is made according to the actual mileage of energy storage through market-based bidding, and is calculated as the product of the frequency regulation market clearing price, frequency regulation mileage and comprehensive frequency regulation performance indicators within a unit billing period.

[0115] W M =M I ×M F ×K×C F (3-6)

[0116] Where M I M is the total plate adjustment coefficient of the frequency modulation market service fee; F is the frequency modulation mileage; K is the comprehensive index of frequency modulation performance; C F Clearing price for the market.

[0117] According to regulations, the total adjustment coefficient of the frequency modulation market service fee is MI The value range is 0 to 2. Referring to the current frequency modulation market in various provinces, my country's market is currently in the initial operation stage. I Temporarily take 1. The frequency regulation comprehensive index K is related to the regulation rate K1, response time K2, and regulation accuracy K3. The regulation rate and regulation accuracy of energy storage are obviously superior to those of traditional units. The response time is not considered to be related to communication transmission lag and control system delay, and the response speed is fast. The calculation formula of the frequency regulation comprehensive index K is:

[0118]

[0119] In the formula, K1, K2, and K3 are the regulation rate, regulation accuracy, and response time indicators in the energy storage regulation process, respectively; K 1max , K 2max , K 3max It is the maximum value of the regulation rate, regulation accuracy and response time indicators of all units; B1, B2 and B3 are the weights of each indicator respectively; A is the comprehensive performance indicator adjustment coefficient. During the simulation operation, A is temporarily set to 3, and B1, B2 and B3 are 1 respectively.

[0120] Because within the rated power range, a mature energy storage system can output the specified power with an accuracy of more than 99% in a very short time, and problems such as adjustment deviation and delay will no longer occur, K1, K2, and K3 all take their maximum values, that is, K is the maximum value 1.

[0121] W M,d =Σk f mPC F (3-8)

[0122] The above formula represents the daily income of energy storage mileage compensation, where k f is the average number of calls per dispatch cycle (15 minutes); m is the average frequency modulation mileage coefficient of each call of energy storage; P is the rated power of energy storage, C F It is the price of energy storage frequency regulation mileage.

[0123] 4) Capacity compensation income

[0124] At present, independent energy storage power stations on the grid side that are included in the demonstration project enjoy capacity compensation. The compensation standard is calculated based on the discharge amount. The upper limit of compensation is temporarily set at 0.35 yuan / kWh, and the compensation period is temporarily considered to be 10 years.

[0125] 5) Backup service income (backup service income)

[0126] When energy storage is in standby mode, it can obtain income by participating in the voltage and frequency regulation of the power grid; or by smoothing fluctuations and improving grid connection capacity in areas rich in new energy and hydropower. The calculation formula is:

[0127]

[0128] In the formula, R fz is the ancillary service market revenue, q sac The power price for energy storage backup compensation, Q sac is the reserve capacity, r is the social discount rate, which is generally 6% to 8%.

[0129] In summary, the direct benefit value R of the energy storage side is ESS The calculation formula is as follows:

[0130] R ESS =R e +R tf +R by +R tp (3-10)

[0131] Furthermore, this independent energy storage can also generate indirect value for other entities:

[0132] 1) Power generation side

[0133] ① Reduce the amount of electricity lost from wind and solar power curtailment

[0134] R qf =ηE r (q B -C M )(3-11)

[0135] In the formula, R qf To reduce the amount of electricity gained from wind and solar power abandonment; η is the ratio of the discharged electricity to the input electricity of the energy storage (including the charging electricity, the electricity required for heating, etc.); E r is the average annual abandoned wind and photovoltaic power of wind-storage and photovoltaic-storage power stations (unit: kWh); B is the benchmark electricity price of thermal power in the area where the energy storage project is located (unit: yuan / kWh). Under the renewable energy subsidy condition, q B is the benchmark electricity price of wind power and photovoltaic power in the area where the energy storage project is located (rewritten as q b );C M The marginal cost of curtailing wind and solar power.

[0136] ② Replacement system installed capacity value

[0137] This part of the income includes the reduction of power transmission and distribution investment by replacing the installed capacity of thermal power units for peak load regulation, rotating reserve, and new energy unit reserve. The calculation formula for replacing the installed capacity of thermal power units with equivalent energy storage is:

[0138] R tf =ηC fd P max (3-12)

[0139] In the formula, R tf is the installed capacity value of the replacement system, C fd is the unit capacity cost of the system unit, P max is the rated power of the energy storage.

[0140] 2) Grid side

[0141] Replacement value of grid investment. Energy storage power stations can provide load support for the grid in a short period of time, reducing the investment in capacity construction due to the grid's time-limited shortcomings. The replacement value measurement can be determined based on the average cost of transformers, substations, transmission lines and other equipment required for grid expansion. The calculation formula is:

[0142] R td =ηC d P max (3-13)

[0143] In the formula, R td To replace the grid investment value, C d is the unit capacity cost of power grid equipment, P max is the rated power of the energy storage.

[0144] (3) User side

[0145] Power supply reliability is difficult to quantify directly, and in practice, power outage loss evaluation methods are often used for indirect estimation. This study uses the user's power outage loss to measure power supply reliability, and the calculation formula is:

[0146] R rel =P re min{P av ,P max}T re (3-14)

[0147] In the formula, R rel To improve the reliability of power supply for energy storage, P re The price of power outage compensation for users, P av P is the average power load that the user may use during the power outage period. max is the rated power of energy storage, T re The power outage time.

[0148] (4) Social aspect

[0149] 1) Coal saving value

[0150] In fact, energy storage can assist thermal power units in peak load regulation, which can reduce the peak load of thermal power units and thus reduce fuel costs. The income from energy storage that reduces the fuel costs of thermal power units is called coal saving value. Its calculation formula is:

[0151]

[0152] In the formula, R jm For coal saving value, P fuel is the unit fuel quantity for power generation, C fuel The unit price of fuel.

[0153] 2) Pollutant emission reduction value

[0154] Energy storage assists the peak load regulation of thermal power units, which can reduce the peak load of thermal power units and thus reduce fuel costs, which is equivalent to an additional income from energy storage. The income from energy storage that is equivalent to reducing the pollution cost of thermal power units is called environmental value. Its calculation formula is:

[0155]

[0156] Where: R pw is the total pollutant emission reduction value brought by the energy storage system; K is the total number of pollutants, α k is the emission density of the kth pollutant, is the unit emission cost of the kth pollutant.

[0157] In a possible implementation of the embodiment of the present application, when the target scenario is photovoltaic / wind power side energy storage, the obtaining of the direct benefit of the energy storage power station in the target scenario includes:

[0158] Obtaining a target off-grid capacity; the target off-grid capacity is used to indicate the number of times the total off-grid capacity of the photovoltaic / wind turbine generator set exceeds a specified proportion of the installed capacity;

[0159] Determining the benefit of reducing off-line traffic based on the target off-line traffic volume;

[0160] Based on the real-time active power of the photovoltaic / wind power station after energy storage configuration, the time-limited period scheduling plan processing and the time-limited period, determine the benefits of reducing the light / wind limit period;

[0161] Obtain the grid-connected electricity revenue based on the increased annual grid-connected electricity revenue and the number of days per month when wind power / PV output cannot meet the dispatch plan power;

[0162] Based on the reduction of off-grid benefits, the reduction of limited light / wind time benefits, and the acquisition of grid-connected electricity benefits, direct benefits of the energy storage power station under the photovoltaic / wind power side energy storage are generated.

[0163] Replacing thermal power generating units with energy storage to participate in frequency regulation services can not only bring direct benefits to power plants, but also increase the flexibility of the power grid, improve power reliability, improve power quality, and reduce carbon emissions. It will generate value in various links such as power plants and power grids, as shown in Table 2.

[0164]

[0165] Table 2. Comprehensive value assessment index system for thermal power side energy storage

[0166] Thermal power side energy storage can include the following direct benefits:

[0167] 1) Frequency regulation income (frequency regulation capacity compensation income)

[0168] The value quantification model of thermal power side energy storage participating in frequency regulation is shown in formulas (3-4) to (3-8). However, unlike independent energy storage, its regulation rate, response time, regulation accuracy, mileage and capacity all undergo significant changes after the thermal power side energy storage is combined.

[0169] 2) Reduction in total coal consumption

[0170] After energy storage assists thermal power units in participating in frequency regulation services, the units respond to automatic power generation control instructions at a rate of 1% of rated power instead of 2% of rated power. The difference in coal consumption before and after energy storage participates in frequency regulation can be calculated based on the rate. The total coal consumption reduction benefit is shown in the following formula.

[0171] R h =Q d ×Δq d × h (3-17)

[0172] In the formula, R h is the total coal consumption reduction benefit, Q d is the total power generation during the regulation period, Δq d is the difference in coal consumption per kilowatt-hour, r h The standard coal price.

[0173] 3) Annual assessment reduces income

[0174] For the combined thermal-storage frequency regulation system, if the unit's availability and regulation performance can meet the standard requirements, the benefits of reduced availability and regulation performance assessments will be obtained. The unit's availability and regulation performance assessments both adopt a quota assessment method, and the annual assessment reduction benefits of the assessed unit are shown in the following formula.

[0175]

[0176] In the formula, K A is the measured unit availability, P N is the unit capacity, μ AGC,A is the availability assessment coefficient (value is 1), K P is the actual measured unit regulation performance, μ AGC,P To adjust the performance assessment coefficient (value is 2), r W For the on-grid electricity price.

[0177] This independent energy storage can also generate indirect value for other entities:

[0178] After the energy storage system is put into use, the frequency becomes more stable, more wind power and photovoltaic power output in the power grid can be absorbed, and pollutant emissions are reduced. The calculation formulas for these two indirect benefits are shown in equations (3-10) and (3-15). However, this part of the indirect benefit is difficult to quantify in actual measurement.

[0179] By investing in energy storage systems, the frequency regulation resources of the power system will become better quality, and the total frequency regulation compensation cost will be reduced. The reduction in cost is the difference in frequency regulation compensation cost before and after the investment in energy storage, and the calculation is as shown below.

[0180]

[0181] In the formula, R C To reduce the cost of overall frequency regulation, D1 is the comprehensive performance index of unit i when energy storage is not put into use. i is the regulation mileage of unit i when energy storage is not put into use, K b For compensation standards, is the comprehensive performance index of unit i when energy storage is put into use, is the regulation mileage of unit i when energy storage is put into use.

[0182] In a possible implementation of the embodiment of the present application, when the target scenario is photovoltaic / wind power side energy storage, the obtaining of the direct benefit of the energy storage power station in the target scenario includes:

[0183] Obtaining a target off-grid capacity; the target off-grid capacity is used to indicate the number of times the total off-grid capacity of the photovoltaic / wind turbine generator set exceeds a specified proportion of the installed capacity;

[0184] Determining the benefit of reducing off-line traffic based on the target off-line traffic volume;

[0185] Based on the real-time active power of the photovoltaic / wind power station after energy storage configuration, the time-limited period scheduling plan processing and the time-limited period, determine the benefits of reducing the light / wind limit period;

[0186] Obtain the grid-connected electricity revenue based on the increased annual grid-connected electricity revenue and the number of days per month when wind power / PV output cannot meet the dispatch plan power;

[0187] Based on the reduction of off-grid benefits, the reduction of limited light / wind time benefits, and the acquisition of grid-connected electricity benefits, direct benefits of the energy storage power station under the photovoltaic / wind power side energy storage are generated.

[0188] Specifically, the benefits currently obtained from the configuration of energy storage systems in new energy stations mainly include reduced assessment costs and increased power generation benefits.

[0189]

[0190] Table 3. Comprehensive value assessment index system for energy storage on the new energy side

[0191] Solar / wind power side energy storage can include the following direct benefits:

[0192] 1) Reduce the offline assessment benefits (i.e. the above-mentioned reduction in offline benefits)

[0193] According to the detailed regulations, when a photovoltaic power station causes a large area of ​​photovoltaic power generation units to be disconnected from the grid due to its own reasons, and the total capacity of photovoltaic power generation units disconnected from the grid at one time exceeds 30% of the installed capacity of the photovoltaic power station, each time it is assessed according to 1% of the total grid-connected electricity of the site that month. When a wind farm causes a large area of ​​wind turbines to be disconnected from the grid due to its own reasons, and the total capacity of wind turbines disconnected from the grid at one time exceeds 30% of the installed capacity of the wind farm, each time it is assessed according to 1% of the total grid-connected electricity of the site that month. Taking a photovoltaic power station as an example, the calculation formula for reducing the grid disconnection assessment income is as follows.

[0194] R kh1 =12×μ TW ×1%×W a ×p pv (3-20)

[0195] In the formula, R kh1 To reduce the annual income of offline assessment, μ TW The number of times the total capacity of off-grid photovoltaic power generation units exceeds 30% of the installed capacity of the photovoltaic power station in that month, W a is the amount of electricity online in that month, p pv It is the benchmark on-grid electricity price for photovoltaic power stations.

[0196] 2) Reducing the assessment benefits of limited light / wind periods (i.e. the above-mentioned reduction of limited light / wind period benefits)

[0197] According to the detailed rules, when it is necessary to limit the output of photovoltaic power stations, photovoltaic power stations should strictly implement the dispatching plan curve (including real-time dispatching curve) issued by the grid dispatching agency, and the electricity exceeding the curve should be included in the assessment. In North China, it is required to collect the electricity of photovoltaic power stations in real time from the dispatching automation system of the power dispatching agency according to the settlement unit of photovoltaic power stations, and the actual power generated during the limited light period shall not exceed 2% of the planned power. When the actual power generation output during the limited light period exceeds the allowable deviation range of the planned power, the integral power of the excess part shall be counted as the assessment power at 2 times. When it is necessary to limit the output of wind power, the wind farm should strictly implement the dispatching plan curve (including real-time dispatching curve) issued by the grid dispatching agency, and the electricity exceeding the curve shall be included in the assessment. The dispatching automation system of the power dispatching agency collects the electricity of the wind farm in real time according to the settlement unit of the wind farm, and requires that the actual power generated during the limited wind period shall not exceed 2% of the planned power. When the actual power generated during the limited wind period exceeds the allowable deviation range of the planned power, the integral power of the excess part shall be counted as the assessment power at 2 times. Taking photovoltaic as an example, the calculation formula for the assessment income during the limited light period is as follows.

[0198]

[0199] In the formula, R kh2 To reduce the annual income of the light-limited period assessment, P g (t) is the active power generated by the photovoltaic power station at time t after energy storage is configured, P a (t) is the scheduled output at time t during the light-limited period, D m is the number of days per month when light restriction occurs, T1 is the start time of light restriction on that day, and T2 is the end time of light restriction on that day.

[0200] 3) Reduce the assessment benefits of the active power control substation commissioning rate

[0201] According to the implementation rules, photovoltaic power stations should have the ability to regulate active power and be equipped with active power control systems to receive and automatically execute active power control signals (AGC function) sent remotely by power dispatching agencies to ensure that the maximum active power value of the photovoltaic power station does not exceed the given value of the power dispatching agency. The uplink information of the active power control substation of the photovoltaic power station should include key data such as effective capacity and ultra-short-term forecasts. If the installation and commissioning of the active power control substation are not completed within the prescribed period, a monthly assessment will be conducted based on 3% of the total online power consumption of the station that month. The commissioning rate of grid-connected photovoltaic power stations that have installed active power control substations will be assessed. When the active power control substation of the grid-connected photovoltaic power station is in closed-loop operation, the power dispatching agency will count the commissioning rate of the active power control substation of each photovoltaic power station on a monthly basis. The formula for calculating the commissioning rate is as follows:

[0202]

[0203] When calculating the commissioning rate, the system exit time caused by power grid reasons or substation cooperation and commissioning during the commissioning of new equipment is deducted. The commissioning rate is 98% as the qualified standard. The assessment power of photovoltaic power stations with a full-month commissioning rate below 98% is calculated according to the following formula:

[0204]

[0205] In the formula, λ 投运 is the operation rate of active power control substation of photovoltaic power station, W a The amount of electricity consumed on the grid in that month.

[0206] Assuming that after configuring the energy storage system, the operation rate of the photovoltaic power station substation is not less than 98%, the profit calculation formula is as follows:

[0207]

[0208] In the formula, R kh3 In order to reduce the active power control substation commissioning rate assessment income, λ ty is the operation rate of active power control substation of photovoltaic power station, W a The amount of electricity consumed on the grid in that month.

[0209] The reference formulas (3-21) to (3-23) for assessing the benefits of reducing the active power control substation commissioning rate in wind farms are as follows. The specific details are the same as those for photovoltaic power generation.

[0210] 4) Increased on-grid electricity revenue (i.e. on-grid electricity revenue)

[0211] In the operation of new energy stations, there is a situation where the power of the grid dispatch plan is greater than the actual power generation of the new energy station. After configuring the energy storage system, while smoothing the volatility of new energy power generation, it can further track the dispatch plan curve and meet the AGC active power dispatch demand in time, thereby indirectly increasing the grid-connected power of the new energy station and obtaining corresponding benefits. The calculation formula is as follows.

[0212]

[0213] In the formula, R sw is the annual income from the increased grid-connected electricity, D s The number of days per month when the wind power / photovoltaic power output cannot meet the dispatch plan power, T3 is the starting time of the day, and T4 is the ending time of the day.

[0214] Optionally, the wind power / photovoltaic side energy storage in the embodiment of the present application may also have the following indirect benefits:

[0215] The calculation formulas for the indirect benefits generated by investing in energy storage on the new energy side, such as the value of pollutant emission reduction and coal saving, refer to formulas (3-12) and (3-15). The calculation formula for the annual benefit of reducing grid loss costs is shown below.

[0216] R ws =η g ×p ele ×Q a (3-26)

[0217] In the formula, R ws To reduce the annual benefit of grid loss cost, η g is the power grid loss rate (%) when the system is running, p ele is the local electricity price, Q a is the annual power generation of the system.

[0218] In a possible implementation of the embodiment of the present application, when the target scenario is grid-side energy storage, obtaining the direct benefit of the energy storage power station in the target scenario includes:

[0219] Obtain the power change of the system at each moment, the active power of the section after the energy storage charging and discharging power, the load demand in the section, the power output, the energy storage charging and discharging power, the network loss and the line flow limit value;

[0220] Obtaining system congestion cost based on the power change, section active power after energy storage charging and discharging power, load demand in section, power supply output, energy storage charging and discharging power, network loss and line flow limit value;

[0221] When obtaining grid-side energy storage, the grid loss amount and grid loss rate reduced by the grid system, and obtaining grid loss reduction benefits based on the grid loss amount and grid loss rate;

[0222] Based on the system congestion cost and the benefits of reducing network losses, the direct benefits of the energy storage power station in the target scenario are obtained.

[0223] Although grid-side energy storage invested by power grid companies cannot be included in the transmission and distribution pricing cost, if it is properly configured and used, it can directly or indirectly generate relevant benefits and improve the profit level of the power grid by reducing grid operating costs, delaying transmission and distribution investment, and increasing grid power supply capacity. At the same time, it can also improve the consumption of new energy and the reliability of power grid power supply.

[0224]

[0225] Table 4. Comprehensive value assessment index system for grid investment in energy storage

[0226] The grid-side energy storage in the embodiments of the present application can have the following direct benefits:

[0227] Grid congestion refers to the situation where the power supply plan cannot be met due to the capacity limitation of the grid itself, and the active power of the line or main transformer exceeds the limit in normal operation and accident state. If the network congestion is solved by adding or modifying the existing transmission and distribution facilities, there will be problems of long construction period or high cost. At this time, the system congestion can be alleviated by configuring energy storage with high flexibility and short construction period at the key nodes of the grid. In this scenario, the economic impact of energy storage on the grid is mainly to reduce the cost of network congestion and delay the return on grid investment.

[0228] 1) Reduce system congestion costs

[0229] The grid reduces the system congestion cost R by adding energy storage block The calculation formula is as follows.

[0230]

[0231] In formula (3-26) and (3-27): ΔP L,t is the power change of the system at time t; P L,t P is the cross-section active power after considering the energy storage charging and discharging power; load,t , P G,t , P sto,t , P loss,t They are the load demand, power output, energy storage charging and discharging power, and network loss in the section at time t; P lim is the line power flow limit value; L t is the unit power outage loss cost at time t; α is the pre-controlled load ratio (i.e. the maximum load rate allowed by the dispatching operation for the line or main transformer control, α≤1α); T is the statistical period.

[0232] 2) Delaying the return on grid investment

[0233] The financial benefits that the power grid obtains by deploying energy storage to delay the investment in transmission and distribution facilities:

[0234]

[0235] Where: R def To delay the return on investment in the power grid, P inf The capacity of energy storage to delay grid expansion; inf is the cost of unit capacity expansion; p is the annual interest rate; ΔN is the number of years that energy storage is deployed to delay grid upgrades; τ is the annual growth rate of peak load; and λ is the peak reduction rate of the energy storage system. In summary, in the scenario of energy storage alleviating grid congestion, the network congestion cost R that energy storage reduces for the system is considered. block , delay investment income R def and energy storage cost R sto After that, the total revenue of the power grid is:

[0236]

[0237] Where R sto is the total investment cost and operating cost of the energy storage system.

[0238] 3) Benefits from participating in power grid peak load regulation

[0239] Although the energy storage invested in the power grid cannot be directly included in the transmission and distribution costs, it can participate in the peak load balance of the power grid through unified dispatching of the power grid, and play an indirect equivalent benefit, mainly including two aspects: ① It can replace some high-cost (such as deep peak load regulation of gas-fired power and coal-fired power), and reduce the average power purchase cost of the power grid; ② At the peak of the power grid, the peak load capacity shortage is large, and the peak load demand of the system is supported by discharge, reducing the power restriction on the load side, and bringing the benefits of increased power supply. The benefits of the power grid in this scenario:

[0240]

[0241] Where: p' b The average electricity purchase price after configuring energy storage for the grid to participate in peak load regulation; ΔQ s Energy storage supports the peak load demand of the system through discharge and reduces the increased power supply caused by power limitation on the load side.

[0242] 4) Reduce network loss and gain

[0243] Energy storage increases system losses by charging at low loads and reduces system losses by discharging at peak loads. However, overall, the reduction in network losses caused by energy storage is greater than the increase in network losses. Therefore, overall, the network losses of the power grid are reduced, the power sales of the power grid increase, and the revenue increases. The revenue in this scenario is:

[0244]

[0245] Where ΔQ loss and η′ are the reduced grid loss power and grid loss rate after the grid is equipped with energy storage.

[0246] 5) Promote the benefits of new energy consumption

[0247] In the future, my country will build a new power system with new energy as the main body. Due to the randomness and intermittency of new energy output, and the replacement of some conventional power sources, the flexible power supply has been further reduced. The proportion of spare capacity in the system is obviously insufficient. Under the huge peak-shaving pressure, it may cause different degrees of new energy abandonment. If the system is solely based on backup power supply, the safety cost is expensive; energy storage devices have fast response speed, flexible charging and discharging, and can respond in time to smooth out the volatility of new energy. Therefore, in the future new power system, battery energy storage will become the main flexibility resource.

[0248] At present, the main operating models of energy storage projects in my country are contract energy management and financial leasing models. Under the current market environment, the investment cost of energy storage is relatively high, and the enthusiasm of new energy sites to actively configure energy storage needs to be improved; therefore, power grid companies need to actively assume the responsibility of energy storage infrastructure construction. For example: the power grid can bear the design of energy storage power stations, the construction of other related equipment and the operation and maintenance costs of power stations; energy storage companies lease core equipment to the power grid and bear the operation and maintenance and inspection of core equipment during the lease period; new energy sites can pay fees to the power grid by purchasing services. By adopting a shared leasing model for energy storage power stations, the investment cost of energy storage equipment can be greatly reduced, alleviating the embarrassing situation of "no one is willing to pay for the configuration of energy storage", promoting the consumption of new energy in the power grid, and supporting the safe operation of the power grid. At the same time, the power grid can also recover certain construction costs, and there is a lot of room for profit under this model. The energy storage invested by the power grid can recover the construction cost through the leasing model. The power grid's income in this scenario is:

[0249]

[0250] Where: V ser,et The income obtained by the power grid from leasing and selling the right to use the energy storage system to new energy stations; C sto,cons The investment cost of building energy storage power stations and related equipment for the power grid; C sto,rt The cost of leasing key energy storage equipment to energy storage companies for the power grid.

[0251] 6) Reduce power restrictions for users and reduce power supply reliability benefits

[0252] Some important users in the system have high requirements for power supply reliability. Once a system failure causes the load to lose power, it will cause varying degrees of economic losses or even accidents. If the regional power supply pressure is to be alleviated by building new power sources or large-capacity external power transmission channels, it is usually limited by construction costs, construction periods, and construction conditions. Therefore, configuring energy storage in load centers that lack power support not only has a short construction period, flexible configuration, and fast response speed, but can also support system voltage stability at critical moments, or serve as a backup power source or uninterruptible power supply for important loads, reducing power outage losses and improving power supply reliability. In this scenario, the power grid can reduce the frequency of power restrictions on the user side and increase power supply, and the power grid's revenue will increase accordingly. The specific benefits are:

[0253] R s5 =(Q b +ΔQ b )[p s (1-η)-p b ]-C f (3-36)

[0254] Where ΔQ b The amount of power outage avoided by the grid after the system is configured with energy storage. Since the electricity consumption behavior of the third type of load is greatly affected by the electricity price, it is assumed that the real-time electricity price is λt The user's critical low electricity price and high electricity price are λ L and λ H respectively. Then: when λ t < λ L , the user's electricity consumption behavior is not affected by the electricity price; when λ t > λ L , the load demand takes the minimum value; when λ L ≤ λ t ≤ λ H , the user's electricity consumption behavior is affected by the electricity price and other factors. Assume that the system reliability is threatened, and the power grid takes power rationing measures for the third type of load. Considering the demand-side response, in the time period (t1, t2), the reduced power supply for this part is:

[0255]

[0256] In the formula: is the demand power of the third type of load at time t (t1 < t < t2); is the minimum load demand in the time period t1 ≤ t ≤ t2; y is other factors that affect the load electricity consumption behavior except the electricity price.

[0257] 7) Support the safety benefits of the power grid

[0258] Compared with the traditional power grid transmission and distribution facilities, the cost advantage of energy storage, especially electrochemical energy storage, is that its construction scale can be invested in stages according to the change of demand capacity, and the cost generated by the flexible investment process can be regarded as a continuous variable of power or electricity demand, and the cost recovery channels are flexible and diverse. The energy storage system on the power grid side can replace the relevant investment and construction of the traditional power grid to maintain the stable operation of the system, such as the primary frequency modulation auxiliary equipment participating in frequency stabilization, the reactive power compensation equipment supporting the investment in local voltage stabilization, the system standby power supply and the black start power supply and other project investments. By comprehensively considering factors such as technology, utility, economy and environment, the problem is transformed into multi-objective optimization modeling and solution, and the scheme comparison and selection are carried out to form alternative schemes and reduce the investment cost. The power grid revenue in the above scenario:

[0259]

[0260] In the formula, ΔC f is the investment cost reduced by the energy storage on the power grid side replacing the relevant investment of the traditional power grid to maintain the stable operation of the system.

[0261] In a possible implementation manner of the embodiment of the present application, when the target scenario is the user-side energy storage, the obtaining of the direct revenue of the energy storage power station in the target scenario includes:

[0262] Determine the first planned capacity of the transformer when there is no energy storage, the second planned capacity of the transformer when there is energy storage, and the maximum calculated load of the user when the energy storage is erroneous;

[0263] Determine the capacity of a dedicated transformer based on the first planned capacity, the second planned capacity, and the maximum calculated load of the user;

[0264] Based on the dedicated transformer capacity, the transformer capacity benefits are reduced;

[0265] Determine the peak and valley benefits of energy storage based on the real-time peak and valley time-of-use electricity prices of the power grid and the efficiency of the energy storage system;

[0266] Based on the transformer capacity benefit and the energy storage peak-valley benefit, the direct benefit of the energy storage power station for user-side energy storage is obtained.

[0267] This project selects large industrial users who adopt a two-part pricing system, and establishes a cost and benefit model for battery energy storage systems on the large industrial user side, which is used to comprehensively calculate the various costs and benefits of this system; although large industrial user-side energy storage is more economical in theory, in actual operation, important parameters such as energy conversion efficiency and life may be difficult to reach the feasibility measurement conditions, and the internal rate of return will be lower than the expected measurement. In addition, with the improvement of the electricity price mechanism in the future, the user-side energy storage income will no longer be based only on the dynamic peak-valley price difference, but will also be closely linked to market demand. Therefore, the development of large industrial user-side energy storage must not only have peak-shaving and valley-filling arbitrage, but also actively engage in finding new profit models in the power system.

[0268]

[0269]

[0270] Table 5. Comprehensive value evaluation index system for user-side energy storage

[0271] Specifically, user-side energy storage can have the following direct benefits:

[0272] 1) Reduce transformer capacity benefits

[0273] Large industrial users who use dedicated transformers for power supply usually determine the capacity of the dedicated transformer based on their own maximum load. If an energy storage system is built, the capacity of the dedicated transformer can be reduced.

[0274] R byq =C by (S by -S' by ) (3-39)

[0275]

[0276] Where: R byqCost saved by reducing transformer capacity; C by S is the unit capacity cost of the special transformer; by The planned capacity of the transformer when there is no energy storage (the first planned capacity); S' by To increase the transformer planning capacity after energy storage (the second planning capacity); P max It is the maximum calculated load of the user when no energy storage device is installed.

[0277] 2) Reduce basic electricity bill benefits

[0278] Large industrial users use a two-part electricity price. The basic electricity fee in this article is charged according to the transformer capacity. For new users, if an energy storage system is installed, the planned transformer capacity can be appropriately reduced, which will correspondingly reduce the basic electricity fee paid by the user every month.

[0279] Reduce basic electricity bill by R per year df for:

[0280] R df =12(S by -S' by )Q by (3-41)

[0281] Where: Q by It is the basic electricity price charged according to the transformer capacity.

[0282] 3) Reduce electricity consumption and electricity bill benefits

[0283] After the peak-valley time-of-use electricity price is applied to the user-side energy storage system, the user side uses the energy storage device to charge during the valley period and discharge during the peak period, thereby realizing the peak-valley price difference arbitrage and reducing the electricity bill. nj for:

[0284]

[0285] E dn =E rat (1-d) n-1 (3-44)

[0286] Where: Q d is the discharge electricity price; Q c is the charging electricity price; d is the equipment attenuation rate; E cn is the charging capacity in the nth year; E dn is the discharge capacity in the nth year.

[0287] 4) Reduced power outage losses

[0288] The calculation formula for the user’s power shortage loss is shown in (3-13).

[0289] Optionally, the user-side energy storage in the implementation of this application may also have the following indirect values:

[0290] 1) Investment value of alternative power grids

[0291] Energy storage power stations can provide load support for the power grid in a short period of time, reducing the investment in capacity construction due to the grid's time-limited shortcomings. The replacement value measurement can be determined based on the average cost of transformers, substations, transmission lines and other equipment required for grid expansion, and its calculation formula is shown in (3-12).

[0292] 2) Pollutant emission reduction value

[0293] Energy storage assists the peak load regulation of thermal power units, which can reduce the peak load of thermal power units and thus reduce fuel costs, which is equivalent to an additional income from energy storage. The income from energy storage that is equivalent to reducing the pollution cost of thermal power units is called environmental value. Its calculation formula is shown in (3-15).

[0294] Step 303: Obtain the weight coefficient corresponding to the target scene.

[0295] After the direct value and the indirect value in each scenario are calculated by the formulas shown in step 302, a corresponding weight coefficient may be assigned to each target scenario.

[0296] Different investment entities have different requirements for application functions and values, resulting in different application scenarios for energy storage projects. The use of the energy storage comprehensive benefit evaluation index system includes the following steps: first, clarify the needs and conduct single-level evaluation or multi-level evaluation; second, select key indicators based on the needs; third, calculate the values ​​of each indicator; fourth, set the indicator weight; and fifth, obtain the evaluation results.

[0297] The evaluation method first establishes an overall indicator evaluation system, then refines the evaluation indicators and assigns corresponding weights, and finally obtains the overall evaluation results of the project through the evaluation function. At present, the methods for determining indicator weights include the subjective weighting method of the month-on-month score and the objective weighting method of entropy weight. In order to take into account different quantifiable and non-quantifiable evaluation indicators and make the evaluation results more systematic, comprehensive and accurate, this study uses the least squares method to determine the weights, and the comprehensive weights of each indicator are set as shown in the following formula.

[0298] W=(W1,W2,W3,W4,W5)

[0299] In the implementation of this application, the following methods can be used to assign corresponding weight coefficients to each target scene:

[0300] 1. The decision alternative ratio evaluation (DARE) is a subjective weighted evaluation method that obtains the important coefficient of each indicator based on expert experience and then determines the weight of each indicator. In the process of using the chain scoring method, experts only need to compare each indicator with the adjacent previous indicator and the next indicator, and do not need to compare with all factors. Theory shows that compared with the hierarchical analysis method, the DARE method requires evaluation experts to determine fewer evaluation values, is less likely to produce contradictions in judgment, and does not require consistency testing. The steps for determining the weight of each indicator using the DARE method are as follows:

[0301] (1) Fill in the evaluation indicators in the first column of the following table in any order and number them U1-U K , where K is the number of evaluation indicators.

[0302] Table 6. Evaluation index importance coefficient X k Determination

[0303]

[0304] (2) Based on expert experience, the importance of adjacent evaluation indicators in the first column of the above table is compared from top to bottom, and the resulting score is recorded as the provisional coefficient A. k (k = 1~K, indicating the kth evaluation index), added to the second column. A k Indicates U k and U k+1 importance ratio.

[0305] (3) For the provisional coefficient A in column 2 of the table k Correction is made and the result is recorded as correction coefficient Y k (k = 1 ~ K, indicating the kth evaluation index), fill in the third column. The correction method is to change the last object Y K The correction coefficient is set to 1, then Y K-1 =Y K A K-1 , Y K-2 =Y K-1 A K-2 , and so on, calculate the correction coefficients.

[0306] (4) The correction factor Y in column 3 k Perform normalization and use the result as weight to fill in column 4. The normalization equation is:

[0307]

[0308] 2. Entropy weight method is a method to determine weights based on the entropy principle. It is an objective weighting method that determines weights based on the amount of information contained in each evaluation indicator. The smaller the entropy value of the indicator, the more information it provides, the more important the indicator, and the larger the corresponding weight value.

[0309] In the embodiment of the present application, the direct benefit and the indirect benefits of each other scenario can be used as evaluation indicators to construct a judgment matrix;

[0310] The entropy weight of each evaluation index is calculated, and the weight coefficient of each evaluation index is generated by the least square method.

[0311] Assuming there are M evaluation objects and K evaluation indicators, the steps to determine the weights using the entropy weight method are as follows:

[0312] (1) Determine the evaluation matrix R based on the original data mk ) M×K , r mk is the value of the kth indicator of the mth evaluation object. Where m = 1, 2, ..., M; k = 1, 2, ... K. The matrix form is as follows:

[0313]

[0314] 2) To eliminate the different properties of the indicators, the evaluation matrix is ​​unified and standardized to obtain the standardized matrix S = (s mk ) M×K The indicator standardization method is as follows:

[0315]

[0316] 3) The entropy of each evaluation index is

[0317]

[0318] When mk = 0, let s mk Ins mk =0.

[0319] 4) Define the coefficient of difference of the kth evaluation index as

[0320] λ k =1-E k (k=1,2,…,K)(3-50)

[0321] 5) The entropy weight of the kth evaluation index is

[0322]

[0323] Entropy Weight V kIt reflects the amount of information contained in the indicator. The entropy weight reflects the importance of the indicator. The larger the value, the greater the role of the indicator in the evaluation system.

[0324] After the weights are calculated through the above scheme, a least squares optimization model can be established to optimize the weights, thereby obtaining the comprehensive weights corresponding to each target scenario.

[0325] Assume that the weight obtained by the subjective weighting method of the month-on-month rating is

[0326] X=[X1,X2,…,X K ] T (3-52)

[0327] The weight obtained using the objective weighting entropy weight method is

[0328] V=[V1,V2,…,V K ] T (3-53)

[0329] In order to simultaneously consider the subjective experience preference and the authenticity of objective data information and achieve the unity of subjectivity and objectivity, the deviation between the final comprehensive weight and the subjective and objective weights should be as small as possible. To this end, the least squares optimization model is established as shown in the following formula. The established least squares decision model is shown in the following formula.

[0330]

[0331] Where: W k is the comprehensive weight; X k is the subjective weight; V k is the objective weight; mk The index is the index after standardization.

[0332] Step 304, based on the weight coefficients, direct benefits and indirect benefits corresponding to the various evaluation indicators, the energy storage value corresponding to the target scenario is obtained.

[0333] Based on the determined weights, taking third-party social capital investment in energy storage as an example, the comprehensive benefits of energy storage combined with frequency regulation are evaluated. The evaluation calculation is shown in the following formula.

[0334] R Z =W1·R1+W2·R2+...+W n ·R n (3-55)

[0335] In the formula, R Z The comprehensive value of energy storage participating in ancillary services, R1 to R n Respectively represent the values ​​of 1 to n evaluation indicators; W1 to W nare the weights corresponding to each evaluation index.

[0336] Furthermore, the embodiment of the present application can also solve the comprehensive score by the improved TOPSIS method. The TOPSIS method, which can also be called the approximate ideal solution sorting method, is often used for multi-objective decision analysis. The method is to sort the degree of goodness of the scheme according to the distance between each scheme and the ideal scheme. When the scheme is closest to the optimal scheme and farthest from the worst scheme, the scheme is considered to be the best scheme. Grey relational analysis (GRA) is a method that takes into account the influence of factors in two systems, analyzes the subsystems and applies mathematical methods to find the numerical relationship between the corresponding subsystems (factors). Therefore, the embodiment of the present application improves the traditional TOPSIS method, introduces the combination of grey relational analysis and TOPSIS, and proposes an improved TOPSIS comprehensive evaluation method that comprehensively considers grey correlation, which improves the accuracy of relative distance solution, makes up for the defects of the original criteria of the traditional method, and makes the calculation results more scientific and authentic. First, an evaluation index system is constructed, and the weights of each index of the comprehensive value evaluation of energy storage participating in auxiliary services in the traditional TOPSIS method are improved by using the combined weighted least squares method. Secondly, the TOPSIS method is improved by combining the grey correlation analysis method, and a comprehensive evaluation model is constructed. The grey correlation calculated by the grey correlation analysis algorithm and the Euclidean distance calculated by the TOPSIS method are combined to obtain the comprehensive closeness. According to the size of the comprehensive closeness, the scenarios are ranked.

[0337] In a possible implementation, the maximum value and the minimum value of each evaluation index are taken as the positive ideal solution and the negative ideal solution, and the grey correlation degree corresponding to the target scene is calculated; the grey correlation degree includes a positive correlation coefficient and a negative correlation coefficient; the positive Euclidean distance and the negative Euclidean distance between each evaluation index and the positive ideal solution and the negative ideal solution are calculated; the relative closeness of the grey correlation analysis is determined according to the positive correlation coefficient and the negative correlation coefficient; the relative closeness of the Euclidean distance is determined according to the positive Euclidean distance and the negative Euclidean distance; the comprehensive value of the energy storage solution of the target scene is calculated according to the closeness of the Euclidean distance and the closeness of the grey correlation analysis.

[0338] Please refer to Figure 4 , which shows a flow chart of an energy storage comprehensive value evaluation implementation involved in the embodiment of the present application. Figure 4As shown, in an embodiment of the present application, after the weight matrix is ​​generated, the direct benefit and the indirect benefit of each other scenario can be used as evaluation indicators to construct the original evaluation matrix, and then standard normalization processing is performed, and then weighted judgment processing is performed through the weight matrix to obtain a weighted judgment matrix; for the weighted evaluation indicators in the weighted judgment matrix, the positive ideal solution and the negative ideal solution are calculated (that is, the evaluation indicators in the above steps can be processed by the weight matrix).

[0339] Specifically, the weighted method can be used to determine the combined weights of the evaluation indicators and calculate the corresponding weighted values ​​of the indicators. However, the comprehensive value score of energy storage participating in power auxiliary services in different scenarios has not yet been obtained. The relationship between each indicator and the comprehensive score cannot be simply calculated through a simple linear relationship. Therefore, this section uses the improved TOPSIS method to solve the comprehensive score.

[0340] The TOPSIS method, which can also be called the method of ranking by approximating the ideal solution, is often used for multi-objective decision analysis. This method is to rank the degree of quality of the solutions according to the distance between each solution and the ideal solution. When the solution is closest to the optimal solution and farthest from the worst solution, the solution is considered to be the best solution. Traditional TOPSIS calculates the degree of proximity based on Euclidean distance, and often has problems of insufficient evaluation validity and median vertical line between sample data in certain cases. Therefore, the embodiment of the present application improves the traditional TOPSIS method, introduces grey relational analysis (GRA) and combines it with TOPSIS, and proposes an improved TOPSIS comprehensive evaluation method that comprehensively considers grey correlation, which effectively improves the adaptability of the method.

[0341] Since the indicators have been normalized in the process of weight standardization, the maximum value of the indicator is the positive ideal solution, and the minimum value of the indicator is the negative ideal solution.

[0342] The positive ideal solution is:

[0343]

[0344] The negative ideal solution is:

[0345]

[0346] Then the grey correlation degree and traditional Euclidean distance of each solution to the positive and negative ideal solutions can be calculated.

[0347] The calculation of the positive and negative grey correlation coefficients first requires the calculation of the grey correlation degree using the following formula:

[0348]

[0349] In the formula, ρ is the resolution coefficient, which affects the positive and negative grey correlation coefficients, and is generally taken as 0.5. The positive and negative grey correlation matrix can be obtained from the above calculation formula, and then the correlation coefficients of each solution with the positive and negative ideal solutions can be obtained:

[0350]

[0351] According to the Euclidean distance, the distances between each solution and the positive and negative ideal solutions can be obtained as follows:

[0352]

[0353] Solve the relative closeness for comprehensive evaluation, obtain the ranking results of the schemes and analyze the results. The results are dimensionless, and then the pros and cons of the solutions can be judged based on their relative closeness.

[0354] The expression of relative closeness based on Euclidean distance is:

[0355]

[0356] The expression of relative closeness based on grey relational analysis is:

[0357]

[0358] The comprehensive closeness calculated based on the closeness of traditional Euclidean distance and the closeness based on grey correlation analysis is:

[0359] U i =e1D i +e2Y i ,i=1,2,…,m

[0360] When the value of comprehensive closeness is larger, it is closer to the positive ideal solution, which means that the solution is closer to the optimal solution, that is, the comprehensive value is higher. Conversely, it means that the solution is closer to the negative ideal solution and the comprehensive value is worse.

[0361] That is, in the embodiment of the present application, in addition to obtaining the energy storage value of the energy storage solution in the scenario through weights, the comprehensive value of the energy storage solution can also be obtained through the above-mentioned TOPSIS comprehensive evaluation method, thereby judging the reliability of the energy storage solution from multiple dimensions.

[0362] In summary, when a power system is deployed with an energy storage power station, a multi-scenario energy storage value assessment system can be first constructed, and the target scenario in which the energy storage power station is deployed can be obtained, and the various evaluation indicators of the energy storage power station in the target scenario in terms of independent energy storage, thermal power side, photovoltaic / wind power side, user side, and grid side can be determined. Finally, the energy storage value of the target scenario can be determined by calculating the weight coefficients of different evaluation indicators, as well as the direct and indirect benefits in the evaluation indicators. The above scheme constructs a multi-scenario energy storage value assessment system, taking into account that energy storage power stations have different evaluation indicators in different scenarios, and assigning different weights to different evaluation indicators, and obtaining the final energy storage value by weighting, providing an automated value assessment method for multi-scenario energy storage, while taking into account the value of multiple scenarios, and improving the efficiency and accuracy of the value assessment of multi-scenario energy storage.

[0363] In the embodiments of the present application, a multi-scenario energy storage value assessment device is also provided, which is used to implement the above embodiments and preferred implementation modes, and will not be repeated hereafter. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0364] Figure 5 is a schematic diagram of a multi-scenario energy storage value assessment device provided in an embodiment of the present application, such as Figure 5 As shown, the device comprises:

[0365] The scenario determination module 501 is used to construct a multi-scenario energy storage value evaluation system and determine the target scenario to be evaluated; the target scenario includes independent energy storage, thermal power side, photovoltaic / wind power side, user side and grid side; the energy storage on different sides in the multi-scenario energy storage value evaluation system has different evaluation indicators; the types of evaluation indicators include direct benefits and indirect benefits;

[0366] The benefit acquisition module 502 is used to obtain the evaluation index of the energy storage power station on each side of the target scenario;

[0367] The energy storage value acquisition module 503 is used to acquire the energy storage value corresponding to the target scenario based on the weight coefficients corresponding to the evaluation indicators, the direct benefits and the indirect benefits.

[0368] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0369] The device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0370] The embodiment of the present invention also provides a computer device having the above-mentioned device. Figure 6 , Figure 6 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 6 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Take a processor 10 as an example.

[0371] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0372] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0373] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0374] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0375] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0376] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0377] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0378] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A multi-scenario energy storage value assessment method, characterized in that: The method comprises: Construct a multi-scenario energy storage value evaluation system and determine the target scenario to be evaluated; the target scenario includes independent energy storage, thermal power side, photovoltaic / wind power side, user side and grid side; the energy storage on different sides in the multi-scenario energy storage value evaluation system has different evaluation indicators; the types of evaluation indicators include direct benefits and indirect benefits; Obtain the evaluation indicators of the energy storage power station on each side of the target scenario; Based on the weight coefficients corresponding to the evaluation indicators, the direct benefits and the indirect benefits, the energy storage value corresponding to the target scenario is obtained.

2. The method according to claim 1, characterized in that Before obtaining the energy storage value corresponding to the target scenario based on the weight coefficients corresponding to the evaluation indicators, the direct benefits, and the indirect benefits, the method further includes: Constructing a judgment matrix according to the direct benefits and the indirect benefits; The entropy weight of each evaluation index is calculated, and the weight coefficient of each evaluation index is generated by the least square method.

3. The method according to claim 2, characterized in that The method further comprises: The maximum value and the minimum value of each evaluation index are used as the positive ideal solution and the negative ideal solution, and the grey correlation degree corresponding to the target scene is calculated; the grey correlation degree includes a positive correlation coefficient and a negative correlation coefficient; Calculating the positive Euclidean distance and the negative Euclidean distance between each evaluation index and the positive ideal solution and the negative ideal solution; Determine the relative closeness of the grey relational analysis according to the positive relational coefficient and the negative relational coefficient; Determining the relative closeness of the Euclidean distance according to the positive Euclidean distance and the negative Euclidean distance; The comprehensive value of the energy storage solution for the target scenario is calculated based on the closeness of the Euclidean distance and the closeness of the grey relational analysis.

4. The method according to any one of claims 1 to 3, characterized in that: For independent energy storage in the target scenario, the evaluation indicators of the energy storage power station on each side of the target scenario are obtained, including: Determine the peak and valley benefits of energy storage based on the real-time peak and valley time-of-use electricity prices of the power grid and the efficiency of the energy storage system; Determine the emergency power support benefit based on the emergency power support times, wherein the emergency power support times are the times of stable load shedding by the energy storage power station within a specified time; Determine the frequency regulation capacity compensation income based on the allocated capacity; Obtain standby service income; the standby service income is the benefit value obtained by assisting other scenarios when the energy storage power station is in a standby state.

5. The method according to any one of claims 1 to 3, characterized in that: For the thermal power side in the target scenario, the evaluation indicators of the energy storage power station on each side of the target scenario are obtained, including: Determine the frequency regulation capacity compensation income based on the allocated capacity; Based on the speed of the thermal power unit, the difference in coal consumption before and after the energy storage power station participates in the deployment is calculated, and the total coal consumption reduction benefit is obtained through the difference in coal consumption; Based on the compensation income for the deployment capacity and the income from the reduction in total coal consumption, direct income of the energy storage power station under the energy storage on the thermal power side is obtained.

6. The method according to any one of claims 1 to 3, characterized in that: For the photovoltaic / wind power side in the target scenario, the evaluation indicators of the energy storage power station on each side of the target scenario are obtained, including: Obtaining a target off-grid capacity; the target off-grid capacity is used to indicate the number of times the total off-grid capacity of the photovoltaic / wind turbine generator set exceeds a specified proportion of the installed capacity; Determining the benefit of reducing off-line traffic based on the target off-line traffic volume; Based on the real-time active power of the photovoltaic / wind power station after energy storage configuration, the time-limited period scheduling plan processing and the time-limited period, determine the benefits of reducing the light / wind limit period; The grid-connected electricity revenue is obtained based on the increased annual revenue from grid-connected electricity and the number of days per month when the wind power / photovoltaic power output cannot meet the dispatch plan power.

7. The method according to any one of claims 1 to 3, characterized in that: For the grid side in the target scenario, the evaluation indicators of the energy storage power station on each side of the target scenario are obtained, including: Obtain the power change of the system at each moment, the active power of the section after the energy storage charging and discharging power, the load demand in the section, the power output, the energy storage charging and discharging power, the network loss and the line flow limit value; Obtaining system congestion cost based on the power change, section active power after energy storage charging and discharging power, load demand in section, power supply output, energy storage charging and discharging power, network loss and line power flow limit value; When grid-side energy storage is obtained, the grid system reduces the grid loss power and grid loss rate, and obtains grid loss reduction benefits based on the grid loss power and grid loss rate.

8. The method according to any one of claims 1 to 3, characterized in that: For the user side in the target scenario, the evaluation index of the energy storage power station on each side of the target scenario is obtained, including: Determine the first planned capacity of the transformer when there is no energy storage, the second planned capacity of the transformer when there is energy storage, and the maximum calculated load of the user when the energy storage is erroneous; Determine the capacity of a dedicated transformer based on the first planned capacity, the second planned capacity, and the maximum calculated load of the user; Based on the dedicated transformer capacity, the transformer capacity benefits are reduced; Determine the peak and valley benefits of energy storage based on the real-time peak and valley time-of-use electricity prices of the power grid and the efficiency of the energy storage system.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the multi-scenario energy storage value assessment method according to any one of claims 1 to 8 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the multi-scenario energy storage value assessment method described in any one of claims 1 to 8.

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