CN116885800A - Cloud energy storage mode construction method and device based on entity operators - Google Patents

Cloud energy storage mode construction method and device based on entity operators Download PDF

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CN116885800A
CN116885800A CN202310845557.4A CN202310845557A CN116885800A CN 116885800 A CN116885800 A CN 116885800A CN 202310845557 A CN202310845557 A CN 202310845557A CN 116885800 A CN116885800 A CN 116885800A
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energy storage
cloud
energy
entity
day
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曹芬
周智行
杨安源
马永吉
王慧芳
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Zhejiang University ZJU
State Grid Hubei Electric Power Co Ltd
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Zhejiang University ZJU
State Grid Hubei Electric Power Co Ltd
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Abstract

The application discloses a cloud energy storage mode construction method and device based on an entity operator. The application builds a cloud energy storage configuration optimization model with minimum social total energy consumption cost based on an entity operator, and builds a scheduling model with optimal peak clipping and valley filling benefits, and a settlement pricing model with energy storage scheduling and settlement separated, and energy storage charging and discharging prices and new energy internal selling prices are constrained. Taking several types of users for configuring energy storage and new energy sources as examples, the energy storage optimizing configuration result of the entity operator is verified, the basic benefits of the energy storage and new energy source users are guaranteed, the entity operator and other cloud energy storage participating users are guaranteed to benefit, and the sustainable development of the cloud energy storage mode is realized. The cloud energy storage mode construction method based on the entity operators can aggregate different types of users, realize two charging and two discharging of energy storage, and improve the utilization rate and efficiency of the energy storage.

Description

Cloud energy storage mode construction method and device based on entity operators
Technical Field
The application belongs to the technical field of power systems, and particularly relates to a cloud energy storage mode construction method and device based on an entity operator.
Background
At present, the power demand of China is steadily increased, the installed proportion of new energy sources such as wind power, photovoltaic and the like is continuously increased, and the trend of greatly developing green low-carbon energy sources is not changed. Because new energy power generation such as wind power, photovoltaic and the like has intermittence and uncertainty, the task of balancing loads and power generation becomes complex and difficult, and the reliability and stability of a power system are seriously affected. In this context, energy storage that can change the temporal-spatial distribution of electrical energy and enhance the capacity of the electrical power system is expected. However, the existing energy storage has the problems of high investment cost, insufficient and reasonable application and the like.
In order to alleviate the contradiction between the stability of the power grid and the volatility of the new energy, the new energy needs to be configured with 5-20% of rated power for storing energy during installation and construction. The measure has an active side for promoting the improvement of the energy storage configuration capacity, but if the energy storage is not properly used, the enthusiasm of photovoltaic and wind power project construction can be affected. In order to improve the utilization rate of energy storage and expand the profit space, energy storage operation modes such as shared energy storage, yun Chuneng and the like are presented. The cloud energy storage has the nature of energy storage sharing, and does not actually control participating users, so that the cloud energy storage serves the users, the generation of profit comes from the generation of economic benefits of scale by multi-user aggregation and the value space of retail electricity price change along with time, and therefore the cloud energy storage becomes one of research hotspots of energy storage operation modes.
The cloud energy storage is to concentrate the originally dispersed independent energy storage information of each user to the cloud end by an operator, replace the physical energy storage by the virtual energy storage of the cloud end, and the operator schedules the virtual energy storage and settles the cost of each user participating in the cloud energy storage. The users participating in the cloud energy storage mode can be configured with certain entity energy storage or have the energy storage requirement of new energy sources such as wind and light, and can also only have the electric load requirement. The cloud virtual energy storage is used for replacing the physical energy storage, an operator schedules the virtual energy storage, and the cost of each user participating in the cloud energy storage is settled, so that the utilization rate and benefit of the energy storage are improved, the mode is more flexible and variable, and the cloud virtual energy storage system becomes a mode with development prospect in the industry.
In the research of the cloud energy storage at present, a cloud energy storage construction mode of an entity operator is generally considered. The entity operators can configure centralized energy storage, the scheduling targets have diversity, but the benefits of the energy storage owners and new energy users are generally considered, so that the benefits are ensured to be obtained through resource sharing. In the cloud energy storage mode of the entity operator, the operator needs to participate in the mode as a main body, the profit mode is more, the electric quantity cost and the service cost are involved, and the scheduling and pricing settlement mechanism is complex.
Disclosure of Invention
The application aims to overcome the defects of the prior art and provides a cloud energy storage mode construction method, device and equipment based on an entity operator and a storage medium.
The application is suitable for the user side, has simple construction, gives consideration to fair and good benefits to dispatching and settlement, and has no limit to the users with configured energy storage and the new energy users with energy storage requirements among the participants. The primary task of the entity operator is to determine how to optimally configure the centralized energy storage, so that the overall benefit in the whole cloud system is optimal, and then the entity operator realizes relatively fair and reasonable good benefits of the entity operator and other users through daily scheduling and in-cloud settlement.
The first aspect of the application provides a cloud energy storage mode construction method based on an entity operator, which comprises the following steps:
step 1: the entity carrier carries out centralized energy storage optimization configuration decision according to the collected configuration of the user distributed energy storage devices in the cloud, typical daily load curves of all the users participating in the cloud energy storage and typical new energy power generation curves;
step 2: the entity operator performs energy storage day-ahead optimization scheduling according to the day load curves of all cloud users collected day-ahead, the new energy power generation predicted by the entity operator and the owned cloud energy storage devices;
step 3: solving the purchase and sale power of the cloud and the power grid at each moment of a dispatching day by the step 2, and carrying out the settlement in the cloud by adopting a settlement mode separated from the dispatching;
step 4: and introducing a Nash social welfare function as an objective function, and determining the energy storage charge and discharge price and the new energy internal sales price, thereby completing the construction of a cloud energy storage mode.
A second aspect of the present application provides a cloud energy storage mode construction apparatus based on an entity operator, including:
the centralized energy storage optimizing configuration module is used for the entity operator to make a centralized energy storage optimizing configuration decision according to the collected information of the distributed energy storage devices of the users in the cloud, the typical daily load curves of all the users participating in the cloud energy storage and the typical new energy power generation curve of the region.
The energy storage day-ahead optimization scheduling module is used for carrying out energy storage day-ahead optimization scheduling according to day load curves of all cloud users collected in the day ahead and new energy power generation and owned in-cloud energy storage devices predicted by the entity operators;
the cloud settlement module is used for carrying out cloud settlement by adopting a settlement mode separated from scheduling according to the purchase and sale power of the cloud and the power grid at each moment of the scheduling day;
and an objective function solving module: the cloud energy storage system is used for introducing a Nash social welfare function as an objective function and determining the energy storage charge and discharge price and the new energy internal sales price, so that the construction of a cloud energy storage mode is completed.
A third aspect of the present application provides a cloud energy storage mode construction device based on an entity operator, including: the cloud energy storage mode construction method based on the entity operators comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the cloud energy storage mode construction method based on the entity operators when executing the program.
A fourth aspect of the present application provides a computer readable storage medium, wherein the storage medium stores a computer program for executing the above-mentioned cloud energy storage mode construction method based on an entity carrier.
The application has the beneficial effects that: aiming at the condition of multiple types of loads, the application combines peak-valley electricity prices and new energy networking rules to make decisions on centralized energy storage configuration of entity operators, and researches on scheduling operation and settlement pricing in a cloud energy storage mode. The application reasonably sets the charge and discharge price of the energy storage and the internal selling price of the new energy on the basis of balancing the internal balance and guaranteeing the basic benefits of the energy storage and the new energy by adopting a relatively fair settlement method which is easy to understand and apply and is separated from scheduling, thereby guaranteeing the healthy development of the cloud energy storage mode based on entity operators. And based on the cloud energy storage mode of the entity operator, different types of users are aggregated, and under the condition that the entity operator optimally configures the centralized energy storage, the two-charge and two-discharge of the energy storage can be realized, and the utilization rate and the efficiency of the energy storage are improved.
Drawings
Fig. 1 is a cloud energy storage mode diagram.
Fig. 2 is a graph of peak valley price distribution of a grid.
Fig. 3 is a graph of typical daily user loads and photovoltaic power.
Fig. 4 is a graph of total load and total photovoltaic power in a typical solar cloud energy storage mode.
FIG. 5 is a graph showing the relationship between the power of the stored energy configuration and the cost and the number of charges/discharges per day.
Fig. 6 is a graph of scheduled household loads and photovoltaic power.
Fig. 7 is a graph of total load and total photovoltaic power in a modulated solar cloud energy storage mode.
Fig. 8 is a graph of the charge and discharge results of stored energy.
Fig. 9 is a graph of the result of charging and discharging stored energy by a user under independent operation.
Fig. 10 is a schematic diagram of a cloud energy storage mode construction device based on an entity operator.
Fig. 11 is a schematic diagram of a cloud energy storage mode construction device structure based on an entity operator.
Detailed Description
In order that the above objects, features and advantages of the application will be readily understood, a more particular description of the application will be rendered by reference to the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
According to the application, a centralized energy storage optimization configuration decision with the lowest total energy cost is firstly carried out by an entity operator according to the configuration of the user distributed energy storage devices in the cloud, the typical daily load curve of each user and the typical new energy power generation curve of the area; and the maximum overall benefit of the users in the cloud is realized through daily scheduling, and the relatively reasonable distribution of the benefits of each user in the cloud is realized through the price of the internal new energy and the charging and discharging price of the energy storage. The cloud energy storage mode provided by the application can fully exert the values of energy storage and new energy, realize the improvement of efficiency and reduce the cost of user load in the cloud, thereby mobilizing the enthusiasm of users to participate in the construction of the cloud energy storage.
The application is further described below with reference to the accompanying drawings, which comprise the following steps:
step 1: and the entity operator makes a centralized energy storage optimization configuration decision according to the typical daily load curve, the typical new energy power generation curve and the distributed energy storage device information configured by the users in the cloud, wherein the typical daily load curve and the typical new energy power generation curve are collected by investigation, and the distributed energy storage device information is configured by the users in the cloud. The method specifically comprises the following steps:
the total cost of energy for typical daily society as a whole C CES The minimum is taken as an objective function, and the total cost is the electricity purchasing cost of the user power grid and the cloud energy storageThe sum of the costs of the energy storage resource and the new energy resource set can be expressed as:
wherein T is s The total number of time points representing a typical day; h is the time window length; wherein C is Grid The method comprises the steps that the electricity purchasing cost of a user is the sum of electricity purchasing and selling cost of the cloud energy storage whole to the power grid at each moment; m is m Grid The purchase price is the electricity price for trading with the power grid; p (P) Grid,t And (5) the power of electricity purchase and selling of the power grid by the operator at the t-th moment of the adjustment day is indicated, the electricity purchase is indicated in positive time, and the electricity selling is indicated in negative time. C (C) ES The energy storage aggregate cost is as follows: epsilon is the cost of energy storage unit capacity conversion, P Storage,t And the operating power of energy storage in the cloud at the t moment is positive, and the discharging power is negative. C (C) New The new energy cost is as follows: c PV /c WF Respectively representing the power cost of photovoltaic/wind power generation unit in cloud energy storage, P PV,t /P WF,t And respectively representing photovoltaic and wind power supply power at the time t.
Wherein, purchase and sale electricity price m for trading the whole cloud energy storage with the power grid Grid The definition is as follows:
m Grids,base the price of the reverse power grid is sold, and a coal-fired reference price is adopted; m is m Grid,t And (5) purchasing price, namely, peak-valley electricity price of the power grid at the t-th moment of the dispatching day.
The cost epsilon of the energy storage unit capacity is calculated as:
wherein m is p To store the construction cost of each kilowatt of power, m om The annual operating cost per kw power is maintained; l is the energy storage life in units ofYears of life; m is m s As construction costs for capacity per kilowatt-hour, they will vary with advances in technology; q is the total recycling times of the energy storage; p (P) Storage,N And S is Storage,N The rated power and rated capacity of the energy storage in the cloud are respectively the sum of the rated power and rated capacity of the distributed energy storage of all users and the concentrated energy storage built by investment of operators, and the rated power of the energy storage of the ith user is assumed to be P Storage,i,N Rated capacity S Storage,i,N Then there are:
wherein P is CO,N Configuring rated power of energy storage for a cloud energy storage manufacturer; e (E) CO,N And configuring rated capacity of energy storage for the cloud energy storage manufacturer. Setting the energy storage requirement of investment construction of operators to meet the constraint of energy storage multiplying power, namely:
wherein eta is CO Is the energy multiplying power of the energy storage battery.
Further, the energy storage operation constraint comprises a charge and discharge power constraint, a capacity constraint, a power balance constraint and the like, and the energy storage operation constraint comprises the following constraints:
-P Storage,N ≤P Storage,t ≤P Storage,N (6)
0.17S Storage,N ≤S Storage,t ≤0.9S Storage,N (7)
P Storage,t ＝P Grid,t +P New,t -P Load,t (8)
S Storage,t ＝S Storage,t-1 -h[(η C P Storage,t ) - +(P Storage,t /η D ) + ] (10)
wherein S is Storage,t For the electric quantity stored in the cloud at the t-th moment, considering that the full charge and discharge are not allowed to be fully carried out for prolonging the service life of the energy storage battery, the lower limit of the electric quantity is set to be 0.17S N The upper limit is 0.9S Storage,N The method comprises the steps of carrying out a first treatment on the surface of the The running power of the energy storage is balanced with the output power of the power grid, the power generated by the new energy and the load power, P New,t Representing total power generated by new energy in cloud energy storage at t moment, P Load,t Representing the total load in the cloud at the t-th moment; s is S Storage,1 、For the initial capacity and the final capacity of the energy storage in the scheduling period, balancing is needed; electric quantity S of energy storage battery in cloud at t time Storage,t For the previous time of the electric quantity S Storage,t-1 Adding the charge-discharge power, eta, taking charge-discharge efficiency into consideration at time t C Represents the energy storage and charging efficiency eta D Representing the energy storage discharge efficiency, operation (.) + And ( - Is defined as
Linearizing nonlinear constraint by using a Big-M method, converting the nonlinear constraint into a constraint condition formula, wherein the whole can be expressed as:
in U C,t And U D,t Respectively represent the charge and discharge state bits of the cloud energy storage, when U D,t The value of 1 represents discharge of the energy storage device to the user, the value of 0 represents no discharge to the user, U C,t And the same is done; two charge and discharge status bits are used to ensure that charge and discharge cannot be performed simultaneously in the same period; m represents a sufficiently large constant for representing the activation state of the constraint.
To restrict nonlinearity to linearityAfter the chemical processing, a linear solver can be adopted, a YALMIP tool kit in Matlab software is adopted, and a CPLEX solver is called to realize rated power P of energy storage in the cloud Storage,N And rated capacity S Storage,N Solving the optimal value, and calculating the unknown number in the equation according to the formula (4) to obtain the rated power P of the cloud energy storage operator needing investment construction configuration energy storage CO,N And rated capacity E CO,N As a result. Taking 5 typical large industrial users participating in cloud energy storage as examples, the types are respectively in a late peak type, a double peak type, a single peak type, a stable type and a peak avoidance type, and a construction mode schematic diagram is shown as a figure 1, wherein the late peak type users have photovoltaic with installed capacity of 400kW, and energy storage resources of 1, 80kW/240kWh; bimodal users possess an energy storage of 2, 120kW/360kWh; the unimodal users have a wind power resource with a installed capacity of 250 kW. The peak valley price of the power grid in the region is shown in fig. 2, the load curve of each user on a typical day, the predicted new energy power generation curve is shown in fig. 3, specific parameters are shown in table 1, and the total load and the total photovoltaic power of the users on a typical day in the mode are shown in fig. 4.
TABLE 1 cloud energy storage detail parameters
The configuration result is used for obtaining the optimal energy storage capacity planning value S of the energy storage in the cloud Storage,N At 972.47kWh, the optimal energy storage charge-discharge power rating P Storage,N For 324.16kW, the rated power and rated capacity of distributed energy storage of users in the cloud are known, so that the rated power P of energy storage which needs investment, construction and configuration of cloud energy storage operators is obtained CO,N Rated capacity E of 124.16kW CO,N Results the configuration result was 372.47kWh.
The relationship curve of the configured energy storage power and the total cost of typical daily social energy consumption and the number of times of daily charging and discharging is shown in fig. 5, and it can be seen that at the optimal energy storage configuration point, the total cost of daily social energy consumption can be minimized, and the daily charging and discharging can be realized, so that the energy storage value is reasonably and fully exerted.
Step 2: and the entity carrier performs energy storage day-ahead optimal scheduling according to the day load curves of all cloud users collected day-ahead, the new energy power generation predicted by the entity carrier and the owned cloud internal distributed and centralized energy storage set. The method specifically comprises the following steps:
1) And predicting the power generation amount of new energy sources in the cloud at each time of a dispatching day, and respectively calculating the power generation power of different types of new energy sources such as photovoltaic, wind power and the like.
Predicting the power generation amount of new energy in cloud at each time of scheduling day by P New,t And (5) representing the new energy generating capacity at the t-th moment of the scheduling day. And reasonably assuming that all new energy sources are in the same region, the generated power ratio of the new energy sources at the t moment of the ith user is consistent with the installed capacity ratio of the new energy sources.
The power generation power of different types of new energy sources such as photovoltaic power, wind power and the like needs to be calculated respectively, N users are arranged in the cloud, and the power generation power of the new energy source of the user i at the t moment is P New,i,t The following steps are:
2) And (5) counting the load at each time of the scheduling day in the cloud.
By P Load，i，t Representing the load of the ith user at the ith moment, P Load，t Indicating the cloud load at time t of the adjustment day, there are
3) Based on the load and the new energy power generation amount at each moment, under various constraint conditions of energy storage operation, energy storage optimization scheduling is carried out with the maximum peak clipping and valley filling benefits of the power grid as targets.
The operation power of the energy storage is balanced with the output power of the power grid, the generation power of the new energy and the load power, wherein the operation constraint of the energy storage comprises the constraint of charge and discharge power, the constraint of capacity and the constraint of preferentially absorbing the new energy in the cloud.
Based on the load and the new energy generating capacity at each moment, under various constraint conditions of energy storage operation, peak clipping and valley filling benefits F from the power grid are taken into consideration 1 And optimally scheduling energy storage for the maximum purpose. The method comprises the following steps:
wherein T represents the total number of time points in the scheduling day; purchase price m with electric network Grid The definition is the same as equation (2) and the relevant constraints for energy storage operation are the same as equations (6-11). In one embodiment, the model is solved, an energy storage scheduling instruction is output, and a CPLEX solver is called to solve by adopting a YALMIP tool kit in Matlab software.
In order to verify the effectiveness and rationality of the energy storage scheduling operation optimization model of the embodiment, taking 5 typical large industrial users participating in cloud energy storage as an example, the load curve of each user on a certain scheduling day and the predicted new energy power generation interval curve are shown in fig. 6, and the total load and the total photovoltaic power of the users in the model are shown in fig. 7.
By adopting the cloud energy storage day-ahead scheduling method, the charge and discharge conditions of the whole cloud energy storage and the electricity purchasing and selling conditions to the power grid can be solved, and the result is shown in figure 8. If the late peak user and the bimodal user independently operate, the same scheduling strategy is adopted, and the charging and discharging conditions of the stored energy are shown in fig. 9.
Therefore, in the cloud energy storage mode constructed by the application, energy storage 1 and 2 are charged and discharged two by two on the dispatching day, the utilization rate is high, the energy storage is charged at the low electricity price at one time and discharged at the low price, and the photovoltaic power generation is insufficient to meet the load demand; and the charging is performed at the peak of sufficient electricity price of the photovoltaic power generation for the second time, the income of the photovoltaic power generation is increased, and finally the discharging is performed at the peak moment of the electricity price, so that the electricity grid electricity purchasing quantity at the peak moment is reduced as much as possible, and the purposes of energy storage, peak clipping and valley filling are realized. Under independent operation, the two stored energy sources are not fully utilized because of load limitation or the need of storing new energy sources.
After participating in cloud energy storage, for a late peak type user, the first energy storage charging and discharging period which cannot be fully exerted by the owned energy storage 1 under independent operation is fully exerted, the energy storage charging and discharging energy charge is acquired, and the new energy selling price is improved, so that the income is more satisfied; for the double-peak type user, the electricity purchasing of the owned energy storage 2 at the second energy storage charging moment is direct absorption of new energy in the cloud energy storage mode, and the new energy price is lower than the electricity purchasing price of the power grid, so that the peak clipping and valley filling benefits of the second charging and discharging stage are improved, and the energy storage benefits can be obtained through the calling of other users in the second discharging stage which is not used for charging and discharging originally.
Furthermore, the scheduling method uniformly considers all loads, new energy and energy storage in the cloud, and has the following advantages compared with the respective consideration of each user:
1) The identity of a user with physical energy storage can be flexibly switched between different periods of the same day, regardless of whether the user is an energy storage provider or a consumer.
2) The energy storage charging and discharging time periods of all users in the cloud cannot conflict, namely the existing energy storage charging and existing energy storage discharging conditions cannot occur at a certain moment, the charging and discharging amount of the energy storage is reduced to the greatest extent, and the service life of the energy storage is prolonged.
3) After the total consideration of the energy storage in the cloud, the use and settlement of the entity energy storage can be separated. The energy storage module can be recycled in sequence, so that the total charge and discharge times of energy storage of each entity are reduced, and the service life is prolonged; and the energy storage benefits are distributed according to the rated power of the physical energy storage, the rated capacity is the constraint of the charge and discharge capacity, and the benefits are fair.
4) And each user in the cloud only needs to report the daily load demand quantity, but does not need to report the price, and a leasing mode is not adopted, so that the energy storage utilization rate and the new energy consumption rate can be improved, and the scheduling can be simplified.
5) The new energy internet electricity price executes the local coal reference price, and the user cannot directly obtain peak-valley difference benefits through energy storage and new energy, but can internally obtain the partial benefits by utilizing a cloud energy storage mode.
Step 3: and 2, the purchase and sale power of the cloud and the power grid at each moment of the dispatching day can be solved, and the settlement method separated from the dispatching is adopted to perform the cloud settlement with fairness. The method comprises the following specific steps:
1) And calculating the electricity purchasing and selling cost paid to the power grid by the dispatching date.
The cloud energy storage day-ahead dispatching model can be used for solving the purchase and sale electric power P in the cloud and at each moment of dispatching day of the power grid Grid,t 。
Electricity purchasing and selling expense F paid to power grid on schedule Grid The method comprises the following steps:
2) And calculating the electricity selling cost of the new energy.
In order to enable a new energy provider to obtain price difference benefits by participating in a cloud energy storage mode, the new energy price is assumed to be related to the electricity price of a power grid, and when the new energy price is valley price, the new energy price is a coal-fired reference price; and at other moments, the power cost of the power grid is w times.
Electricity selling cost F of new energy New The method comprises the following steps:
wherein m is New,t The electricity price of the new energy at the t-th moment in the cloud energy storage mode is obtained by a new energy provider, so that price difference income can be obtained by participating in the cloud energy storage mode, the price is assumed to be related to the electricity price of the power grid, and the price is a coal-fired reference price when the price is valley; and at other moments, the power cost of the power grid is w times.
3) And calculating charge and discharge benefits of the stored energy. The method of obtaining the same fixed benefit by charging and discharging the energy storage is adopted, namely the charge and discharge amount cost of the energy storage. Counting the charge-discharge switching times of the stored energy in a dispatching day; and each energy storage is subjected to profit distribution according to a relative fairness principle, and a settlement mode separated from scheduling is adopted. If a user has energy storage, the energy storage benefit will be related to the rated power and capacity of the energy storage.
The income obtained by charging and discharging the energy storage is calculated according to the ideal electricity price at the time of charging and discharging, but when the load in the cloud is used by taking into account the energy storage discharging, the electricity price of the load is not yet determined, so that the same fixed income is obtained by adopting the method of charging and discharging the energy storage, namely the charge and discharge amount cost F of the energy storage Storage The method comprises the following steps:
wherein m is Storage Charging and discharging price for storing energy for user, m Storage,CO The two types of energy storage charge and discharge fees charged by operators are stable in price, but can be different, the charge and discharge fees can be generated during charge and discharge, reasonable pricing is needed to achieve the purpose that an energy storage owner obtains benefits, and if the price is too high, the energy storage owner can give up using.
4) And calculating and adjusting the load cost in the cloud of days. The cost of all the loads is balanced with the cost, and the loads are divided according to the ratio of the loads of all the users at all the time to the total load, and the cost F of the loads Load Balanced with the above costs, namely:
F Load ＝F Grid +F New +F Storage (18)
adjusting load fee F of ith user in cloud of days User,i,Load Dividing according to the ratio of the load of the user at each moment to the total load, wherein the formula is as follows:
5) And calculating the benefits of each user, including new energy benefits and energy storage benefits, and subtracting the load cost.
The stored energy is distributed according to the principle of relative fairness, and a settlement mode separated from scheduling is adopted. If the ith user has energy storage, the energy storage income R User,i,Storage Will be related to the stored energy power rating and capacity:
the energy storage capacity of the user can influence the using time of the energy storage, namely T i,Storage The values are different, specifically:
wherein S is Storage,i,0 Initial energy storage capacity for schedule day i user.
If the ith user has new energy, the income R of the new energy User,i,New The method comprises the following steps:
thus, the i-th user's benefit R on the scheduling day User,i The method comprises the following steps:
R User,i ＝F User,i,o -(F User,i,Load -R User,i,New -R User,i,Storage )-(C ES,i +C New,i ) (23)
wherein C is ES,i For the energy storage cost of user i on the scheduling day, C New,i For the new energy cost of the user i on the dispatching day, the two cost conversion methods are the same as the formulas (1) and (3), if the user does not have the resources, the corresponding item is 0; f (F) User,i,o And the energy consumption cost of independent operation of the ith user before the ith user participates in the cloud energy storage mode in the scheduling day is indicated. The users in the cloud can ensure balance of balance, and the benefits of energy storage and new energy sources in the cloud are both increased, so that the participation enthusiasm of the users can be attracted, otherwise, the users tend to participate in a pure-load identity participation mode without selecting to share own resources.
The settlement mode of the application assumes that the load demands of all users in the day are matched with the daily report, and the new energy power generation prediction is accurate. If deviation occurs in actual operation, the load deviation causes the change of the transaction cost with the power grid to be borne by the user, and the cost of the new energy source caused by the deviation is shared by the new energy source user due to higher prediction accuracy at present.
6) Calculating the benefits of an operator
The cloud energy storage operator is responsible for planning and scheduling, and reasonable energy storage configuration is carried out after the mode user determines, so that energy storage is newly built, the energy storage requirement of the user in the mode is met, and the cost recovery of self energy storage is realized. The objective function is net benefit, i.e. the difference between the energy storage service cost and the investment operation cost. Benefit R of CO Can be expressed as:
wherein ε CO The equivalent unit capacity loss price of energy storage is built for the cloud energy storage operator; c (C) CO The cost of the operator investment energy storage is converted into the adjustment day, and the calculation method is the same as the formula (1-3) and is not repeated; m is m Storage,CO Charging and discharging charge for energy storage charged by operator and charging and discharging price m of energy storage of user Storage The energy storage unit price obtained by the operators can be set higher, and the newly built energy storage income of the operators can be larger than the energy storage investment cost to obtain the income, f CO Representing the profitability of the operator setting, only if f CO >And 0, operators can benefit by investment in newly built energy storage. The mode gives consideration to the interests of all the main bodies, and in the development process of the mode, if an energy storage provider has a load, the energy storage provider can obtain the saving of the electric charge, and the energy storage service charge is lower; if no load exists, the energy storage service charge charged by the system is equivalent to that of an operator, and the energy storage cost can be guaranteed to be recovered.
Step 4: and determining the charge and discharge price of the stored energy and the internal selling price of the new energy.
The new energy electricity price and the energy storage charging and discharging price are key factors influencing the internal settlement of the cloud energy storage, when the settlement mode of the step 3 is adopted to prepare the transaction price, a Nash social benefit function W is introduced as an objective function, is the product of benefits or benefits of all the subjects, and the larger the value is, the more balanced the benefits of all the subjects are represented. For the operator, his benefit is chosen as net benefit; while for the user, the benefit is defined as the increase of the benefits after the user participates in cloud energy storage, the Nash social benefit function can be expressed as:
in order to ensure the new energy income, the internal selling price of the new energy is restricted to be not lower than the reference price of fire coal, namely:
w·m Grid,t ≥m Grids,base when t is not at the valley price (25)
According to the settlement mode of the step 3 and the formula (24), solving to obtain m Storage =0.24-membered kWh -1 ，m Storage,CO =0.42 yuan kWh -1 And w=0.48, the greatest social benefit can be obtained. At this time, the settlement results of the respective users are shown in table 2. When each user independently operates, the energy storage user performs optimal scheduling according to the formula step 2, the energy storage, the new energy and the load only consider the self situation, the non-energy storage user calculates according to the power grid electricity price, and each cost is shown in the table 3.
Table 2 cloud energy storage settlement results
TABLE 3 Settlement results operated independently
Comparing table 2 and table 3, it can be found that after all users participate in cloud energy storage, the total electricity purchasing cost is reduced, and the profits of having energy storage or new energy resources are all improved in the cloud energy storage mode, and the expenditure costs in independent operation are reduced by 69.52%, 31.6%, 24.2%, 9.1% and 9.1% respectively, and on the scheduling day, the profit of the operator is 456.80 yuan, and the profit coefficient is 28.3%, which indicates that the operator can obtain better energy storage charging and discharging cost profits, thereby completing the recovery of the energy storage cost more quickly. Because the cost of energy storage, namely new energy resources, is considered in the mode, the benefit of resource owners is guaranteed in relatively balanced income settlement, and the mode can be developed more continuously.
Fig. 10 is a schematic diagram of a cloud energy storage mode construction device based on an entity operator according to an embodiment of the present application; the device comprises:
the centralized energy storage optimizing configuration module is used for the entity operator to make a centralized energy storage optimizing configuration decision according to the collected information of the distributed energy storage devices of the users in the cloud, the typical daily load curves of all the users participating in the cloud energy storage and the typical new energy power generation curve of the region.
The energy storage day-ahead optimization scheduling module is used for carrying out energy storage day-ahead optimization scheduling according to day load curves of all cloud users collected in the day ahead and new energy power generation and owned cloud energy storage devices predicted by an entity operator;
the cloud settlement module is used for carrying out cloud settlement by adopting a settlement mode separated from scheduling according to the purchase and sale power of the cloud and the power grid at each moment of the scheduling day;
and an objective function solving module: the cloud energy storage system is used for introducing a Nash social welfare function as an objective function and determining the energy storage charge and discharge price and the new energy internal sales price, so that the construction of a cloud energy storage mode is completed.
Embodiments of the computing apparatus of the present application may be applied to a network device. The apparatus embodiments may be implemented by software, or may be implemented by hardware or a combination of hardware and software. Taking software implementation as an example, the device in a logic sense is formed by reading corresponding computer program instructions in a nonvolatile memory into a memory through a processor of a device where the device is located, and the computer program is used for executing a cloud energy storage mode construction method based on an entity operator. In terms of hardware level, as shown in fig. 11, a hardware structure diagram of the cloud energy storage mode building device based on the entity operator according to the present application is shown, where the device may generally include other hardware besides the processor, the network interface, the memory and the nonvolatile memory shown in fig. 11, so as to extend at the hardware level. On the other hand, the application also provides a computer readable storage medium, and the storage medium stores a computer program which executes a cloud energy storage mode construction calculation method based on an entity operator.
For computing device embodiments, as they substantially correspond to method embodiments, reference is made to the description of method embodiments for relevance. The device embodiments described above are illustrative only and will be understood and practiced by those of ordinary skill in the art without undue burden.
In summary, the application provides a method, a device, equipment and a storage medium for constructing a cloud energy storage mode based on an entity operator, which aim to optimally configure and optimally schedule energy storage with the maximum overall benefits of peak clipping and valley filling, and reasonably set the charge and discharge price of the energy storage and the internal selling price of the new energy by adopting a relatively fair, easy-to-understand and-apply and separate settlement mode from scheduling on the basis of balancing internal balance and guaranteeing the basic benefits of the energy storage and the new energy, so that each user participating in cloud energy storage can obtain benefits, and sustainable development of the cloud energy storage mode is ensured. Based on cloud energy storage modes of entity operators, different types of users are aggregated, two charges and two discharges of energy storage can be achieved, and the utilization rate and efficiency of the energy storage are improved.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. The specification and examples are to be regarded in an illustrative manner only.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The foregoing description of the preferred embodiments of the application is not intended to be limiting, but rather to enable any modification, equivalent replacement, improvement or the like to be made within the spirit and principles of the application.

Claims (10)

1. The cloud energy storage mode construction method based on the entity operators is characterized by comprising the following steps of:
step 1: the entity operator carries out centralized energy storage optimization configuration decision according to the typical daily load curve, the typical new energy power generation curve and the distributed energy storage device information configured by the users in the cloud, which are collected through investigation;
step 2: the entity carrier performs energy storage day-ahead optimization scheduling according to the day load curves of all cloud users collected day-ahead and the new energy power generation and the owned in-cloud energy storage device predicted by the entity carrier;
step 3: solving the purchase and sale power of the cloud and the power grid at each moment of a dispatching day by the step 2, and carrying out the settlement in the cloud by adopting a settlement mode separated from the dispatching;
step 4: and introducing a Nash social welfare function as an objective function, and determining the energy storage charge and discharge price and the new energy internal sales price, thereby completing the construction of a cloud energy storage mode.
2. The cloud energy storage mode construction method based on the entity operator according to claim 1, wherein: the step 1 specifically comprises the following steps:
1) Selecting the generated energy and the generated power of new energy in cloud at each time of a typical day;
2) Counting the load of each time of a typical day in the cloud;
3) Based on the load and the new energy power generation amount at each moment, under various constraint conditions of energy storage operation, the configuration optimization decision of energy storage is carried out with the aim of minimizing the total cost of social energy consumption.
3. The cloud energy storage mode construction method based on the entity operator according to claim 1, wherein: the step 2 specifically comprises the following steps:
1) Predicting the power generation amount and the power generation power of new energy in cloud at each time of a scheduling day;
2) Counting the load of each time of a scheduling day in the cloud;
3) Based on the load and the new energy power generation amount at each moment, under various constraint conditions of energy storage operation, energy storage optimization scheduling is carried out with the maximum peak clipping and valley filling benefits of the power grid as targets.
4. A method for constructing a cloud energy storage model based on an entity operator according to claim 2 or 3, wherein: the constraint conditions of energy storage operation comprise charge and discharge power constraint, capacity constraint and constraint of prior absorption of new energy in cloud.
5. The cloud energy storage mode construction method based on the entity operator according to claim 1, wherein: the step 3 specifically comprises the following steps:
1) Calculating electricity purchasing and selling cost paid to the power grid on a dispatching day;
2) Calculating electricity selling cost of new energy;
3) Calculating charge and discharge benefits of energy storage;
4) Calculating and adjusting the load cost in the cloud of days;
5) Calculating the income of each user;
6) And calculating the benefits of the cloud energy storage operators.
6. The cloud energy storage mode construction method based on the entity operator according to claim 5, wherein: in the process of calculating the electricity selling cost of the new energy, in order to enable a new energy provider to obtain price difference income through participating in a cloud energy storage mode, the new energy price is assumed to be related to the electricity price of a power grid, and when the new energy price is valley price, the new energy price is a coal-fired reference price; and at other moments, the electricity fee of the power grid is multiple times.
7. The cloud energy storage mode construction method based on the entity operator according to claim 6, wherein: in the process of calculating charge and discharge benefits of the energy storage, adopting a mode of obtaining the same fixed benefits by charging and discharging of the energy storage, namely charging and discharging amount cost of the energy storage;
counting the charge-discharge switching times of the stored energy in a dispatching day; the energy storage distributes benefits according to a relatively fair principle; if a user has stored energy, the energy storage profit of the user is related to the rated power and capacity of the stored energy by adopting a settlement mode separated from scheduling.
8. Cloud energy storage mode construction device based on entity operator, characterized by comprising:
the centralized energy storage optimizing configuration decision-making module is used for carrying out centralized energy storage optimizing configuration decision-making according to the typical daily load curves of all cloud users collected by investigation, the typical new energy power generation curve of the area and the distributed energy storage device information configured by the users in the cloud;
the energy storage day-ahead optimization scheduling module is used for carrying out day-ahead optimization scheduling on the energy storage according to day load curves of all cloud users collected in the day ahead, new energy power generation predicted by the entity and the distributed energy storage of the owned cloud users and the centralized energy storage configured by the entity;
the cloud settlement module is used for carrying out cloud settlement by adopting a settlement mode separated from scheduling according to the purchase and sale power of the cloud and the power grid at each moment of the scheduling day;
and an objective function solving module: the cloud energy storage system is used for introducing a Nash social welfare function as an objective function and determining the energy storage charge and discharge price and the new energy internal sales price, so that the construction of a cloud energy storage mode is completed.
9. Cloud energy storage mode construction equipment based on entity operator, characterized by comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for building a cloud energy storage model based on an entity operator according to any one of the preceding claims 1-7 when executing the program.
10. A computer readable storage medium, characterized in that the storage medium stores a computer program for executing the entity operator based cloud energy storage mode construction method according to any of the preceding claims 1-7.
CN202310845557.4A 2023-07-11 2023-07-11 Cloud energy storage mode construction method and device based on entity operators Pending CN116885800A (en)

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