CN115000985A - Aggregation control method and system for user-side distributed energy storage facilities - Google Patents
Aggregation control method and system for user-side distributed energy storage facilities Download PDFInfo
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- CN115000985A CN115000985A CN202210456405.0A CN202210456405A CN115000985A CN 115000985 A CN115000985 A CN 115000985A CN 202210456405 A CN202210456405 A CN 202210456405A CN 115000985 A CN115000985 A CN 115000985A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Abstract
The invention provides a method and a system for aggregation control of user-side distributed energy storage facilities, which comprise the following steps: acquiring information of all accessed distributed energy storage facilities and a power grid interaction target of each application scene; performing characteristic analysis on the information of each distributed energy storage facility to obtain the adjustment condition of each distributed energy storage facility in each application scene; aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scene; the method has the advantages that the adjusting instruction for managing and controlling the energy storage facility categories is generated based on the power grid interaction targets of the application scenes and the adjusting capacity of the distributed energy storage categories, the problems that distributed energy storage points on the user side are dispersed, the scale is small, the distributed energy storage points are difficult to effectively aggregate, and the distributed energy storage facilities cannot participate in power grid interaction can be effectively solved, the flexible adjusting characteristic of energy storage resources is exerted, the power balance level of the power distribution network is improved, clean energy power generation and consumption are promoted, and the power supply quality and reliability of the regional power distribution network are improved.
Description
Technical Field
The invention relates to the field of aggregation and control of distributed energy storage facilities on a user side of a power distribution network, in particular to a method and a system for aggregation control of distributed energy storage facilities on the user side.
Background
At present, new energy is rapidly developed, and the characteristics of double-high and double-peak (high proportion renewable energy, power electronic equipment; load peak in summer and winter) of a power system are highlighted in one step. The randomness, the volatility and the anti-peak regulation characteristic of new energy enable the net load of a system to be changed greatly, and huge pressure is brought to the balance of electric power and electric quantity. The electrochemical energy storage has rapid bidirectional flexible adjustment capability, can be widely permeated into each link of power generation, power transmission and power distribution, improves the flexibility of the power system, and becomes an optimal scheme for solving the problem of a novel power system taking new energy as a main body. By the end of 2020, the cumulative electrochemical energy storage installed scale of China is 3269.2 MW. With the further development of new energy, the scale of user-side distributed energy storage will grow explosively in the future.
The user side energy storage comprises various forms such as user side independent energy storage, distributed photovoltaic + energy storage, distribution network side energy storage and electric automobiles, and has the characteristics of small scale, multipoint dispersion and individual camping. At present, various energy storage facilities mainly control local operation, energy storage facilities and energy storage and other power supplies cannot effectively cooperate, and the charge-storage interaction of a user side source network is difficult; meanwhile, the scale of the energy storage at the user side is small, so that the minimum capacity requirement of power grid interaction such as power peak regulation, demand response and the like is difficult to meet, and the flexible adjusting capability of the distributed energy storage at the user side cannot be effectively utilized.
Disclosure of Invention
In order to solve the problems that distributed energy storage at a user side of a power distribution network is difficult to effectively aggregate, source network load storage interaction is difficult, and the distributed energy storage at the user side cannot participate in power grid interaction in the prior art, the invention provides a method for aggregation control of distributed energy storage facilities at the user side, which comprises the following steps:
acquiring information of all accessed distributed energy storage facilities and a power grid interaction target of each application scene;
performing characteristic analysis on the information of each distributed energy storage facility to obtain the adjustment condition of each distributed energy storage facility in each application scene;
aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scene;
and generating an adjusting instruction for managing and controlling each energy storage facility category based on the power grid interaction target of each application scene and the adjusting capacity of each distributed energy storage category.
Preferably, the adjusting condition of each distributed energy storage facility includes: maximum adjustable power up, maximum adjustable power down and adjustment time.
Preferably, the maximum adjustable power increase is calculated according to the following formula:
ΔP adj,up ＝P d,max -P curr
in the formula,. DELTA.P adj,up The maximum adjustable power increase is carried out on the energy storage facility; p d,max The maximum discharge power of the energy storage facility; p curr Is the current power of the energy storage facility;
the maximum adjustable derated power is calculated as:
ΔP adj,down ＝P c,max -P curr
in the formula,. DELTA.P adj,down The maximum adjustable power reduction for the energy storage facility; p c,max The maximum discharge power of the energy storage facility; p curr Is the current power of the energy storage facility;
the adjustment time is calculated as follows:
in the formula, T adj Adjusting the corresponding adjusting time of the power delta P for the energy storage facility; Δ P is the regulated power; q spe Rated capacity for energy storage; SOC is a state of charge; p curr Is the current power of the energy storage facility; p d,max Maximum allowable discharge power for the energy storage facility; p c,max And the maximum allowable charging power of the energy storage facility is obtained.
Preferably, the adjusting range of the adjusting power is determined according to the following formula:
ΔP adj,down ≤ΔP≤ΔP adj,up
in the formula,. DELTA.P adj,down The maximum adjustable power reduction for the energy storage facility; delta P adj,up And the maximum adjustable power increase is realized for the energy storage facility.
Preferably, the aggregating all the distributed energy storage facilities based on the adjustment conditions of all the distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scenario includes:
constructing a clustering feature set based on all distributed energy storage facilities, information of the distributed energy storage facilities and clustering index sets set for each application scene;
based on the clustering feature set, calculating the distance between every two distributed energy storage facilities in the clustering feature set, and constructing a proximity matrix:
based on the proximity matrix, clustering the distributed energy storage facilities by using K-MEANS, and determining the adjusting capacity of each distributed energy storage category;
wherein the adjustment capability comprises: power regulation capability, and regulation response time;
the application scenario includes at least one or more of the following: participating in power grid frequency modulation, participating in power grid peak shaving and participating in demand response.
Preferably, the constructing a clustering feature set based on all the distributed energy storage facilities, the information of the distributed energy storage facilities, and the clustering index set for each application scenario includes:
constructing a facility set based on all accessed distributed energy storage facilities:
constructing a clustering characteristic index set of the energy storage facilities based on the information and the adjustment condition of all the accessed distributed energy storage facilities:
constructing an initial set based on the facility set and the index set;
and constructing a clustering feature set based on the clustering index set and the initial set for each application scene.
Preferably, the cluster feature set is as follows:
in the formula, M is a clustering feature set; AS is an initial set; IN is a clustering characteristic index set; ST (ST) i For the ith distributed energy storage facility, CT i The cluster characteristic index of the ith item; m is a group of l The characteristic value of the first distributed energy storage facility is obtained; v. of ij The value of the jth characteristic index of the ith distributed energy storage facility is obtained; IN k The parameter is the k-th characteristic index; n is the number of aggregated energy storage facilities, and m is the number of clustering characteristic indexes.
Preferably, the power regulation capability of each distributed energy storage category is calculated according to the following formula:
in the formula,. DELTA.P ass,i Power conditioning capability for the ith category; delta P j Adjustable power for the jth distributed energy storage implementation in the classification; o is the number of distributed energy storage facilities in the classification;
the electric quantity regulating capacity of each distributed energy storage category is calculated according to the following formula:
in the formula,. DELTA.Q ass,i Capacity adjustment for the ith class; delta Q j An adjustable amount of power implemented for the jth distributed energy storage in the classification;
the adjustment response time of each distributed energy storage type is calculated according to the following formula:
in the formula, t ass,i An adjustment response time for the ith class; t is t j The adjustment response time implemented for the jth distributed energy store in this classification.
Preferably, the generating of the adjusting instruction for controlling each energy storage facility category based on the power grid interaction target of each application scenario and the adjusting capability of each distributed energy storage category includes:
converting the interactive target of each application scene into each adjusting capacity, and setting the maximum adjusting response time;
determining an objective function by taking the optimal economy as a target, and setting constraint conditions for the objective function;
solving the objective function based on the adjusting capacities, the maximum adjusting response time and the constraint condition to obtain the adjusting capacity values of the distributed energy storage classifications;
and taking each adjusting capacity value of each distributed energy storage classification as a control instruction of each distributed energy storage classification.
Preferably, the objective function is as follows:
f＝min{c 1,i ×ΔP i +c 2,i ×ΔQ i }
the constraint is as follows:
in the formula, c 1,i Adjusting costs for the power of the ith class; c. C 2,i Adjusting costs for the ith classified power; delta P i A regulated power provided for the ith class; delta Q i A regulated amount of power provided for the ith category; t is t i The adjusted response time for the ith class.
Preferably, the acquiring distributed energy storage facility information of all accesses includes:
acquiring information of each distributed energy storage facility based on a pre-constructed distributed energy storage data model;
the distributed energy storage data model comprises: basic information, control characteristics, operation information and regulation and control information;
the basic information includes at least one or more of the following: facility type, energy storage medium, voltage class, rated capacity, rated power, commissioning date, owner and the aggregator it belongs to;
the control characteristics include at least one or more of: whether controllable, charge response time, discharge response time, charge regulation time, discharge regulation time, charge-to-discharge transition time, and discharge-to-charge transition time;
the operation information comprises at least one or more of the following: operating state, state of charge, charge power, discharge power, charge amount, and discharge amount;
the regulatory information includes at least one or more of: controlled state, chargeable amount, dischargeable amount, maximum discharge power allowable value, maximum charge power allowable value, maximum discharge power available time, and maximum charge power available time.
Based on the same inventive concept, the invention also provides a user-side distributed energy storage facility aggregation control system, which comprises:
the access layer is used for acquiring information of all accessed distributed energy storage facilities and power grid interaction targets of all application scenes;
the application layer is used for performing characteristic analysis on the information of each distributed energy storage facility to obtain the adjustment condition of each distributed energy storage facility in each application scene; aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scene; and generating an adjusting instruction for managing and controlling each energy storage facility category based on the power grid interaction target of each application scene and the adjusting capacity of each distributed energy storage category.
Preferably, the system further comprises a device layer;
the device layer comprises an accessed distributed energy storage facility;
and the access layer is used for acquiring information of all accessed distributed energy storage facilities and power grid interaction targets of all application scenes based on the equipment layer.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention provides a method and a system for aggregation control of user-side distributed energy storage facilities, which comprise the following steps: acquiring information of all accessed distributed energy storage facilities and a power grid interaction target of each application scene; performing characteristic analysis on the information of each distributed energy storage facility to obtain the adjustment condition of each distributed energy storage facility in each application scene; aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scene; generating an adjusting instruction for managing and controlling each energy storage facility category based on the power grid interaction target of each application scene and the adjusting capability of each distributed energy storage category, so that distributed energy storage aggregation can participate in power grid interaction, the problems that power peak regulation service and demand response threshold are high and distributed energy storage cannot participate are solved, energy storage cost is effectively dredged, and the flexible adjusting resource characteristic of energy storage is fully exerted;
2. the technical scheme provided by the invention can also realize the wide access of various types of distributed energy storage facilities, effectively polymerize decentralized distributed energy storage resources and solve the problem of distributed energy storage coordination control;
3. the technical scheme provided by the invention can also realize that distributed energy storage participates in source network charge storage interaction, active power regulation and the like, the flexible regulation characteristic of energy storage resources is exerted, the power balance level of the power distribution network is improved, the power generation and consumption of clean energy are promoted, and the power supply quality and reliability of the regional power distribution network are improved;
4. the technical scheme provided by the invention can effectively solve the problems that distributed energy storage multipoint at the user side is dispersed, the scale is small, the distributed energy storage multipoint is difficult to be effectively aggregated and the distributed energy storage multipoint cannot participate in power grid interaction.
Drawings
Fig. 1 is a flowchart of a method for aggregation control of a user-side distributed energy storage facility according to the present invention;
FIG. 2 is a schematic diagram of a distributed energy storage data model;
FIG. 3 is a schematic view of operational signature analysis;
fig. 4 is an architecture diagram of a user-side distributed energy storage facility aggregation management and control system according to the present invention.
Detailed Description
For a better understanding of the present invention, reference is made to the following description taken in conjunction with the accompanying drawings and examples.
Example 1:
the method for aggregation control of user-side distributed energy storage facilities provided by the present invention, as shown in fig. 1, includes:
s1, acquiring information of all accessed distributed energy storage facilities and power grid interaction targets of all application scenes;
s2, performing characteristic analysis on the information of each distributed energy storage facility to obtain the adjustment condition of each distributed energy storage facility in each application scene;
s3, aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scene;
and S4, generating an adjusting instruction for controlling each energy storage facility type based on the power grid interaction target of each application scene and the adjusting capacity of each distributed energy storage type.
The method has important significance for effectively aggregating various distributed energy storage resources, widely participating in power grid interaction, promoting power and electric quantity balance of the power distribution network and ensuring safe and reliable operation of the power distribution network.
In step S1, obtaining information of each distributed energy storage facility through a pre-constructed distributed energy storage data model;
as shown in fig. 2, the distributed energy storage data model includes: basic information, control characteristics, operation information and regulation information;
the basic information comprises at least one or more of the following: facility type, energy storage medium, voltage class, rated capacity, rated power, commissioning date, owner and the aggregator it belongs to;
the control characteristics include at least one or more of: whether controllable, charge response time, discharge response time, charge regulation time, discharge regulation time, charge-to-discharge transition time, and discharge-to-charge transition time;
the operation information comprises at least one or more of the following: operating state, state of charge, charging power, discharging power, charge amount, and discharge amount;
the regulatory information includes at least one or more of: controlled state, chargeable amount, dischargeable amount, maximum discharge power allowable value, maximum charge power allowable value, maximum discharge power available time, and maximum charge power available time.
The distributed energy storage data model is constructed, so that the informationized access of various distributed energy storage facilities can be realized, and the distributed energy storage data model is the basis of user-side distributed energy storage aggregation. The data model includes:
1. basic information, containing at least the following data items:
facility types: user side independent energy storage, distributed photovoltaic configured energy storage, distribution network side energy storage and electricity generation
Electric automobile charging pile and the like
Energy storage medium: lead acid, lithium ion, liquid flow, etc
Voltage class: 200(380) V, 10kV and the like
Rated capacity
Rated power
Delivery date
Seventhly, the owner
(iii) the aggregator
2. Control characteristics, comprising at least the following data items:
whether controllable: yes, no
Charging response time
Discharge response time
Charging time regulation
Discharge regulating time
Sixthly, charge-discharge conversion time
Seventhly, the conversion time from discharging to charging
3. The operation information at least comprises the following data items:
operating states: shutdown, standby, charge, discharge, fault, etc
State of charge (SOC)
Third charging power
Discharge power
Charge amount
Discharge capacity
4. The regulation and control information at least comprises the following data items:
the controlled state: remote control (discharging), remote control (charging), local control, etc
② chargeable quantity
(iii) dischargeable quantity
Maximum discharge power allowable value
Maximum allowable charging power value
Maximum discharge power available time
And the maximum available time of the charging power.
Step S2, performing characteristic analysis on the information of each distributed energy storage facility to obtain an adjustment condition of each distributed energy storage facility in each application scenario, specifically including:
and analyzing the operation characteristics of the distributed energy storage facility based on the data model.
The operation constraint and the adjustable capability of the distributed energy storage facility under different scenes are analyzed to obtain the adjustable power range and the adjustable time of the distributed energy storage facility, and the analysis result is shown in fig. 3, so that support is provided for various distributed energy storage aggregations. Here, the adjustment conditions of each distributed energy storage facility include: maximum adjustable power up, maximum adjustable power down and adjustment time.
1. The maximum adjustable power increase is calculated according to the following formula:
ΔP adj,up ＝P d,max -P curr
in the formula,. DELTA.P adj,up The power is increased for the maximum adjustable power (kW); p d,max Maximum discharge power (kW) for the energy storage facility; p curr The current power (kW) of the energy storage facility is negative during charging and positive during discharging.
2. The maximum adjustable reduction power is calculated according to the following formula:
ΔP adj,down ＝P c,max -P curr
in the formula,. DELTA.P adj,down Maximum adjustable power reduction (kW) for energy storage facilities; p c,max The maximum discharge power (kW) of the energy storage facility is a negative value; p curr The current power (kW) of the energy storage facility is negative during charging and positive during discharging.
3. The adjustment time is calculated according to the following formula:
in the formula, T adj Adjusting time (h) corresponding to the adjusting power delta P; the delta P is the adjusting power, the increasing time is a positive value, the decreasing time is a negative value, the adjusting range is delta P adj,down ≤ΔP≤ΔP adj,up ；Q spe Rated capacity for energy storage (kWh); SOC is state of charge (%); p curr The current power of the energy storage facility is discharged to a positive value; the charge is a negative value; p d,max Maximum allowable discharge power for the energy storage facility; p c,max Maximum allowable charging power for the energy storage facility; delta P adj,up And the maximum adjustable power increase is realized for the energy storage facility.
Step S3, aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scenario, which specifically includes:
1. all accessed user-side distributed energy storage facilities are constructed into a facility set ST:
ST＝{ST 1 ,ST 2 ,...,ST n }
2. based on a data model and an operation characteristic analysis result, constructing an energy storage facility clustering characteristic index set CT:
CT＝{CT 1 ,CT 2 ,...,CT m }
the CT item comprises an operation state, whether the operation state is controllable or not, charging response time, discharging response time, charging regulation time, discharging regulation time, charging-discharging conversion time, discharging-charging conversion time, SOC, adjustable power increasing and the like.
3. Constructing and forming an n multiplied by m initial set AS according to the facility set and the index set:
in the formula, v ij The j is the value of the j characteristic index of the ith distributed energy storage facility, i is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to m.
4. Aiming at application scenes that distributed energy storage aggregation participates IN power grid frequency modulation, peak regulation, demand response and the like, different clustering index sets IN are set:
IN the formula k Is the parameter of the kth characteristic index, and k is more than or equal to 1 and less than or equal to m.
5. Constructing a clustering feature set M according to the initial set AS and the clustering index set IN:
in the formula, M is a clustering feature set; AS is an initial set; IN is a clustering characteristic index set; ST (ST) i For the ith distributed energy storage facility, CT i Clustering feature index M for the ith item l Is the first distributionThe characteristic value of the energy storage facility is 1-m; v. of ij The value of the jth characteristic index of the ith distributed energy storage facility is obtained; IN k The parameter is the k-th characteristic index; n is the number of aggregated energy storage facilities, and m is the number of clustering characteristic indexes.
6. Calculating the distance between every two points according to the clustering feature set M, and constructing an adjacent matrix PM:
in the formula, s ij And the distance between the characteristic value of the ith distributed energy storage facility and the characteristic value of the jth distributed energy storage facility is more than or equal to 1 and less than or equal to n, and j is more than or equal to 1 and less than or equal to n.
7. And aiming at the PM of the adjacent matrix, a K-MEANS algorithm is used to realize that the distributed energy storage aggregation participates in clustering under different application scenes such as frequency modulation, peak regulation, demand response and the like.
8. And evaluating the electric power, the electric quantity regulation capability and the regulation response time of each distributed energy storage category, and providing a foundation for the distributed energy storage to participate in the interaction of the power grid.
Power regulation capability of ith classification:
in the formula,. DELTA.P ass,i Power regulation capacity (kW) for the ith classification; delta P j Calculating the adjustable power of the jth distributed energy storage implementation in the classification, wherein the adjustable power is equal to the maximum adjustable power increase when the adjustable capacity is increased, and the adjustable power is equal to the maximum adjustable power decrease when the adjustable capacity is decreased; and o is the number of distributed energy storage facilities in the classification.
Electric quantity adjusting capability of ith classification:
in the formula,. DELTA.Q ass,i For the ith classification of the quantity of electricityJoint capacity (kWh); delta Q j The adjustable amount of power implemented for the jth distributed energy storage in this classification is equal to the dischargeable amount when calculating the up-adjustable energy and equal to the chargeable amount when calculating the down-adjustable capacity.
Third, the ith classified adjustment response time:
in the formula, t ass,i An adjustment response time(s) for the ith class; t is t j The adjustment response time implemented for the jth distributed energy storage in the classification may be a charging response time, a discharging response time, a charging-to-discharging conversion time, a discharging-to-charging conversion time, or the like.
Step S4, generating an adjustment instruction for controlling each energy storage facility category based on the power grid interaction target of each application scenario and the adjustment capability of each distributed energy storage category, specifically including:
1. dividing interaction targets such as grid frequency modulation, peak shaving and demand response into electric power delta P tar Electric quantity delta Q tar Regulation capacity requirement, setting maximum regulation response time t max ；
2. The optimal economy is taken as a target, and constraint conditions are set for the target function;
the objective function is as follows:
f＝min{c 1,i ×ΔP i +c 2,i ×ΔQ i }
the constraints are as follows:
in the formula, c 1,i Adjusting costs (dollars/kW) for the power of the ith class; c. C 2,i Adjusting costs (dollars/kWh) for the electricity quantity of the ith classification; delta P i A provided regulated power (kW) for the ith class; delta Q i The provided regulated electrical quantity (kWh) for the ith class; t is t i Adjusted response for ith classTime(s).
3. Solving the objective function based on the adjusting capacities, the maximum adjusting response time and the constraint condition to obtain the adjusting capacity values of the distributed energy storage classifications; and determining the electric power and electric quantity adjusting instructions which meet the requirements of the distributed energy storage classification by taking the adjusting capacity values of the distributed energy storage classifications as the control instructions of the distributed energy storage classifications.
Example 2:
based on the same inventive concept, the invention also provides a user-side distributed energy storage facility aggregation management and control system, as shown in fig. 4, the system is composed of a facility layer, an access layer and an application layer, which are three layers of architectures:
facility layer: the system comprises a plurality of forms of distributed energy storage facilities such as user side independent energy storage, distributed photovoltaic and energy storage, distribution network side energy storage and electric automobile charging pile;
an access layer: the communication between a facility layer and an application layer is realized, and various distributed energy storage facilities can be accessed to the system in the forms of a user or energy enterprise self-building management system, a platform area intelligent fusion terminal, an acquisition terminal and the like;
an application layer: the method is used for deploying the distributed energy storage aggregation control system and realizing communication with other systems such as power distribution, marketing and electric quantity markets.
The facility layer supports aggregation control of various types of user-side distributed energy storage facilities, wherein the 'distributed photovoltaic + energy storage' refers to energy storage facilities configured according to requirements during construction of distributed photovoltaic, and the energy storage facilities and the distributed photovoltaic are operated jointly; the 'distribution network side energy storage' refers to energy storage facilities which are built by power enterprises and are installed at the positions of transformers, transformer substations and the like; the 'user side independent energy storage' refers to an independent operation energy storage facility installed inside a user.
The access layer supports a user side distributed energy storage facility to access the aggregation management and control system through a public network or a private network, and supports multiple access modes:
the first method is as follows: system level interconnect access
The aggregation management and control system is suitable for energy storage facilities which are accessed to a self-established management system of a user or an energy enterprise, the aggregation management and control system is communicated with the aggregation management and control system through a public network by providing a data interface, and the access of distributed energy storage facilities at the user side is realized;
the second method comprises the following steps: intelligent integrated terminal access of platform area
The intelligent integrated terminal is suitable for accessing various distributed energy storage facilities at a user side, the energy storage facilities are connected with the intelligent integrated terminal of the transformer area through various communication protocols such as a 104 protocol, HTTP, Modbus and the like, and the intelligent integrated terminal of the transformer area collects information and then communicates with an application layer through a private power network.
The third method comprises the following steps: dedicated acquisition terminal access
The system is suitable for accessing various distributed energy storage facilities at the user side, a special acquisition terminal is installed on the distributed energy storage facilities at the user side, and the special acquisition terminal is communicated with an application layer through a public network to realize the access of various distributed energy storage facilities at the user side.
The access layer, user side distributed energy storage facility and aggregation management and control system realize information communication through the access layer, and the content includes: uploading the state of charge (SOC), the charge and discharge power, the charge and discharge amount, the allowed maximum charge and discharge power, the adjustable increase/decrease charge and discharge power, the chargeable amount, the dischargeable amount and the like of the energy storage facility, and receiving control instructions such as the charge and discharge state, the charge and discharge power and the like issued by the aggregation management and control system.
And the application layer carries out monitoring and analysis on the running condition of the accessed distributed energy storage facility according to the distributed energy storage data model, and the monitoring and analysis include but are not limited to energy storage aggregation monitoring, running statistical analysis, active coordination control and the like. According to the aggregation control method, cluster division of different distributed energy storage facilities is achieved, the power and electric quantity adjusting targets are decomposed according to the requirements of frequency modulation, peak shaving, demand response and the like, and the distributed energy storage aggregation is achieved to participate in application of source network charge storage interaction, power auxiliary service, demand response and the like.
Energy storage polymerization monitoring: the method comprises the steps of monitoring the running states of various distributed energy storage facilities in real time, wherein the running states of the facilities (charging/discharging/standby/halt/fault and the like), the charging/discharging power, the charging/discharging amount, the battery SOC and the like.
Running statistical analysis: the statistical analysis of the running conditions of various distributed energy storage facilities is realized, and the statistical analysis comprises energy storage charging and discharging power, charging and discharging capacity, charging and discharging cycle efficiency, facility utilization rate, equivalent cycle coefficient and the like.
Active coordination control: according to the real-time operation state of the power distribution network, the new energy power prediction, the load prediction and the like, under the constraint condition that the system operation is met, the active power output of the distributed energy storage facility is optimized and adjusted, and the economic operation of the power distribution network is realized.
Source network load storage interaction: and responding to a marketing/dispatching master station control instruction, cooperatively interacting with distributed photovoltaic and various power loads in the region, and supporting safe and stable operation and clean energy consumption of the power distribution network.
Electric power auxiliary service: and aggregating various types of distributed energy storage at the user side, analyzing and evaluating the aggregated power regulation capacity, participating in power peak regulation service, and optimally decomposing the planned output curve to various energy storage facilities.
And (3) demand response: and aggregating various types of distributed energy storage at the user side to form an adjusting resource library, developing power grid demand response invitations, analyzing and evaluating response capabilities such as electric power and electric quantity, and participating in electric power demand response.
It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.
Claims (13)
1. A user side distributed energy storage facility aggregation control method is characterized by comprising the following steps:
acquiring information of all accessed distributed energy storage facilities and a power grid interaction target of each application scene;
performing characteristic analysis on the information of each distributed energy storage facility to obtain the adjustment condition of each distributed energy storage facility in each application scene;
aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scene;
and generating an adjusting instruction for controlling each energy storage facility category based on the power grid interaction target of each application scene and the adjusting capability of each distributed energy storage category.
2. The method of claim 1, wherein the adjusting of each distributed energy storage facility comprises: maximum adjustable power up, maximum adjustable power down and adjustment time.
3. The method of claim 2, wherein the maximum adjustable power increase is calculated as:
ΔP adj,up ＝P d,max -P curr
in the formula,. DELTA.P adj,up The maximum adjustable power increase is carried out on the energy storage facility; p d,max The maximum discharge power of the energy storage facility; p curr Is the current power of the energy storage facility;
the maximum adjustable derated power is calculated as:
ΔP adj,down ＝P c,max -P curr
in the formula,. DELTA.P adj,down The maximum adjustable power reduction for the energy storage facility; p c,max The maximum discharge power of the energy storage facility; p curr Is the current power of the energy storage facility;
the adjustment time is calculated as follows:
in the formula, T adj Adjusting the corresponding adjusting time of the power delta P for the energy storage facility; Δ P is the regulated power; q spe Rated capacity for energy storage(ii) a SOC is a state of charge; p curr Is the current power of the energy storage facility; p d,max Maximum allowable discharge power for the energy storage facility; p c,max And (4) the maximum allowable charging power of the energy storage facility is provided.
4. The method of claim 3, wherein the adjustment range for the adjustment power is determined as follows:
ΔP adj,down ≤ΔP≤ΔP adj,up
in the formula,. DELTA.P adj,down The maximum adjustable power reduction for the energy storage facility; delta P adj,up And the maximum adjustable power increase is realized for the energy storage facility.
5. The method according to claim 1, wherein the aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scenario comprises:
constructing a clustering feature set based on all distributed energy storage facilities, information of the distributed energy storage facilities and clustering index sets set for each application scene;
based on the clustering feature set, calculating the distance between every two distributed energy storage facilities in the clustering feature set, and constructing a proximity matrix:
clustering the distributed energy storage facilities by using K-MEANS based on the proximity matrix, and determining the adjusting capacity of each distributed energy storage category;
wherein the adjustment capability comprises: power regulation capability, and regulation response time;
the application scenario includes at least one or more of the following: participating in power grid frequency modulation, participating in power grid peak shaving and participating in demand response.
6. The method according to claim 5, wherein the constructing a cluster feature set based on all the distributed energy storage facilities, the information of the distributed energy storage facilities and the cluster index set for each application scenario comprises:
constructing a facility set based on all accessed distributed energy storage facilities:
constructing a clustering characteristic index set of the energy storage facilities based on the information and the adjustment condition of all the accessed distributed energy storage facilities:
constructing an initial set based on the facility set and the index set;
and constructing a clustering feature set based on the clustering index set and the initial set for each application scene.
7. The method of claim 6, wherein the set of cluster features is of the formula:
in the formula, M is a clustering feature set; AS is an initial set; IN is a clustering characteristic index set; ST (ST) i For the ith distributed energy storage facility, CT i The ith clustering characteristic index is used as the ith clustering characteristic index; m is a group of l The characteristic value of the first distributed energy storage facility is obtained; v. of ij The value of the jth characteristic index of the ith distributed energy storage facility is obtained; IN k The parameter is the k-th characteristic index; n is the number of aggregated energy storage facilities, and m is the number of clustering characteristic indexes.
8. The method of claim 5, wherein the power regulation capability of each distributed energy storage class is calculated as:
in the formula,. DELTA.P ass,i Power conditioning capability for the ith category; delta P j Adjustable power for the jth distributed energy storage implementation in the classification; o is the number of distributed energy storage facilities in the classification;
the electric quantity regulating capacity of each distributed energy storage category is calculated according to the following formula:
in the formula,. DELTA.Q ass,i Capacity adjustment for the ith class; delta Q j An adjustable amount of power to implement for the jth distributed energy store in the classification;
the adjustment response time of each distributed energy storage category is calculated according to the following formula:
in the formula, t ass,i An adjustment response time for the ith class; t is t j The adjustment response time implemented for the jth distributed energy store in this classification.
9. The method according to claim 5, wherein the generating of the adjustment instruction for controlling each energy storage facility category based on the grid interaction goal of each application scenario and the adjustment capability of each distributed energy storage category comprises:
converting the power grid interaction target of each application scene into each adjusting capacity, and setting the maximum adjusting response time;
determining an objective function by taking the optimal economy as a target, and setting constraint conditions for the objective function;
solving the objective function based on the adjusting capacities, the maximum adjusting response time and the constraint condition to obtain the adjusting capacity values of the distributed energy storage classifications;
and taking each adjusting capacity value of each distributed energy storage classification as a control instruction of each distributed energy storage classification.
10. The method of claim 9, wherein the objective function is as follows:
f＝min{c 1,i ×ΔP i +c 2,i ×ΔQ i }
the constraint is as follows:
in the formula, c 1,i Adjusting costs for the power of the ith class; c. C 2,i Adjusting costs for the ith classified power; delta P i A regulated power provided for the ith class; delta Q i A regulated amount of power provided for the ith category; t is t i The adjusted response time for the ith class.
11. The method of claim 1, wherein the obtaining all accessed distributed energy storage facility information comprises:
acquiring information of each distributed energy storage facility based on a pre-constructed distributed energy storage data model;
the distributed energy storage data model comprises: basic information, control characteristics, operation information and regulation and control information;
the basic information comprises at least one or more of the following: facility type, energy storage medium, voltage class, rated capacity, rated power, commissioning date, owner and affiliated aggregator;
the control characteristics include at least one or more of: whether controllable, charge response time, discharge response time, charge regulation time, discharge regulation time, charge-to-discharge conversion time, and discharge-to-charge conversion time;
the operation information comprises at least one or more of the following: operating state, state of charge, charge power, discharge power, charge amount, and discharge amount;
the regulatory information includes at least one or more of: controlled state, chargeable amount, dischargeable amount, maximum discharge power allowable value, maximum charge power allowable value, maximum discharge power available time, and maximum charge power available time.
12. The utility model provides a user side distributed energy storage facility aggregation management and control system which characterized in that includes:
the access layer is used for acquiring information of all accessed distributed energy storage facilities and power grid interaction targets of all application scenes;
the application layer is used for performing characteristic analysis on the information of each distributed energy storage facility to obtain the adjustment condition of each distributed energy storage facility in each application scene; aggregating all distributed energy storage facilities based on the adjustment conditions of all distributed energy storage facilities to obtain the adjustment capability of each distributed energy storage category in each application scene; and generating an adjusting instruction for managing and controlling each energy storage facility category based on the power grid interaction target of each application scene and the adjusting capacity of each distributed energy storage category.
13. The system of claim 12, wherein the system further comprises a device layer;
the device layer comprises an accessed distributed energy storage facility;
and the access layer is used for acquiring information of all accessed distributed energy storage facilities and power grid interaction targets of all application scenes based on the equipment layer.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115296349A (en) * | 2022-10-08 | 2022-11-04 | 合肥华思系统有限公司 | Efficient economical power distribution method for comprehensive energy storage power station |
| CN116388227A (en) * | 2023-04-14 | 2023-07-04 | 南京国电南自电网自动化有限公司 | Damping control method and system suitable for hybrid energy storage power station |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115296349A (en) * | 2022-10-08 | 2022-11-04 | 合肥华思系统有限公司 | Efficient economical power distribution method for comprehensive energy storage power station |
| CN115296349B (en) * | 2022-10-08 | 2023-01-13 | 合肥华思系统有限公司 | Efficient economical power distribution method for comprehensive energy storage power station |
| CN116388227A (en) * | 2023-04-14 | 2023-07-04 | 南京国电南自电网自动化有限公司 | Damping control method and system suitable for hybrid energy storage power station |
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