CN118100245A - Energy management method of household light energy storage and charging system based on V2H - Google Patents
Energy management method of household light energy storage and charging system based on V2H Download PDFInfo
- Publication number
- CN118100245A CN118100245A CN202410193027.0A CN202410193027A CN118100245A CN 118100245 A CN118100245 A CN 118100245A CN 202410193027 A CN202410193027 A CN 202410193027A CN 118100245 A CN118100245 A CN 118100245A
- Authority
- CN
- China
- Prior art keywords
- power
- photovoltaic
- charge
- constraint
- soc
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004146 energy storage Methods 0.000 title claims abstract description 51
- 238000007726 management method Methods 0.000 title claims abstract description 34
- 238000003860 storage Methods 0.000 claims abstract description 92
- 238000005457 optimization Methods 0.000 claims abstract description 33
- 238000005096 rolling process Methods 0.000 claims abstract description 27
- 230000003993 interaction Effects 0.000 claims abstract description 4
- 230000003287 optical effect Effects 0.000 claims description 66
- 238000000034 method Methods 0.000 claims description 36
- 230000005611 electricity Effects 0.000 claims description 31
- 230000008569 process Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 13
- 230000006870 function Effects 0.000 claims description 10
- 230000004927 fusion Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000007599 discharging Methods 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- 230000005622 photoelectricity Effects 0.000 abstract description 2
- 238000003780 insertion Methods 0.000 description 20
- 230000037431 insertion Effects 0.000 description 20
- 238000012545 processing Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 4
- 230000000903 blocking effect Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000000739 chaotic effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 230000002269 spontaneous effect Effects 0.000 description 1
Landscapes
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention discloses an energy management method of a household photo-electricity storage and charging system based on V2H, which predicts the photovoltaic and load power of the next day according to historical data and numerical weather forecast; based on the prediction result and real-time data rolling optimization, taking the stored charge and discharge power, the EV charge and discharge power, the system and main power grid interaction power, the stored SOC, the electric vehicle SOC and the light rejection power as decision variables, taking the stored charge and discharge power constraint, the stored SOC upper and lower limit constraint, the EV charge and discharge power constraint, the EV SOC upper and lower limit constraint, the stored energy converter capacity constraint and the photovoltaic limit emission constraint into consideration, and taking the least energy cost of a user on the same day as an objective function to construct a light storage and charge system rolling optimization model and solve to obtain an optimal energy management strategy. The user can independently select to charge the electric automobile unordered or orderly, open or close the V2H, the flexibility and the adjustability of the EV are fully exerted, and the electric power is saved for the user provided with the photovoltaic and energy storage.
Description
Technical Field
The invention belongs to the technical field of energy management, and particularly relates to an energy management method of a household optical storage and charging system based on V2H.
Background
New energy mainly comprising photovoltaic and wind power is increasingly rapidly developed in an electric power system, and small-capacity distributed new energy represented by roof photovoltaic is also greatly developed besides high-capacity photovoltaic power stations and wind power stations. The user can install the photovoltaic board on the house roof, and the energy storage system of certain capacity is supporting simultaneously, and when spontaneous self-service, surplus electricity can be on the net, can save the power consumption, improves the rate of absorption of new forms of energy. With the development of electric vehicles, electric vehicles (ELECTRIC VEHICLE, EV) gradually enter thousands of households, and for households originally provided with photovoltaic and energy storage, the access of the EV can upgrade the optical storage system into an optical storage and charging system. Meanwhile, considering that the aggregation effect of the photovoltaic and the load is weak in the household scene, the short-term prediction accuracy of the photovoltaic and the load for the household is not high. In view of the above, there is a need for improved energy management strategies for consumer optical storage and retrieval systems.
In existing energy management strategies for consumer optical storage and charging systems, EVs are often modeled purely as loads, without consideration of their flexibility and adjustability. The EV is connected into a household, and the essence of the EV is to charge and discharge a power battery in the EV, and only needs to meet the vehicle requirements of users. The characteristics of the power battery can be fully developed in other idle periods, the power battery can be used as energy storage equipment, EV (electric Vehicle) can be charged, and V2H (electric Vehicle to Home) discharge can be carried out when necessary, so that more considerable electric power is saved for users. Meanwhile, the negative influence of low prediction precision on the optimization model can be weakened by the proposal of the daily rolling optimization, so that a better result is obtained.
Disclosure of Invention
The invention provides an energy management method of a household optical storage and filling system based on V2H, which aims to improve the technical problem that the energy management strategy of the existing household system cannot fully utilize the flexibility and the adjustability of EV.
In order to achieve the above purpose, the invention adopts the following technical scheme that the method comprises the following steps:
s1: collecting historical and real-time data and numerical weather forecast data of photovoltaic and load in a household optical storage and charging system according to a time scale;
S2, building and training a daily prediction model, inputting photovoltaic and load historical data and future numerical weather forecast data, and outputting photovoltaic and load predicted values;
S3, performing rolling optimization on the photovoltaic and load predicted values output by the day-ahead prediction model according to time by using real-time data;
s4, classifying the time periods according to application scenes, and establishing a rolling optimization model of the user optical storage and filling system according to EV use conditions of different time periods;
The establishment of the rolling optimization model of the household optical storage and filling system is specifically as follows:
Taking the charge and discharge power of energy storage, the charge and discharge power of EV, the interaction power of a system and a main power grid, the energy storage SOC, the electric automobile SOC and the light rejection power as decision variables, taking the energy storage charge and discharge power constraint, the energy storage SOC upper and lower limit constraint, the EV charge and discharge power constraint, the EV SOC upper and lower limit constraint, the energy storage converter capacity constraint and the photovoltaic limit emission constraint into consideration, and taking the minimum energy cost of the user in the current day remaining period as an objective function to construct a rolling optimization model of the light storage and charge system for the user;
s5, substituting the photovoltaic and load predicted values after rolling optimization into a user optical storage and charging system rolling optimization model to solve, and obtaining an optimal energy management strategy.
Further, the day-ahead prediction model comprises a photovoltaic day-ahead predictor model and a load day-ahead predictor model; the photovoltaic day-ahead predictor model and the load day-ahead predictor model each comprise an input layer, a fusion layer, a first LSTM layer, a second LSTM layer and an output layer.
Further, the input of the photovoltaic day-ahead predictor model is photovoltaic historical power and numerical weather forecast meteorological parameters, and the output is a photovoltaic power predicted value; the load day-ahead predictor model is input into a load historical power and a numerical weather predicted time-temperature parameter, and is output into a load power predicted value.
Further, the rolling optimization specifically includes: the time granularity of the schedule day is set to 15 minutes, namely 24 hours a day is divided into 96 time periods; and setting the photovoltaic and load power of the current period as a real-time value, and setting the photovoltaic and load power of the subsequent period as a predicted value.
Further, the energy costs include purchase electricity cost C buy and surplus electricity online revenue C sell;
the objective function calculation formula is as follows:
Wherein, the subscript buy represents purchase, the subscript sell represents sell, the superscript t represents period, and i represents current period; c represents electricity charge, P represents power, and price represents price.
Further, the specific form of each constraint condition is as follows:
energy storage charge-discharge power constraint: the maximum limit of the charge and discharge power of the energy storage battery in the optical storage and charge system is as follows:
In the method, in the process of the invention, Representing the energy storage charging power at the time t-Representing the energy storage discharge power at the time t; /(I)Representing the maximum charging power of the stored energy,/>Representing the maximum discharge power of the stored energy;
Upper and lower limit constraints of energy storage SOC: the energy storage battery in the optical storage charging system is constrained according to the upper limit and the lower limit of the charge state required by safe operation:
SOCmin≤SOCt≤SOCmax
Wherein, SOC min represents the minimum allowable value of the SOC under the safe operation, and SOC max represents the maximum value of the SOC under the safe operation;
EV charge-discharge power constraint: the EV in the optical storage and charging system has the technical limitations of a power battery and a charging pile, the maximum limitation of charging and discharging power,
In the method, in the process of the invention,Represents EV charging power at time t-Represents EV discharge power at time t; /(I)Representing EV maximum charging Power,/>Represents EV maximum discharge power;
SOC upper and lower limit constraints of EV: EV in the optical storage charging system is constrained according to the upper and lower limits of the state of charge of the power battery:
Wherein, SOC ev max represents the maximum value of SOC allowed under EV safe operation;
PCS capacity constraint:
In the method, in the process of the invention, Representing the photovoltaic power at time t of the photovoltaic, S pcs represents the power capacity of the PCS.
Photovoltaic limit hair constraint:
In the method, in the process of the invention, Representing the power sold from PCS to the main grid at time t,/>Representing the power sold from the EV to the main grid at time t, P sell_constraint represents the local photovoltaic power limit.
According to another aspect of the present invention, there is provided a terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the V2H-based energy management method of a consumer optical storage and charging system when executing the computer program.
According to another aspect of the present disclosure, there is provided a computer readable storage medium, wherein the computer readable storage medium includes a stored computer program, and when the computer program runs, the device in which the computer readable storage medium is controlled to execute the V2H-based energy management method of the optical storage system for a user.
The invention has the beneficial effects that:
According to the energy management method of the household light energy storage system considering V2H, which is provided by the invention, the flexibility and the adjustability of EV can be fully exerted, and the electric power is saved for the household users provided with photovoltaic and energy storage. The prediction and daily rolling optimization method is also more suitable for the problem of low prediction precision under the user scene than the algorithm which does not perform prediction and daily rolling optimization and only performs daily optimization, thereby achieving better effect.
Drawings
FIG. 1 is a flow chart of a method for managing energy of a household optical storage and inflation system taking V2H into consideration, which is provided by an embodiment of the invention;
FIG. 2 is a flow chart of a photovoltaic and load prediction model in embodiment S1 of the present invention;
FIG. 3 is a flow chart of the scroll optimization provided in embodiment S2 of the present invention;
FIG. 4 is a topological diagram and symbol illustration of a household optical storage and inflation system according to embodiment S3 of the present invention;
fig. 5 is a typical application scenario classification set forth in embodiment S3 of the present invention;
fig. 6 is an all-day operation graph of the V2H considered user optical storage and charging system according to the embodiment S3 of the present invention in the EV non-insertion scenario at the time-of-use electricity price;
Fig. 7 is a graph of the full-day operation of the V2H considered user-light storage charging system proposed in embodiment S3 of the present invention at EV insertion at time-of-use electricity prices, but not allowing for a chaotic charging daytime scenario in V2H;
fig. 8 is a graph of the full day operation of the night scenario for unordered charging in V2H without allowing EV insertion of the V2H considered user-light storage charging system at the time-of-use electricity price set forth in embodiment S3 of the present invention;
fig. 9 is a graph of the full day operation of the V2H considered user-light storage charging system proposed in embodiment S3 of the present invention at EV insertion at time-of-use electricity prices, but not allowing for an orderly charging daytime scenario in V2H;
Fig. 10 is a graph of the full-day operation of the household-use optical storage charging system proposed in embodiment S3 of the present invention considering V2H, EV insertion at time-of-use electricity prices, but not allowing for orderly charging night scenarios in V2H;
fig. 11 is a graph of the full day operation of the charging mode V2H daytime scenario in V2H, with EV insertion at time-of-use electricity prices, in consideration of V2H, with the household electricity storage system proposed in embodiment S3 of the present invention;
Fig. 12 is a graph of the full day operation of the charging mode V2H night scenario in V2H, which is proposed in embodiment S3 of the present invention, considering EV insertion of the V2H for the user' S light storage system at the time-of-use electricity price;
FIG. 13 is a graph of the full day operation of the user optical storage and fill system set forth in embodiment S3 taking into account V2H for EV insertion at a time-of-use electricity price, and allowing an idle mode V2H scenario in V2H;
Fig. 14 is a schematic diagram of a terminal of an energy management device of a V2H-based household optical storage and charging system according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
As shown in fig. 1, the present embodiment provides an energy management method of a V2H-based household optical storage and charging system; specific equipment and parameters of the home optical storage and charging system in the application scene of the embodiment are shown in table 1:
Table 1 specific apparatus and parameters
The method comprises the following specific steps:
s1: collecting historical and real-time data and numerical weather forecast data of photovoltaic and load in a household optical storage and charging system according to a time scale;
S2, building and training a daily prediction model, inputting photovoltaic and load historical data and future numerical weather forecast data, and outputting photovoltaic and load predicted values;
Specifically, referring to fig. 2, for photovoltaic prediction, input data of the photovoltaic prediction is historical photovoltaic data and numerical weather forecast meteorological parameters, the photovoltaic prediction is performed by entering a 2-layer LSTM network after passing through a fusion layer, and finally the next day of predicted photovoltaic data is output; for load prediction, the input data are historical load data and numerical weather predicted time-temperature parameters, the load prediction is carried out by entering a 2-layer LSTM network after passing through a fusion layer, and finally the load data predicted in the next day are output.
S3, performing rolling optimization on the photovoltaic and load predicted values output by the day-ahead prediction model according to time by using real-time data;
Specifically, referring to fig. 3, an embodiment of the present invention provides an intra-day rolling optimization method for an optical storage and filling system based on a daily prediction error improvement. The time granularity for the scroll optimization was set to 15 minutes during 24 hours a day, dividing the day into 96 time periods. The predictive algorithm will run at time t=0, and then will perform real-time data acquisition every 15 seconds, and will perform scroll optimization every 15 minutes. The rolling optimization model replaces the prediction data with real-time data, so that negative influence of future prediction errors on optimization is reduced.
S4, classifying the time periods according to application scenes, and establishing a rolling optimization model of the user optical storage and filling system according to EV use conditions of different time periods;
The establishment of the rolling optimization model of the household optical storage and filling system is specifically as follows:
Taking the charge and discharge power of energy storage, the charge and discharge power of EV, the interaction power of a system and a main power grid, the energy storage SOC, the electric automobile SOC and the light rejection power as decision variables, taking the energy storage charge and discharge power constraint, the energy storage SOC upper and lower limit constraint, the EV charge and discharge power constraint, the EV SOC upper and lower limit constraint, the energy storage converter (Power Conversion System, PCS) capacity constraint and the photovoltaic limit emission constraint into consideration, and taking the minimum energy cost of the user in the current day remaining period as an objective function to construct a rolling optimization model of the photo-electricity storage and charge system for the user;
in the step S3, the objective function is that the electricity fee of the user in the remaining period of the current day is the least, the electricity fee includes electricity purchase fee C buy and surplus electricity online gain C sell, and the calculation formula of the objective function is:
wherein, the subscript buy represents purchase, the subscript sell represents sell, the superscript t represents period, and i represents current period; c represents electricity charge, P represents power, and price represents price.
Further, in the step S3, constraint conditions include energy storage charge and discharge power constraint, energy storage SOC upper and lower limit constraint, EV charge and discharge power constraint, EV SOC upper and lower limit constraint, PCS capacity constraint, photovoltaic limit constraint, and specific forms of each constraint condition are as follows:
energy storage charge-discharge power constraint
The energy storage battery in the optical storage and charging system has the maximum limit on the charge and discharge power due to the technical condition, and can be described as follows:
In the method, in the process of the invention, Representing the energy storage charging power at the time t-Representing the energy storage discharge power at the time t; /(I)Representing the maximum charging power of the stored energy,/>Representing the stored maximum discharge power.
Energy storage SOC upper and lower limit constraints
The energy storage battery in the optical storage charging system has upper and lower limit constraints according to the safe operation requirement, and can be described as:
Where SOC min represents the SOC minimum allowed for safe operation and SOC max represents the SOC maximum for safe operation.
EV charge-discharge power constraint
EV in the optical storage and charging system, because of its technical limitations of power battery and charging pile, its charging and discharging power has the greatest limitation, which can be described as:
In the method, in the process of the invention, Represents EV charging power at time t-Represents EV discharge power at time t; /(I)Representing EV maximum charging Power,/>Representing EV maximum discharge power.
SOC upper and lower limit constraints for EV
EV in the optical storage and charging system, according to the safe operation requirement of the power battery, the SOC has upper and lower limit constraints, and can be described as follows:
Where SOC ev max represents the SOC maximum allowed under EV safe operation.
PCS capacity constraint
The PCS in the optical storage and charging system is a key device for exchanging direct current and alternating current energy, wherein the direct current access device is provided with photovoltaic and energy storage, and the alternating current access device is provided with a load and a main power grid. Due to PCS technology limitations, it has an upper power capacity limit, which can be described as:
In the method, in the process of the invention, Representing the photovoltaic power at time t of the photovoltaic, S pcs represents the power capacity of the PCS.
Photovoltaic hair limiting constraint
In the optical storage charging system, the discharge power of photovoltaic, energy storage and EV is common, electric equipment (load and EV charging) in the system is preferentially supplied, and redundant power can be sold to a main power grid according to the residual electricity internet electricity price so as to obtain benefits. However, because of uncontrollable distributed photovoltaic, when high power is connected to the power grid, impact is caused to the main power grid, so the local government often has a photovoltaic limited-generation policy, which can be described as:
In the method, in the process of the invention, Representing the power sold from PCS to the main grid at time t,/>Representing the power sold from the EV to the main grid at time t, P sell_constraint represents the local photovoltaic power limit.
As shown in fig. 4, the present embodiment provides a topology diagram of the optical storage and charging system for the user, and details of the power flow direction therein are described in symbols.
Specifically, the household optical storage and charging system consists of a direct current side and an alternating current side. The direct current side equipment has photovoltaic and energy storage, the alternating current side equipment has load and EV, the energy exchange between the direct current side and the alternating current side is completed by PCS, and meanwhile, the alternating current side is connected with a main power grid and can exchange power. Specific symbols in the topology are as follows: p buy_load represents the power transmitted by the grid to the load; p buy_pcs represents the power transmitted by the grid to the PCS; p buy_ev represents the power transmitted by the grid to the EV; p sell_load represents the power transmitted by the PCS to the load; p sell_pcs represents the power transmitted by the PCS to the grid; p sell_ev represents the power of PCS to EV transmission; p pv represents the photovoltaic output power; p ch represents the stored charge power; p dh represents the energy storage discharge power. It is worth emphasizing that unlike optical storage systems that do not consider V2H, the present topology adds P ev_grid and P ev_pcs for describing the process of V2H, where P ev_grid represents the EV power transmitted to the grid; p ev_pcs represents the EV power transmitted to the home.
As shown in fig. 5, typical classifications for classifying time periods according to application scenarios are: the EV may be divided into an insertion case and a non-insertion case, and the EV insertion is an optical storage and filling system, and the EV insertion is not an optical storage system. During EV insertion, V2H is allowed and V2H is not allowed according to user requirements. When V2H is allowed, it may be classified into a charging mode V2H and an idle mode V2H according to the type of V2H. Charging mode V2H represents allowing V2H to be performed on the EV while sequentially charging it; the idle mode V2H represents that the user has no charging requirement on the EV, but the EV is still plugged into the system, and the EV at this time can be regarded as a large-capacity energy storage device, so that the functions of absorbing photovoltaic and utilizing time-of-use electricity price are played for the user's family, and the energy cost is further saved for the user. When the user does not allow V2H, the EV can only charge, and may be classified into disordered charge and ordered charge according to the type of charge.
It should be noted that all EV charging actions performed by the user, the present embodiment takes user actions into account on different time scales. The present embodiment classifies EV charging behavior into 2 typical scenarios, i.e., daytime charging and night charging, and uniformly sets the charging duration to 12 hours. The time period of daytime charging is 6:00-18:00 of the same day, and the time period of night charging is 20:00-8:00 of the same day.
S5, substituting the photovoltaic and load predicted values after rolling optimization into a user optical storage and charging system rolling optimization model to solve, and obtaining an optimal energy management strategy.
The result of the optimal energy management strategy under different application scenes is specifically as follows: wherein the time period of daytime charging is set to 6:00-18:00 of the same day, and the time period of night charging is set to 20:00-8:00 of the same day. Fig. 6 is a graph showing the whole day operation of the user light storage system considering V2H in the present embodiment in the case of EV non-insertion under the time-sharing electricity price; fig. 7 is a graph showing the whole day operation of the present embodiment in which EV insertion is considered with the V2H user-use optical storage system at the time-of-use electricity price, but the unordered charging in V2H is not allowed in the daytime scenario; fig. 8 is a graph showing the whole day operation of the night scenario in the present embodiment considering that V2H is inserted with EV at the time-of-use electricity price but unordered charging in V2H is not allowed; fig. 9 is a graph showing the whole day operation of the present embodiment in which the V2H user-oriented optical storage system is considered for EV insertion at a time-of-use electricity price, but the ordered charging in V2H is not allowed for daytime scenario; fig. 10 is a graph showing the whole day operation of the present embodiment considering EV insertion of the V2H user-use optical storage system at the time-of-use electricity price, but not allowing the orderly charging night scenario in V2H; fig. 11 is a graph showing the full-day operation of the charging mode V2H daytime scenario in V2H, considering EV insertion of the V2H-user optical storage charging system at the time-of-use electricity price in the present embodiment; fig. 12 is a graph showing the full day operation of the charging mode V2H night scenario in the present embodiment considering EV insertion of the V2H user-use optical storage charging system at the time-of-use electricity price; fig. 13 is a graph showing the full day operation of the V2H scenario in the idle mode in V2H, considering EV insertion of the V2H user optical storage system at the time-of-use electricity price in the present embodiment.
Corresponding to the embodiment of the energy management method of the household optical storage and filling system based on the V2H, the invention further provides the embodiment of the energy management device of the household optical storage and filling system based on the V2H.
Referring to fig. 14, the V2H-based energy management terminal device of the user optical storage system according to the embodiment of the present invention includes a memory and one or more processors, where the memory stores executable codes, and when the processor executes the executable codes, the processor is configured to implement a method for predicting message blocking based on spectral regularization variation self-encoder in the above embodiment.
The embodiment of the message blocking prediction terminal equipment based on the spectrum regularization variation self-encoder can be applied to any equipment with data processing capability, and the equipment with the data processing capability can be equipment or a device such as a computer. 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 by a processor of any device with data processing capability. In terms of hardware, as shown in fig. 14, a hardware structure diagram of an arbitrary device with data processing capability, where the V2H-based energy management terminal device of the optical storage and charging system for a user is provided in the present invention, except for the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 14, the arbitrary device with data processing capability in the embodiment generally includes other hardware according to the actual function of the arbitrary device with data processing capability, which is not described herein again.
The implementation process of the functions and roles of each unit in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.
For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present invention. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The embodiment of the invention also provides a computer readable storage medium, on which a program is stored, which when executed by a processor, implements an energy management method of the V2H-based user optical storage system in the above embodiment.
The computer readable storage medium may be an internal storage unit, such as a hard disk or a memory, of any of the data processing enabled devices described in any of the previous embodiments. The computer readable storage medium may also be an external storage device of any device having data processing capabilities, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), an SD card, a flash memory card (FLASH CARD), etc. provided on the device. Further, the computer readable storage medium may include both internal storage units and external storage devices of any data processing device. The computer readable storage medium is used for storing the computer program and other programs and data required by the arbitrary data processing apparatus, and may also be used for temporarily storing data that has been output or is to be output.
The invention also provides a computer program product, which comprises a computer program/instruction, wherein the computer program/instruction realizes the energy management method of the household optical storage and filling system based on V2H when being executed by a processor.
The foregoing is a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention and are intended to be comprehended within the scope of the present invention.
Claims (8)
1. The energy management method of the household optical storage and filling system based on the V2H is characterized by comprising the following steps of:
s1: collecting historical and real-time data and numerical weather forecast data of photovoltaic and load in a household optical storage and charging system according to a time scale;
S2, building and training a daily prediction model, inputting photovoltaic and load historical data and future numerical weather forecast data, and outputting photovoltaic and load predicted values;
S3, performing rolling optimization on the photovoltaic and load predicted values output by the day-ahead prediction model according to time by using real-time data;
s4, classifying the time periods according to application scenes, and establishing a rolling optimization model of the user optical storage and filling system according to EV use conditions of different time periods;
The establishment of the rolling optimization model of the household optical storage and filling system is specifically as follows:
Taking the charge and discharge power of energy storage, the charge and discharge power of EV, the interaction power of a system and a main power grid, the energy storage SOC, the electric automobile SOC and the light rejection power as decision variables, taking the energy storage charge and discharge power constraint, the energy storage SOC upper and lower limit constraint, the EV charge and discharge power constraint, the EV SOC upper and lower limit constraint, the energy storage converter capacity constraint and the photovoltaic limit emission constraint into consideration, and taking the minimum energy cost of the user in the current day remaining period as an objective function to construct a rolling optimization model of the light storage and charge system for the user;
s5, substituting the photovoltaic and load predicted values after rolling optimization into a user optical storage and charging system rolling optimization model to solve, and obtaining an optimal energy management strategy.
2. The V2H-based household optical storage and inflation system energy management method of claim 1, wherein the day-ahead predictive model comprises a photovoltaic day-ahead predictive sub-model and a load day-ahead predictive sub-model; the photovoltaic day-ahead predictor model and the load day-ahead predictor model each comprise an input layer, a fusion layer, a first LSTM layer, a second LSTM layer and an output layer.
3. The energy management method of the V2H-based household optical storage and inflation system according to claim 2, wherein the photovoltaic day-ahead predictor model is input of photovoltaic historical power and numerical weather forecast meteorological parameters, and output of the photovoltaic historical power and numerical weather forecast meteorological parameters is a photovoltaic power predicted value; the load day-ahead predictor model is input into a load historical power and a numerical weather predicted time-temperature parameter, and is output into a load power predicted value.
4. The V2H-based household optical storage and charging system energy management method of claim 1, wherein the rolling optimization specifically comprises: the time granularity of the schedule day is set to 15 minutes, namely 24 hours a day is divided into 96 time periods; and setting the photovoltaic and load power of the current period as a real-time value, and setting the photovoltaic and load power of the subsequent period as a predicted value.
5. The V2H-based energy storage and management method for a consumer use of the energy storage and management system of claim 4, wherein the energy costs include a purchase cost Cbuy and a surplus electricity online revenue Csell;
the objective function calculation formula is as follows:
Wherein, the subscript buy represents purchase, the subscript sell represents sell, the superscript t represents period, and i represents current period; c represents electricity charge, P represents power, and price represents price.
6. The V2H-based energy storage and management method for a household use, as set forth in claim 1, wherein each constraint is in the following specific form:
energy storage charge-discharge power constraint: the maximum limit of the charge and discharge power of the energy storage battery in the optical storage and charge system is as follows:
In the method, in the process of the invention, Representing the energy storage charging power at the time t-Representing the energy storage discharge power at the time t; /(I)Representing the maximum charging power of the stored energy,/>Representing the maximum discharge power of the stored energy;
Upper and lower limit constraints of energy storage SOC: the energy storage battery in the optical storage charging system is constrained according to the upper limit and the lower limit of the charge state required by safe operation:
SOCmin≤SOCt≤SOCmax
Wherein, SOC min represents the minimum allowable value of the SOC under the safe operation, and SOC max represents the maximum value of the SOC under the safe operation;
EV charge-discharge power constraint: the EV in the optical storage and charging system has the technical limitations of a power battery and a charging pile, the maximum limitation of charging and discharging power,
In the method, in the process of the invention,Represents EV charging power at time t-Represents EV discharge power at time t; /(I)Representing EV maximum charging Power,/>Represents EV maximum discharge power;
SOC upper and lower limit constraints of EV: EV in the optical storage charging system is constrained according to the upper and lower limits of the state of charge of the power battery:
Wherein, SOC evmax represents the maximum value of SOC allowed under EV safe operation;
PCS capacity constraint:
In the method, in the process of the invention, Representing photovoltaic power at photovoltaic time t, S pcs representing power capacity of PCS;
photovoltaic limit hair constraint:
In the method, in the process of the invention, Representing the power sold from PCS to the main grid at time t,/>Representing the power sold from the EV to the main grid at time t, P sell_constraint represents the local photovoltaic power limit.
7. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing a V2H-based energy management method for a consumer optical storage system as claimed in any one of claims 1 to 6 when the computer program is executed by the processor.
8. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform a V2H-based energy management method of a household optical storage system according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410193027.0A CN118100245A (en) | 2024-02-21 | 2024-02-21 | Energy management method of household light energy storage and charging system based on V2H |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410193027.0A CN118100245A (en) | 2024-02-21 | 2024-02-21 | Energy management method of household light energy storage and charging system based on V2H |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN118100245A true CN118100245A (en) | 2024-05-28 |
Family
ID=91162612
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410193027.0A Pending CN118100245A (en) | 2024-02-21 | 2024-02-21 | Energy management method of household light energy storage and charging system based on V2H |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118100245A (en) |
-
2024
- 2024-02-21 CN CN202410193027.0A patent/CN118100245A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| He et al. | Optimal bidding strategy of battery storage in power markets considering performance-based regulation and battery cycle life | |
| CN109787263B (en) | Family energy mutual-aid system based on multilevel cloud energy storage and scheduling method | |
| CN109473976B (en) | Combined cooling heating and power type microgrid energy scheduling method and system | |
| CN113541166B (en) | Distributed energy storage optimal configuration method, system, terminal and storage medium | |
| CN109146320B (en) | Virtual power plant optimal scheduling method considering power distribution network safety | |
| CN111626527A (en) | Intelligent power grid deep learning scheduling method considering fast/slow charging/discharging form of schedulable electric vehicle | |
| Zheng et al. | Optimal short-term power dispatch scheduling for a wind farm with battery energy storage system | |
| CN108512238B (en) | Two-stage optimal scheduling method for smart home based on demand side response | |
| CN115169723A (en) | Power generation power prediction method, load prediction method and model training method | |
| CN115841187A (en) | Method, device, equipment and storage medium for optimizing operation strategy of flexible power distribution network | |
| CN115313519A (en) | Power distribution network energy storage optimal configuration method, device, equipment and storage medium | |
| Wen et al. | Optimal distributed energy storage investment scheme for distribution network accommodating high renewable penetration | |
| CN116502832A (en) | Multi-micro-grid joint planning method, system, storage medium and electronic equipment | |
| CN109950900B (en) | Micro-grid load reduction control method based on electric vehicle load minimum peak model | |
| CN112670982B (en) | Active power scheduling control method and system for micro-grid based on reward mechanism | |
| CN112510690B (en) | Optimal scheduling method and system considering wind-fire-storage combination and demand response reward and punishment | |
| CN114036825A (en) | Collaborative optimization scheduling method, device, equipment and storage medium for multiple virtual power plants | |
| CN117595261A (en) | Optical storage micro-grid energy management strategy optimization method and device and electronic equipment | |
| CN117522014A (en) | Storage and distribution network joint planning method considering multiple uncertainties | |
| Yao et al. | Determination of a dispatch strategy to maximize income for a wind turbine-BESS power station | |
| CN118100245A (en) | Energy management method of household light energy storage and charging system based on V2H | |
| Saadatmandi et al. | Smart electric vehicle charging for reducing photovoltaic energy curtailment | |
| CN114358383A (en) | Multi-energy microgrid robust optimization method and system under complex uncertain scene | |
| Borghetti et al. | Scenario tree generation for the optimization model of a parking lot for electric vehicles | |
| CN109038624B (en) | Household energy scheduling method based on double-storage-battery capacity dynamic allocation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |