CN116054242A - Integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge - Google Patents

Integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge Download PDF

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CN116054242A
CN116054242A CN202211619122.XA CN202211619122A CN116054242A CN 116054242 A CN116054242 A CN 116054242A CN 202211619122 A CN202211619122 A CN 202211619122A CN 116054242 A CN116054242 A CN 116054242A
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power
photovoltaic
grid
charging
charge
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杨晨钧
孟涛
孙勇
马海洋
石振宇
李海燕
齐士伟
李德鑫
王伟
张海锋
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Electric Power Research Institute of State Grid Jilin Electric Power Co Ltd
State Grid Jilin Electric Power Corp
Northeast Electric Power University
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Northeast Dianli University
Electric Power Research Institute of State Grid Jilin Electric Power Co Ltd
State Grid Jilin Electric Power Corp
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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
    • 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
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
    • 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
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • 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
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • 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
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • 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
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • 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
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • 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
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical
    • H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

An integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge belongs to the technical field of micro-grid operation and maintenance, and comprises the steps of establishing a mathematical model of an integrated system for optical storage and charge and constraint conditions of the mathematical model, and obtaining a charge and discharge strategy of energy storage equipment through the established constraint conditions and the power difference of photovoltaic and load of the integrated system for optical storage and charge; the invention considers the actual energy consumption situation in rural areas on the basis of considering the related constraint and the system balance constraint of various energy conversion, storage and transmission devices, and further provides an integrated low-carbon rural micro-grid optimal operation control method for optical storage based on time-of-use electricity price, thereby promoting photovoltaic absorption and playing a role of peak clipping and valley filling.

Description

Integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge
Technical Field
The invention belongs to the technical field of operation and maintenance of micro-grids, and particularly relates to an optimal operation control method for a rural micro-grid with photovoltaic and charging piles.
Background
With the advent of the "two carbon goal," low carbon development modes have become increasingly accepted. A large number of photovoltaic cells are paved in rural areas and a certain number of charging piles are built, so that the photovoltaic cell absorption rate is effectively improved, and the new energy electric vehicle is increased in quantity. An effective integrated low-carbon rural micro-grid operation control method for light storage has great significance for maintaining the power balance of the rural micro-grid and improving the reliability, economy and cleanliness of rural production and life energy.
Although some results are achieved in the research of the operation control method of the integrated system for optical storage and filling at present, the existing results do not fully consider the application scenario of the integrated system for optical storage and filling in rural areas, and how to effectively utilize the integrated system for optical storage to realize peak clipping and valley filling.
Therefore, a new technical scheme is needed in the prior art to solve the problems of reduced photovoltaic absorption rate and peak-to-peak increase in energy consumption caused by the integration of a large number of photovoltaic and charging piles into a rural micro-grid.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the integrated low-carbon rural micro-grid optimal operation control method for the optical storage and the charge is provided, and based on the consideration of the related constraint of various energy conversion, storage and transmission devices and the system balance constraint, the rural actual energy situation is considered, so that the integrated low-carbon rural micro-grid optimal operation control method for the optical storage and the charge based on the time-of-use electricity price is provided, and the photovoltaic absorption and the peak clipping and valley filling effects are promoted.
The integrated low-carbon rural micro-grid optimal operation control method for optical storage comprises the following steps which are sequentially carried out,
step one, establishing a mathematical model of an integrated system for light storage and charge, wherein the mathematical model comprises a photovoltaic model, an energy storage model and a charging pile model;
establishing constraint conditions of a mathematical model of an integrated system for light storage and charge, wherein the constraint conditions comprise photovoltaic power output constraint of a photovoltaic model, charging load of an energy storage model, power balance constraint between an energy storage system ESS and a power grid, battery charging and discharging power constraint, electric energy state constraint and battery charging and discharging rate constraint of a charging pile model;
and thirdly, obtaining a charging and discharging strategy of the energy storage device through the constraint condition established in the second step and the power difference of the photovoltaic and the load of the integrated system for optical storage and charging.
The step one photovoltaic model is the output power of a photovoltaic power generation system
Figure BDA0003998448200000021
Wherein P is PV For photovoltaic power generationOutput power; p (P) STC Rated power for photovoltaic power generation; i is solar irradiance; i STC Solar irradiance under STC; t is the operating temperature of photovoltaic power generation; t (T) STC Is the operating temperature at STC; k is the power temperature coefficient.
The first energy storage model is the state of charge (SOC) of the storage battery,
Figure BDA0003998448200000022
in which Q n For rated capacity of the storage battery, i (tau) is charge-discharge current, SOC is percentage of residual charge (state of charge) of the storage battery, N b-s And N b-q The number of the batteries in the storage battery is respectively the number of the batteries in series connection and parallel connection.
The first charging pile model is a centralized charging pile model,
Figure BDA0003998448200000023
Figure BDA0003998448200000024
wherein P is centralBESS,t The power of the energy storage system ESS at the moment t; p (P) limit Is P grid Maximum allowable power, P grid Is grid-connected power; μ is the percentage of initial charge load peak reduction; p (P) i,t Is the charging power.
The photovoltaic power output constraint of the photovoltaic model of the step two is that,
Figure BDA0003998448200000025
wherein PoutPV (t) is the output power of the photovoltaic at the moment t; pmaxPV (t), pmin PV (t) are the maximum and minimum output power of the photovoltaic at time t, respectively.
The power balance constraint among the charging load of the energy storage model and the power balance constraint among the energy storage system ESS and the power grid is that,
Figure BDA0003998448200000031
wherein P is grid,t The power of the upper layer power grid at the time t; l (L) i,t The charging load of the ith charging pile at the moment t is set; p (P) i,t Charging and discharging power of the distributed energy storage system ESS at the time of the ith charging pile t, + is charging power and-is discharging power; p (P) central,t The charging power and the discharging power of the ESS are respectively +charging power and-discharging power.
The battery charging and discharging power constraint of the second charging pile model is that,
Figure BDA0003998448200000032
wherein P is dis,t Discharging power for the ESS; p (P) ch,t Charging power for the ESS; Δt is the power sampling interval;
the electric energy state constraint comprises a battery charge-discharge depth, a relation constraint of an energy storage system ESS capacity and a power input-output capacity and an energy storage system ESS capacity constraint,
the relation constraint of the battery charge and discharge depth, the energy storage system ESS capacity and the power input/output capacity is that,
Figure BDA0003998448200000033
Figure BDA0003998448200000034
SOE min ≤SOE(t)≤SOE max (10)
wherein SOE (t) is the energy state of the battery at the time t, SOE min SOE as minimum depth of discharge of stored energy max To store energyIs a maximum depth of discharge of (2); η (eta) dis Is the discharge efficiency; η (eta) ch Is the charging efficiency; e is the rated capacity of the ESS;
the ESS capacity constraint of the energy storage system is the constraint of the centralized charging pile,
setting the ESS capacity upper limit to C limit ，
Figure BDA0003998448200000041
In SOE of max Is the maximum depth of discharge of the stored energy; q (Q) ct1 (t) is the ESS residual capacity at time t;
the battery charge-discharge rate is constrained to be,
Figure BDA0003998448200000042
wherein C is the charge and discharge rate of the battery.
The power difference delta P of the photovoltaic and the load in the step three is,
ΔP＝P pv -P load (13)
wherein P is pv For photovoltaic power generation, P load Is the load power;
delta P is less than 0, the peak electricity price is the electricity price, the photovoltaic power generation power does not meet the power required by the load, after the charging pile consumes the photovoltaic electric energy, the energy storage device discharges with the maximum discharge power to offset the differential power, the surplus electric quantity is reversely transmitted to the power grid, and the insufficient electric quantity is obtained from the power grid;
delta P is less than 0, the electricity price at valley time is not satisfied with the power required by the load, and after the charging pile consumes the photovoltaic electric energy, the energy storage device counteracts the differential power, and the insufficient electric quantity is obtained from the power grid;
Δp >0, and is the electricity price at valley, the photovoltaic power generation power meets the power required by the charging pile and the civil load, after the charging pile and the civil load consume photovoltaic power, the differential power is charged into the energy storage device, and the residual power is fed back to the power grid;
Δp >0, and is peak electricity price, the photovoltaic power generation power meets the power required by the charging pile and the civil load, after the charging pile and the civil load consume photovoltaic power, the differential power is fed back to the power grid, and the residual power is charged into the energy storage device.
Through the design scheme, the invention has the following beneficial effects: the integrated low-carbon rural micro-grid optimal operation control method for the optical storage and charging aims to reduce the load pressure of the rural micro-grid in the electricity consumption peak period and improve the photovoltaic absorption rate of the grid. The electric automobile and the energy storage system are charged by purchasing electricity from the power grid in the off-peak period of the night electricity consumption, the electric automobile is charged only by photovoltaic and energy storage in the peak period of the daytime electricity consumption, and the redundant electric energy is reversely conveyed to the power grid so as to achieve the effect of peak clipping and valley filling. And during the daytime, the peak period of non-electricity consumption is used for conveying the surplus electric energy to the energy storage system to supplement consumption.
Drawings
The invention is further described with reference to the drawings and detailed description which follow:
fig. 1 is a flowchart of an integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge.
Fig. 2 is a charging station load curve and a photovoltaic output curve chart of an embodiment of the integrated low-carbon rural micro-grid optimal operation control method for optical storage.
Fig. 3 is a graph of charging loads of electric vehicles before and after optimization in a specific embodiment of the integrated low-carbon rural micro-grid optimizing operation control method for optical storage.
Detailed Description
The integrated low-carbon rural micro-grid optimal operation control method for the optical storage, as shown in figure 1, comprises the following steps which are sequentially carried out,
step one, establishing a mathematical model of an integrated system for light storage and charge, wherein the mathematical model comprises a photovoltaic model, an energy storage model and a charging pile model;
establishing constraint conditions of a mathematical model of an integrated system for light storage and charge, wherein the constraint conditions comprise photovoltaic power output constraint of a photovoltaic model, charging load of an energy storage model, power balance constraint between an energy storage system ESS and a power grid, battery charging and discharging power constraint, electric energy state constraint and battery charging and discharging rate constraint of a charging pile model;
and thirdly, obtaining a charging and discharging strategy of the energy storage device through the constraint condition established in the second step and the power difference of the photovoltaic and the load of the integrated system for optical storage and charging.
The charging and discharging strategy of the energy storage equipment provided by the invention can be adjusted according to the power difference of the photovoltaic and load and the operation constraint condition of the energy storage. The energy flow can be managed through different time periods of peak Gu Ping, so that the whole light storage and charging system is in an optimal running state, and the power difference delta P in the light storage and charging rural micro-grid system based on the time-sharing electricity price condition is as follows
ΔP＝P pv -P load
Wherein P is pv For photovoltaic power generation, P load Is the load power.
The present invention will discuss the system energy flow situation in each case in four cases:
(1) The photovoltaic power is smaller than the load power and is at peak electricity price
When the photovoltaic power generation power cannot meet the power required by the load, the power difference delta P in the system is less than 0. The charging stake will consume photovoltaic power preferentially and discharge the energy storage device with maximum discharge power to offset the differential power preferentially within the allowable range. And if the load of the charging pile still cannot be met, purchasing electricity from the power grid by the insufficient part. If the surplus electric quantity part exists, the surplus electric quantity needed by civil load is firstly met, and then the surplus electric quantity is directly transmitted to a public power grid to obtain benefits so as to relieve load pressure and achieve the effect of peak clipping and valley filling.
(2) The photovoltaic power is smaller than the load power and is at the valley time electricity price
When the photovoltaic power generation power cannot meet the power required by the load, the power difference delta P in the system is less than 0. Because the electricity price is lower in the valley period at this time, the electric quantity is not reversely fed to the power grid. At this time, the charging pile consumes photovoltaic power preferentially, and the energy storage device counteracts the differential power preferentially within the allowable range. If the requirements of the charging pile can not be met, the electric energy required by the charging pile and the civil load part is met by purchasing electricity from a power grid.
(3) Photovoltaic power is greater than load power and is at off-peak electricity price
When the photovoltaic power generation power can meet the power required by the charging pile and the civil load, the power difference delta P in the system is more than 0. The charging pile and civil load will consume photovoltaic power preferentially, and the differential power within the allowable range is charged into the energy storage device preferentially (used for coping with the next electricity utilization peak period), and if the residual power is still available, the reverse power grid obtains benefits.
(4) The photovoltaic power is larger than the load power and is at peak electricity price
When the photovoltaic power generation power can meet the power required by the charging pile and the civil load, the power difference delta P in the system is more than 0. The charging pile and civil load consume photovoltaic electric energy preferentially, and the differential power is converted into the power grid preferentially within the allowable range to obtain benefits (relieving load pressure and achieving peak clipping and valley filling effects), and the residual power is charged into the energy storage device (used for coping with the next electricity consumption peak period).
According to the first embodiment, a simulation model is built according to the actual running condition of the optical storage station in a certain area of Jilin province, and simulation analysis and verification are carried out.
The simulation model comprises a photovoltaic power generation system with 60kW and an energy storage system with the capacity of 500 kWh. By filling the storage at night, the operation of the charging station is commonly maintained by photovoltaic and energy storage in the daytime. The charging station operator charges a charging fee of 1.5 yuan/kWh, including a service fee of 0.8 yuan/kWh. A typical charging station load curve and a photovoltaic output curve are simulated according to charging station historical data, and are shown in FIG. 2. The electric vehicle running in the system is assumed to be of a Tesla Model 3, and has a capacity of 60kWh, a hundred kilometers power consumption of 13kWh and a charging power of 7kW. The power reference value is set to 100kW and the power in fig. 2 and 3 are each per unit value.
As can be seen from fig. 2, in the case of unordered charging, since the charging price is fixed, the user can charge according to his own behavior habit, and the number of users selecting charging at night is small. When the power supply is 9:00, the user starts working, the number of electric vehicles needing to be charged starts to gradually increase, and when the power supply is 16:00, the charging peak value is reached, but the photovoltaic output in the same period is obviously insufficient, so that the load pressure of the energy storage system can be seriously increased. As a whole, electric vehicles are concentrated in the period of 13:00-20:00 for charging, and at the moment, the electric vehicles are at the higher daily load stage. If a large number of electric vehicles are charged in this period of time, a situation of "peak-to-peak" tends to result.
Fig. 3 is a graph showing the charge load of the electric vehicle before and after optimization. Taking 16:00 as an example, comparison shows that after the time-of-use electricity price strategy is adopted, part of users select to charge in the electricity consumption valley period at night, and through load transfer, the charging station can reduce the total capacity of the energy storage system, and the users can also reduce the charging cost. The load peak Gu Chalv and the standard deviation of the load of the charging station are reduced to a certain extent, the user cannot intensively charge in a certain time period, and the load overall tends to be balanced.
The power difference delta P is used as a judging condition, and the integrated low-carbon rural micro-grid optimizing operation control method for the light storage and charge provided by the peak-valley flat electricity price is combined, so that the photovoltaic absorption rate of the rural micro-grid can be improved, the charging of users in the electricity consumption peak period can be effectively avoided, the load fluctuation can be stabilized, the system peak Gu Chalv is reduced, and the safe and stable operation of the charging station is ensured.

Claims (8)

1. The integrated low-carbon rural micro-grid optimal operation control method for the optical storage is characterized by comprising the following steps of: comprising the following steps, which are sequentially carried out,
step one, establishing a mathematical model of an integrated system for light storage and charge, wherein the mathematical model comprises a photovoltaic model, an energy storage model and a charging pile model;
establishing constraint conditions of a mathematical model of an integrated system for light storage and charge, wherein the constraint conditions comprise photovoltaic power output constraint of a photovoltaic model, charging load of an energy storage model, power balance constraint between an energy storage system ESS and a power grid, battery charging and discharging power constraint, electric energy state constraint and battery charging and discharging rate constraint of a charging pile model;
and thirdly, obtaining a charging and discharging strategy of the energy storage device through the constraint condition established in the second step and the power difference of the photovoltaic and the load of the integrated system for optical storage and charging.
2. The integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge according to claim 1, wherein the method is characterized by comprising the following steps of: the step one photovoltaic model is the output power of a photovoltaic power generation system
Figure FDA0003998448190000011
Wherein P is PV The output power of the photovoltaic power generation; p (P) STC Rated power for photovoltaic power generation; i is solar irradiance; i STC Solar irradiance under STC; t is the operating temperature of photovoltaic power generation; t (T) STC Is the operating temperature at STC; k is the power temperature coefficient.
3. The integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge according to claim 1, wherein the method is characterized by comprising the following steps of: the first energy storage model is the state of charge (SOC) of the storage battery,
Figure FDA0003998448190000012
in which Q n For rated capacity of the storage battery, i (tau) is charge-discharge current, SOC is percentage of residual charge (state of charge) of the storage battery, N b-s And N b-q The number of the batteries in the storage battery is respectively the number of the batteries in series connection and parallel connection.
4. The integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge according to claim 1, wherein the method is characterized by comprising the following steps of: the first charging pile model is a centralized charging pile model,
Figure FDA0003998448190000021
Figure FDA0003998448190000022
wherein P is centralBESS,t The power of the energy storage system ESS at the moment t; p (P) limit Is P grid Maximum allowable power, P grid Is grid-connected power; μ is the percentage of initial charge load peak reduction; please supplement P i,t Is the charging power.
5. The integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge according to claim 1, wherein the method is characterized by comprising the following steps of: the photovoltaic power output constraint of the photovoltaic model of the step two is that,
Figure FDA0003998448190000023
wherein PoutPV (t) is the output power of the photovoltaic at the moment t; pmaxPV (t), pmin PV (t) are the maximum and minimum output power of the photovoltaic at time t, respectively.
6. The integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge according to claim 1, wherein the method is characterized by comprising the following steps of: the power balance constraint among the charging load of the energy storage model and the power balance constraint among the energy storage system ESS and the power grid is that,
Figure FDA0003998448190000024
wherein P is grid,t The power of the upper layer power grid at the time t; l (L) i,t The charging load of the ith charging pile at the moment t is set; p (P) i,t Charging and discharging power of the distributed energy storage system ESS at the time of the ith charging pile t, + is charging power and-is discharging power; p (P) central,t The charging power and the discharging power of the ESS are respectively +charging power and-discharging power.
7. The integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge according to claim 1, wherein the method is characterized by comprising the following steps of: the battery charging and discharging power constraint of the second charging pile model is that,
Figure FDA0003998448190000025
wherein P is dis,t Discharging power for the ESS; p (P) ch,t Charging power for the ESS; Δt is the power sampling interval;
the electric energy state constraint comprises a battery charge-discharge depth, a relation constraint of an energy storage system ESS capacity and a power input-output capacity and an energy storage system ESS capacity constraint,
the relation constraint of the battery charge and discharge depth, the energy storage system ESS capacity and the power input/output capacity is that,
Figure FDA0003998448190000031
Figure FDA0003998448190000032
SOE min ≤SOE(t)≤SOE max (10)
wherein SOE (t) is the energy state of the battery at the time t, SOE min SOE as minimum depth of discharge of stored energy max Is the maximum depth of discharge of the stored energy; η (eta) dis Is the discharge efficiency; η (eta) ch Is the charging efficiency; e is the rated capacity of the ESS;
the ESS capacity constraint of the energy storage system is the constraint of the centralized charging pile,
setting the ESS capacity upper limit to C limit ，
Figure FDA0003998448190000033
In SOE of max Is the maximum depth of discharge of the stored energy; q (Q) ct1 (t) is the ESS residual capacity at time t;
the battery charge-discharge rate is constrained to be,
Figure FDA0003998448190000034
wherein C is the charge and discharge rate of the battery.
8. The integrated low-carbon rural micro-grid optimal operation control method for optical storage and charge according to claim 1, wherein the method is characterized by comprising the following steps of: the power difference delta P of the photovoltaic and the load in the step three is,
ΔP＝P pv -P load (13)
wherein P is pv For photovoltaic power generation, P load Is the load power;
delta P is less than 0, the peak electricity price is the electricity price, the photovoltaic power generation power does not meet the power required by the load, after the charging pile consumes the photovoltaic electric energy, the energy storage device discharges with the maximum discharge power to offset the differential power, the surplus electric quantity is reversely transmitted to the power grid, and the insufficient electric quantity is obtained from the power grid;
delta P is less than 0, the electricity price at valley time is not satisfied with the power required by the load, and after the charging pile consumes the photovoltaic electric energy, the energy storage device counteracts the differential power, and the insufficient electric quantity is obtained from the power grid;
Δp >0, and is the electricity price at valley, the photovoltaic power generation power meets the power required by the charging pile and the civil load, after the charging pile and the civil load consume photovoltaic power, the differential power is charged into the energy storage device, and the residual power is fed back to the power grid;
Δp >0, and is peak electricity price, the photovoltaic power generation power meets the power required by the charging pile and the civil load, after the charging pile and the civil load consume photovoltaic power, the differential power is fed back to the power grid, and the residual power is charged into the energy storage device.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117595261A (en) * 2024-01-19 2024-02-23 石家庄科林电气股份有限公司 Optical storage micro-grid energy management strategy optimization method and device and electronic equipment
CN117663503A (en) * 2023-10-27 2024-03-08 中国电建集团江西省电力设计院有限公司 Method and system for intelligently adjusting molten salt heat storage rate
CN117811050A (en) * 2024-01-16 2024-04-02 夏尔特拉(上海)新能源科技有限公司 Active instantaneous operation control system of light storage and charge integrated energy system model

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117663503A (en) * 2023-10-27 2024-03-08 中国电建集团江西省电力设计院有限公司 Method and system for intelligently adjusting molten salt heat storage rate
CN117811050A (en) * 2024-01-16 2024-04-02 夏尔特拉(上海)新能源科技有限公司 Active instantaneous operation control system of light storage and charge integrated energy system model
CN117811050B (en) * 2024-01-16 2024-05-31 夏尔特拉(上海)新能源科技有限公司 Active instantaneous operation control system of light storage and charge integrated energy system model
CN117595261A (en) * 2024-01-19 2024-02-23 石家庄科林电气股份有限公司 Optical storage micro-grid energy management strategy optimization method and device and electronic equipment
CN117595261B (en) * 2024-01-19 2024-03-26 石家庄科林电气股份有限公司 Optical storage micro-grid energy management strategy optimization method and device and electronic equipment

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