CN108649566B - A battery charging and discharging method based on real-time electricity price - Google Patents

Abstract

The invention relates to a storage battery charging and discharging method based on real-time electricity price, which comprises the following steps: s1, acquiring input data of the optimization system for one day; s2 dividing the utility company parameters and the household power parameters into N time periods; s3 initializing the charging and discharging power of the storage battery; s4, selecting a charging time period of the storage battery and determining the maximum allowable charging power; s5, determining the allowed maximum discharge power, and updating the charge and discharge power of the storage battery; s6 determining the maximum discharge power of the storage battery, and executing the step S6 in a circulating mode until the storage battery is discharged to the minimum capacity percentage or no new discharge time period exists in the storage battery; s7 determining the maximum charging power allowed by the battery for the time period; s8 determines the maximum discharge power allowed by the storage battery in the time period, and executes steps S7-S8 circularly. Compared with the prior art, the method provided by the invention not only avoids the defect that the traditional optimization method is difficult to converge to the optimal solution, but also can obtain the optimal charge and discharge strategy in a short time.

Description

A battery charging and discharging method based on real-time electricity price

technical field

The invention relates to the field of smart home battery scheduling, in particular to a battery charging and discharging method based on real-time electricity prices.

Background technique

In the context of smart grid, users can exchange information with the grid. This kind of exchange will be win-win. According to the real-time electricity price, users can arrange electricity consumption by themselves, so that the production cost of the user can be further reduced, and the user can adjust the electricity consumption according to the real-time electricity price released by the power grid to a certain extent. The role of peak filling. In the future smart grid, many households will install renewable energy systems and electrical energy storage systems, which provide better dispatch flexibility for the implementation of smart grids.

At present, due to the complex constraints of the battery, the convergence speed of many battery charge and discharge optimization algorithms is very slow. For example, using a general planning algorithm is sensitive to the setting of the initial feasible solution, and different optimization results may be obtained by setting different initial solutions; using a genetic algorithm to optimize the charging and discharging of the battery may be caused by the weak local search ability of the algorithm. The optimization results are difficult to converge to the optimal solution. Therefore, a battery charging and discharging strategy based on real-time electricity price is proposed.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a battery charging and discharging method based on real-time electricity price in order to overcome the above-mentioned defects of the prior art.

The object of the present invention can be realized through the following technical solutions:

A battery charging and discharging method based on real-time electricity price, comprising the following steps:

S1 obtains one day's optimization system input data, including power company parameters, household power parameters, and battery parameters;

S2 divides a day into N equally spaced time periods, and divides power company parameters and household power parameters into N time periods;

S3 uniformly sorts the buying and selling electricity prices from large to small to obtain a time period set T _{pr_buysell_sort} , and initializes the battery charge and discharge power P _bat =[0,0,0...,0] _1*N ;

S4 updates the discarded power P1 of discarded renewable energy, filters out elements greater than 0 and the corresponding time period set T1, selects the first time period of T1 as the charging time period of the battery, and determines the maximum allowable charging in this time period power P1 _ch ;

S5 selects a feasible time period from T _{pr_buysell_sort} as the battery discharge time period in positive order, determines the maximum allowable discharge power P1 _dch in combination with the constraints of the battery and the power company's trading power limit, and takes min{P1 _ch , P1 _dch } as the battery is charging The charging power in the time period and the discharging power in the discharging period are updated, and the battery charging and discharging power P _bat is updated, and steps S4-S5 are executed cyclically until the set T1 is an empty set or the battery does not have a new discharge time period;

S6 updates the battery capacity percentage SOC, selects the time period from T _{pr_buysell_sort} as the battery discharge time period in positive order, determines the maximum discharge power of the battery in combination with the constraints of the battery and the power company's trading power limit, and updates the battery charge and discharge power P _bat and the user and power For the exchange power P _grid between companies, step S6 is executed cyclically until the battery is discharged to the minimum capacity percentage SOC _min or the battery does not have a new discharge time period;

S7 selects a feasible time period from T _{pr_buysell_sort} in reverse order as the battery charging time period, and determines the maximum charging power P3 _ch allowed by the battery in this time period in combination with the constraints of the battery and the power company's trading power limit;

S8 selects a feasible time period from T _{pr_buysell_sort} as the battery discharge time period in positive sequence, and determines the maximum discharge power P3 _dch allowed by the battery in this time period in combination with the constraints of the battery and the power limit of the power company, and selects P3=min{P3 _ch , P3 _dch } are used as the charging power in the charging time period and the discharging power in the discharging time period, and update the battery charging and discharging power P _bat and the exchange power P _grid , calculate the total electricity bill of the user before and after the update, and execute steps S7-S8 cyclically until The updated electricity bill is not reduced or the charging time period selected is the same as the discharging time period.

In the step S1, the parameters of the electric power company include the real-time electricity purchase price RTP _buy , the real-time electricity selling price RTP _sell , the user's maximum buying power limit P _{buy_max} and the user's maximum selling power limit P _{sell_max} , and the household power parameters include household power consumption P _load . and renewable energy generation power _Pre , battery parameters include battery current capacity C _bat , battery initial capacity C _ini , battery maximum capacity E _ESS , battery maximum allowable capacity C _max , battery minimum allowable capacity C _min , battery maximum allowable charging power P _{ch_max} and discharge power P _{dch_max} .

In the step S3, the time period set T _{pr_buysell_sort} is a 1*2N matrix, and the expression of the battery charge and discharge power P _bat is:

为蓄电池充电功率，

为蓄电池放电功率，当蓄电池充放电功率P_bat大于0时表示充电，小于0时表示放电。in,

charging power for the battery,

is the battery discharge power. When the battery charge and discharge power P _bat is greater than 0, it means charging, and when it is less than 0, it means discharge.

In the described step S4,

Allows users to buy or sell power from the grid within the power limit, the exchange power P _grid between the user and the power company, when it is greater than 0, it means buying power, and when it is less than 0, it means selling power, and the exchange between the user and the power company The power P _grid is limited by the maximum selling power P _aell,max and the maximum buying power P _buy,max , expressed as follows:

The updated discarded renewable energy power calculation formula is as follows:

The charging power P1 _ch (h)=min{P _{ch_max} -P _bat (h), P1 (h)} of the battery having the largest time period h.

In the step S5, when a feasible discharge time period is selected in sequence from T _{pr_buysell_sort} , when the selected time period corresponds to the electricity purchase price, it means that the battery discharge in this time period is used to offset the electricity purchase power. If no electric energy is purchased, the next time period is selected. When the selected time period corresponds to the selling price of electricity, it means that the battery is discharged in this time period to sell electric energy to the grid.

In steps S5-S8, the constraints that the battery needs to satisfy in the time period h∈{1,2,...,N} include:

分别为充电效率和放电效率，E_B为蓄电池的额定容量，Δh为时间段长度。Among them, SOC _max is the maximum capacity percentage of the battery, u _ESS is a 0/1 variable,

are the charging efficiency and discharging efficiency, respectively, _EB is the rated capacity of the battery, and Δh is the length of the time period.

In the described step S8, the calculation formula of the user's total electricity cost Cost _pay is:

Among them, RTP _buy (h) is the real-time electricity price of the user's purchase, and RTP _sell (h) is the real-time electricity price of the user's sale.

Compared with the prior art, the present invention has the following advantages:

The present invention is different from the current optimization method. Based on the order of electricity price, the optimal utilization of the discarded part of renewable energy, the optimal utilization of the initial capacity of the battery and the optimal utilization of the battery in the low electricity price section of charging and the high electricity price section of discharge are respectively carried out, so as to obtain the optimal utilization. This strategy can quickly obtain the optimal battery charging and discharging strategy.

Description of drawings

Figure 1 is a basic flow chart of a battery charging and discharging strategy based on real-time electricity prices.

Figure 2 shows the working environment of a home under the smart grid, in which Figure (2a) shows the power generated by renewable energy, user power consumption, and trading power limits, and Figure (2b) shows the real-time electricity price for trading.

Figure 3 is a schematic diagram of the discarded part of renewable energy after optimal utilization, wherein Figure (3a) is the power exchange with the grid after optimization, and Figure (3b) is a schematic diagram of battery charging and discharging after optimization.

Figure 4 is a schematic diagram of the optimal utilization of the initial capacity of the battery, in which Figure (4a) is the power exchange with the power grid after optimization, and Figure (4b) is a schematic diagram of the charging and discharging of the battery after optimization.

Figure 5 is a schematic diagram of the battery after optimal utilization after charging in the low-price segment of the battery and discharging in the high-price segment. Figure (5a) is the power exchange with the grid after optimization, and Figure (5b) is the schematic diagram of battery charging and discharging after optimization.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

Example

As shown in FIG. 1, the present invention provides a battery charging and discharging method based on real-time electricity price, comprising the following steps:

(S1) Acquire the input data of the optimization system for one day, including the parameters of the electric power company, the parameters of the household electric power, and the parameters of the battery. Among them, power company parameters: real-time electricity purchase price RTP _buy , real-time electricity selling price RTP _sell , user maximum purchase power limit P _{buy_max} , user maximum selling power limit P _{sell_max} ; household power parameters: household electricity power P _load , renewable energy power generation power _Pre . Battery parameters: initial battery capacity percentage SOC _ini = 0.5, battery maximum capacity E _ESS = 20kWh, battery maximum allowable capacity percentage SOC _max = 0.9, battery minimum allowable capacity percentage SOC _min = 0.2, battery maximum allowable charging power P _{ch_max} = 5kW and Discharge power P _{dch_max} =5kW.

(S2) divide one day into 48 equally spaced time periods, and divide the power company parameters and household power parameters in step (S1) into 48 time periods;

和放电功率

存在以下关系：(S3) Uniformly sort the buying and selling electricity prices from large to small to obtain a time period set T _{pr_buysell_sort} , and initialize the battery charge and discharge power P _bat =[0,0,0...,0] _1*48 ; the time period set T _{pr_buysell_sort} is a 1*96 It refers to a set of 96 data of buying and selling electricity prices sorted from large to small. The battery charge and discharge power P _bat , greater than 0 means charging, and less than 0 means discharging, so the charge and discharge power P _bat is related to the battery charging power

and discharge power

The following relationships exist:

(S4) Update the discarded power P1 of the discarded renewable energy, filter out elements greater than 0 and the corresponding time period set T1, select the first time period of T1 as the charging time period of the battery, and determine the maximum allowable time period. Charging power P1 _ch ; the user can purchase or sell electrical energy from the grid within the allowable power limit. The exchange power P _grid between the user and the power company, which is greater than 0 means buying electric energy, and less than 0 means selling electric energy. In addition, the exchange power P _grid between the user and the power company needs to be limited by the maximum selling power P _sell,max and the maximum buying power P _buy,max , and the constraints are expressed as follows:

The updated discarded renewable energy power calculation formula is as follows:

The charging power P1 _ch (h)=min{P _{ch_max} -P _bat (h), P1 (h)} of the battery having the largest time period h.

(S5) Select a feasible time period from T _{pr_buysell_sort} as the battery discharge time period in positive order, and select a feasible discharge time period from T _{pr_buysell_sort} in order, when the selected time period corresponds to the electricity purchase price, it means that the battery in this time period Discharge is used to offset the purchased power, and the next time period is selected if no power is purchased during this time period. When the selected time period corresponds to the electricity selling price, it means that the battery is discharged for selling electricity to the power grid in this time period. Determine the maximum allowable discharge power P1 _dch according to the constraints of the battery and the power company's trading power limit, take min{P1 _ch , P1 _dch } as the charging power of the battery in the charging time period and the discharging power in the discharging time period to update the battery charging and discharging power P _bat . The constraints that the battery needs to satisfy in the time period h∈{1,2,…,48} are as follows:

或者放电功率

之一存在，需要定义一个01变量u_ESS；参数

和

分别表示充电效率和放电效率。循环执行步骤(S4-S5)，直到集合T1为空集或者蓄电池不存在新的放电时间段时结束循环，经过可再生能源丢弃部分最优利用后的结果如图3所示。Among them, SOC is the percentage of the maximum capacity of the battery energy station; because the battery has the maximum and minimum capacity allowed, the battery has the maximum and minimum capacity percentages SOC _max and SOC _min ; considering that the battery only allows charging power in the same time period

or discharge power

One exists, a 01 variable u _ESS needs to be defined; parameter

and

are the charge efficiency and discharge efficiency, respectively. Steps (S4-S5) are performed cyclically until the set T1 is empty or the battery does not have a new discharge time period to end the cycle. The result after the optimal utilization of the discarded part of the renewable energy is shown in Figure 3.

(S6) Update the battery capacity percentage SOC, select a time period from T _{pr_buysell_sort} in positive order as the battery discharge time period, determine the maximum discharge power of the battery in combination with the constraints of the battery and the power company's trading power limit, update the battery charge and discharge power P _bat and exchange Power P _grid . Step ( S6 ) is performed cyclically until the battery is discharged to the minimum capacity percentage SOC _min or the battery does not have a new discharge period to end the cycle. The results after optimal utilization of the initial capacity of the battery are shown in Figure 4.

(S7) Select a feasible time period from T _{pr_buysell_sort} as the battery charging time period in reverse order, and determine the maximum charging power P3 _ch allowed by the battery in this time period in combination with the constraints of the battery and the power company trading power limit;

(S8) Select a feasible time period from T _{pr_buysell_sort} as the battery discharge time period in positive order, and determine the maximum discharge power P3 _dch allowed by the battery in this time period in combination with the constraints of the battery and the power company’s trading power limit, and select P3=min {P3 _ch , P3 _dch } are used as the charging power in the charging period and the discharging power in the discharging period. Update the battery charge and discharge power P _bat and the exchange power P _grid , and calculate the total electricity bill before and after the update. The formula for calculating the total electricity bill of a user is as follows:

Among them, the calculation formulas of purchasing power P _grid,buy (h) and selling power P _grid,sell (h) are as follows:

Steps (S7-S8) are executed cyclically, and the cycle ends when the updated electricity bill does not decrease or the selected charging time period is the same as the discharging time period. Figure 5 shows the results of optimal utilization of the battery after charging in the low-price segment and discharging in the high-price segment.

Most of the existing technologies use planning problem solving or genetic algorithm to solve the optimal charging and discharging of the battery. This method not only has a slow convergence speed, but also obtains unstable results. In fact, the optimization problem of battery charging and discharging can be divided into three parts: the optimal utilization of the discarded part of renewable energy, the optimal utilization of the initial capacity of the battery, and the optimal utilization of the battery in the low-price segment and the high-price segment for discharging. For each sub-optimization problem, the charging and discharging scheduling can be selected according to the order of the real-time electricity price, and the final battery charging and discharging strategy will be the optimal result.

Claims (7)

1. a battery charging and discharging method based on real-time electricity price, is characterized in that, comprises the following steps: S1 obtains one day's optimization system input data, including power company parameters, household power parameters, and battery parameters; S2 divides a day into N equally spaced time periods, and divides power company parameters and household power parameters into N time periods; S3 uniformly sorts the buying and selling electricity prices from large to small to obtain a time period set T _{pr_buysell_sort} , and initializes the battery charge and discharge power P _bat =[0,0,0...,0] _1*N ; S4 updates the discarded power P1 of discarded renewable energy, filters out elements greater than 0 and the corresponding time period set T1, selects the first time period of T1 as the charging time period of the battery, and determines the maximum allowable charging in this time period power P1 _ch ; S5 selects a feasible time period from T _{pr_buysell_sort} as the battery discharge time period in positive order, determines the maximum allowable discharge power P1 _dch in combination with the constraints of the battery and the power company's trading power limit, and takes min{P1 _ch , P1 _dch } as the battery is charging The charging power in the time period and the discharging power in the discharging period are updated, and the battery charging and discharging power P _bat is updated, and steps S4-S5 are executed cyclically until the set T1 is an empty set or the battery does not have a new discharge time period; S6 updates the battery capacity percentage SOC, selects the time period from T _{pr_buysell_sort} as the battery discharge time period in positive order, determines the maximum discharge power of the battery in combination with the constraints of the battery and the power company's trading power limit, and updates the battery charge and discharge power P _bat and the user and power For the exchange power P _grid between companies, step S6 is executed cyclically until the battery is discharged to the minimum capacity percentage SOC _min or the battery does not have a new discharge time period; S7 selects a feasible time period from T _{pr_buysell_sort} in reverse order as the battery charging time period, and determines the maximum charging power P3 _ch allowed by the battery in this time period in combination with the constraints of the battery and the power company's trading power limit; S8 selects a feasible time period from T _{pr_buysell_sort} as the battery discharge time period in positive sequence, and determines the maximum discharge power P3 _dch allowed by the battery in this time period in combination with the constraints of the battery and the power limit of the power company, and selects P3=min{P3 _ch , P3 _dch } are used as the charging power in the charging time period and the discharging power in the discharging time period, and update the battery charging and discharging power P _bat and the exchange power P _grid , calculate the total electricity bill of the user before and after the update, and execute steps S7-S8 cyclically until The updated electricity bill is not reduced or the charging time period selected is the same as the discharging time period. 2. a kind of battery charging and discharging method based on real-time electricity price according to claim 1, is characterized in that, in described step S1, electric power company parameter comprises real-time electricity buying electricity price RTP _buy , real-time electricity selling electricity price RTP _sell , user The maximum buying power limit P _{buy_max} and the user’s maximum selling power limit P _{sell_max} , the household electric power parameters include the household electric power P _load and the renewable energy power generation power _Pre , the battery parameters include the current battery capacity C _bat , the initial battery capacity C _ini , and the maximum battery capacity The capacity E _ESS , the maximum allowable capacity C _max of the battery, the minimum allowable capacity C _min of the battery, the maximum allowable charging power P _{ch_max} and the discharging power P _{dch_max} of the battery. 3. The method for charging and discharging storage batteries based on real-time electricity prices according to claim 2, wherein in the step S3, the time period set T _{pr_buysell_sort} is a 1*2N matrix, and the storage battery charging and discharging power P _bat The expression is:

in,

charging power for the battery,

is the battery discharge power. When the battery charge and discharge power P _bat is greater than 0, it means charging, and when it is less than 0, it means discharge. 4. A kind of battery charging and discharging method based on real-time electricity price according to claim 1, is characterized in that, in described step S4, Allows users to buy or sell power from the grid within the power limit, the exchange power P _grid between the user and the power company, when it is greater than 0, it means buying power, and when it is less than 0, it means selling power, and the exchange between the user and the power company The power P _grid is limited by the maximum selling power P _sell,max and the maximum buying power P _buy,max , expressed as follows:

The updated discarded renewable energy power calculation formula is as follows:

The charging power P1 _ch (h)=min{P _{ch_max} -P _bat (h), P1 (h)} of the battery having the largest time period h. 5 . The battery charging and discharging method based on real-time electricity price according to claim 1 , wherein, in the step S5 , when a feasible discharge time period is selected in order from T _{pr_buysell_sort} , the selected time period corresponds to 5 . When the price is the electricity price for buying electricity, it means that the battery discharge is used to offset the power of buying electricity in this time period. If no electricity is purchased during this time period, the next time period is selected. When the selected time period corresponds to the electricity selling price, it means that The battery discharges during this time period to sell power to the grid. 6 . The battery charging and discharging method based on real-time electricity price according to claim 3 , wherein in steps S5 - S8 , the constraints that the battery needs to meet in the time period h∈{1,2,...,N} Conditions include:

Among them, SOC _max is the maximum capacity percentage of the battery, u _ESS is a 0/1 variable,

are the charging efficiency and discharging efficiency, respectively, _EB is the rated capacity of the battery, and Δh is the length of the time period. 7. A kind of battery charging and discharging method based on real-time electricity price according to claim 4, is characterized in that, in described step S8, the calculation formula of user's total electricity cost Cost _pay is:

Among them, RTP _buy (h) is the real-time electricity price of the user's purchase, and RTP _sell (h) is the real-time electricity price of the user's sale.

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