A composite control method based on flywheel energy storage and cascade retired battery

Abstract

The application discloses a kind of based on flywheel energy storage cooperation gradient retired battery composite control method, specific steps are as follows: first, the state of charge (State Of Charge, SOC) of gradient retired battery is monitored using SCADA system, and it is divided into 5 working areas, and the speed ωfw of mobile flywheel energy storage is established mapping connection using artificial bee colony algorithm with the SOC of gradient retired battery;Second, using the SOC adjustment strategy based on gradient retired battery, the working state and output of itself are determined according to the SOC of gradient retired battery, and the output condition of flywheel is determined to prevent the overcharge and overdischarge of gradient retired battery and other phenomena.The application features are that: artificial bee colony algorithm is combined together, and effective reference is provided for gradient retired battery and flywheel energy storage energy scheduling.

Description

TECHNICAL FIELD

[0001] The application discloses a composite control method based on a flywheel energy storage and a gradiently retired battery, and specifically comprises the following steps: firstly, a SCADA system is used to monitor the state of charge (SOC) of the gradiently retired battery, and the SOC is divided into five working regions; an artificial bee colony algorithm is used to establish a mapping relationship between the SOC of the gradiently retired battery and the rotating speed ω of the mobile flywheel energy storage fw The application discloses a composite control method based on a flywheel energy storage and a gradiently retired battery, and specifically comprises the following steps: firstly, a SCADA system is used to monitor the state of charge (SOC) of the gradiently retired battery, and the SOC is divided into five working regions; an artificial bee colony algorithm is used to establish a mapping relationship between the SOC of the gradiently retired battery and the rotating speed ω of the mobile flywheel energy storage BACKGROUND

[0002] The rapid development of electric vehicles brings about a problem of a sharp increase in the number of retired batteries. According to industry experience, when the capacity of a power battery for an electric vehicle attenuates to 80%, the power battery will not be able to meet the driving demand of the electric vehicle and will face retirement. According to the current development speed of electric vehicles in China, it is predicted that the peak of the number of retired batteries will be reached around 2022. For these retired batteries, if they are directly scrapped and disassembled, the service life of the batteries will be greatly shortened, and resources will be seriously wasted. Therefore, the state vigorously promotes the gradient reuse of retired power batteries.

[0003] However, the retired power battery monomers have a high inconsistency in parameters (capacity, internal resistance and voltage, etc.), and direct gradient utilization will greatly reduce the specific energy and specific power of the battery system, which not only causes resource waste, but also easily causes overcharging and overdischarging among the monomers in the module, causes thermal runaway of the battery, and even causes self-ignition, which is very dangerous. Therefore, solving the above problems has become a research difficulty. SUMMARY

[0004] The application discloses a composite control method based on a flywheel energy storage and a gradiently retired battery, and specifically comprises the following steps:

[0005] 1) an artificial bee colony algorithm is used to establish a mapping relationship between the SOC of the gradiently retired battery and the rotating speed ω of the mobile flywheel energy storage fw establish a mapping relationship;

[0006] 2) a SCADA system is used to monitor the state of charge (SOC) of the gradiently retired battery, and the SOC is divided into five working regions; an artificial bee colony algorithm is used to establish a mapping relationship between the SOC of the gradiently retired battery and the rotating speed ω of the mobile flywheel energy storage

[0007] The mapping relationship established in step 1) includes the following steps:

[0008] 11) The parameters used in the artificial bee colony algorithm include the population size N, the maximum number of iterations maxCycle, and the speed of each flywheel ω fw The maximum number of stays limit, the SOC state of the step-down retired battery input by the SCADA system, the initialization of the flywheel speed, at this time all the bees are scout bees, the bees carry N different SOC states of the step-down retired battery, and find N flywheel speeds, that is, randomly generate N flywheel speeds:

[0009] ω fw = ω min + rand(0, 1)(ω max - ω min ) (1)

[0010] In the formula, ω min is the minimum speed of the flywheel energy storage system; ω max is the minimum speed of the flywheel energy storage system; rand(0, 1) is a random number between 0 and 1;

[0011] 12) Evaluate the output degree of the hybrid energy storage system, the scout bees with low output degree are converted into employed bees, and the scout bees with high output degree are converted into onlookers, and the evaluation function fit i is calculated by the following formula:

[0012]

[0013] In the formula, f i is the difference between the output degree of the position of the employed bee and the output degree meeting the output demand;

[0014] 13) The onlookers know the output degree of each speed according to the waggle dance of the employed bees, and select according to the output degree, the higher the output, the more onlookers recruited, that is:

[0015]

[0016] In the formula, P i is the probability of the onlooker selecting a certain speed; SN is the number of employed bees;

[0017] The employed bees perform local search, each employed bee searches for a new speed near the original speed, and according to the greedy rule, if the new speed searched has higher output than the original speed, the output of the new speed replaces the output of the original speed, and the position is updated as follows:

[0018] NEW_ω fw = ω fw + Pi (ω fw -ω fw_ ) (4)

[0019] In the formula, NEW_ω fw is a new rotating speed found by the hired bee; ω fw_ is another rotating speed randomly selected and different from the current rotating speed;

[0020] 14) After the observation bee selects the rotating speed according to the output degree, a new rotating speed is searched near the rotating speed, if the output degree of the new rotating speed is greater than that of the original rotating speed, the observation bee is converted into a hired bee, and starts to recruit observation bees, and the position updating mode is consistent with that of the hired bee, if the observation bee and the hired bee search above limit times near a rotating speed, and still cannot find a better rotating speed, a new rotating speed is randomly generated, so as to prevent the algorithm from falling into local optimization;

[0021] All optimal rotating speeds found by the current bee colony are recorded, the output degree is evaluated again, and the algorithm ends until the number of algorithm cycles is greater than maxCycle or the error requirement is met.

[0022] In step 2), the five region states of the SOC are divided by four division nodes of SOC max , SOC low , SOC high and SOC min , and the output power of the flywheel in different region states is confirmed according to the different rotating speeds of the flywheel in the five region states.

[0023] When the energy storage system SOC reaches the upper and lower limits, the SOC is prohibited from exceeding the limits, and SOCmax and SOCmin are the overcharge warning upper limit and the overdischarge warning lower limit.

[0024] In step 2), when the power provided by the step-down retired battery and the mobile flywheel energy storage can meet the external demand power, the flywheel energy storage rotating speed is optimized by the artificial bee colony algorithm according to the SOC state of the step-down battery; when the power provided by the step-down retired battery and the mobile flywheel energy storage cannot meet the external demand power, the flywheel energy storage provides power as the main output device; when the power provided by the step-down retired battery and the mobile flywheel energy storage exceeds the external demand power, the step-down battery and the flywheel energy storage both provide power as the main output device, wherein when the step-down battery SOC is greater than SOC max , the external power demand is entirely borne by the step-down battery.

[0025] The mobile flywheel energy storage is adopted in the present application to cooperate with the step-down retired battery, the output of the mobile flywheel is reasonably adjusted according to the output of the step-down retired battery, and the reliability of the power supply capacity is ensured when the output of the step-down retired battery is insufficient. The method forms recycling and reuse of the retired battery, and saves resources. Attached Figure Description

[0026] Figure 1 This is a flowchart of the artificial bee colony algorithm;

[0027] Figure 2 This is a state of charge distribution diagram of a tiered retired battery energy storage system;

[0028] Figure 3 This is a flowchart of the combined control of flywheel energy storage and cascaded batteries. Detailed Implementation

[0029] This invention discloses a composite control method based on flywheel energy storage combined with decommissioned batteries. The specific steps are as follows: First, a SCADA system is used to monitor the state of charge (SOC) of the decommissioned batteries and divide it into 5 working regions. Then, an artificial bee colony algorithm is used to correlate the SOC of the decommissioned batteries with the rotational speed ω of the flywheel energy storage. fw First, a mapping relationship is established. Second, a SOC adjustment strategy based on the SOC of the retired batteries is applied to determine the battery's operating state and output, thereby determining the flywheel's output and preventing overcharging and over-discharging of the retired batteries. The key feature of this invention is the integration of an artificial bee colony algorithm, providing an effective reference for energy scheduling between retired batteries and flywheel energy storage.

[0030] To achieve the above objectives, the technical solution of the present invention is as follows:

[0031] (1) The SOC status of the retired batteries is monitored in real time using the SCADA system to determine the working status of the retired batteries and divide them into 5 working intervals. Based on this, the SOC of the retired batteries is used as the input of the artificial bee colony algorithm to map the SOC status to the speed of the flywheel energy storage motor.

[0032] (2) Adopt a SOC correction and adjustment strategy based on the retired batteries, adjust the working state and output of the mobile flywheel energy storage according to the SOC state of the retired batteries, so as to achieve the requirement of the flywheel energy storage to cooperate with the output of the retired batteries.

[0033] Step (1) includes the following:

[0034] 11) The parameters used in the artificial bee colony algorithm include the population size N, the maximum number of iterations maxCycle, and the rotational speed ω of each flywheel. fwThe maximum number of stays limit. The above parameters are constants, the SOC state of the step-down retired battery is input by the SCADA system, the flywheel speed is initialized, at this time all the bees are scout bees, the honey bees carry N different SOC states of the step-down retired battery, and find N flywheel speeds, that is, N flywheel speeds are randomly generated:

[0035] ω fw = ω min + rand(0, 1) (ω max - ω min ) (1)

[0036] In the formula, ω min is the minimum speed of the flywheel energy storage system; ω max is the minimum speed of the flywheel energy storage system; rand(0, 1) is a random number between 0 and 1.

[0037] 12) Evaluate the output degree of the hybrid energy storage system, the scout bees with low output degree are converted into employed bees, and the scout bees with high output degree are converted into observer bees, and the evaluation function fit i is:

[0038]

[0039] In the formula, f i is the difference between the output degree of the position of the employed bee and the output degree meeting the output demand.

[0040] 13) The observer bees know the output degree of each speed according to the waggle dance of the employed bees, and select according to the output degree, the higher the output, the more observer bees are recruited, that is:

[0041]

[0042] In the formula, P i is the probability of the observer bee selecting a certain speed; SN is the number of employed bees.

[0043] The employed bees perform local search, each employed bee searches for a new speed near the original speed, and according to the greedy rule, if the new speed searched has higher output than the original speed, the output of the new speed replaces the output of the original speed, and the position is updated as:

[0044] NEW_ω fw = ω fw + P i (ω fw - ω fw_ ) (4)

[0045] In the formula, NEW_ω fw is the new speed found by the employed bee; ω fw_Another rotating speed different from the current rotating speed is randomly selected.

[0046] 14) After the observation bee selects the rotating speed according to the output degree, a new rotating speed is searched near the rotating speed, and if the output degree of the new rotating speed is greater than that of the original rotating speed, the observation bee is converted into a hired bee, and starts to recruit observation bees, and the position updating mode is consistent with that of the hired bee. If the observation bee and the hired bee search for more than limit times near a rotating speed, and still cannot find a better rotating speed, the rotating speed is abandoned, and a new rotating speed is randomly generated, so as to prevent the algorithm from falling into local optimization.

[0047] All optimal rotating speeds found by the current bee colony are recorded, and the output degree is evaluated again until the number of algorithm cycles is greater than maxCycle or the error requirement is met, and the algorithm ends.

[0048] 15) The flowchart of the artificial bee colony algorithm is as shown in Figure 1 .

[0049] The step (2) comprises the following contents:

[0050] 21) The ladder retirement battery SOC distribution diagram is as shown in Figure 2 .

[0051] 22) As shown in Figure 2 , S1, S2, S3, S4 and S5 are five states of the ladder retirement battery energy storage system SOC, and when the energy storage system SOC reaches the upper and lower limits, the SOC out-of-limit should be prohibited. SOC max and SOC min are the overcharge warning upper limit and the overdischarge warning lower limit.

[0052] 23) The composite control flowchart of the flywheel energy storage cooperating with the ladder battery is as shown in Figure 3 , in which, P bat is the output power of the ladder retirement battery; P fw is the output power of the flywheel energy storage; SOC bat , SOC fw are the state of charge of the ladder retirement battery and the flywheel energy storage respectively; P h is the power required by the ladder retirement battery and the mobile flywheel energy storage.

[0053] When the power provided by the retired step battery and the mobile flywheel energy storage can meet the external demand power, the flywheel energy storage speed is optimized according to the SOC state of the retired step battery by the artificial bee colony algorithm (step 1, corresponding to Table 1 operation mode 14); when the power provided by the retired step battery and the mobile flywheel energy storage cannot meet the external demand power, the flywheel energy storage will be used as the main output device to provide power externally (corresponding to Table 1 operation modes 1-3, 10-12, 19-24); when the power provided by the retired step battery and the mobile flywheel energy storage exceeds the external demand power, both the retired step battery and the mobile flywheel energy storage will be used as the main output device to provide power externally (corresponding to Table 1 operation modes 4-9, 13, 15, 25-27), wherein when the SOC of the retired step battery is greater than SOCmax, the external power demand is entirely borne by the retired step battery (16-18).

[0054] Next, according to Table 1, the energy management of the retired step battery and the mobile energy storage system is performed according to the state of charge of the retired step battery:

[0055]

[0056]

[0057] In Table 1, P bat is the output power of the retired step battery; P fw is the output power of the flywheel energy storage; P bat,min , P bat,max are the minimum and maximum values of the charging and discharging power of the retired step battery, respectively; P h is the power provided by the retired step battery and the mobile flywheel energy storage.

Claims

1. A composite control method based on flywheel energy storage combined with decommissioned batteries, characterized in that: Includes the following steps: 1) Using the artificial bee colony algorithm to compare the SOC of retired batteries with the rotational speed ω of mobile flywheel energy storage. fw Establish mapping relationships; 2) The SCADA system is used to monitor the state of charge (SOC) of the retired batteries and divide them into 5 working areas. The SOC adjustment strategy based on the retired batteries is used to determine the working state and output of the retired batteries according to their SOC, thereby determining the output of the flywheel to prevent overcharging and over-discharging of the retired batteries. Step 1) establishing the mapping relationship includes the following steps: 11) The parameters used in the artificial bee colony algorithm include the population size N, the maximum number of iterations maxCycle, and the rotational speed ω of each flywheel. fw Maximum number of stops; Input the SOC state of the decommissioned battery monitored in real time by the SCADA system, initialize the flywheel speed, at this time all bees are scout bees, the bees carry N different SOC states of the decommissioned battery and find N flywheel speeds, that is, randomly generate N flywheel speeds: oh fw =ω min +rand(0,1)(ω max -oh min ) (1) In the formula, ω min This is the minimum rotational speed of the flywheel energy storage system; ω max This represents the minimum rotational speed of the flywheel energy storage system; rand(0,1) is a random number between (0,1); 12) Evaluate the output level of the hybrid energy storage system. Scouts with low output levels are converted into mercenary bees, while scouts with high output levels are converted into observer bees. The evaluation function is fit. i Calculate using the following formula: In the formula, f i The difference between the output level of the hired bee at its location and the output requirement. 13) Observer bees determine the output level at each rotation speed based on the wobble dance of the hired bees, and select bees according to the output level. The higher the output, the more observer bees are recruited. In the formula, P i To observe the probability of a bee choosing a certain rotation speed; SN represents the number of hired bees; The hired bees perform a local search. Each hired bee searches for a new rotational speed near its original speed. According to the greedy rule, if the output of the new rotational speed is higher than that of the original speed, the output of the new speed replaces the output of the original speed. The position update method is as follows: NEW_oh fw =ω fw +P i (oh fw -oh fw_ ) (4) In the formula, NEW_ω fw A new rotational speed was found for the mercenary bee; ω fw_ It is a randomly selected rotational speed that is different from the current rotational speed; 14) After the observation bee selects the rotation speed according to the output level, it searches for a new rotation speed in the vicinity of the rotation speed. If the output level of the new rotation speed is greater than that of the original rotation speed, the observation bee is transformed into a mercenary bee and begins to recruit observation bees. Its position update method is the same as that of the mercenary bee. If the observation bee and the mercenary bee search in the vicinity of a rotation speed more than a limit number of times and still fail to find a better rotation speed, then abandon this rotation speed and randomly generate a new rotation speed to prevent the algorithm from getting trapped in a local optimum. Record all the optimal rotation speeds found by the current bee colony, evaluate the output again, and continue until the number of algorithm loops exceeds maxCycle or meets the error requirement, at which point the algorithm ends.

2. The composite control method based on flywheel energy storage combined with cascaded retired batteries according to claim 1, characterized in that: In step 2), the five region states of the SOC are determined by the SOC. max SOC low SOC high and SOC min The system is divided into four partition nodes, and the flywheel output power in different regions is determined based on the different flywheel speeds in the five regions.

3. The composite control method based on flywheel energy storage combined with cascaded retired batteries according to claim 2, characterized in that: When the SOC of the energy storage system reaches the upper or lower limit, it is prohibited to exceed the SOC limit. SOCmax and SOCmin are the upper limit for overcharge warning and the lower limit for over-discharge warning.

4. The composite control method based on flywheel energy storage combined with cascaded retired batteries according to claim 2, characterized in that: In step 2), when the power provided by the decommissioned battery and the mobile flywheel energy storage can meet the external power demand, the artificial bee colony algorithm optimizes the flywheel energy storage speed based on the SOC state of the decommissioned battery. When the power provided by the decommissioned battery and the mobile flywheel energy storage cannot meet the external power demand, the flywheel energy storage acts as the main output device to provide power. When the power provided by the decommissioned battery and the mobile flywheel energy storage exceeds the external power demand, both the decommissioned battery and the flywheel energy storage act as the main output devices to provide power. Specifically, when the SOC of the decommissioned battery is greater than the SOC... max At that time, all external power requirements are met by the secondary battery.

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