CN103368193B - Method for distribution real-time power of battery energy storage power station for tracking planned output - Google Patents
Method for distribution real-time power of battery energy storage power station for tracking planned output Download PDFInfo
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- 238000004146 energy storage Methods 0.000 title claims abstract description 216
- 238000000034 method Methods 0.000 title claims abstract description 36
- 230000002068 genetic effect Effects 0.000 claims abstract description 20
- 238000004891 communication Methods 0.000 claims abstract description 13
- 238000012544 monitoring process Methods 0.000 claims abstract description 13
- 238000007726 management method Methods 0.000 claims abstract description 10
- 238000013523 data management Methods 0.000 claims abstract description 8
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- 108090000623 proteins and genes Proteins 0.000 claims description 16
- 238000013439 planning Methods 0.000 claims description 10
- 230000035772 mutation Effects 0.000 claims description 8
- 238000010248 power generation Methods 0.000 claims description 7
- 150000001875 compounds Chemical class 0.000 claims description 4
- 230000004083 survival effect Effects 0.000 claims description 4
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 abstract description 17
- 229910052744 lithium Inorganic materials 0.000 abstract description 17
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- 229910001416 lithium ion Inorganic materials 0.000 description 2
- BNOODXBBXFZASF-UHFFFAOYSA-N [Na].[S] Chemical compound [Na].[S] BNOODXBBXFZASF-UHFFFAOYSA-N 0.000 description 1
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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Abstract
The invention provides a method and a system for distributing real-time power of a battery energy storage power station for tracking planned output. The method comprises the following steps of reading relevant data of a battery energy storage power station in real time, and carrying out storage and management through the data; calculating a total power requirement command value of the current battery energy storage power station; calculating power command values of energy storage units in the battery energy storage power station; and summarizing the power command values of the energy storage units and outputting the summarized power command values to an external monitoring platform. The system comprises that the method for distributing the real-time power of the battery energy storage power station for tracking planned output is completed through a communication module, a data storage and management module, a tracking plan control module and a genetic algorithm control module, which are arranged on an industrial personal computer, together with the external monitoring platform, thereby being capable of realizing a function that a tracking plan curve is supported by applying the battery energy storage power station, and realizing the purposes of effectively controlling and distributing the real-time power of megawatt-grade lithium battery energy storage power stations.
Description
Technical field
The invention belongs to intelligent grid and stored energy and switch technology field, be specifically related to a kind of realtime power control method based on extensive lithium battery energy storage battery power station, be particularly useful for megawatt battery energy storage power station and participate in tracking plan when exerting oneself, the energy storage unit realtime power in energy-accumulating power station distributes and energy-accumulating power station energy management.
Background technology
Along with the development of battery and integrated technology thereof, apply extensive battery energy storage power station and participate in tracking plan and exert oneself and become a kind of feasible program gradually.Battery energy storage unit in battery energy storage power station has fast response time compared with traditional generating set, and the advantages such as the start-stop time is short, play a significant role in the cooperation control of distribution network system and intelligent grid.Several Large Copacity energy-storage batteries conventional at present in battery energy storage system have sodium-sulphur battery, the type such as flow battery and lithium battery.
From the angle of battery energy storage, excessive charging and excessive electric discharge all can impact the life-span of battery.Therefore, monitored battery charge state, in the good active power demand of the inner reasonable distribution of energy-accumulating power station, and the state-of-charge of battery is controlled to be necessary within the specific limits.
One of mode that battery energy storage power station participation tracking plan is exerted oneself is the difference between real-Time Compensation combining wind and light to generate electricity actual power and wind light generation plan, and the generation of electricity by new energy such as wind power generation and solar power generation equipment can well be generated electricity according to the Plan Curve worked out in advance.
Patent, document, technical report etc. at present about the wind light generation plan tracking aspect based on the extensive battery energy storage power station of MW class are little, need further investigation and explore.
Summary of the invention
For the problems referred to above, an object of the present invention be to provide a kind of safety and stability, convenient operation to realize for following the tracks of the battery energy storage power station realtime power distribution method of planning to exert oneself.
Method of the present invention is achieved by the following technical solution:
For following the tracks of a battery energy storage power station realtime power distribution method of planning to exert oneself, comprise the following steps:
The related data of A, in real time reading battery energy storage power station, and carry out store and management by above-mentioned data;
The overall power requirement bid value of B, calculating present battery energy-accumulating power station;
Each energy storage unit power command value in C, calculating battery energy storage power station;
D, each energy storage unit power command value is gathered after export outer monitoring platform to.
Further, in step, the related data of described battery energy storage power station comprises: the wind light generation Plan Curve issued by outer monitoring platform, the controllable signal of each energy storage unit, SOC, maximum permission discharge power, maximum permission charge power and rated power etc. in wind power generation total power value and photovoltaic generation total power value and battery energy storage power station.
Further, in stepb, the method calculating the overall power requirement of battery energy storage power station comprises:
First, according to the wind light generation Plan Curve that steps A reads, the wind light generation planned value of each time scale is determined;
Secondly, according to the wind light generation planned value under each time scale, determine current wind-solar-storage joint generating total power value;
Finally, from wind-solar-storage joint generating total power value, deduct read wind power generation total power value and photovoltaic generation total power value, obtain the overall power requirement of present battery energy-accumulating power station.
Further, in step C, the method calculating each energy storage unit power command value comprises:
When the overall power requirement of battery energy storage power station is zero, directly each energy storage unit power command value is set to zero; When the overall power requirement non-zero of battery energy storage power station, select according to the symbol of overall power requirement the decision variable being calculated each energy storage unit by maximum permission discharge power or maximum permission charge power, and then ask for the power command value participating in each energy storage unit that tracking plan is exerted oneself; Then judge whether each energy storage unit meets maximum permission discharge power constraints or maximum permission charge power constraints, if against anti-phase energy storage unit of answering constraints, then recalculated the power command value of this energy storage unit by maximum permission discharge power or maximum permission charge power; Otherwise, terminate to judge.
Further, in step D, export outer monitoring platform to after each energy storage unit power command value calculated in step C being stored, to perform, the power of battery energy storage power station is controlled, realize realtime power controlling functions when battery energy storage power station participation tracking plan is exerted oneself simultaneously.
Another object of the present invention is to proposition a kind of for following the tracks of the battery energy storage power station realtime power distribution system planning to exert oneself, this system comprises:
Communication module, for receiving the related data of the battery energy storage power station that outer monitoring platform issues;
Data storage and management module, for the related data of store and management battery energy storage power station, and by each energy storage unit power command value assignment of calculating to the corresponding interface variable;
Follow the tracks of plan control module, for determining the current total power demand of battery energy storage power station in real time; With
Genetic algorithm control module, for calculating each energy storage unit power command value in real time.
Compared with prior art, the beneficial effect that the present invention reaches is:
Of the present inventionly plan the battery energy storage power station realtime power distribution method of exerting oneself and system is easy to realize and grasp in practical engineering application for following the tracks of, by the battery energy storage power station safety and stability more of the method and Systematical control, the real-time monitoring requirement of active power demand that extensive battery energy storage power station tracking plan exerts oneself and high capacity cell energy-accumulating power station stored energy can be met simultaneously.The method mainly combines permission charging and discharging capabilities (that is: the maximum permission discharge power of each lithium battery energy storage battery unit that can represent lithium battery energy storage battery unit realtime power characteristic, maximum permission charge power etc.) and the state-of-charge SOC of lithium battery energy storage battery unit stored energy characteristic can be represented, based on tracking plan control module and genetic algorithm control module, the tracking plan to battery energy storage power station is exerted oneself and is undertaken online distributing in real time by overall power requirement, thus the distribution lithium battery energy storage battery power station tracking plan in real time that achieves is exerted oneself with while overall power requirement, the energy management and the realtime power that also achieve tracking plan megawatt battery energy storage power station control object.
Accompanying drawing explanation
Fig. 1 is the system schematic in MW class lithium battery energy storage battery power station of the present invention;
Fig. 2 is that the present invention is for following the tracks of the structured flowchart planning the battery energy storage power station realtime power distribution system embodiment of exerting oneself;
Fig. 3 is that the present invention is for following the tracks of the enforcement block diagram planning the battery energy storage power station realtime power distribution method embodiment of exerting oneself;
Embodiment
Below for lithium battery energy storage battery unit, be described in further detail method and system of the present invention by reference to the accompanying drawings.
As shown in Figure 1, lithium battery energy storage battery power station comprises each lithium battery energy storage battery unit parallel with one another, include the Li-ion batteries piles of a two way convertor and multiple parallel setting in each energy storage unit, can be performed by two way convertor and the switching of corresponding Li-ion batteries piles be controlled and the function such as charge-discharge electric power instruction.
Fig. 2 is the enforcement block diagram dividing distribution controlling method for following the tracks of the lithium battery energy storage battery power station realtime power planning to exert oneself.As shown in Figure 2, the present invention be by being arranged on communication module 10 in industrial computer, data storage and management module 20, tracking plan control module 30, genetic algorithm control module 40 realize.
Communication module 10, be responsible for the related data receiving battery energy storage power station, and externally monitor supervision platform sends each energy storage unit power command value, monitor supervision platform is arranged on the left of communication module, carry out being connected with communication module and communicate, realize the effect of monitor and forecast communication module;
Data storage and management module 20, for the related data of store and management battery energy storage power station; And to be responsible for each lithium battery energy storage battery power of the assembling unit bid value of calculating by the agreement assignment of setting in advance to relevant interface variable, for outer monitoring platform invoke;
Follow the tracks of plan control module 30, for calculating the current total power demand bid value of battery energy storage power station in real time;
Genetic algorithm control module 40, for calculating each battery energy storage power of the assembling unit bid value in real time.
Fig. 3 is the battery energy storage power station power division control algolithm block diagram that the present invention participates in tracking plan and exerts oneself.Below in conjunction with concrete implementation step, its execution mode is described in detail.As shown in Figure 3, for following the tracks of the battery energy storage power station realtime power distribution method of planning to exert oneself in this example, comprise the steps:
Then data are reached data storage and management module 20 and carry out store and management by steps A: the related data being read battery energy storage power station by communication module 10; Wherein, the related data of battery energy storage power station is that communication module reading outer monitoring platform directly issues, comprise: wind light generation Plan Curve, the controllable signal of each energy storage unit, SOC (SOC), maximum permission discharge power, maximum permission charge power and rated power etc. in wind power generation total power value, photovoltaic generation total power value and battery energy storage power station.
Step B: based on tracking plan control module 30, calculate the overall power requirement of present battery energy-accumulating power station in real time.
Step C: based on genetic algorithm control module 40, calculates each lithium battery energy storage battery power of the assembling unit bid value in battery energy storage power station in real time.
Step D: each energy storage unit power command value calculated by step C, after data storage and management module 20 gathers, is exported by communication module 10.
In stepb, the computational methods of the overall power requirement bid value of described energy-accumulating power station are as follows:
First, based on the wind light generation Plan Curve that steps A reads, the wind light generation planned value under each time scale is determined;
Then, based on the wind light generation planned value under each time scale, determine current wind-solar-storage joint generating total power value P
wind-light storage;
According to specific requirement, scale access time following the tracks of planned value of exerting oneself is desirable, as 5 minutes or 15 minutes etc.Such as when follow the tracks of planned value of exerting oneself access time, scale was 5 minutes time, then the computing formula of current wind-solar-storage joint generating total power value is as follows:
T
time scalefor following the tracks of scale access time of planned value of exerting oneself, unit is second.
Finally, based on the total power requirements of the wind-solar-storage joint generating calculated, the overall power requirement of present battery energy-accumulating power station is determined based on following formula (3):
Above-mentioned various in,
with
be respectively current, the wind light generation planned value of future time scale (namely after 5 minutes), above-mentioned planned value carries out real-time update every a time interval (namely 5 minutes); Δ t is control cycle, such as, can be set to 2 seconds; P
wind-powered electricity generation, P
photovoltaicbe respectively wind-force, photovoltaic generation total power value.
In step C, the computational methods of described each battery energy storage power of the assembling unit bid value are as follows:
Step C1, when the overall power requirement of following the tracks of planned power consumption pond energy-accumulating power station
for on the occasion of time, represent that this battery energy storage power station will be in discharge condition, then based on state-of-charge (State of Charge:SOC) and the maximum permission discharge power value of each energy storage unit, calculate each energy storage unit power command value P through the following steps
i:
C11) based on genetic algorithm control module 40, the decision variable x of each energy storage unit is calculated
i:
(11a) determine individuality (chromosome) the number N in colony, the gene number in each chromosome is energy storage unit number L.(be encoded into vector, i.e. a chromosome, vectorial each element is gene, and whether each for correspondence energy storage unit is participated in the decision value x of this power division by corresponding gene value to carry out binary coding to each individuality
i(i=1 ..., L)), stochastic generation individuality, as initial population, obtains 0,1 compound mode of the gene string in each chromosome; And make evolutionary generation Counter Value G=0;
(11b) judge whether evolutionary generation Counter Value G is less than or equal to maximum evolutionary generation Counter Value G
max, and whether each individuality meets following formula constraints: if above-mentioned two Rule of judgment are all satisfied, perform step 11c, otherwise, jump to step 11f;
(11c) the adaptive value S corresponding to each individual k is calculated based on following formula
k, by S
ksize evaluate its fitness;
(k＝1，...，N)(5)
(11d) based on the fitness value that step 11c calculates, carry out selection operation, such as, roulette wheel selection can be adopted to select winning individuality according to the principle of the survival of the fittest, in the method, individual select probability will be proportional with its fitness value.Then filial generation is obtained after carrying out restructuring and mutation operation respectively based on crossover probability and mutation probability;
(11e) select optimum filial generation based on following target function (I), and it is reinserted in population carry out substituting operation according to certain probability that inserts; Then make G=G+1, turn back to step 11b;
(11f) optimal solution meeting target function (I) is calculated, the individuality corresponding to optimal solution draws its gene string permutation and combination method through decoding, each genic value be energy storage unit i corresponding with it decision variable value xi (i=1 ..., L); C12) each energy storage unit i power command value participating in tracking plan and exert oneself is calculated:
C13) each energy storage unit i power command value P of drawing of determining step C12
iwhether meet the maximum permission discharge power constraints of following energy storage unit active power:
C14) if there is the energy storage unit violating above-mentioned maximum permission discharge power constraints, then perform step C15, otherwise terminate to judge;
C15) based on following formula, each energy storage unit power command value P is redefined
i;
Step C2, when tracking planned power consumption pond energy-accumulating power station overall power requirement
during for negative value, represent that this battery energy storage power station will be in charged state, then based on discharge condition and the maximum permission charge power value of each energy storage unit, calculate each energy storage unit power command value P through the following steps
i:
C21) based on genetic algorithm control module, the decision variable x of each energy storage unit is calculated
i:
(21a) determine individuality (chromosome) the number N in colony, the gene number in each chromosome is energy storage unit number L.(be encoded into vector, i.e. a chromosome, vectorial each element is gene, and whether each for correspondence energy storage unit is participated in the decision value x of this power division by corresponding gene value to carry out binary coding to each individuality
i(i=1 ..., L)), stochastic generation individuality, as initial population, obtains 0,1 compound mode of the gene string in each chromosome; And make evolutionary generation Counter Value G=0;
(21b) judge whether evolutionary generation Counter Value G is less than or equal to maximum evolutionary generation Counter Value G
max, and whether each individuality meets following formula constraints: if above-mentioned two Rule of judgment are all satisfied, perform step 21c, otherwise, jump to step 21f;
(21c) the adaptive value S corresponding to each individual k is calculated based on following formula
k, by S
ksize evaluate its fitness;
(k＝1，...，N)(10)
(21d) based on the fitness value that step 21c calculates, carry out selection operation, such as, roulette wheel selection can be adopted to select winning individuality according to the principle of the survival of the fittest, in the method, individual select probability will be proportional with its fitness value.Then filial generation is obtained after carrying out restructuring and mutation operation respectively based on crossover probability and mutation probability;
(21e) select optimum filial generation based on following target function (II), and it is reinserted in population carry out substituting operation according to certain probability that inserts; Then make G=G+1, turn back to step 21b;
(21f) calculate the optimal solution meeting target function (II), the individuality corresponding to optimal solution draws its gene string permutation and combination method through decoding, and each genic value is the decision variable value x of energy storage unit i corresponding with it
i(i=1 ..., L).
C22) each energy storage unit i power command value P participating in tracking plan and exert oneself is calculated
i;
SOD
i＝1-SOC
i(12)
C23) each energy storage unit i power command value P of drawing of determining step C22
iwhether meet the maximum permission charge power constraints of following energy storage unit active power:
| P
i|≤| P
i maximum permission charging| (13)
C24) if there is the energy storage unit violating above-mentioned maximum permission charge power constraints, then perform the following step C25, otherwise terminate to judge;
C25) based on following formula, each energy storage unit power command value P is redefined
i;
Step C3, overall power requirement when battery energy storage power station
when being zero, then by each energy storage unit power command value P
ibe set to zero;
In formula (4)-(14), u
ifor the controllable signal of i energy storage unit, this signal is read by steps A, and when this energy storage unit i is controlled, this controllable signal value is 1, and other case values are 0; x
ifor 0-1 decision variable, x
irepresent when=1 that energy storage unit i is participated in power division to be calculated, x
ithen represent when=0 and do not participate in this power division; SOC
ifor the state-of-charge of i energy storage unit; SOD
ifor the discharge condition of i energy storage unit; L is battery energy storage unit number; P
i maximum permission electric dischargefor the maximum permission discharge power value of i energy storage unit; P
i maximum permission chargingfor the maximum permission charge power value of i energy storage unit.
In step D, the each energy storage unit power command value calculated in step C is sent to communication module 10 by data storage and management module, outer monitoring platform is exported to again by communication module, to perform, the power in lithium battery energy storage battery power station is controlled, realize realtime power controlling functions when battery energy storage power station participation tracking plan is exerted oneself simultaneously.
Adopt technique scheme, the present invention has the tracking plan distributing in real time lithium battery energy storage battery power station and exerts oneself by the function of overall power requirement, thus realizes convenient, effective realizations and participate in tracking plan and exert oneself by the control of lithium battery energy storage battery power station realtime power and energy management functionality.This megawatt battery energy storage power station participates in realtime power control method when tracking plan is exerted oneself and system, can meet the real-time monitoring requirement of active power demand that extensive battery energy storage power station tracking plan exerts oneself and high capacity cell energy-accumulating power station stored energy simultaneously.In addition, the present invention first picks out the energy storage unit participating in this power division by genetic algorithm, then power division is carried out to this part unit, substantially increase operating efficiency, thus realize the realtime power controlling functions of convenient, effective enforcement to battery energy storage power station.
Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit; in conjunction with above-described embodiment to invention has been detailed description; those of ordinary skill in the field are to be understood that: those skilled in the art still can modify to the specific embodiment of the present invention or equivalent replacement, but these amendments or change are all being applied among the claims awaited the reply.
Claims (6)
1., for following the tracks of a battery energy storage power station realtime power distribution method of planning to exert oneself, it is characterized in that, the method comprises the following steps:
The related data of A, in real time reading battery energy storage power station, and store and management is carried out to above-mentioned data;
The overall power requirement bid value of B, calculating present battery energy-accumulating power station;
Each energy storage unit power command value in C, calculating battery energy storage power station;
D, each energy storage unit power command value is gathered after export outer monitoring platform to;
In step C, the method calculating each energy storage unit power command value comprises:
When the overall power requirement of battery energy storage power station is zero, directly each energy storage unit power command value is set to zero; When the overall power requirement non-zero of battery energy storage power station, select according to its symbol the decision variable being calculated each energy storage unit by maximum permission discharge power or maximum permission charge power, and then ask for the power command value participating in each energy storage unit that tracking plan is exerted oneself; Then judge whether each energy storage unit meets maximum permission discharge power constraints or maximum permission charge power constraints, if against anti-phase energy storage unit of answering constraints, then recalculated the power command value of this energy storage unit by maximum permission discharge power or maximum permission charge power; Otherwise, terminate to judge;
Described step C comprises the steps: further
Step C1, overall power requirement when battery energy storage power station
for on the occasion of time, represent that this battery energy storage power station will be in discharge condition, then calculate each energy storage unit power command value P by following step
i:
C11) the decision variable x of each energy storage unit is calculated by genetic algorithm
i, pass through x
idetermine the assembled state of the energy storage unit participating in this power division;
C12) each energy storage unit i power command value participating in tracking plan and exert oneself is calculated:
C13) each energy storage unit i power command value P of drawing of determining step C12
iwhether meet the maximum permission discharge power constraints of following energy storage unit active power:
C14) if there is the energy storage unit violating maximum permission discharge power constraints, then each energy storage unit power command value P is redefined by following formula
i:
otherwise terminate to judge;
Step C2, overall power requirement when battery energy storage power station
during for negative value, represent that this battery energy storage power station will be in charged state, then calculate each energy storage unit power command value P by following step
i:
C21) the decision variable x of each energy storage unit is calculated by genetic algorithm
i, pass through x
idetermine the assembled state of the energy storage unit participating in this power division;
C22) each energy storage unit i power command value participating in tracking plan and exert oneself is calculated:
C23) each energy storage unit i power command value P of drawing of determining step C22
iwhether meet the maximum permission charge power constraints of following energy storage unit active power:
C24) if there is the energy storage unit violating maximum permission charge power constraints, then each energy storage unit power command value P is redefined by following formula
i:
otherwise terminate to judge;
Step C3, overall power requirement when battery energy storage power station
when being zero, then by each energy storage unit power command value P
ibe set to zero;
Above-mentioned various in, u
ifor the controllable signal of i energy storage unit; x
ifor 0-1 decision variable; SOC
i, SOD
ibe respectively charged, the discharge condition of i energy storage unit, SOD
i=1-SOC
i; L is battery energy storage unit number;
be respectively i energy storage unit maximumly allow to put, charge power value.
2. the method for claim 1, it is characterized in that, in step, the related data of described battery energy storage power station comprises: the wind light generation Plan Curve issued by outer monitoring platform, controllable signal, SOC, maximum permission discharge power, the maximum permission charge power of each energy storage unit in wind power generation total power value and photovoltaic generation total power value and battery energy storage power station.
3. method as claimed in claim 2, is characterized in that, in stepb, the method calculating the overall power requirement of battery energy storage power station comprises:
First, according to the wind light generation Plan Curve that steps A reads, the wind light generation planned value of each time scale is determined;
Secondly, according to the wind light generation planned value under each time scale, determine current wind-solar-storage joint generating total power value;
Finally, from wind-solar-storage joint generating total power value, deduct read wind power generation total power value and photovoltaic generation total power value, obtain the overall power requirement of present battery energy-accumulating power station.
4. method as claimed in claim 3, is characterized in that, determines current wind-solar-storage joint generating total power value by following formula:
Above-mentioned various in, P
wind-light storagefor current wind-solar-storage joint generating total power value;
be respectively current, the wind light generation planned value of future time scale; Δ t is control cycle; T
time scalefor following the tracks of scale access time of planned value of exerting oneself, unit is second.
5. the method for claim 1, is characterized in that,
Calculated the decision variable x of each energy storage unit by genetic algorithm in described step C11
imethod comprise:
(11a) the individual number N in colony is determined, gene number in each individuality is energy storage unit number L, binary coding is carried out to each individuality, stochastic generation individuality is as initial population, obtain 0 of gene string in each individuality, 1 compound mode, and make evolutionary generation Counter Value G=0;
(11b) judge whether evolutionary generation Counter Value G is less than or equal to maximum evolutionary generation Counter Value G
max, and whether each individuality meets the constraints of following formula: if above-mentioned two Rule of judgment are all satisfied, then perform step 11c; Otherwise, jump to step 11f;
(11c) the fitness value S corresponding to each individual k is calculated based on following formula
k;
(11d) based on the fitness value that step 11c calculates, carry out selection operation according to survival of the fittest principle, after then carrying out restructuring and mutation operation respectively based on crossover probability and mutation probability, obtain filial generation;
(11e) select optimum filial generation based on following target function (I), and by its according to insertion probability reinsert in population carry out substitute operation; Then make G=G+1, jump to step 11b;
(11f) calculate the optimal solution meeting target function (I), draw the permutation and combination method of its gene string to the individuality corresponding to optimal solution after decoding, each genic value is the decision variable value x of energy storage unit i corresponding with it
i, wherein i=1 ..., L;
Calculated the decision variable x of each energy storage unit by genetic algorithm in described step C21
imethod comprise:
(21a) the individual number N in colony is determined, gene number in each individuality is energy storage unit number L, binary coding is carried out to each individuality, stochastic generation individuality is as initial population, obtain 0 of gene string in each individuality, 1 compound mode, and make evolutionary generation Counter Value G=0;
(21b) judge whether evolutionary generation Counter Value G is less than or equal to maximum evolutionary generation Counter Value G
max, and whether each individuality meets the constraints of following formula: if above-mentioned two Rule of judgment are all satisfied, then perform step 21c; Otherwise, jump to step 21f;
(21c) the fitness value S corresponding to each individual k is calculated based on following formula
k;
(21d) based on the fitness value that step 21c calculates, carry out selection operation according to survival of the fittest principle, after then carrying out restructuring and mutation operation respectively based on crossover probability and mutation probability, obtain filial generation;
(21e) select optimum filial generation based on following target function (II), and by its according to insertion probability reinsert in population carry out substitute operation; Then make G=G+1, jump to step 21b;
(21f) calculate the optimal solution meeting target function (II), the individuality corresponding to optimal solution draws the permutation and combination method of its gene string after decoding, and each genic value is the decision variable value x of energy storage unit i corresponding with it
i, wherein i=1 ..., L.
6., for following the tracks of the battery energy storage power station realtime power distribution system planning to exert oneself, it is characterized in that, this system comprises:
Communication module, for receiving the related data of battery energy storage power station;
Data storage and management module, for the related data of store and management battery energy storage power station, and by each energy storage unit power command value assignment of calculating to the corresponding interface variable;
Follow the tracks of plan control module, for determining the current total power demand of battery energy storage power station in real time; With
Genetic algorithm control module, for calculating each energy storage unit power command value in real time;
Described genetic algorithm control module, for when the overall power requirement of battery energy storage power station is zero, is directly set to zero by each energy storage unit power command value; When the overall power requirement non-zero of battery energy storage power station, select according to its symbol the decision variable being calculated each energy storage unit by maximum permission discharge power or maximum permission charge power, and then ask for the power command value participating in each energy storage unit that tracking plan is exerted oneself; Then judge whether each energy storage unit meets maximum permission discharge power constraints or maximum permission charge power constraints, if against anti-phase energy storage unit of answering constraints, then recalculated the power command value of this energy storage unit by maximum permission discharge power or maximum permission charge power; Otherwise, terminate to judge;
Described genetic algorithm control module, also for the overall power requirement when battery energy storage power station
for on the occasion of time, represent that this battery energy storage power station will be in discharge condition, then calculate each energy storage unit power command value P by following step
i:
C11) the decision variable x of each energy storage unit is calculated by genetic algorithm
i, pass through x
idetermine the assembled state of the energy storage unit participating in this power division;
C12) each energy storage unit i power command value participating in tracking plan and exert oneself is calculated:
C13) each energy storage unit i power command value P of drawing of determining step C12
iwhether meet the maximum permission discharge power constraints of following energy storage unit active power:
C14) if there is the energy storage unit violating maximum permission discharge power constraints, then each energy storage unit power command value P is redefined by following formula
i:
otherwise terminate to judge;
Described genetic algorithm control module, also for the overall power requirement when battery energy storage power station
during for negative value, represent that this battery energy storage power station will be in charged state, then calculate each energy storage unit power command value P by following step
i:
C21) the decision variable x of each energy storage unit is calculated by genetic algorithm
i, pass through x
idetermine the assembled state of the energy storage unit participating in this power division;
C22) each energy storage unit i power command value participating in tracking plan and exert oneself is calculated:
C23) each energy storage unit i power command value P of drawing of determining step C22
iwhether meet the maximum permission charge power constraints of following energy storage unit active power:
C24) if there is the energy storage unit violating maximum permission charge power constraints, then each energy storage unit power command value P is redefined by following formula
i:
otherwise terminate to judge;
Described genetic algorithm control module, also for the overall power requirement when battery energy storage power station
when being zero, then by each energy storage unit power command value P
ibe set to zero;
Above-mentioned various in, u
ifor the controllable signal of i energy storage unit; x
ifor 0-1 decision variable; SOC
i, SOD
ibe respectively charged, the discharge condition of i energy storage unit, SOD
i=1-SOC
i; L is battery energy storage unit number;
be respectively i energy storage unit maximumly allow to put, charge power value.
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| CN106779340B (en) * | 2016-12-01 | 2023-08-15 | 中国电力科学研究院 | Extraction method and evaluation system of typical working condition curve of energy storage system |
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| CN114387128A (en) * | 2022-01-12 | 2022-04-22 | 中广核风电有限公司 | Provincial energy storage scale demand planning method in power market environment |
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