CN113689023A - Wind/storage/hydrogen grid-connected power generation system wind curtailment and energy absorption management method - Google Patents

Wind/storage/hydrogen grid-connected power generation system wind curtailment and energy absorption management method Download PDF

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CN113689023A
CN113689023A CN202110267469.1A CN202110267469A CN113689023A CN 113689023 A CN113689023 A CN 113689023A CN 202110267469 A CN202110267469 A CN 202110267469A CN 113689023 A CN113689023 A CN 113689023A
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马泽涛
舒杰
崔琼
黄磊
江才俊
沈洁
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Guangzhou Institute of Energy Conversion of CAS
Shenzhen China Guangdong Nuclear Engineering Design Co Ltd
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Shenzhen China Guangdong Nuclear Engineering Design Co Ltd
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Abstract

The invention relates to a wind/storage/hydrogen grid-connected power generation system wind curtailment and energy absorption management method based on convex optimization, and belongs to the field of new energy. The method specifically comprises the following steps: obtaining a maximum output active power curve of the fan in a period of time; establishing a steady-state mathematical model of the system and setting constraints of the steady-state mathematical model; establishing a system active power balance relation and limiting the fluctuation of the system active power balance relation; determining an objective function when the system runs; carrying out convex treatment and initializing the on-off state of the electrolytic bath; solving optimal power distribution and dual variables by convex optimization; calculating an optimal Hamilton value according to the dual variable; optimizing the on-off state of each part by adopting a dynamic programming method; and judging whether the system state meets a final value condition, if so, terminating the calculation and outputting the result, and otherwise, repeating the steps. The invention considers the problem of wind/storage/hydrogen grid-connected power generation system optimization control of grid-connected power fluctuation, realizes wind abandoning and smooth grid-connected active power fluctuation, and effectively utilizes surplus wind power.

Description

Wind/storage/hydrogen grid-connected power generation system wind curtailment and energy absorption management method
Technical Field
The invention relates to the technical field of new energy, in particular to a wind curtailment and energy absorption management method of a wind/storage/hydrogen grid-connected power generation system based on convex optimization.
Background
On one hand, wind power resources have randomness, volatility and uncontrollable property, and wind power grid-connected power is often required to be controlled in order to avoid impact of wind power generation on stable operation of a power grid at the power peak valley moment, so that a large amount of abandoned wind is caused, and the return on investment of a wind power plant is reduced. On the other hand, hydrogen energy is becoming a global energy development strategy due to its advantages of high calorific value, zero emission, and the like. In order to absorb the abandoned wind energy, the hydrogen production device by using the electrolyzed water can be utilized to convert redundant electric energy into hydrogen energy when the wind power is surplus, and the economic benefit of the wind power plant is improved by selling the hydrogen.
In order to ensure stable and efficient operation of a wind/storage/hydrogen grid-connected power generation system and achieve the purposes of reducing grid-connected active power fluctuation and eliminating abandoned wind, a reasonable energy management strategy is required. The energy management based on global optimal control can comprehensively and efficiently operate each component within a period of time, so that the wind/storage/hydrogen grid-connected power generation system achieves the optimal performance index.
However, the optimal control of the wind/storage/hydrogen grid-connected power generation system is a nonlinear 0-1 hybrid programming problem, and not only needs to solve the power distribution of equipment such as a fan, a storage battery, hydrogen production and storage, but also relates to the on-off control of the equipment, so that how to manage the energy of the wind/storage/hydrogen grid-connected power generation system is an urgent technical problem to be solved.
Disclosure of Invention
Based on the method, the optimal power distribution of each component of the wind power plant is quickly and accurately obtained by utilizing convex optimization under the condition that nonlinear factors such as an energy storage model, a hydrogen production model, a switching state and the like are considered, the switching state of each electrolytic cell is optimized by adopting dynamic programming, the waste wind is eliminated, the smooth grid-connected active power fluctuation is realized, the surplus wind power is effectively utilized, and the aim of multi-target efficient operation is fulfilled.
The invention relates to a wind/storage/hydrogen grid-connected power generation system wind curtailment and energy absorption management method based on convex optimization, which comprises the following steps:
s1: predicting the active power of the fan, or directly adopting historical data of the active power of the fan to obtain a maximum active power curve of the fan within a period of time, wherein the time scale of the period of time includes but is not limited to year, month, day, hour and minute;
the maximum active power of each fan at the moment k can be expressed as
Figure BDA0002972524410000021
Figure BDA0002972524410000022
wherein ,nwtThe number of the fans of the wind power plant;
s2: establishing a stable mathematical model of storage battery energy storage equipment and electrolytic hydrogen production and storage equipment, and setting constraint conditions for running of each component;
s3: establishing a balance relation of system active power and limiting the fluctuation of the grid-connected active power;
s4: determining an objective function when the system runs;
s5: carrying out convex treatment on each model and each constraint condition by a fitting or relaxation method, and assuming the on-off state of each hydrogen production electrolytic cell in the required optimization time;
s6: rapidly solving the optimal power distribution and dual variables of the state equation of the storage battery and each hydrogen production electrolytic cell by using a convex optimization tool box;
s7: calculating the optimal Hamilton value of the system at each moment according to the values of the dual variables;
s8: optimizing the switch state of each hydrogen production electrolytic cell by adopting a dynamic programming method;
s9: and (4) judging whether the capacities of the storage battery and the hydrogen storage tank meet the final value condition, if so, stopping calculating the output result, and otherwise, repeating S6 to S9.
The steady state mathematical model of the storage battery energy buffer device and the electrolytic hydrogen production and storage device in the S2 can be expressed as follows:
Figure BDA0002972524410000023
Figure BDA0002972524410000024
wherein ,PbIs the output power of the battery, EbIs the energy of the battery, etabFor battery efficiency, EtkAs the remaining capacity of the hydrogen storage tank,
Figure BDA0002972524410000025
hydrogen gas produced for each cell;
the operation constraint in S2 may then be expressed as:
Pbmin≤Pb(k)≤Pbmax
Ebmin≤Eb(k)≤Ebmax
Etkmin≤Etk(k)≤Etkmax
Figure BDA0002972524410000026
Figure BDA0002972524410000031
…
Figure BDA0002972524410000032
Figure BDA0002972524410000033
Figure BDA0002972524410000034
…
Figure BDA0002972524410000035
wherein ,Pbmin and PbmaxPower limit of the accumulator, Ebmin and EbmaxIs the energy limit of the storage battery,
Figure BDA0002972524410000036
Figure BDA0002972524410000037
is the input power of each electrolytic cell,
Figure BDA0002972524410000038
is the minimum input power of each electrolytic cell,
Figure BDA0002972524410000039
is the maximum input power, n, of each cellelzNumber of electrolytic cells, Etkmin and EtkmaxThe minimum and maximum capacities of the hydrogen storage tank,
Figure BDA00029725244100000310
for the active power of each of the fans,
Figure BDA00029725244100000311
for maximum active power of each fan, nwtThe number of the fans is.
In S3, the balance relationship between the system active power and the grid-connected active power fluctuation limit may be represented as:
Figure BDA00029725244100000312
|Pg(k)-Pg(k-1)|≤D
wherein ,PgGrid-connected active power, and D is a grid-connected active power fluctuation constraint;
the objective function of the S4 when the system runs may be defined as:
J＝Jwc+Jelz+Jb
Figure BDA00029725244100000313
Figure BDA00029725244100000314
Figure BDA00029725244100000315
wherein J is an objective function, JwcTo discard wind power, JelzFor cell energy loss, JbFor the energy loss of the battery, Δ t is the time interval,
Figure BDA00029725244100000316
is the heating value of hydrogen.
The protruding treatment of the storage battery charge state and the electrolytic cell hydrogen production model in the S5 comprises the following steps:
Figure BDA0002972524410000041
Figure BDA0002972524410000042
wherein ,
Figure BDA0002972524410000043
in order to obtain the hydrogen production amount,
Figure BDA0002972524410000044
is a fitting coefficient of hydrogen production of the electrolytic cell, wherein y is 1,2elz；
The optimal hamiltonian value for the system in S7 may be expressed as:
Figure BDA0002972524410000045
wherein ,HminAs a function of Hamiltonian, λb and λtkThe dual variables described in S6;
the objective function of the optimization problem of searching the switch state of the electrolytic cell by using dynamic programming in the step S8 can be expressed as:
Figure BDA0002972524410000046
wherein ,JhTo take account of the hamilton values of the cell switches,
Figure BDA0002972524410000047
alpha is the switch penalty term for the switch state of the z-th electrolytic cell at the moment k.
The final value conditions of the state of charge of the battery and the state of capacity of the hydrogen storage tank in S9 may be expressed as:
|Eb(tf)-Eb(t0)|≤εb
Etk≤Etk_max
wherein ,εbIs an error allowance value, t0 and tfStart and end times.
The method has the advantages that under the condition that nonlinear factors such as an energy storage model, a hydrogen production model, a switching state and the like are considered, the optimal power distribution of each component of the wind power plant is quickly and accurately obtained by utilizing convex optimization, and the switching state of each electrolytic cell is optimized by adopting dynamic programming, so that the waste wind is eliminated, the fluctuation of active power of smooth grid connection is realized, the surplus wind power is effectively utilized, and the aim of multi-target efficient operation is fulfilled.
Drawings
Fig. 1 is a flowchart of a wind curtailment and energy absorption management method of a wind/storage/hydrogen grid-connected power generation system according to an embodiment of the present invention;
fig. 2 is a wind/storage/hydrogen and wind power generation system to which the present invention is applied.
Detailed Description
Example (b):
the technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Referring to fig. 1, the method for managing wind curtailment and energy consumption of a wind/storage/hydrogen grid-connected power generation system provided by the embodiment mainly includes the following steps:
s1: predicting the active power of the fan, or directly adopting historical data of the active power of the fan to obtain a maximum active power curve of the fan within a period of time, wherein the time scale of the period of time includes but is not limited to year, month, day, hour and minute;
the maximum active power of each fan at the moment k can be expressed as
Figure BDA0002972524410000051
Figure BDA0002972524410000052
wherein ,nwtThe number of the fans of the wind power plant;
s2: establishing a stable mathematical model of the storage battery energy storage equipment and the electrolytic hydrogen production and storage equipment, and setting constraint conditions of the storage battery energy storage equipment and the hydrogen production and storage equipment during operation;
s3: establishing a balance relation of system active power and limiting the fluctuation of the grid-connected active power;
s4: determining an objective function when the system runs;
s5: carrying out convex treatment on each model and each constraint condition by a fitting or relaxation method, and assuming the on-off state of each hydrogen production electrolytic cell in the required optimization time;
s6: rapidly solving the optimal power distribution and dual variables of the state equation of the storage battery and each hydrogen production electrolytic cell by using a convex optimization tool box;
s7: calculating the optimal Hamilton value of the system at each moment according to the values of the dual variables;
s8: optimizing the switch state of each hydrogen production electrolytic cell by adopting a dynamic programming method;
s9: and (4) judging whether the capacities of the storage battery and the hydrogen storage tank meet the final value condition, if so, stopping calculating the output result, and otherwise, repeating S6 to S9.
Therefore, the method considers nonlinear factors such as an energy storage model, a hydrogen production model, a switching state and the like, quickly and accurately obtains the optimal power distribution of each component of the wind power plant by utilizing convex optimization, optimizes the switching state of each electrolytic cell by adopting dynamic programming, realizes the purposes of eliminating wind curtailment and smooth grid-connected active power fluctuation, achieves the aim of multi-target high-efficiency operation, and effectively utilizes the surplus wind power.
Specifically, the steady state mathematical models and the operation constraints of the storage battery energy buffer device and the electrolytic hydrogen production and storage equipment in S2 can be expressed as:
Figure BDA0002972524410000061
Figure BDA00029725244100000615
wherein ,PbIs the output power of the battery, EbIs the energy of the battery, etabFor battery efficiency, EtkAs the remaining capacity of the hydrogen storage tank,
Figure BDA0002972524410000062
hydrogen gas produced for each cell;
the operation constraint in S2 may then be expressed as:
Pbmin≤Pb(k)≤Pbmax
Ebmin≤Eb(k)≤Ebmax
Etkmin≤Etk(k)≤Etkmax
Figure BDA0002972524410000063
Figure BDA0002972524410000064
…
Figure BDA0002972524410000065
Figure BDA0002972524410000066
Figure BDA0002972524410000067
…
Figure BDA0002972524410000068
wherein ,Pbmin and PbmaxPower limit of the accumulator, Ebmin and EbmaxIs the energy limit of the storage battery,
Figure BDA0002972524410000069
Figure BDA00029725244100000610
is the input power of each electrolytic cell,
Figure BDA00029725244100000611
is the minimum input power of each electrolytic cell,
Figure BDA00029725244100000612
is the maximum input power, n, of each cellelzNumber of electrolytic cells, Etkmin and EtkmaxThe minimum and maximum capacities of the hydrogen storage tank,
Figure BDA00029725244100000613
for the active power of each of the fans,
Figure BDA00029725244100000616
for maximum active power of each fan, nwtThe number of the fans is.
In S3, the balance relationship between the system active power and the grid-connected active power fluctuation limit may be represented as:
Figure BDA00029725244100000614
|Pg(k)-Pg(k-1)|≤D
wherein ,PgGrid-connected active power, and D is a grid-connected active power fluctuation constraint;
the objective function of the S4 when the system runs may be defined as:
J＝Jwc+Jelz+Jb
Figure BDA0002972524410000071
Figure BDA0002972524410000072
Figure BDA0002972524410000073
wherein J is an objective function, JwcTo discard wind power, JelzFor cell energy loss, JbFor the energy loss of the accumulator,. DELTA.t is the time interval, qH2Is the heat value of hydrogen;
the protruding treatment of the storage battery charge state and the electrolytic cell hydrogen production model in the S5 comprises the following steps:
Figure BDA0002972524410000074
Figure BDA0002972524410000075
wherein ,
Figure BDA0002972524410000076
is a fitting coefficient of hydrogen production of the electrolytic cell, wherein y is 1,2elz；
The optimal hamiltonian value for the system in S7 may be expressed as:
Figure BDA0002972524410000077
wherein ,HminAs a function of Hamiltonian, λb and λtkThe dual variables described in S6;
the objective function of the optimization problem of searching the switch state of the electrolytic cell by using dynamic programming in the step S8 can be expressed as:
Figure BDA0002972524410000078
wherein ,JhFor considering the Hamilton of the cell switchThe value of the one or more of the one,
Figure BDA0002972524410000079
alpha is the switch penalty term for the switch state of the z-th electrolytic cell at the moment k.
The final value conditions of the state of charge of the battery and the state of capacity of the hydrogen storage tank in S9 may be expressed as:
|Eb(tf)-Eb(t0)|≤εb
Etk≤Etk_max
wherein ,εbIs an error allowance value, t0 and tfStart and end times.
The above embodiments are only for illustrating the technical concept and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention accordingly, and not to limit the protection scope of the present invention accordingly. All equivalent changes or modifications made in accordance with the spirit of the present disclosure are intended to be covered by the scope of the present disclosure.

Claims (9)

1. A wind/storage/hydrogen grid-connected power generation system wind abandoning and energy absorbing management method is disclosed, the power generation system comprises a fan, storage battery energy storage equipment and electrolysis hydrogen production and storage equipment, the storage battery energy storage equipment comprises a storage battery, and the electrolysis hydrogen production and storage equipment comprises a hydrogen production electrolytic tank and a hydrogen storage tank, and is characterized in that the method comprises the following steps:
s1, obtaining a maximum active power curve of the fan in a period of time;
s2, establishing a stable mathematical model of the storage battery energy storage equipment and the electrolytic hydrogen production and storage equipment, and setting constraint conditions for the storage battery energy storage equipment and the electrolytic hydrogen production and storage equipment during operation;
s3, establishing a balance relation of active power of the power generation system and limiting the fluctuation of the grid-connected active power;
s4, determining an objective function when the power generation system operates;
s5, carrying out convex optimization processing on the stable mathematical models and constraint conditions of the storage battery energy storage equipment and the electrolytic hydrogen production and storage equipment, and assuming the on-off state of each hydrogen production electrolytic cell in the required optimization time;
s6, solving the dual variables of the optimal power distribution and the state equation of the storage battery and each hydrogen production electrolytic cell;
s7, calculating the optimal Hamilton value of the power generation system at each moment according to the value of the dual variable;
s8, searching the on-off state of each hydrogen production electrolytic cell by adopting dynamic programming;
and S9, judging whether the charge state of the storage battery and the capacity state of the hydrogen storage tank meet final value conditions, if so, terminating the calculation and outputting optimized power distribution and switch states, and otherwise, repeating S6 to S9.
2. The wind curtailment and absorption energy management method of the wind/storage/hydrogen grid-connected power generation system according to claim 1, wherein in the step S2, the steady-state mathematical models of the storage battery energy storage device and the electrolysis hydrogen production and storage device are established as follows:
Figure FDA0002972524400000011
Figure FDA0002972524400000012
wherein ,PbIs the output power of the battery, EbIs the energy of the battery, etabFor battery efficiency, EtkAs the remaining capacity of the hydrogen storage tank,
Figure FDA0002972524400000013
hydrogen gas produced for each hydrogen-producing electrolyzer.
3. The wind abandoning and energy absorbing management method for wind/storage/hydrogen grid-connected power generation system according to claim 2, wherein in step S2, the constraint conditions of the storage battery energy storage device and the electrolytic hydrogen production and storage device during operation are expressed as:
Pbmin≤Pb(k)≤Pbmax
Ebmin≤Eb(k)≤Ebmax
Etkmin≤Etk(k)≤Etkmax
Figure FDA0002972524400000021
Figure FDA0002972524400000022
…
Figure FDA0002972524400000023
Figure FDA0002972524400000024
Figure FDA0002972524400000025
…
Figure FDA0002972524400000026
wherein ,Pbmin and PbmaxPower limit of the accumulator, Ebmin and EbmaxIs the energy limit of the storage battery,
Figure FDA0002972524400000027
Figure FDA0002972524400000028
is the input power of each electrolytic cell,
Figure FDA0002972524400000029
is the minimum input power of each electrolytic cell,
Figure FDA00029725244000000210
is the maximum input power, n, of each cellelzNumber of electrolytic cells, Etkmin and EtkmaxThe minimum and maximum capacities of the hydrogen storage tank,
Figure FDA00029725244000000211
for the active power of each of the fans,
Figure FDA00029725244000000212
for maximum active power of each fan, nwtThe number of the fans is.
4. The wind curtailment and energy absorption management method of the wind/storage/hydrogen grid-connected power generation system based on convex optimization according to claim 3, characterized in that: in step S3, establishing a balance relationship between the active power of the power generation system and limiting the grid-connected active power fluctuation as follows:
Figure FDA00029725244000000213
|Pg(k)-Pg(k-1)|≤D
wherein ,PgAnd D is the fluctuation constraint of the grid-connected active power.
5. The wind curtailment and energy absorption management method of the wind/storage/hydrogen grid-connected power generation system based on convex optimization according to claim 4, characterized in that: in step S4, the objective function of the power generation system during operation is defined as:
J＝Jwc+Jelz+Jb
Figure FDA00029725244000000214
Figure FDA00029725244000000215
Jb＝∑ηb|Pb(k)|Δt
wherein J is an objective function, JwcTo discard wind power, JelzFor cell energy loss, JbFor the energy loss of the battery, Δ t is the time interval,
Figure FDA0002972524400000031
is the heating value of hydrogen.
6. The wind/storage/hydrogen grid-connected power generation system wind curtailment and energy absorption management method based on convex optimization of claim 5, wherein the convex processing is as follows:
Figure FDA0002972524400000032
Figure FDA0002972524400000033
wherein ,
Figure FDA0002972524400000034
in order to obtain the hydrogen production amount,
Figure FDA0002972524400000035
is a fitting coefficient of hydrogen production of the electrolytic cell, wherein y is 1,2elz。
7. The wind curtailment and energy absorption management method of the wind/storage/hydrogen grid-connected power generation system based on convex optimization according to claim 6, characterized in that: in step S7, the optimal hamiltonian value of the power generation system is represented by:
Figure FDA0002972524400000036
wherein ,HminAs a function of Hamiltonian, λb and λtkThe dual variables described in S6, respectively.
8. The wind curtailment and energy absorption management method of the wind/storage/hydrogen grid-connected power generation system based on convex optimization according to claim 7, characterized in that: in step S8, the objective function for searching the optimization problem of the on-off state of each hydrogen production electrolytic cell by dynamic programming is represented as:
Figure FDA0002972524400000037
wherein ,JhTo take account of the hamilton values of the cell switches,
Figure FDA0002972524400000038
alpha is the switch penalty term for the switch state of the z-th electrolytic cell at the moment k.
9. The wind curtailment and energy absorption management method of the wind/storage/hydrogen grid-connected power generation system based on convex optimization according to claim 8, characterized in that: in step S9, the final value conditions of the battery state of charge and the hydrogen storage tank state of charge are represented as:
|Eb(tf)-Eb(t0)|≤εb
Etk≤Etk_max
wherein ,εbIs an error allowance value, t0 and tfStart and end times.
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