CN112531753A - Energy storage system operation optimization method - Google Patents
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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
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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
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
- H02J3/241—The oscillation concerning frequency
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Abstract
The invention discloses an energy storage system operation optimization method, which comprises the following steps: firstly, establishing a daily energy storage battery charge-discharge peak-valley time-of-use electricity price mechanism; secondly, a compensation mechanism for energy storage to participate in power grid frequency modulation is established; thirdly, establishing an energy storage life calculation mechanism; fourthly, establishing a maximum optimization objective function of the energy storage comprehensive income; fifthly, establishing energy storage charging and discharging and power system constraint conditions; and sixthly, calculating the operation strategy of the energy storage system by adopting a particle swarm algorithm. The invention can realize the maximization of the comprehensive energy storage income on the premise of ensuring the safe operation of the power grid.
Description
Technical Field
The invention relates to an operation optimization method of an energy storage system.
Background
In recent years, energy storage systems have been widely used in power systems due to their dual capabilities of flexible power regulation and energy carrying. The energy storage system can assist renewable energy sources in grid connection in various modes, and effectively realizes power balance during power gaps. Therefore, energy storage has the potential to significantly improve grid efficiency, stability and resiliency. Although the popularization and application of energy storage in a power system are promoted by the improvement of the technology and the reduction of the energy storage cost, the investment cost of energy storage is still high at the present stage, and the energy storage system faces insufficient economic benefits in the application process.
The reform of the power market promotes energy storage to participate in auxiliary services, and in order to realize the value of the energy storage auxiliary services, compensation mechanisms of the energy storage system auxiliary services are proposed in many countries. Currently, a single operation mode of an energy storage system brings more uncertainty to network access income of the energy storage system, and development of energy storage is hindered to a certain extent.
Disclosure of Invention
The invention provides an energy storage system operation optimization method, which aims to: under the premise of guaranteeing safe operation of a power grid, energy storage comprehensive income maximization is realized.
The technical scheme of the invention is as follows:
an energy storage system operation optimization method comprises the following steps:
step 1: establishing a time-of-use electricity price mechanism of the charging and discharging peak valley of the daily energy storage battery;
step 2: establishing a compensation mechanism for energy storage to participate in power grid frequency modulation;
and step 3: establishing an energy storage life calculation mechanism;
and 4, step 4: establishing a maximum optimization objective function of the energy storage comprehensive income;
and 5: establishing energy storage charging and discharging and power system constraint conditions;
step 6: and calculating the operation strategy of the energy storage system by adopting a particle swarm algorithm, and realizing the maximization of the comprehensive energy storage profit on the premise of ensuring the safe operation of the power grid.
Further, the method for constructing the energy storage battery charge-discharge peak-valley time-of-use electricity price mechanism in the step 1 is as follows: the energy storage system correspondingly establishes an energy storage battery electricity price mechanism according to different electricity market electricity price rule mechanisms:
wherein, Cn(t) is the charge and discharge electrovalence of the energy storage battery at the moment t, etap、ηfAnd ηvRespectively, peak electricity price, flat electricity price and valley electricity price, Tp、TfAnd TvRespectively, a peak period, a flat period, and a valley period.
Further, the method for constructing the compensation mechanism for the energy storage participation in the grid frequency modulation in step 2 is as follows:
Cs(t)＝Cc(t)*δc+m*Cp(t)*δm
wherein, Cs(t) frequency-modulated price for time period t, Cc(t) frequency modulation capacity unit price in t period, Cp(t) frequency-adjusted mileage unit price at time t, m is average mileage, δcAnd deltamIs a frequency adjustment performance index.
Further, the method for constructing the energy storage life calculation mechanism in step 3 is as follows: equivalent operating life T of energy storage systemlifeAs shown in the following formula:
wherein N is the charge-discharge frequency of energy storage in one year, and LiThe cycle life of the stored energy during the ith charge and discharge is shown;
Lithe calculation method comprises the following steps:
Li＝4000D-0.795
wherein D is the charge-discharge depth.
Further, the maximum optimization objective function of the energy storage comprehensive profit in the step 4 is set as follows:
max f＝f1+f2-fin
wherein f is the net income of the energy storage system, f1For the price arbitrage of energy storage systems, f2Adjusting the income for the frequency of the energy storage system, finFor the investment and operational maintenance costs of the energy storage system, T1For the period of daily use of the energy storage system, T2For the frequency adjustment period, Ps(t) is the active power of the energy storage system during a time period t, Δ t corresponds to Cn(t) time of use of different electricity rate periods, Pbr(t) the energy storage system frequency regulation capacity in time period t, fcAs capital recovery factor, ceIs the unit cost of electricity of the energy storage system, cpIs the unit electricity cost, P, of the energy storage systemcapAnd ScapThe rated charge-discharge power and the rated capacity of the energy storage system are respectively, and r is the annual rate.
Further, the energy storage charging and discharging and power system constraint conditions in the step 5 include power system static power flow constraint conditions, energy storage power and charging state constraint conditions and node voltage constraint conditions.
The power system static power flow constraint conditions are as follows:
wherein, PWTiAnd QWTiIs the active and reactive power, P, of the wind power generation at node iPViAnd QPViIs the active and reactive power of the photovoltaic on node i, PsiIs the active power stored on node i, PLiAnd QLiIs the active and reactive power of the load on node i, N is the number of nodes, UiAnd UjVoltages of nodes i and j, G, respectivelyijAnd BijAre respectively the real and imaginary parts of the nodal admittance, thetaijIs the phase difference between nodes i and j;
the energy storage power and charging state constraint conditions are as follows:
wherein, Ps(t) is the charging and discharging power of the energy storage system at the time t, SoC (t) is the charging state of the energy storage system at the time t, Pmax(t) maximum charging and discharging power of the energy storage system at time t, SoCmax(t) is the maximum charging state of the energy storage system at time t;
the node voltage constraints are as follows:
wherein the content of the first and second substances,
and
the minimum allowed voltage and the maximum allowed voltage of the node i.
Compared with the prior art, the invention has the following beneficial effects: the method comprises the steps of establishing a maximum optimization objective function of the comprehensive energy storage profit by considering the influence of a charge and discharge strategy on the cycle life of the energy storage based on the electricity price and compensation mechanism of charge and discharge of the energy storage battery and frequency modulation and combining the multi-aspect constraint conditions of the energy storage and power system, performing optimization calculation on the operation strategy of the energy storage system by utilizing a particle swarm algorithm, and realizing the maximization of the comprehensive energy storage profit on the premise of ensuring the safe operation of a power grid.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The technical scheme of the invention is explained in detail in the following with the accompanying drawings:
referring to fig. 1, a method for optimizing the operation of an energy storage system includes the following steps:
step 1: and establishing a time-of-use electricity price mechanism of the charging and discharging peak valley of the daily energy storage battery. Under daily condition, the energy storage system carries out arbitrage through the price difference of electricity at different times, according to the electricity price rule mechanism of different electric power markets, can correspond and establish energy storage battery electricity price mechanism:
wherein, Cn(t) is the charge and discharge electrovalence of the energy storage battery at the moment t, t is the time period, etap、ηfAnd ηvRespectively, peak electricity price, flat electricity price, valley electricity price, Tp、TfAnd TvRespectively, a peak period, a flat period, and a valley period. Different electricity price mechanisms in different time periods can also be provided according to different policies.
Step 2: and establishing a compensation mechanism for energy storage participation in power grid frequency modulation. The construction method comprises the following steps:
Cs(t)＝Cc(t)*δc+m*Cp(t)*δm
wherein, Cs(t) frequency-modulated price for time period t, Cc(t) frequency modulation capacity unit price in t period, Cp(t) frequency-adjusted mileage unit price at time t, m is average mileage, δcAnd deltamIs a frequency adjustment performance index. Generally speaking, δcAnd deltamThe frequency may be 1.
And step 3: and establishing an energy storage life calculation mechanism. Equivalent operating life T of energy storage systemlifeAs shown in the following formula:
wherein N is the charge-discharge frequency of energy storage in one year, and LiThe cycle life of the stored energy during the ith charge and discharge is shown. L isiThe calculation method comprises the following steps:
Li＝4000D-0.795
wherein D is the charge-discharge depth.
And 4, step 4: and establishing a maximum optimization objective function of the comprehensive energy storage income. The objective function is set as follows:
max f＝f1+f2-fin
wherein f is the net income of the energy storage system, f1For the price arbitrage of energy storage systems, f2Adjusting the income for the frequency of the energy storage system, finFor the investment and operational maintenance costs of the energy storage system, T1For the period of daily use of the energy storage system, T2For the frequency adjustment period, Ps(t) is the active power of the energy storage system during a time period t, Δ t corresponds to Cn(t) use of different electricity rate periodsTime of use, Pbr(t) the energy storage system frequency regulation capacity in time period t, fcAs capital recovery factor, ceIs the unit cost of electricity of the energy storage system, cpIs the unit electricity cost, P, of the energy storage systemcapAnd ScapThe rated charge-discharge power and the rated capacity of the energy storage system are respectively, and r is the annual rate.
And 5: and establishing constraint conditions such as energy storage charging and discharging and an electric power system, wherein the constraint conditions comprise a static power flow constraint condition, an energy storage power and charging state constraint condition and a node voltage constraint condition of the electric power system.
The power system static power flow constraint conditions are as follows:
wherein, PWTiAnd QWTiIs the active and reactive power, P, of the wind power generation at node iPViAnd QPViIs the active and reactive power of the photovoltaic on node i, PsiIs the active power stored on node i, PLiAnd QLiIs the active and reactive power of the load on node i, N is the number of nodes, UiAnd UjVoltages of nodes i and j, G, respectivelyijAnd BijAre respectively the real and imaginary parts of the nodal admittance, thetaijIs the phase difference between nodes i and j.
The energy storage power and state of charge constraints are as follows:
wherein, Ps(t) is the charging and discharging power of the energy storage system at the time t, SoC (t) is the charging state of the energy storage system at the time t, Pmax(t) maximum charging and discharging power of the energy storage system at time t, SoCmaxAnd (t) is the maximum charging state of the energy storage system at the moment t.
The node voltage constraints are as follows:
wherein the content of the first and second substances,
and
the minimum allowed voltage and the maximum allowed voltage of the node i.
Step 6: and (3) aiming at the maximum comprehensive yield of the energy storage, combining all the equations, calculating the operation strategy of the energy storage system by adopting a particle swarm algorithm, and applying the operation strategy to the actual energy storage system. Therefore, the energy storage comprehensive income maximization can be realized on the premise of ensuring the safe operation of the power grid.
Claims (6)
1. An energy storage system operation optimization method is characterized in that: the method comprises the following steps:
step 1: establishing a time-of-use electricity price mechanism of the charging and discharging peak valley of the daily energy storage battery;
step 2: establishing a compensation mechanism for energy storage to participate in power grid frequency modulation;
and step 3: establishing an energy storage life calculation mechanism;
and 4, step 4: establishing a maximum optimization objective function of the energy storage comprehensive income;
and 5: establishing energy storage charging and discharging and power system constraint conditions;
step 6: and calculating the operation strategy of the energy storage system by adopting a particle swarm algorithm, and realizing the maximization of the comprehensive energy storage profit on the premise of ensuring the safe operation of the power grid.
2. The energy storage system operation optimization method of claim 1, wherein: the method for constructing the energy storage battery charge-discharge peak-valley time-of-use electrovalence mechanism in the step 1 comprises the following steps: the energy storage system correspondingly establishes an energy storage battery electricity price mechanism according to different electricity market electricity price rule mechanisms:
wherein, Cn(t) is the charge and discharge electrovalence of the energy storage battery at the moment t, etap、ηfAnd ηvRespectively, peak electricity price, flat electricity price and valley electricity price, Tp、TfAnd TvRespectively, a peak period, a flat period, and a valley period.
3. The energy storage system operation optimization method of claim 2, wherein: the construction method of the compensation mechanism for the energy storage participation power grid frequency modulation in the step 2 is as follows:
Cs(t)＝Cc(t)*δc+m*Cp(t)*δm
wherein, Cs(t) frequency-modulated price for time period t, Cc(t) frequency modulation capacity unit price in t period, Cp(t) frequency-adjusted mileage unit price at time t, m is average mileage, δcAnd deltamIs a frequency adjustment performance index.
4. The energy storage system operation optimization method of claim 3, wherein: the construction method of the energy storage life calculation mechanism in the step 3 comprises the following steps: equivalent operating life T of energy storage systemlifeAs shown in the following formula:
wherein N is the charge-discharge frequency of energy storage in one year, and LiThe cycle life of the stored energy during the ith charge and discharge is shown;
Lithe calculation method comprises the following steps:
Li＝4000D-0.795
wherein D is the charge-discharge depth.
5. The energy storage system operation optimization method of claim 4, wherein: and 4, setting the maximum optimization objective function of the energy storage comprehensive income as follows:
max f＝f1+f2-fin
wherein f is the net income of the energy storage system, f1For the price arbitrage of energy storage systems, f2Adjusting the income for the frequency of the energy storage system, finFor the investment and operational maintenance costs of the energy storage system, T1For the period of daily use of the energy storage system, T2For the frequency adjustment period, Ps(t) is the active power of the energy storage system during a time period t, Δ t corresponds to Cn(t) time of use of different electricity rate periods, Pbr(t) the energy storage system frequency regulation capacity in time period t, fcAs capital recovery factor, ceIs the unit cost of electricity of the energy storage system, cpIs the unit electricity cost, P, of the energy storage systemcapAnd ScapThe rated charge-discharge power and the rated capacity of the energy storage system are respectively, and r is the annual rate.
6. The energy storage system operation optimization method according to any one of claims 1 to 5, characterized in that: step 5, the constraint conditions of the energy storage charging and discharging and the power system comprise a static power flow constraint condition, an energy storage power and charging state constraint condition and a node voltage constraint condition of the power system; the power system static power flow constraint conditions are as follows:
wherein, PWTiAnd QWTiIs the active and reactive power, P, of the wind power generation at node iPViAnd QPViIs the active and reactive power of the photovoltaic on node i, PsiIs the active power stored on node i, PLiAnd QLiIs the active and reactive power of the load on node i, N is the number of nodes, UiAnd UjVoltages of nodes i and j, G, respectivelyijAnd BijAre respectively the real and imaginary parts of the nodal admittance, thetaijIs the phase difference between nodes i and j;
the energy storage power and charging state constraint conditions are as follows:
wherein, Ps(t) is the charging and discharging power of the energy storage system at the time t, SoC (t) is the charging state of the energy storage system at the time t, Pmax(t) maximum charging and discharging power of the energy storage system at time t, SoCmax(t) is the maximum charging state of the energy storage system at time t;
the node voltage constraints are as follows:
wherein, Ui minAnd Ui maxThe minimum allowed voltage and the maximum allowed voltage of the node i.
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| CN113098040A (en) * | 2021-04-09 | 2021-07-09 | 国网新疆电力有限公司经济技术研究院 | Power grid side energy storage capacity optimal configuration method for obtaining multi-scene benefits |
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| US20170337646A1 (en) * | 2016-05-19 | 2017-11-23 | Hefei University Of Technology | Charging and discharging scheduling method for electric vehicles in microgrid under time-of-use price |
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| CN113098040B (en) * | 2021-04-09 | 2023-07-11 | 国网新疆电力有限公司经济技术研究院 | Power grid side energy storage capacity optimal configuration method for obtaining multi-scene benefits |
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