WO2017161785A1 - Procédé de régulation d'une sortie de puissance photovoltaïque stable en fonction de l'état de fonctionnement d'un stockage d'énergie - Google Patents

Procédé de régulation d'une sortie de puissance photovoltaïque stable en fonction de l'état de fonctionnement d'un stockage d'énergie Download PDF

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WO2017161785A1
WO2017161785A1 PCT/CN2016/091834 CN2016091834W WO2017161785A1 WO 2017161785 A1 WO2017161785 A1 WO 2017161785A1 CN 2016091834 W CN2016091834 W CN 2016091834W WO 2017161785 A1 WO2017161785 A1 WO 2017161785A1
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energy storage
power
storage system
charging
charge
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PCT/CN2016/091834
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Chinese (zh)
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李春来
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严利容
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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
    • 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
    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/383—
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin

Definitions

  • the invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic power stable output control method based on an energy storage operation state.
  • photovoltaic power generation has developed rapidly in recent years, and has delivered a large amount of clean energy to the power grid.
  • the installed capacity and permeability of photovoltaic power generation systems are constantly improving, and it also brings many negative effects to the safe and stable operation of power systems, such as poor peak shaving capability.
  • the impact on the power grid is large, and the rotating spare capacity needs to be increased. Therefore, the energy storage energy storage system equipped with a certain capacity for the photovoltaic electric field can effectively suppress the fluctuation of the photovoltaic output power, improve the power quality of the system, and achieve friendly access to the power grid.
  • the wavelet packet method is used to decompose the photovoltaic output power signal, combined with the cycle life performance of different types of energy storage, and the charge-discharge power of energy-type energy storage and power-type energy storage is adjusted in real time through fuzzy adaptive control of power-type energy storage SOC;
  • the filter time constant of the filter is adjusted in real time by relevant rules to achieve the goal of controlling the state of charge to be stable in the normal working state;
  • the capacity estimation function of energy storage equipment is obtained by interval estimation method, and the prediction error variance of energy storage capacity under distributed configuration and centralized configuration is compared to achieve better power compensation effect;
  • the capacity optimization model is established.
  • the genetic algorithm is used to optimize the minimum cost.
  • the optimal capacity configuration of each power supply in a given scheduling strategy is discussed.
  • the above research has made more considerations on the fluctuation of grid-connected power of photovoltaic power plants, but does not consider the influence of the operating state of the energy storage body on the fluctuation of photovoltaic power, which makes the above-mentioned methods have a large demand for energy storage capacity.
  • an object of the present invention is to provide a photovoltaic power stable output control method based on an energy storage operation state.
  • a photovoltaic power stable output control method based on an energy storage operation state comprising:
  • step S1 in the optimal power output model in step S1:
  • ⁇ C is the charging efficiency of the energy storage system
  • ⁇ D is the discharge efficiency of the energy storage system.
  • step S1 in the optimal power output model in step S1:
  • P ESS (t) ⁇ i (t) ⁇ P(t) ⁇ C
  • ⁇ C the charging efficiency of the energy storage system
  • ⁇ i (t) the correction coefficient of the charging and discharging power at time t
  • P ESS (t) ⁇ i (t) ⁇ P(t) / ⁇ D
  • the charging and discharging power of the energy storage system at time t ⁇ D is the discharge efficiency of the energy storage system
  • ⁇ i (t) is the correction coefficient of the charging and discharging power at time t.
  • the energy storage system is classified according to the limitation of the operating SOC, including: pre-discharge area [Q SOClow-L2 , Q SOClow-L1 ], normal area [Q SOClow-L1 , Q SOChigh-L1 ] , pre-charge area [Q SOChigh-L1 , Q SOChigh-L2 ].
  • the charge-discharge power correction coefficient ⁇ i (t) at the time t is specifically:
  • ⁇ i (t) is 1 in both the state of charge and the state of discharge
  • ⁇ i (t) 1 in the state of charge, and in the state of discharge
  • the goal of the energy storage capacity optimization is:
  • ⁇ L , ⁇ S , and ⁇ E are respectively the corresponding unit price of the photovoltaic power plant's abandoned light loss energy, the smooth power shortage loss energy, and the converted energy of the energy storage system crossing the line;
  • ⁇ L L LOST is the photovoltaic power plant abandoned light energy cost;
  • ⁇ S L SHORT is the energy cost lost by the smooth power shortage of the photovoltaic power station;
  • ⁇ E L ESS is the converted energy cost of the energy storage system crossing the line;
  • K L , K S and K E are the penalty coefficients of the running cost;
  • the photovoltaic power plant abandoned light loss energy, the smooth power shortage loss energy and the energy storage system cross-line operation conversion energy are respectively:
  • the constraint conditions include:
  • P D and P C are the ultimate charge and discharge power of the energy storage system, respectively;
  • ⁇ ⁇ P d max ⁇ ⁇ ⁇ , ⁇ P d (t) ⁇ P d (t) is the fluctuation value of the photovoltaic power plant output power after being stabilized by the energy storage system, and ⁇ P d max is the maximum fluctuation value Allow the upper limit of the range, which is the corresponding level of credibility;
  • the invention considers that the photovoltaic power is affected by natural conditions and has strong volatility, and uses the energy storage to realize the smooth output control of the photovoltaic power.
  • the charge and discharge power correction coefficient the effective adjustment of the energy storage state is realized, thereby avoiding excessive charge and discharge, thereby effectively prolonging the energy storage operation life and reducing the system operation cost while fully suppressing the photovoltaic output fluctuation.
  • FIG. 1 is a schematic flow chart of a photovoltaic power stable output control method based on an energy storage operation state according to the present invention.
  • FIG. 2 is a graph of a desired output cross-section of a selected time section in accordance with an embodiment of the present invention.
  • FIG. 3 is a schematic diagram showing the effect of the selected time section leveling effect in an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a SOC curve in accordance with an embodiment of the present invention.
  • the energy storage operation strategy for suppressing photovoltaic power fluctuations does not consider the state of charge of the energy storage system.
  • the energy storage system frequently exhibits overcharge and over discharge, or is in an abnormal working state for a long time.
  • its service life is greatly reduced, the cost of the energy storage system is greatly increased, which is not conducive to economic considerations.
  • the overcharge and overdischarge of the energy storage system makes the charge and discharge power difficult to control, resulting in severe power injection into the grid. Fluctuations affect the stability of the grid.
  • the maximum state of charge in each battery pack is taken as the state of charge of the entire energy storage system during charging; the minimum state of charge in each battery pack is taken as the entire storage during discharge. The state of charge of the system. This can effectively prevent overcharging and overdischarging of a single battery.
  • the invention adjusts the energy storage charging and discharging system to adjust the energy storage device to always work in the normal working range, and simultaneously considers the energy storage state and the photovoltaic power output stability, can simultaneously stabilize the grid power fluctuation and accurately adjust the energy storage system load. Electrical state.
  • a photovoltaic power stable output control method based on an energy storage operation state of the present invention includes:
  • the invention adjusts the energy storage and discharge system to adjust the energy storage device to always work in the normal working range.
  • the method simultaneously considers the energy storage state and the photovoltaic power output stability, and can effectively stabilize the grid power fluctuation and accurately adjust the energy storage. System state of charge.
  • the energy storage strategy of the photovoltaic power storage system is: when the photovoltaic power output power is greater than the grid-connected power reference value, the energy storage system is charged to stabilize the output power fluctuation; when the photovoltaic power output power is less than the grid-connected power reference value, the energy storage system Discharge to compensate for the lack of output power, in order to smooth the output power of photovoltaic power, to achieve the stability of photovoltaic power grid-connected power.
  • the charge and discharge power command of the energy storage station should consider the current SOC level and the power command size at the current time, that is, when the SOC is in the normal working range, the charge and discharge power of the energy storage power station remains unchanged; When crossing the line to the abnormal working range, it is necessary to adjust the charging and discharging power in time to prevent overcharge and overdischarge.
  • [Q SOClow-L1 , Q SOChigh-L1 ] is the normal area
  • [Q SOChigh-L1 , Q SOChigh-L2 ] is the pre-overcharge area
  • [Q SOChigh-L2 , Q SOCmax ] is the overcharge area
  • the above is the reserve The operating range of the system with different state of charge, wherein Q SOChigh-L2 and Q SOClow-L2 are respectively overcharged and over -alarmed .
  • the change of the operating range of the energy storage system's state of charge will trigger the corresponding adjustment of the power correction coefficient, and the power correction coefficient will be used to change the charging and discharging power of the energy storage system to achieve the pre-control operation of the energy storage system to avoid overcharge and over discharge. status.
  • the specific control strategy is shown in Table 1.
  • ⁇ i (t) is the charge/discharge power correction coefficient at time t, and is 1 when the energy storage system is in the normal region;
  • Q SOC (t) is the state of charge of the energy storage system at time t.
  • the present invention adopts a logarithmic barrier function. When the state of charge is close to Q SOCmax or Q SOClow-L2 , the logarithmic function is highly convergent, and ⁇ i (t) can be lowered more quickly, and the charge and discharge can be better controlled in advance. The role of power effectively prevents the state of charge of the energy storage system from reaching an overcharge or overdischarge state.
  • P ESS (t) is the charge/discharge power of the energy storage system after the power correction factor is adjusted at time t.
  • P ESS (t)>0 the energy storage system is charged
  • P ESS (t) ⁇ 0 the energy storage system is discharged.
  • the goal of optimizing the energy storage capacity of photovoltaic power plants is to ensure the mutual control of the input power and operating costs under the premise of reducing the fluctuation of photovoltaic power output power.
  • the input cost of the lowest energy storage and The operating cost optimizes the operational efficiency of the photovoltaic power storage system.
  • the input cost C C of the energy storage system includes the maintenance cost C M of the energy storage system, and the replacement cost of each energy storage unit of the energy storage system (only when the service life of the energy storage unit is less than the engineering life) C R and energy storage
  • the basic investment cost of the system is C B .
  • the operating cost includes the cost of light loss from the photovoltaic power station caused by the adjustment of the power correction factor, the cost of smoothing the power shortage and the cost of the conversion of the energy storage system across the line, all of which vary due to changes in energy storage capacity.
  • the annual output power of photovoltaic power plants is the research object of energy storage capacity optimization.
  • the photovoltaic power plant abandoned light loss energy, smooth power shortage loss energy and storage.
  • the conversion energy of the system can be operated as shown in equations (11), (12), and (13):
  • N y is the time year of the study object
  • g, h is the total number of times during the charging and discharging process in the year of y i ⁇ 1 to adjust the operation interval
  • p and q are the initial and end times of the g interval respectively
  • u, v is the initial and final time interval h
  • K exceeds the maximum number of which is on the state of charge is N y annual energy storage system in the operating state
  • L is N y annual energy storage system in the operating state is located lower than the minimum state
  • the goal of optimizing the energy storage capacity of photovoltaic power plants is:
  • ⁇ L , ⁇ S , ⁇ E are the corresponding unit price of photovoltaic power plant abandoned light loss energy, smooth power shortage loss energy and energy conversion system cross-line operation;
  • ⁇ L L LOST is photovoltaic power plant abandoned light energy cost ;
  • ⁇ S L SHORT is the energy cost of the smooth power shortage of the photovoltaic power station;
  • ⁇ E L ESS is the converted energy cost of the energy storage system crossing the line;
  • K L , K S and K E are the penalty coefficients of the operating cost;
  • C C storage The input cost of the system.
  • the cost of conversion loss of the energy storage system across the line consists of two parts: First, when the energy storage system is operating in an excessively high state, the energy storage system is not in a reasonable operating state and affects its life cycle. Cost; Second, when the state of charge of the energy storage system is too low, the energy storage system is not in a reasonable operating state and affects the conversion cost of its life cycle.
  • constraints in the charge and discharge strategy of the present invention include:
  • P D and P C are the ultimate charge and discharge power of the energy storage system, respectively, and the discharge is regarded as a negative charging process, the size of which is based on its absolute value.
  • Constraints include photovoltaic power plant output power fluctuation level constraints:
  • ⁇ P d (t) ⁇ P d (t) is the fluctuation value of the photovoltaic power plant output power after being stabilized by the energy storage system
  • ⁇ P d max is the upper limit of the maximum allowable range of the fluctuation value
  • ⁇ is the corresponding credibility level.
  • the optimal energy storage capacity is calculated based on the actual operational data of a photovoltaic power plant in Qinghai.
  • This embodiment considers the PSO algorithm to solve the stochastic optimization problem of the present invention including dynamic boundary conditions and containing a plurality of random variables.
  • the specific model solving steps are:
  • Step 1 Select the time interval window length y of the research object and its operation data P(t);
  • Step 2 Determine a desired output target value PG based on the optimal power output model, and give an initial SOC equivalent
  • Step 3 Set the particle swarm dimension D, the maximum iteration number M max , the convergence precision C ⁇ , and initialize the particle swarm position x and velocity v;
  • Step 4 According to the charge and discharge strategy of the present invention, parameters such as c 1 , c 2 , ⁇ , V min , and V max are set, and the fitness value px id of each particle is calculated according to the formula (11-17), and the particle size of the particle itself is Comparing the value p i with the global example extreme value p g , if the fitness value is small, updating p i and p g , if not updating the particle velocity V id and the position X id ;
  • Step 5 Calculate ⁇ 2 to determine whether the convergence condition is satisfied.
  • the search convergence condition is:
  • ⁇ 2 is the amount of change in the population or global fitness variance of the particle population
  • C ⁇ is a constant constant close to zero. If yes, obtain the optimal energy storage capacity W O ; if not, re-release the example to form a new ethnic group and repeat step (4).
  • the invention measures the effectiveness of the method of the invention from the index parameters such as the optimal capacity W O , the leveling power offset ⁇ , the SOC extreme value limit number N, and the SOC process curve.
  • the installed capacity of the photovoltaic power station is 9MW, the acquisition frequency is 5min, and the target value is as shown in Figure 2.
  • the smoothing fluctuation output curve is obtained as shown in FIG. 3, and the calculation result of the method of the present invention is shown in Table 2.
  • the method of the present invention effectively realizes the optimization of the energy storage capacity; in terms of the power offset, the method of the present invention is similar to the conventional method and slightly increased, and the reason is the power correction coefficient adjustment strategy.
  • the probability of abandoning or stabilizing the insufficient energy is improved; in terms of the limit value operation, the invention greatly reduces the value of N, and the decrease is 96.2%, and the effect is obvious.
  • the capacity optimization calculation model of the present invention comprehensively considers the overall economics of the configuration and operation of the energy storage power station, and is beneficial to the effective combination with the site.
  • the above theoretical research provides theoretical premise and guarantee for the optimization of energy storage capacity.
  • the actual data example analysis verified the above conclusions.
  • the invention considers that the photovoltaic power is affected by natural conditions and has strong volatility, and uses the energy storage to realize the smooth output control of the photovoltaic power.
  • the charge and discharge power correction coefficient Through the charge and discharge power correction coefficient, the effective adjustment of the energy storage state is realized, thereby avoiding excessive charge and discharge, thereby effectively prolonging the energy storage operation life and reducing the system operation cost while fully suppressing the photovoltaic output fluctuation.
  • the technical director further explored the optimal capacity of photovoltaic power plant configuration energy storage, and provided important theoretical support for the optimal operation of the optical storage system.
  • the actual operation data of photovoltaic power station in Qinghai area is used for calculation.
  • the results show that the photovoltaic power can be output smoothly, and the fluctuation range of the stored energy state can be controlled, which can effectively avoid excessive charging and discharging, which indicates that the method has strong feasibility and application. Sex.

Abstract

L'invention concerne un procédé de régulation d'une sortie de puissance photovoltaïque stable sur la base de l'état de fonctionnement d'un stockage d'énergie, ledit procédé consistant à : S1) sélectionner une longueur de fenêtre de section temporelle d'objet de recherche y et des données de fonctionnement P(t) correspondantes ; S2) sur la base d'un modèle de sortie de puissance optimale, déterminer une valeur cible PG de sortie voulue ; S3) régler le nombre D de dimensions d'essaim de particules, le nombre maximal Mmax d'itérations et une précision de convergence Cσ, et initialiser une position x d'essaim de particules et une vitesse v simultanément ; S4) selon une politique de charge et de décharge, calculer une valeur d'adaptation Pxid de chaque particule, et comparer une valeur extrême de particule pi associée à une valeur extrême de particule globale pg ; si la valeur d'adaptation est inférieure, mettre à jour pi et pg, et si tel n'est pas le cas, mettre à jour une vitesse de particule Vid et une position Xid ; et S5) calculer Δσ2 et déterminer si une formule I de condition de convergence est satisfaite, si tel est le cas, acquérir la capacité Wo de stockage d'énergie optimale, et si tel n'est pas le cas, libérer à nouveau des particules pour construire un nouvel essaim de particules et répéter l'étape S4. Le procédé permet de supprimer efficacement une fluctuation de puissance de raccordement au réseau et de régler en même temps précisément l'état de charge d'un système de stockage d'énergie.
PCT/CN2016/091834 2016-03-23 2016-07-27 Procédé de régulation d'une sortie de puissance photovoltaïque stable en fonction de l'état de fonctionnement d'un stockage d'énergie WO2017161785A1 (fr)

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CN201610170019.XA CN107230974A (zh) 2016-03-23 2016-03-23 基于储能运行状态的光伏功率稳定输出控制方法
CN201610170019.X 2016-03-23

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CN116826816A (zh) * 2023-08-30 2023-09-29 湖南大学 考虑电能质量分级治理的储能有功-无功协调复用方法
CN117254526A (zh) * 2023-11-06 2023-12-19 河北大学 一种光储充检微电网一体站能源协同优化控制方法
CN117254526B (zh) * 2023-11-06 2024-05-07 河北大学 一种光储充检微电网一体站能源协同优化控制方法
CN117411087A (zh) * 2023-12-13 2024-01-16 国网山东省电力公司电力科学研究院 一种风光储氢联合发电系统的协同优化控制方法及系统
CN117411087B (zh) * 2023-12-13 2024-04-12 国网山东省电力公司电力科学研究院 一种风光储氢联合发电系统的协同优化控制方法及系统

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