CN116014903A - Coordination control method and system based on energy storage safety chain identification - Google Patents
Coordination control method and system based on energy storage safety chain identification Download PDFInfo
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Abstract
The invention provides a coordination control method and a coordination control system based on energy storage safety chain identification. The method comprises the following steps: and carrying out safety chain identification according to the design planning diagram of the large-scale energy storage system, and further obtaining a basic safety chain. And acquiring required parameters required by the basic safety chain from a preset database, and establishing a basic safety chain model by combining the basic safety chain to perform fault evolution. And acquiring real-time monitoring data and extracting features to obtain the safety feature quantity required by the basic safety chain model. Inputting the safety characteristic quantity into a basic safety chain model for state estimation, generating the health state of each safety chain in the basic safety chain model, and judging the corresponding adjustment coefficient of each safety chain according to the health state so as to obtain the comprehensive adjustment coefficient. And distributing different reference regulating coefficients to the energy storage units in different states according to the comprehensive regulating coefficients for coordination control. According to the invention, the safety risk is judged in advance by establishing the safety chain model, so that the 'post' recognition is avoided, and the safety risk is reduced.
Description
Technical Field
The invention relates to the technical field of new energy storage system regulation and control, in particular to a coordination control method and system based on energy storage safety chain identification.
Background
The existing new energy storage system regulation and control technology mainly takes the self-safety protection of the equipment body in the aspect of safety management, the regulation process is generally shown in fig. 1, the state of charge of the energy storage body and the charge and discharge capacity parameters of the body are only concerned before regulation, after the regulation of the energy storage body is carried out by the regulation system, if abnormality occurs, the regulation system needs to manually participate in abnormality analysis and then carries out regulation parameter processing, so that the operation is repeated, the abnormality is always conducted according to the sequence of an output chain, the sequence is provided, and the correct execution command can be carried out after the feedback is needed for a plurality of times under extreme conditions. Before adjustment, only the safety of an adjustable unit body is generally involved, the safety state of an associated system chain is not fully considered, the safety evaluation strategy is determined by the associated independent system, and is always fed back afterwards, the safety state of the whole system chain is not fully considered before coordination control, and the stable state can be achieved after the feedback of the secondary operation is needed for the extreme case, so that the safety and the efficiency are further reduced especially for a large-scale system.
Therefore, the existing coordination control for the large-scale energy storage system mainly relies on acquiring the states of the battery charge states SOC, SOH or unit converter of each energy storage body to determine the adjustment parameters, and the safe and stable states of other related devices or systems and environments are not considered. For example, the related transformer is abnormal, the related temperature control equipment is abnormal or the communication link is abnormal, the adjustment parameter is unreasonable to set, or the adjustment result is not sent to the terminal due to equipment protection or communication link disconnection, so that the target result has larger deviation and can be realized only through multiple corrections, the efficiency is low, the risk of running safety of the equipment is increased, the loss of the whole product is increased due to unreasonable setting, and the service life of the product is reduced.
Disclosure of Invention
Based on the above, it is necessary to provide a coordination control method and a coordination control system based on energy storage safety chain identification aiming at the problem of unreasonable adjustment parameters in the prior art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a coordination control method based on energy storage safety chain identification comprises the following steps:
s1, carrying out safety chain identification according to a large-scale energy storage system design planning chart, and further obtaining a basic safety chain; the basic safety chain comprises an electrical equipment safety chain, a ring control safety chain and an operation management system safety chain;
s2, acquiring required parameters of a basic safety chain from a preset database, and establishing a basic safety chain model by combining the basic safety chain to perform fault evolution;
s3, acquiring real-time monitoring data of the large energy storage system and extracting features to obtain safety feature quantity required by a basic safety chain model;
s4, inputting the safety characteristic quantity into a basic safety chain model for state estimation, generating the health state of each safety chain in the basic safety chain model, and judging the corresponding adjustment coefficient of each safety chain according to the health state, so as to obtain the comprehensive adjustment coefficient pi:
π=α*β*γ；
wherein alpha is an electrical equipment safety chain adjustment coefficient, beta is an environmental control safety chain adjustment coefficient, and gamma is an operation management system safety chain adjustment coefficient;
s5, distributing different reference adjusting coefficients to the energy storage units in different states through weighted average according to the comprehensive adjusting coefficient pi, and giving corresponding changing ranges, so that charging and discharging power is distributed reasonably.
Further, the basic safety chain model comprises an electrical equipment safety chain model; the safety chain model of the electrical equipment comprises an energy storage battery unit safety sub-model, an energy storage variable-flow boosting integrated unit safety sub-model, a converging line safety sub-model and a grid-connected line safety sub-model;
the energy storage battery unit safety sub-model is used for estimating the safety state of the energy storage battery unit according to the energy storage discharge characteristic, the battery overcharge and overdischarge capacity and the battery capacity temperature; the energy storage, conversion and boosting integrated unit safety submodel is used for estimating the safety state of the energy storage, conversion and boosting integrated unit according to the overcurrent/short circuit capacity, overvoltage/undervoltage capacity, over-frequency/underfrequency capacity, over-temperature capacity and three-phase unbalanced capacity; the converging line safety sub-model is used for estimating the safety state of the converging line according to the line electric quantity, the line temperature and the line protection state; the grid-connected line safety sub-model is used for estimating the safety state of the grid-connected line.
Further, the method for establishing the energy storage battery unit safety submodel comprises the following steps:
obtaining the highest temperature T of the monomer of the energy storage battery cmax Minimum temperature T of monomer cmin According to a preset cell temperature set value T limset Constructing temperature constraint: t (T) cmin ≤T limset ，T limset ≤T cmax ；
Obtaining the highest voltage U of a single body of an energy storage battery cmax Minimum voltage U of single body cmin According to a preset voltage set value U limset Building a voltage constraint: u (U) cmin ≤U limset ，U limset ≤U cmax ；
Determining a battery state Sox according to the state of charge Soc and the state of health Soh of the energy storage battery, and determining a battery state Sox according to a preset lower limit Sox of the operation state low set And an upper operating state limit Sox hi set Building state constraints: sox low set <Sox<Sox hi set ；
Collecting the charging and discharging power P of the energy storage battery at the t moment of the energy storage battery t Maximum monomer temperature T at time T t,cmax Minimum temperature T of monomer at time T t,cmin Battery state Sox at time t t Single highest voltage U at time t t,cmax And the lowest voltage U of the single body at the moment t t,cmin And constructing an energy storage battery unit safety sub-model according to the temperature constraint, the voltage constraint and the state constraint:
wherein Alm is t,gzz For the total fault warning signal at time t, FALSE indicates no fault and P limt To limit the charge-discharge power, flag t,limt For the time t the fill-and-discharge flag is run, TRUE indicates permission.
Further, the method for establishing the energy storage, variable flow and boosting integrated unit safety submodel comprises the following steps:
acquiring three-phase voltage U of the energy storage, conversion and boosting integrated unit at time t At 、U Bt 、U Ct And three-phase current I at 、I bt 、I ct ；
Calculating the three-phase voltage unbalance rate PVUR at t moment t ：
According to a preset voltage three-phase unbalance rate set value PVUR set Constructing the energy storage, variable flow and boosting integrated unit safety sub-model:
wherein Flag is Flag t,limt1 For the operation charge and discharge sign of the t-moment energy storage, current transformation and voltage boosting integrated unit, TRUE indicates permission, P t1 Charging and discharging power P of energy storage, current transformation and voltage boosting integrated unit at time t limt1 For the limit value of charging and discharging power of an energy storage, conversion and boosting integrated unit, alm I t,gzz For the overcurrent/short-circuit protection state at time t, FALSE indicates no fault, alm U t,gzz For the overvoltage/undervoltage protection state at the moment t, alm F t,gzz And the over-frequency/under-frequency protection state is at the t moment.
Further, the method for establishing the bus line safety submodel comprises the following steps:
obtaining the line temperature T of the converging line at the moment T t ；
According to a preset temperature protection set value T set Constructing a bus line safety sub-model:
wherein Alm is line1 t,gzz And (5) converging a line protection state total signal at the time t, wherein FALSE represents no fault.
Further, the method for establishing the grid-connected line security submodel comprises the following steps:
acquiring total signal Alm of grid-connected line protection state at t moment line2 t,gzz ；
Constructing a grid-connected line safety sub-model: alm line2 t,gzz =false; wherein FALSE indicates no failure.
Further, the basic safety chain model also comprises a ring control safety chain model; the environment-control safety chain model comprises an energy storage unit environment-control state sub-model, an energy storage unit fire-fighting state sub-model and an energy storage unit temperature-control state sub-model; the energy storage unit environmental control state submodel is used for determining the internal environment temperature and humidity and water immersion state parameters of the energy storage battery container; the energy storage unit fire-fighting state sub-model is used for determining the fire-fighting state of the energy storage unit; the energy storage unit temperature control state submodel is used for determining the temperature control state of the energy storage unit.
Further, the basic safety chain model also comprises an operation management system safety chain model; the operation management system safety chain model comprises a communication link state sub-model, an intrusion detection state sub-model and a security state sub-model; wherein the communication link state sub-model is used for determining the state of the whole communication link; the intrusion detection state submodel is used for determining a virus intrusion state and an illegal external equipment access state; the security state sub-model is used for determining the surrounding state of the running area.
Further, the feature extraction mode of the real-time monitoring data comprises one or more of wavelet extraction, adaptive observer extraction, deviation rate analysis extraction or self-learning extraction.
The invention also relates to a coordination control system based on the energy storage safety chain identification, which comprises a safety chain identification module, a model building module, a feature extraction module, a state estimation module and a state balance coordination control module.
The safety chain identification module is used for carrying out safety chain identification according to the design planning diagram of the large-scale energy storage system so as to obtain a basic safety chain; the basic safety chain comprises an electrical equipment safety chain, a ring control safety chain and an operation management system safety chain;
the model building module is used for obtaining the required parameters of the basic safety chain from a preset database, and building a basic safety chain model by combining the basic safety chain to perform fault evolution;
the feature extraction module is used for acquiring real-time monitoring data of the large-scale energy storage system and extracting features to obtain safety feature quantity required by the basic safety chain model;
the state estimation module is used for inputting the safety characteristic quantity into the basic safety chain model to perform state estimation, generating the health state of each safety chain in the basic safety chain model, and determining the corresponding adjustment coefficient of each safety chain according to the health state so as to obtain the comprehensive adjustment coefficient pi: pi = α β γ; wherein alpha is an electrical equipment safety chain adjustment coefficient, beta is an environmental control safety chain adjustment coefficient, and gamma is an operation management system safety chain adjustment coefficient;
the state balance coordination control module is used for distributing different reference adjustment coefficients to the energy storage units in different states through weighted average according to the comprehensive adjustment coefficient pi, and giving corresponding change ranges, so that charging and discharging power is distributed reasonably.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the energy storage safety chain with wider monitoring and identification is used, the safety chain characteristic data is extracted, a safety chain model is established, the safety risk is judged in advance, the 'post' identification is avoided, and the safety risk is reduced;
2. according to the invention, through comprehensive state estimation of the energy storage state, different adjustment coefficients are allocated to the energy storage units in different states, and the charge and discharge power is reasonably allocated, so that the safety of the energy storage system is improved, the loss of the units can be reduced, the service life of the energy storage units is prolonged, and the operation efficiency is improved;
3. according to the invention, the abnormal conditions of the energy storage units in different states are automatically analyzed and fed back, so that the feedback times can be reduced, the automation level is improved, and the efficiency is improved on the basis of a wider energy storage safety chain.
Drawings
The disclosure of the present invention is described with reference to the accompanying drawings. It is to be understood that the drawings are designed solely for the purposes of illustration and not as a definition of the limits of the invention. Wherein:
FIG. 1 is a schematic diagram of a safety regulation process of a conventional new energy storage system regulation technology;
FIG. 2 is a flow chart of a coordinated control method based on energy storage safety chain identification according to embodiment 1 of the present invention;
FIG. 3 is a schematic illustration of a tuning process based on the coordinated control method of FIG. 2 based on energy storage safety chain identification;
fig. 4 is a process explanatory diagram of a coordinated control system based on energy storage safety chain identification according to embodiment 2 of the present invention.
Detailed Description
It is to be understood that, according to the technical solution of the present invention, those skilled in the art may propose various alternative structural modes and implementation modes without changing the true spirit of the present invention. Accordingly, the following detailed description and drawings are merely illustrative of the invention and are not intended to be exhaustive or to limit the invention to the precise form disclosed.
Example 1
Referring to fig. 2, the embodiment describes a coordination control method based on energy storage safety chain identification, which includes the following steps:
and step 1, carrying out safety chain identification according to a large-scale energy storage system design planning chart, and further obtaining a basic safety chain.
And (3) completing wider safety chain identification according to a large-scale energy storage system design planning chart, and expanding the safety chain to the whole electric connection equipment and auxiliary system equipment. Its basic security chain extension includes: an electrical equipment safety chain, a ring control safety chain and an operation management system safety chain.
And 2, acquiring required parameters required by the basic safety chain from a preset database, and establishing a basic safety chain model by combining the basic safety chain to perform fault evolution.
The basic safety chain model comprises an electrical equipment safety chain model, a ring control safety chain model and an operation management system safety chain model. The database is built according to the existing historical monitoring data to serve the built model.
2.1, for an electrical equipment safety chain model, the energy storage battery unit safety submodel, the energy storage variable flow boosting integrated unit safety submodel, the converging line safety submodel and the grid-connected line safety submodel are included. Each sub-model is described in detail below.
2.11 energy storage battery cell safety submodel is affected by energy storage discharge characteristics, battery overcharge and overdischarge capabilities, and battery capacity temperature. The parameters can be directly collected by the equipment and comprise: maximum monomer temperature (T) cmax ) Minimum monomer temperature (T) cmin ) Average monomer temperature (T) cavg ) Highest voltage of single body (U) cmax ) Minimum voltage of single body (U) cmin ) Average voltage of monomer (U) cavg ) Total fault alarm signal (Alm) gzz ) Running charge-discharge sign (Flag) limt ) State of charge (Soc), state of health (Soh), remaining available charge and discharge (E) limt ) A charge/discharge power limit value (P) limt ). The model characteristic curves are given by different battery manufacturers, and logic is determined according to the characteristic curves and parameters.
Taking the parameter at the time t as an example, the constructed energy storage battery unit safety sub-model is as follows:
wherein P is t For the charge and discharge power of the energy storage battery at the moment T t,cmax The temperature of the energy storage battery at the moment T is set to be the highest temperature of the single body at the moment T t,cmax In, T t,cmin At the lowest temperature of the monomer at the time T, T limset Is the temperature set value of the battery cell, and is determined by the factory parameters, sox t For the battery state at time t, U t,cmax For the highest voltage of the single body at the moment t, U t,cmin For the lowest voltage of the single body at the moment t, U limset Is a voltage set value, is determined by factory parameters, and is Alm t,gzz For the total fault warning signal at time t, FALSE indicates no fault and P limt To limit the charge-discharge power, P t Should not be greater than P limt ，Flag t,limt For the time t the fill-and-discharge flag is run, TRUE indicates permission.
2.12 energy storage, variable flow and boosting integrated unit safety submodel is subjected to overcurrent/short circuit capability, overvoltage/undervoltage capability, overfrequency/underfrequency capability, overtemperature capability and three-phase imbalance capability. The basic parameters can be directly collected by a terminal and a protection device, and the method comprises the following steps: three-phase voltage (U) At 、U Bt 、U Ct ) Three-phase current (I) at 、I bt 、I ct ) The method comprises the following steps of obtaining an active (P), reactive (Q), power factor cos phi, power grid frequency (F), transformer temperature T, overcurrent/short circuit protection state, overvoltage/undervoltage protection state and overcurrent/undervoltage protection state through an electrical protection control terminal, considering three-phase balance problems for a micro-grid and a load system, and obtaining three-Phase Voltage Unbalance Rate (PVUR) through calculation:
taking the parameter at the time t as an example, the constructed energy storage, conversion and boosting integrated unit safety submodel is as follows:
wherein Flag is Flag t,limt1 For the operation charge and discharge sign of the t-moment energy storage, current transformation and voltage boosting integrated unit, TRUE indicates permission, P t1 Charging and discharging power P of energy storage, current transformation and voltage boosting integrated unit at time t limt1 For the limit value of charging and discharging power of an energy storage, conversion and boosting integrated unit, alm I t,gzz For the overcurrent/short-circuit protection state at time t, FALSE indicates no fault, alm U t,gzz For the overvoltage/undervoltage protection state at the moment t, alm F t,gzz And the over-frequency/under-frequency protection state is at the t moment. PVUR t For the three-phase voltage unbalance rate at the time t, the calculation mode is as follows:
2.13 the confluence line safety submodel is affected by line electrical quantity, line temperature T and line protection state. The state parameters can be obtained through the state of the bus line protection equipment.
Taking the parameter at the time t as an example, the constructed bus line safety submodel is as follows:
wherein Alm is line1 t,gzz For the total signal of the protection state of the bus line at the moment T, FALSE indicates no fault, T t T is the line temperature at time T set Is a temperature protection set point.
2.14 grid-connected line safety submodel state parameters can be obtained through grid-connected line protection equipment.
Grid-connected circuit arrangementThe full sub-model is: alm line2 t,gzz =false; wherein FALSE indicates no fault, alm line2 t,gzz And the total signal is the protection state total signal of the grid-connected line at the moment.
2.2 the environmental control safety chain model is used for establishing monitoring on the whole operation environment of the energy storage unit. The energy storage unit environment control state model comprises an energy storage unit environment control state sub-model, an energy storage unit fire control state sub-model and an energy storage unit temperature control state sub-model.
2.21 the energy storage unit environmental control state submodel is used for determining the environmental temperature and humidity and water immersion state parameters of the energy storage battery. If the energy storage battery is placed in the container, the temperature and humidity (H) of the internal environment of the energy storage battery container are determined.
2.22 energy storage unit fire status sub-model consists in determining fire status. Comprising the following steps: fault status, early warning status, action status, etc.
2.23 energy storage unit temperature control state submodel is to determine energy storage unit temperature control states including air conditioning state (fault state, shutdown state), air cooling equipment state (abnormal state, fault state), water cooling unit state (abnormal state, fault state), and power cable temperature.
2.3 running the management system security chain model. The method comprises a communication link state sub-model, an intrusion detection state sub-model and a security state sub-model.
2.31 communication link state submodel. The model is used for judging the state of the whole communication link, including the state of a BMS (battery management system) and PCS (process control system) link, the state of a PCS and EMS (energy management system) link, the state of a line protection system and EMS link and the state of an EMS internal link, wherein the state value among the systems is judged by a real-time communication acquisition system according to the communication timeout time, and the link fault is judged when the preset timeout time is exceeded.
2.32 intrusion detection status submodel. The model is used for linking a safety protection and situation awareness system, and acquiring abnormal state information from the system, mainly including a virus invasion state and an illegal external equipment access state.
2.33 security state submodel. The model is used for linking the energy storage area security system, acquiring security state information, mainly acquiring parameters as the surrounding state of the operation area, and confirming that the surrounding environment is not invaded by unintended personnel, animals or equipment and the like.
And step 3, acquiring real-time monitoring data of the large energy storage system and extracting features to obtain the safety feature quantity required by the basic safety chain model.
The feature extraction mode can be one or a combination of wavelet extraction, adaptive observer extraction, deviation rate analysis extraction or self-learning extraction, and other feature extraction modes can also be adopted. The feature quantities required for the respective models are described below.
For the safety chain model of the electrical equipment, the characteristic quantities required by the safety sub-model of the energy storage battery unit are mainly the characteristics of the energy storage and discharge power and the voltage protection range, the characteristics of the over-charge and over-discharge capacity of the battery and the characteristics of the temperature capacity of the battery, and the characteristic functions are determined by the characteristics of the energy storage types of different energy storage units. The characteristic quantities required by the energy storage, conversion and boosting integrated unit safety submodel are mainly overcurrent/short circuit capability characteristics, overvoltage/undervoltage capability characteristics, overfrequency/underfrequency capability characteristics, overtemperature capability characteristics, three-phase unbalanced capability characteristics and the like, and are mainly determined by a terminal equipment protection unit. The characteristic quantity required by the bus line safety sub-model is mainly overcurrent protection characteristic, zero sequence overcurrent protection characteristic, acceleration protection characteristic and the like, and is mainly determined by a transformer and a line protection unit.
For the environment-controlled safety chain model, the characteristic quantity required by the energy storage unit environment-controlled state submodel is mainly characterized by over high ambient temperature, over low temperature, over fast temperature rise, abnormal equipment and the like. The characteristic quantities required by the energy storage unit fire state sub-model mainly comprise communication abnormal characteristic quantities, equipment fault characteristics, fire-fighting early warning characteristics and fire-fighting action characteristics, and the characteristic quantities can be acquired by a fire-fighting control system. The characteristic quantity required by the energy storage unit temperature control state submodel is mainly air conditioning system fault characteristics, air conditioning system shutdown characteristics, air cooling equipment abnormal characteristics, air cooling equipment faults, water cooling unit abnormal characteristics, water cooling unit fault characteristics and cable temperature abnormal characteristics.
For the safety chain model of the operation management system, the characteristic quantity required by the communication link state sub-model is mainly the characteristic quantity of overlarge delay and disconnection of a BMS (battery management system) link, a PCS (personal communication System) link, an EMS link, a line protection unit, an EMS link, an EMS internal link and the like. The feature quantity required by the intrusion detection state submodel is mainly the network security risk level feature quantity and can be obtained from a software security protection and situation awareness system. The characteristic quantity required by the security state sub-model is mainly the characteristic quantity without intrusion state such as non-planning personnel, animals or equipment and the like, and can be obtained from a security system.
Step 4, inputting the safety characteristic quantity into a basic safety chain model for state estimation, generating the health state of each safety chain in the basic safety chain model, and judging the corresponding adjustment coefficient of each safety chain according to the health state, so as to obtain the comprehensive adjustment coefficient pi:
π=α*β*γ；
wherein alpha is an electrical equipment safety chain adjustment coefficient, beta is an environmental control safety chain adjustment coefficient, and gamma is an operation management system safety chain adjustment coefficient.
Safety chain adjustment coefficient α of electrical equipment: the constraint condition for satisfying the electrical equipment safety chain model is that the safety coefficient is set to α=1, and any safety constraint does not satisfy the setting to α=0.
Environmental control safety chain adjustment coefficient beta: the safety is classified into a first level, a second level and a third level according to the safety level, wherein the first level, the second level and the safety are determined according to the system setting level coefficient (different system coefficients are confirmed by the system description characteristics), for example, the first level coefficient beta=0.8, the second level coefficient beta=0.5 and the third level is set as beta=0.
Operation management system safety chain adjustment coefficient γ: and determining that the unsatisfied link constraint adjustment coefficient is gamma=0, determining and evaluating the risk parameters of the network environment to the system according to the grade, setting the value azimuth (0.0-1.0) by a user, and setting the security constraint condition to be 1 and the security state evaluation to be 0.
The environment-control safety chain model and the operation management system safety chain model adopt the existing model, and constraint conditions are determined according to the model.
And 5, distributing different reference regulating coefficients to the energy storage units in different states through weighted average according to the comprehensive regulating coefficient pi, and giving corresponding variation ranges so as to reasonably distribute charge and discharge power.
Based on this, in connection with fig. 3, fig. 3 shows a schematic diagram of a coordination control procedure of the coordination control method based on the energy storage safety chain identification according to the present embodiment. As shown in fig. 3, the embodiment monitors and identifies a wider energy storage safety chain product in advance, and the safety chain model is provided with an electrical equipment safety chain model, a ring control safety chain model, an operation management system safety chain model and other needed safety chain models, so as to form a safety regulation parameter, namely a comprehensive regulation coefficient pi. And then, after the state of charge of the energy storage body and the charge and discharge capacity parameters of the energy storage body are regulated by the regulating system, if abnormality occurs, the abnormal part is automatically fed back to the safety chain model, the state of the safety chain model is estimated again, the safety regulating parameters are corrected, and the safety chain model is regulated by the regulating system again, so that the feedback times are reduced, and the automation level is also improved. And the safety risk can be distinguished in advance through a pre-established safety chain model, so that 'post' identification is avoided, and the safety risk is reduced.
The above mentioned are electrical equipment safety chain, environmental control safety chain and operation management system safety chain in basic safety chain extension. More safety chains can be adopted in practical application, so that the energy storage state can be estimated more accurately. The comprehensive state estimation is carried out on the energy storage state according to the influence on safety and stability, a state balance algorithm is adopted according to the comprehensive state estimation result, different reference adjustment coefficients are distributed on the energy storage units in different states, and corresponding change ranges are given, so that the charge and discharge power is reasonably distributed, the safety of the energy storage system is improved, the loss of the units can be reduced, the service life of the units is prolonged, and the operation efficiency is improved.
Example 2
The embodiment introduces a coordination control system based on energy storage safety chain identification, which comprises a safety chain identification module, a model building module, a feature extraction module, a state estimation module and a state balance coordination control module.
The safety chain identification module is used for carrying out safety chain identification according to the design planning diagram of the large-scale energy storage system so as to obtain a basic safety chain; the basic safety chain comprises an electrical equipment safety chain, a ring control safety chain and an operation management system safety chain;
the model building module is used for obtaining the required parameters of the basic safety chain from a preset database, and building a basic safety chain model by combining the basic safety chain to perform fault evolution;
the feature extraction module is used for acquiring real-time monitoring data of the large-scale energy storage system and extracting features to obtain safety feature quantity required by the basic safety chain model;
the state estimation module is used for inputting the safety characteristic quantity into the basic safety chain model to perform state estimation, generating the health state of each safety chain in the basic safety chain model, and determining the corresponding adjustment coefficient of each safety chain according to the health state so as to obtain the comprehensive adjustment coefficient pi: pi = α β γ; wherein alpha is an electrical equipment safety chain adjustment coefficient, beta is an environmental control safety chain adjustment coefficient, and gamma is an operation management system safety chain adjustment coefficient;
the state balance coordination control module is used for distributing different reference adjustment coefficients to the energy storage units in different states through weighted average according to the comprehensive adjustment coefficient pi, and giving corresponding change ranges, so that charging and discharging power is distributed reasonably.
The coordinated control system based on the energy storage safety chain identification of the present embodiment is described in detail below with reference to fig. 4. Fig. 4 shows a step explanatory diagram of the present embodiment system in a specific application, and as shown in fig. 4, the safety chain identification can be obtained from a battery system, a converter system, a transformer system, an air-conditioning fire protection, a battery management system, an energy management system, a container environment, a grid-connected line, and the like.
The model can be a battery cell model, a battery stack model, a fire-fighting model, an environment model, a converter model method, a transformer model, a communication model, a management system model and an intrusion risk model through a fault evolution process, and the models jointly form a basic safety chain model.
The characteristic extraction is carried out from the real-time monitoring data through wavelet extraction, self-adaptive observer extraction, deviation rate analysis extraction or self-learning extraction modes, and the extracted characteristic quantity comprises thermal runaway symptoms, temperature change rules, voltage change rules, current change rules, corresponding data of a transformer model, corresponding data of line protection, communication link abnormality symptoms and the like.
The method is characterized in that the state judgment is carried out in a model, the state estimation comprises thermal runaway state estimation, SOC state estimation, SOH state estimation, transformer state estimation, converter state estimation, environment state estimation, line safety state estimation, system reliability state estimation and the like, corresponding unit adjustment parameters are generated through comprehensive state setting or a state balance algorithm, the unit adjustment parameters are reference adjustment coefficients, and the state balance coordination control module adjusts based on the reference adjustment coefficients, the state of charge of the energy storage body and the charge and discharge capacity parameters of the energy storage body, so that the aim of coordination control is achieved. The state balance coordination control module may be comprised of existing regulation subsystems.
This embodiment has the same advantageous effects as embodiment 1.
The technical scope of the present invention is not limited to the above description, and those skilled in the art may make various changes and modifications to the above-described embodiments without departing from the technical spirit of the present invention, and these changes and modifications should be included in the scope of the present invention.
Claims (10)
1. The coordination control method based on the energy storage safety chain identification is used for coordinating and controlling the charge and discharge power of energy storage units in different states in a large-scale energy storage system, and is characterized by comprising the following steps of:
s1, carrying out safety chain identification according to a large-scale energy storage system design planning chart, and further obtaining a basic safety chain; the basic safety chain comprises an electrical equipment safety chain, a ring control safety chain and an operation management system safety chain;
s2, acquiring required parameters of a basic safety chain from a preset database, and carrying out fault evolution by combining the basic safety chain to establish a basic safety chain model;
s3, acquiring real-time monitoring data of the large energy storage system and extracting features to obtain safety feature quantity required by the basic safety chain model;
s4, inputting the safety characteristic quantity into the basic safety chain model for state estimation, generating the health state of each safety chain in the basic safety chain model, and judging the corresponding adjustment coefficient of each safety chain according to the health state, so as to obtain the comprehensive adjustment coefficient pi:
π=α*β*γ；
wherein alpha is an electrical equipment safety chain adjustment coefficient, beta is an environmental control safety chain adjustment coefficient, and gamma is an operation management system safety chain adjustment coefficient;
s5, distributing different reference adjusting coefficients to the energy storage units in different states through weighted average according to the comprehensive adjusting coefficient pi, and giving corresponding changing ranges, so that charging and discharging power is distributed reasonably.
2. The coordinated control method based on energy storage safety chain identification of claim 1, wherein the basic safety chain model comprises an electrical equipment safety chain model; the safety chain model of the electrical equipment comprises an energy storage battery unit safety sub-model, an energy storage variable-flow boosting integrated unit safety sub-model, a converging line safety sub-model and a grid-connected line safety sub-model;
the energy storage battery unit safety sub-model is used for estimating the safety state of the energy storage battery unit according to the energy storage discharge characteristic, the battery overcharge and overdischarge capacity and the battery capacity temperature; the energy storage, conversion and boosting integrated unit safety submodel is used for estimating the safety state of the energy storage, conversion and boosting integrated unit according to the overcurrent/short circuit capacity, overvoltage/undervoltage capacity, over-frequency/underfrequency capacity, over-temperature capacity and three-phase unbalanced capacity; the converging line safety sub-model is used for estimating the safety state of the converging line according to the line electric quantity, the line temperature and the line protection state; the grid-connected line safety sub-model is used for estimating the safety state of the grid-connected line.
3. The coordination control method based on energy storage safety chain identification according to claim 2, wherein the method for establishing the energy storage battery unit safety sub-model comprises the following steps:
obtaining the highest temperature T of the monomer of the energy storage battery cmax Minimum temperature T of monomer cmin According to a preset cell temperature set value T limset Constructing temperature constraint: t (T) cmin ≤T limset ，T limset ≤T cmax ；
Obtaining the highest voltage U of a single body of an energy storage battery cmax Minimum voltage U of single body cmin According to a preset voltage set value U limset Building a voltage constraint: u (U) cmin ≤U limset ，U limset ≤U cmax ；
Determining a battery state Sox according to the state of charge Soc and the state of health Soh of the energy storage battery, and determining a battery state Sox according to a preset lower limit Sox of the operation state low set And an upper operating state limit Sox hi set Building state constraints: sox low set <Sox<Sox hi set ；
Collecting the charging and discharging power P of the energy storage battery at the t moment of the energy storage battery t Maximum monomer temperature T at time T t,cmax Minimum temperature T of monomer at time T t,cmin Battery state Sox at time t t Single highest voltage U at time t t,cmax And the lowest voltage U of the single body at the moment t t,cmin And constructing an energy storage battery unit safety sub-model according to the temperature constraint, the voltage constraint and the state constraint:
wherein Alm is t,gzz For the total fault warning signal at time t, FALSE indicates no fault and P limt To limit the charge-discharge power, flag t,limt For the time t the fill-and-discharge flag is run, TRUE indicates permission.
4. The coordination control method based on energy storage safety chain identification according to claim 2, wherein the method for establishing the energy storage variable flow boosting integrated unit safety submodel comprises the following steps:
acquiring three-phase voltage U of the energy storage, conversion and boosting integrated unit at time t At 、U Bt 、U Ct And three-phase current I at 、I bt 、I ct ；
Calculating the three-phase voltage unbalance rate PVUR at t moment t ：
According to a preset voltage three-phase unbalance rate set value PVUR set Constructing the energy storage, variable flow and boosting integrated unit safety sub-model:
wherein Flag is Flag t,limt1 For the operation charge and discharge sign of the t-moment energy storage, current transformation and voltage boosting integrated unit, TRUE indicates permission, P t1 Charging and discharging power P of energy storage, current transformation and voltage boosting integrated unit at time t limt1 For the limit value of charging and discharging power of an energy storage, conversion and boosting integrated unit, alm I t,gzz For the overcurrent/short-circuit protection state at time t, FALSE indicates no fault, alm U t,gzz For the overvoltage/undervoltage protection state at the moment t, alm F t,gzz And the over-frequency/under-frequency protection state is at the t moment.
5. The coordination control method based on energy storage safety chain identification according to claim 2, wherein the method for establishing the bus line safety submodel comprises the following steps:
obtaining the line temperature T of the converging line at the moment T t ；
According to a preset temperature protection set value T set Constructing a bus line safety sub-model:
wherein Alm is line1 t,gzz And (5) converging a line protection state total signal at the time t, wherein FALSE represents no fault.
6. The coordination control method based on energy storage safety chain identification according to claim 2, wherein the method for establishing the grid-connected circuit safety sub-model comprises the following steps:
acquiring total signal Alm of grid-connected line protection state at t moment line2 t,gzz ；
Constructing a grid-connected line safety sub-model: alm line2 t,gzz =false; wherein FALSE indicates no failure.
7. The coordinated control method based on energy storage safety chain recognition according to claim 1, wherein the basic safety chain model further comprises a loop control safety chain model; the environment-control safety chain model comprises an energy storage unit environment-control state sub-model, an energy storage unit fire-fighting state sub-model and an energy storage unit temperature-control state sub-model; the energy storage unit environmental control state submodel is used for determining the internal environment temperature and humidity and water immersion state parameters of the energy storage battery container; the energy storage unit fire-fighting state sub-model is used for determining the fire-fighting state of the energy storage unit; the energy storage unit temperature control state submodel is used for determining the temperature control state of the energy storage unit.
8. The coordinated control method based on energy storage safety chain identification of claim 1, wherein the basic safety chain model further comprises an operation management system safety chain model; the operation management system safety chain model comprises a communication link state sub-model, an intrusion detection state sub-model and a security state sub-model; wherein the communication link state sub-model is used for determining the state of the whole communication link; the intrusion detection state submodel is used for determining a virus intrusion state and an illegal external equipment access state; the security state sub-model is used for determining the surrounding state of the running area.
9. The coordination control method based on energy storage safety chain recognition according to claim 1, wherein the feature extraction mode of the real-time monitoring data comprises one or more of wavelet extraction, adaptive observer extraction, deviation rate analysis extraction and self-learning extraction.
10. A coordination control system based on energy storage safety chain identification, which is used for coordinating and controlling charge and discharge power of energy storage units in different states in a large-scale energy storage system, and is characterized in that the coordination control system based on energy storage safety chain identification adopts the coordination control method based on energy storage safety chain identification as claimed in any one of claims 1 to 9, and the coordination control system based on energy storage safety chain identification comprises:
the safety chain identification module is used for carrying out safety chain identification according to the design planning diagram of the large-scale energy storage system so as to obtain a basic safety chain; the basic safety chain comprises an electrical equipment safety chain, a ring control safety chain and an operation management system safety chain;
the model building module is used for obtaining the required parameters of the basic safety chain from a preset database, and building a basic safety chain model by combining the basic safety chain to perform fault evolution;
the feature extraction module is used for acquiring real-time monitoring data of the large energy storage system and extracting features to obtain safety feature quantity required by the basic safety chain model;
the state estimation module is used for inputting the safety characteristic quantity into the basic safety chain model to perform state estimation, generating the health state of each safety chain in the basic safety chain model, and judging the corresponding adjustment coefficient of each safety chain according to the health state so as to obtain the comprehensive adjustment coefficient pi: pi = α β γ; wherein alpha is an electrical equipment safety chain adjustment coefficient, beta is an environmental control safety chain adjustment coefficient, and gamma is an operation management system safety chain adjustment coefficient;
and the state balance coordination control module is used for distributing different reference adjustment coefficients to the energy storage units in different states through weighted average according to the comprehensive adjustment coefficient pi and giving out corresponding change ranges so as to reasonably distribute charge and discharge power.
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