CN108376999A - A kind of more microgrid failure management methods considering islet operation time uncertainty - Google Patents
A kind of more microgrid failure management methods considering islet operation time uncertainty Download PDFInfo
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Abstract
A kind of more microgrid failure management methods considering islet operation time uncertainty, include the following steps：S1：One day continuous time for 24 hours was subjected to sliding-model control；S2：Establish prediction model a few days ago；S3：According to RES outputs, load prediction and uncertain isolated island time, random scene is generated using MC methods；S4：According to the relation between supply and demand of each microgrid, current electricity prices are determined in real time；S5：Single micro-capacitance sensor cost in minimum system establishes micro-capacitance sensor operation total cost model；S6：Based on finite time-domain rolling optimization frame, each micro-capacitance sensor is optimized, optimal operational condition is reached；S7：The game moving model for establishing micro-capacitance sensor group obtains strategy set according to step S6~S7, and each microgrid finds optimizing decision, and calculates whether it reaches Nash Equilibrium.The present invention can effectively improve economy and the safety of micro-capacitance sensor, and load reduction is effectively minimized, reduces operation risk.
Description
Technical field
The invention belongs to more microgrid fault management technical fields, are specifically related to a kind of consideration islet operation time uncertainty
More microgrid failure management methods.
Background technology
It in recent years, can to solar energy, wind energy etc. along with increasing energy crisis and increasingly serious environmental pollution
The utilization of the renewable sources of energy has become the important process of today's society energy field, micro-capacitance sensor by distributed generation resource, energy storage device,
The compositions such as energy conversion devices, load, monitoring and protection equipment, are an intellectualizing systems that can realize high degree of autonomy,
It is as a kind of key link of the novel power supply and distribution pattern and structure intelligent grid of raising distributed electrical source utilization rate, with efficient
The advantages that property, the feature of environmental protection, economy, is paid attention to by countries in the world rapidly.
Micro-capacitance sensor can provide supplement for bulk power grid, and improving block supply reliability and power quality, micro-capacitance sensor has grid-connected
Operation and islet operation both of which, wherein isolated island type micro-capacitance sensor refer to far from bulk power grid or cannot be with big electricity when breaking down
Net micro-capacitance sensor that is grid-connected but having independent operation function.More micro-grid systems, which are one, has apparent probabilistic system,
Its fluctuation of load and internal composition are difficult to accurate evaluation, and people also increasingly pay close attention to micro-grid system probability of malfunction to electric system
The influence of operation.In view of the probability distribution of related is different, carrying out assessment system using Deterministic Methods is
Difficult.If a failure occurs, micro-capacitance sensor islet operation should consider more microgrid operational modes at this time, consider system again
Randomness, the uncertainty contributed including scene and isolated island duration are uncertain, in order to solve the problems, such as these,
The power quality problem that traditional research occurs during switching just for simultaneously off-network is studied, and only considers it for isolated island
Stable operation, management and optimisation strategy to load system consider less.
Invention content
In order to overcome micro-capacitance sensor to break down, more microgrid running mode switchings, system randomness, scene are contributed uncertain
Property and the uncertain of isolated island duration power system stability and load management and optimization operation are adversely affected,
The present invention proposes a kind of novel fault management strategy suitable for more microgrids.By regenerative resource and isolated island duration not really
Deterministic simulation is two independent probability, generates a large amount of random scene by Monte Carlo simulation quantization, introduces internal power source
Price mechanism instructs the consumption behavior of burden with power, to achieve the purpose that stable power network fluctuation.In more microgrid fault times, base
In model prediction (MPC) algorithm using novel interrupt management strategy to optimize single micro-capacitance sensor, based on non-cooperative game to obtain
Much microgrid fault time optimum operating modes.The present invention is solved under more piconet island run time uncertainties, is improved more
Reliability under piconet island operational mode and economy realize that micro-capacitance sensor stable operation, Optimum cost and load are cut down most
Small purpose.
To achieve the goals above, the technical scheme is that：
A kind of to consider more probabilistic failure management methods of piconet island run time, the method includes following steps
Suddenly：
S1：Consider that discrete time model, configuration scheduling period are for 24 hours, to carry out sliding-model control, be divided into T period,
For arbitrary kth time period, there are a k ∈ { 1,2 ..., T }, and the when a length of Δ t of kth time period；
S2：Assuming that the sum of distributed energy micro-capacitance sensor is N, according to existing RES outputs and load prediction, day is established
Preceding prediction model；
S3：Maximum power point tracing method is used in distributed energy stochastic system, calculating distributed energy is at random
Active output power and the base load prediction of system, according to RES outputs, load prediction and uncertain isolated island time, using MC
Method generates random scene；
S4：According to the relation between supply and demand of each microgrid, current electricity prices are determined in real time, micro-capacitance sensor is established according to step S1~S4
Run total cost model；
S5：Single micro-capacitance sensor cost in minimum system, including：Basic cost, user's cost of compensation；
S6：Under malfunction, it is based on finite time-domain rolling optimization frame, each micro-capacitance sensor is optimized, is reached
Optimal operational condition；Using the current system operating status in optimization process as the original state of next optimization process, to obtain
It obtains the following short-term scene output prediction and switch-time load is predicted, carry out Real Time Correction System deviation；
S7：Non-cooperative game is introduced, non-cooperative game model is established, strategy set is obtained according to step S6~S7, it is each micro-
Net is based on Spot Price mechanism and finds optimizing decision, and calculates whether it reaches Nash Equilibrium；Step S5~S7 is repeated, when
It determines that more micro-grid systems are integrally optimal when obtaining preferred plan, terminates game, obtain optimal fault management strategy.
Further, in the step S2, the sum of distributed energy micro-capacitance sensor is N, for any micro-capacitance sensor i=1,
2 ... N }, prediction model indicates as follows：
In formula：Indicate i-th of micro-capacitance sensor k periods inner blower, photovoltaic and load practical output；N=1,2,3, point
Wind turbine, photovoltaic and base load are not corresponded to；RnObey U (- 1,1) Distribution Value；τ indicates the time span of prediction；As τ=24,
It represents at this time as prediction model a few days ago；Indicate the prediction threshold value of wind turbine, photovoltaic and load；
In formula：Indicate that the basic uncertainty percentage of prediction error, J indicate the basic uncertainty percentage of prediction error.
Further, the process of the step S3 is as follows：
Active output power and base load prediction based on distributed energy stochastic system, wind turbine, the light of i-th of microgrid
Volt is contributed with base load prediction expression：
Main power grid is separated with micro-capacitance sensor group's, and micro-capacitance sensor group is caused to be in island state, during failure, micro-capacitance sensor and master
The randomness of power grid isolation operation, RES and load prediction is indicated by Q scenes, does not know isolated island duration probability distribution entirely
It is indicated by Z, therefore whole event uncertainty probability distribution is expressed as Z × Q.
Further, in the step S4, prevent under the action of tou power price, overexcitation user transfer load and lead
Peak load is caused to be transferred to non-peak period generation rebound peak；According in per period electric system relation between supply and demand and all kinds of constraint items
Part makes load distribution keep as far as possible uniformly, cost function can be approximated to be following quadratic function using Combined Spot Price Model：
In formula：A, b, c are expense multinomial coefficient, a>0, b, c >=0, γ represent the valence of falling power transmission of scene output, Δ t tables
Show scheduling time inter, is set as 0.5h；Total net load of more microgrids is represented, while it represents the monolithic stability of micro-capacitance sensor
Property：
In formula：Indicate i-th of microgrid the k periods net load；WithK period i micro-capacitance sensors are indicated respectively
Basic load and burden with power；Indicate the energy storage power of k period i micro-capacitance sensors；Since power cost is continuous function, so
C is set as 0；Cost function can be approximated to be following quadratic function：
In formula：A', b' are approximation coefficient；Then Spot Price can be indicated with following formula：
The process of the step S5 is as follows：
S51. consider that the sum of basic cost is denoted as cost1, including power cost, energy-storage battery charge and discharge electric loss at
Originally, new energy, which is contributed, subsidizes cost, interaction income, as follows：
In formula：Indicate that i interacts power with m micro-capacitance sensors；WithThe charge and discharge of the energy-storage battery of i microgrids is indicated respectively
Electrical power；KBESSIndicate that energy-storage battery loses cost coefficient；KRESIt represents to give per kilowatt hour government and subsidize；PaltIndicate each electricity
Interaction price between net；
S52. consider user's cost of compensation, be denoted as cost2:
In formula：KTLRepresent the cost of compensation coefficient of user's transfer load；Lnet,i(0) i-th of microgrid is represented to hand in power grid
Initial net load before mutually.
The process of the step S6 is as follows：
S61. under nonserviceabling, each micro-capacitance sensor is optimized, optimal operational condition is reached；By optimization process
In original state of the current system operating status as each optimization process, contribute prediction to obtain following short-term scene
With load short-term forecast, Real Time Correction System deviation is carried out；Based on single micro-capacitance sensor, output and load estimation and failure are considered
The uncertainty of time, object function are defined as again：
In formula：The maximum constrained power of energy-storage battery charge and discharge is indicated respectively；Storage is indicated respectively
The charging and discharging state of energy battery, and be a binary number, 1 indicates to be in charged state, and 0 indicates to be in discharge condition；
Indicate maximum power transfer constraint；Indicate the on off operating mode of interconnection；WhenFor positive number when, indicate MGiTo MGmSale electricity
Otherwise power is indicated to MGmIt buys power；Formula (15) (16) shows that energy-storage battery charge and discharge should constrain in energy-storage battery most
In big charge and discharge power；Formula (17) shows that energy-storage battery is charged and discharged state and can not exist simultaneously；Formula (18) shows
Transimission power should meet tie-line power transmission restrict；Formula (19) shows that trading electricity should be limited by its demand
System；Formula (20) indicates the overall power balance of system；
S62. in each period k, based on it is after the optimization in rolling time horizon as a result, interaction power between each microgrid into
Row is redistributed, and is determined optimal scheduling plan and is maximized profit；Interests to realize micro-capacitance sensor individual and group simultaneously are maximum
Change and introduce non-cooperative game, the interconnected operation model for establishing micro-capacitance sensor group is as follows：
In formula：SiRepresent the scheduling strategy of i-th of microgrid, N+For positive integer；Indicate that micro-capacitance sensor i is handed over micro-capacitance sensor m
Mutually strategy；UiIndicate that the profit of i-th of micro-capacitance sensor, value are the opposite numbers of cost.
The process of the step S7 is as follows：
Strategy set, S={ S1, S2... SN}；When formula (21) are set up：
In formula：S*Indicate updated set of strategies；S*It is referred to as the NE solutions of non-cooperative game, each microgrid is based on real-time
Price Mechanisms are scheduled response to respective active load and energy-storage system by workload demand, find optimizing decision, and count
Calculate whether it reaches Nash Equilibrium；By successive ignition optimizing, the microgrid of all participations has chosen optimal strategy, reaches whole
The stabilization and equilibrium state of more micro-grid systems；When having determined that acquisition preferred plan, game is terminated, optimal fault management plan is obtained
Slightly.
Compared with the nearest prior art, the invention has the advantages that and advantageous effect：
1. in the technology of the present invention, contributing based on uncertain scene, monte carlo modelling is taken to generate random comprehensive field
Scape, and consider the uncertainty that new energy is contributed, this to consider that uncertain energy access micro-capacitance sensor reliability assessment is new
The energy is contributed more comprehensive.
2. in inventive technique scheme, proposes this concept of uncertain micro-capacitance sensor fault management, be no longer regarded as micro-capacitance sensor
Fault time can remain unchanged within a certain period of time, consider the uncertainty that failure occurs so that micro-capacitance sensor operation more may be used
It leans on.
3. update each micro-capacitance sensor interior optimization based on MPC real-time onlines, formulate each micro-capacitance sensor electricity consumption strategy, each micro-capacitance sensor into
The non-cooperative game of row, reaches Nash Equilibrium, obtains each micro-capacitance sensor profit maximization.
4. a kind of novel more microgrid fault management strategies proposed by the invention can effectively improve the economy of micro-capacitance sensor
Property, cost is reduced, further, effectively improves micro-capacitance sensor safe operation reliability, reduces operation risk.
Description of the drawings
Fig. 1 is the scene composition probability graph of the present invention；
Fig. 2 is the implementation flow chart of the present invention；
Fig. 3 is 1 operation result of micro-capacitance sensor；
Fig. 4 is 2 operation result of micro-capacitance sensor；
Fig. 5 is 3 operation result of micro-capacitance sensor；
Fig. 6 is micro-capacitance sensor 1-3 net load comparison diagrams；
Fig. 7 is micro-capacitance sensor 1-3 photovoltaic capability diagrams；
Fig. 8 is micro-capacitance sensor 1-3 wind turbine capability diagrams；
Fig. 9 is isolated island micro-capacitance sensor transaction cost figure；
Figure 10 is micro-capacitance sensor net load figure under both of which.
Specific implementation mode
The present invention will be further described below in conjunction with the accompanying drawings.
Referring to Fig.1-Fig. 9, a kind of more microgrid failure management methods considering islet operation time uncertainty, the pipe
Reason method includes the following steps：
S1：Considering discrete time model, set Best Times as 24 hours, progress sliding-model control is divided into T period,
For the arbitrary kth time, there are a k ∈ { 1,2 ..., T }, and the when a length of Δ t of kth time period.
S2：Assuming that the sum of distributed energy micro-capacitance sensor is N, is exported and predicted according to existing RES, mould is predicted in foundation a few days ago
Type and distributed energy stochastic model；
The sum of distributed energy micro-capacitance sensor is N, and for any micro-capacitance sensor i={ 1,2 ... N }, prediction model indicates as follows：
In formula：Indicate i-th of micro-capacitance sensor K times inner blower, photovoltaic and load practical output；N=1,2,3, point
Wind turbine, photovoltaic and base load are not corresponded to；RnIndicate U (- 1,1) random distribution value；τ indicates the time span of prediction；When τ=24
When, it represents at this time as prediction model a few days ago；Indicate the prediction threshold value of wind turbine, photovoltaic and load；In formula：Indicate that the basic uncertainty percentage of prediction error, J indicate prediction error
Basic uncertainty percentage；
S3：Maximum power point tracing method is used in distributed energy stochastic system, calculating distributed energy is at random
Active output power and the base load prediction of system, according to RES outputs, load prediction and uncertain isolated island time, using MC
Method, which generates, does not know combining random scene；
Active output power and base load prediction based on distributed energy stochastic system, distributed energy is contributed and base
This load prediction expression formula is：
Main power grid is separated with micro-capacitance sensor group's, and micro-capacitance sensor group is caused to be in island state, during failure, micro-capacitance sensor and master
The randomness of power grid isolation operation, RES and load prediction is indicated by Q scenes, does not know isolated island duration probability distribution entirely
It is indicated by Z, therefore whole event uncertainty probability distribution is expressed as Z × Q, probability distribution schematic diagram such as Fig. 1 of scene composition
It is shown；
S4：According to the relation between supply and demand of each microgrid, current electricity prices are determined in real time, micro-capacitance sensor is established according to step S1~S4
Run total cost model；
Prevent under the action of tou power price, overexcitation user transfer load and when peak load being caused to be transferred to non-peak
Section generates rebound peak；According in per period electric system relation between supply and demand and all kinds of constraintss made using Combined Spot Price Model
Load distribution is kept uniformly as far as possible, and cost function can be approximated to be following quadratic function：
In formula：A, b, c are expense multinomial coefficient, a>0, b, c >=0, γ represent the valence of falling power transmission of scene output, Δ t tables
Show scheduling time inter, is set as 0.5h；Total net load of more microgrids is represented, while it represents the monolithic stability of micro-capacitance sensor
Property：
In formula：Indicate i-th of microgrid the k periods net load；WithThe micro- electricity of k period i is indicated respectively
The basic load of net and burden with power；Indicate the power of the energy storage of k period i micro-capacitance sensors；Since power cost is continuous function,
So c is set as 0；Cost function can be approximated to be following quadratic function：
In formula：A', b' are approximation coefficient；Then Spot Price can be indicated with following formula：
S5：Single micro-capacitance sensor cost in minimum system, including：Basic cost, user's cost of compensation；
S51. consider basic cost, be denoted as cost1, including power cost, energy-storage battery charge and discharge electric loss cost, new
The energy, which is contributed, subsidizes cost, interaction income, as follows：
In formula：Indicate that i interacts power with m micro-capacitance sensors；WithThe charge-discharge electric power of energy-storage battery is indicated respectively；
KBESSIndicate that energy-storage battery loses cost coefficient；KRESIt represents to give per kilowatt hour government and subsidize；PaltIt indicates between each power grid
Interaction price；
S52. consider user's cost of compensation, be denoted as cost2:
In formula：KTLRepresent the cost of compensation coefficient of user's transfer load；Lnet,i(0) the i-th microgrid is represented to interact in power grid
Initial net load before；
S6：Under nonserviceabling, it is based on finite time-domain rolling optimization frame, each micro-capacitance sensor is optimized, it is made to reach
To optimal operational condition；Using the current system operating status in optimization process as the original state of next optimization process, thus
Following short-term scene output prediction and switch-time load prediction are obtained, Real Time Correction System deviation is carried out；
S61. under nonserviceabling, each micro-capacitance sensor is optimized, optimal operational condition is reached；By optimization process
In original state of the current system operating status as each optimization process, contribute prediction to obtain following short-term scene
With load short-term forecast, Real Time Correction System deviation is carried out；Based on single micro-capacitance sensor, output and load estimation and failure are considered
The uncertainty of time, object function are defined as again：
In formula：The maximum constrained power of energy-storage battery charge and discharge is indicated respectively；Storage is indicated respectively
The charging and discharging state of energy battery, and be a binary number, 1 indicates to be in charged state, and 0 indicates to be in discharge condition；
Indicate maximum power transfer constraint；Indicate the on off operating mode of interconnection；WhenFor positive number when, indicate MGiTo MGmSale electricity
Otherwise power is indicated to MGmIt buys power；Formula (15) (16) shows that energy-storage battery charge and discharge should constrain in energy-storage battery most
In big charge and discharge power；Formula (17) shows that energy-storage battery is charged and discharged state and can not exist simultaneously；Formula (18) shows
Transimission power should meet tie-line power transmission restrict；Formula (19) shows that trading electricity should be limited by its demand
System；Formula (20) indicates the overall power balance of system；
S62. in each period k, based on it is after the optimization in rolling time horizon as a result, interaction power between each microgrid into
Row is redistributed, and is determined optimal scheduling plan and is maximized profit；Interests to realize micro-capacitance sensor individual and group simultaneously are maximum
Change and introduce non-cooperative game, the interconnected operation model for establishing micro-capacitance sensor group is as follows：
In formula：SiRepresent the scheduling strategy of i-th of microgrid；Indicate micro-capacitance sensor i and micro-capacitance sensor m interactive strategies； UiTable
Show that the profit of i-th of micro-capacitance sensor, value are the opposite numbers of cost；
S7：Non-cooperative game is introduced, non-cooperative game model is established, strategy set is obtained according to step S6~S7, it is each micro-
Net is based on Spot Price mechanism and finds optimizing decision, and calculates whether it reaches Nash Equilibrium；Step S2~S7 is repeated, when
It determines that more micro-grid systems are integrally optimal when obtaining preferred plan, terminates game, obtain optimal fault management strategy；
Strategy set, S={ S1, S2... SN}；When formula (21) are set up：
In formula：S*Indicate updated set of strategies；S*It is referred to as the NE solutions of non-cooperative game, each microgrid is based on real-time
Price Mechanisms carry out coordinated scheduling to respective active load and energy-storage system by demand, find optimizing decision, and calculate it
Whether Nash Equilibrium is reached；By successive ignition optimizing, the microgrid of all participations has chosen optimal strategy, reaches whole mostly micro-
The stabilization and equilibrium state of net system；In the case, the microgrid of all participations has chosen optimal strategy, reaches total system
Stabilization with it is balanced；When having determined that acquisition preferred plan, game is terminated, obtains optimal failure reason strategy；
In order to intuitively prove that invention puies forward the effect of strategy, the present invention forms more microgrids with three, somewhere micro-capacitance sensor
The effect of system extracting method to be verified specifically is verified with following 3 kinds of cases：
Case 1：Micro-capacitance sensor group is in island state in trouble time, and each micro-capacitance sensor is made all in island operation state
It is larger at the net load fluctuation of electric system.
Case 2：When micro-capacitance sensor 3 is in photovoltaic generation malfunction, more microgrid failure pipes proposed by the present invention are introduced
Reason strategy.
Case 3：It is similar to case 2, lasting 8 hours power cut-off incidents additionally have occurred at 0 point in addition to the morning.
Result from Fig. 3 to Fig. 6 can be seen that micro-capacitance sensor under 1 pattern of case and be in island state, cause electric system
Great load fluctuation is unfavorable for stable operation and the reliability of electric system.Under 2 pattern of case, due to taking failure pipe
Reason strategy, therefore the fluctuation of micro-capacitance sensor net load, well below Case1 patterns, fault management strategy is run in view of micro-grid system
Uncertainty, transferable load are shifted in the low-power requirements time, and fault management strategy interaction mechanism can not meet electricity needs,
But when interrupt event occurs, since micro-capacitance sensor does not interconnect, net load is fluctuated bigger, is unfavorable for the stabilization of electric system
Operation.
Photovoltaic output connect while being interrupted with main interconnecting ties under 3 pattern of case, and net load fluctuates significantly greater than the
Two kinds of situations, however the unfavorable factor under case 2,3 pattern of case by the fault management strategy that is carried of the present invention very
Good solution, this, which fully demonstrates failure management method, has raising system stability and excellent with good flexibility etc.
Point.
Result from Fig. 7 to Fig. 8 can be seen that the unstability of distributed energy, and 12h or so reaches photovoltaic output at noon
To output peak, and wind turbine output can be followed there is no apparent rule, embody the uncertainty of distributed energy power generation
With unstability.
Table 1
Economically to see, above-mentioned table 1 shows the detailed difference of net load fluctuation and economic benefit under different cases,
Can it can be seen from the table, when break down event when, 3 underpower of micro-capacitance sensor often buys power from other micro-capacitance sensors,
To increase totle drilling cost.It will be apparent that compared with proposed fault management strategy, case II is in all respects always than other cases
Example has advantage.In microgrid 1 and microgrid 2, fault management strategy is taken, net load fluctuation is kept to stablize.In micro-capacitance sensor 3,
Photovoltaic contribute lose, wind turbine power generation cannot meet the primary demand of system, since interconnection is lost within fault time, power grid it
Between do not merchandise, cause 3 load of microgrid cut down it is larger.In this case, proposed fault management strategic planning is mostly micro-
Net system transferring load after event of failure, trading electricity, to meet the requirement of system.
As shown in Figure 9, as fault time extends, transaction cost continues to increase, before failure in 3 hours, case 1 and case
2 transaction cost of example is apparently higher than case 3, and in trouble duration 3 hours to 6 hours, 1 micro-capacitance sensor of case is in island shape
State, transaction cost highest, case 2 are in photovoltaic generation malfunction, and fault management mechanism, transaction cost is taken to be less than case
1, case 3 excludes 12: 8 hours mornings event of failure, takes failure fault management strategy, transaction cost is less than case 1, case
Example 2.After trouble duration 6 hours, micro-capacitance sensor is in long-time island state, and case 1 does not take any measure, transaction
Cost continues to increase, though case 2 takes fault management strategy, when interrupt event occurs, since micro-capacitance sensor does not interconnect,
Transaction cost increases compared with before failure 6 hours in drastically formula, and case 3 takes fault management strategy, with the increasing of fault time
Add, although transaction cost is increasing always, with case 1 compared with case 2, transaction cost maintains in tolerance interval.
The performance of carried fault management strategy in order to further illustrate the present invention, we set a kind of situation, that is, adopt
Optimize more microgrids as a comparison with management strategy a few days ago (DAS).The comparison result of both of which is as shown in Figure 10.It is obvious that
In emergency circumstances the fault management strategy proposed can efficiently reduce cutting load, improve the elasticity of electric system unexpected,
And keep the reliable and stable operation of system.When failure is happened at 0:When 00, fault management strategy is rapidly by system net load tune
It is whole to arrive stable state.When carry the previous day scheduling when there are forecasting inaccuracy it is true in the case of be unable to response system demand, lead to power
Adjustment delay even reversed peak response, the fault management strategy of proposition can improve the flexibility of more micro-grid systems and reliable
Property.Fault management strategy shows it with enough elasticity and flexibility, to keep system balancing simultaneously when emergency occurs
Enhance the operation stability of more micro-grid systems.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiments or example.In addition, those skilled in the art can be by this specification
Described in different embodiments or examples be combined.
Although the embodiments of the present invention has been shown and described above, it is to be understood that this specification embodiment institute
The content stated is only enumerating to the way of realization of inventive concept, and protection scope of the present invention is not construed as being only limitted to reality
The concrete form that example is stated is applied, protection scope of the present invention also can according to present inventive concept including those skilled in the art
The equivalent technologies mean expected.
Claims (7)
1. a kind of considering more probabilistic failure management methods of piconet island run time, which is characterized in that the method packet
Include following steps：
S1：Consider discrete time model, the configuration scheduling period is for 24 hours, to carry out sliding-model control, be divided into T period, for appointing
It anticipates kth time period, there is a k ∈ { 1,2 ..., T }, and the when a length of Δ t of kth time period；
S2：Assuming that the sum of distributed energy micro-capacitance sensor is N, according to existing RES outputs and load prediction, establish a few days ago pre-
Survey model；
S3：Maximum power point tracing method is used in distributed energy stochastic system, calculates distributed energy stochastic system
Active output power and base load prediction, according to RES outputs, load prediction and uncertain isolated island time, using MC methods
Generate random scene；
S4：According to the relation between supply and demand of each microgrid, current electricity prices are determined in real time, and micro-capacitance sensor operation is established according to step S1~S4
Total cost model；
S5：Single micro-capacitance sensor cost in minimum system, including：Basic cost, user's cost of compensation；
S6：Under malfunction, it is based on finite time-domain rolling optimization frame, each micro-capacitance sensor is optimized, reached best
Operating status；Using the current system operating status in optimization process as the original state of next optimization process, to obtain not
Come short-term scene output prediction and switch-time load prediction, carries out Real Time Correction System deviation；
S7：Non-cooperative game is introduced, non-cooperative game model is established, strategy set, each microgrid base is obtained according to step S6~S7
Optimizing decision is found in Spot Price mechanism, and calculates whether it reaches Nash Equilibrium；Step S5~S7 is repeated, is obtained when having determined that
When taking preferred plan, more micro-grid systems are integrally optimal, and terminate game, obtain optimal fault management strategy.
2. a kind of more microgrid failure management methods considering islet operation time uncertainty as described in claim 1, special
Sign is, in the step S2, the sum of distributed energy micro-capacitance sensor is N, for any micro-capacitance sensor i={ 1,2 ... N }, prediction
Model indicates as follows：
In formula：Indicate i-th of micro-capacitance sensor k periods inner blower, photovoltaic and load practical output；N=1,2,3, it is right respectively
Answer wind turbine, photovoltaic and base load；RnObey U (- 1,1) Distribution Value；τ indicates the time span of prediction；As τ=24, represent
It is at this time prediction model a few days ago；Indicate the prediction threshold value of wind turbine, photovoltaic and load；Formula
In：Predict that the basic uncertainty percentage of error, J indicate the basic uncertainty percentage of prediction error.
3. a kind of more microgrid failure management methods considering islet operation time uncertainty as claimed in claim 1 or 2,
It is characterized in that, the process of the step S3 is as follows：
Active output power and base load prediction based on distributed energy stochastic system, wind turbine, the photovoltaic of i-th of microgrid go out
Power is respectively with base load prediction expression：
Main power grid is separated with micro-capacitance sensor group's, and micro-capacitance sensor group is caused to be in island state, during failure, micro-capacitance sensor and main power grid
The randomness of isolation operation, RES and load prediction is indicated that entirely uncertain isolated island duration probability distribution is by Z tables by Q scenes
Show, therefore whole event uncertainty probability distribution is expressed as Z × Q.
4. a kind of more microgrid failure management methods considering islet operation time uncertainty as described in claim 1, special
Sign is, in the step S4, prevents under the action of tou power price, overexcitation user transfer load and lead to peak load
It is transferred to non-peak period generation rebound peak；According in per period electric system relation between supply and demand and all kinds of constraintss, using reality
When Spot Price Model, so that load distribution is kept as far as possible uniformly, cost function can be approximated to be following quadratic function：
In formula：A, b, c are expense multinomial coefficient, a>0, b, c >=0, γ represent the valence of falling power transmission of scene output, and Δ t indicates to adjust
Time interval is spent, 0.5h is set as；Total net load of more microgrids is represented, while it represents the overall stability of micro-capacitance sensor：
In formula：Indicate i-th of microgrid the k periods net load；WithThe base of k period i micro-capacitance sensors is indicated respectively
Plinth load and burden with power；Indicate the energy storage power of k period i micro-capacitance sensors；Since power cost is continuous function, so c is set
It is set to 0；Cost function can be approximated to be following quadratic function：
In formula：A', b' are approximation coefficient；Then Spot Price can be indicated with following formula：
5. a kind of more microgrid failure management methods considering islet operation time uncertainty as claimed in claim 1 or 2,
It is characterized in that, the process of the step S5 is as follows：
S51. consider that the sum of basic cost is denoted as cost1, including power cost, energy-storage battery charge and discharge electric loss cost, new energy
Source, which is contributed, subsidizes cost, interaction income, as follows：
In formula：Indicate that i interacts power with m micro-capacitance sensors；WithThe charge and discharge electric work of the energy-storage battery of i microgrids is indicated respectively
Rate；KBESSIndicate that energy-storage battery loses cost coefficient；KRESIt represents to give per kilowatt hour government and subsidize；PaltIndicate each power grid it
Between interaction price；
S52. consider user's cost of compensation, be denoted as cost2:
In formula：KTLRepresent the cost of compensation coefficient of user's transfer load；Lnet,i(0) it represents i-th of microgrid and interacts it in power grid
Preceding initial net load.
6. a kind of more microgrid failure management methods considering islet operation time uncertainty as claimed in claim 1 or 2,
It is characterized in that, the process of the step S6 is as follows：
S61. under nonserviceabling, each micro-capacitance sensor is optimized, optimal operational condition is reached；It will be in optimization process
Original state of the current system operating status as each optimization process is predicted and is born to which the short-term scene for obtaining following is contributed
Short-term forecast is carried, Real Time Correction System deviation is carried out；Based on single micro-capacitance sensor, output and load estimation and fault time are considered
Uncertainty, object function is defined as again：
In formula：The maximum constrained power of energy-storage battery charge and discharge is indicated respectively；Energy storage electricity is indicated respectively
The charging and discharging state in pond, and be a binary number, 1 indicates to be in charged state, and 0 indicates to be in discharge condition；It indicates
Maximum power transfer constrains；Indicate the on off operating mode of interconnection；WhenFor positive number when, indicate MGiTo MGmElectric power is sold, it is no
It then indicates to MGmIt buys power；Formula (15) (16) shows that energy-storage battery charge and discharge should constrain in energy-storage battery maximum and fill, put
In electrical power；Formula (17) shows that energy-storage battery is charged and discharged state and can not exist simultaneously；Formula (18) shows to transmit work(
Rate should meet tie-line power transmission restrict；Formula (19) shows that trading electricity should be limited by its demand；Formula
(20) the overall power balance of system is indicated；
S62. in each period k, based on after the optimization in rolling time horizon as a result, the interaction power between each microgrid carries out weight
New distribution determines optimal scheduling plan and maximizes profit；To realize that the benefit of micro-capacitance sensor individual and group draws simultaneously
Enter non-cooperative game, the interconnected operation model for establishing micro-capacitance sensor group is as follows：
In formula：SiRepresent the scheduling strategy of i-th of microgrid, N+For positive integer；Indicate that micro-capacitance sensor i interacts plan with micro-capacitance sensor m
Slightly；UiIndicate that the profit of i-th of micro-capacitance sensor, value are the opposite numbers of cost.
7. a kind of more microgrid failure management methods considering islet operation time uncertainty as claimed in claim 1 or 2,
It is characterized in that, the process of the step S7 is as follows：
Strategy set, S={ S1, S2... SN}；When formula (21) are set up：
In formula：S*Indicate updated set of strategies；S*It is referred to as the NE solutions of non-cooperative game, each microgrid is based on Spot Price
Mechanism is scheduled response to respective active load and energy-storage system by workload demand, finds optimizing decision, and calculate it
Whether Nash Equilibrium is reached；By successive ignition optimizing, the microgrid of all participations has chosen optimal strategy, reaches whole mostly micro-
The stabilization and equilibrium state of net system；When having determined that acquisition preferred plan, game is terminated, optimal fault management strategy is obtained.
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