CN109617138A  A kind of independent energy management method for microgrid considering stochastic prediction error  Google Patents
A kind of independent energy management method for microgrid considering stochastic prediction error Download PDFInfo
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 CN109617138A CN109617138A CN201910039847.3A CN201910039847A CN109617138A CN 109617138 A CN109617138 A CN 109617138A CN 201910039847 A CN201910039847 A CN 201910039847A CN 109617138 A CN109617138 A CN 109617138A
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 micro turbine
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Classifications

 H—ELECTRICITY
 H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
 H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
 H02J3/00—Circuit arrangements for ac mains or ac distribution networks
 H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
 H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers

 H—ELECTRICITY
 H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
 H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
 H02J3/00—Circuit arrangements for ac mains or ac distribution networks
 H02J3/28—Arrangements for balancing of the load in a network by storage of energy
 H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means

 H—ELECTRICITY
 H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
 H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
 H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
 H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
 Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
 Y02E10/00—Energy generation through renewable energy sources
 Y02E10/50—Photovoltaic [PV] energy
 Y02E10/56—Power conversion systems, e.g. maximum power point trackers

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
 Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
 Y02E10/00—Energy generation through renewable energy sources
 Y02E10/70—Wind energy
 Y02E10/76—Power conversion electric or electronic aspects

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
 Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
 Y02E70/00—Other energy conversion or management systems reducing GHG emissions
 Y02E70/30—Systems combining energy storage with energy generation of nonfossil origin
Abstract
The present invention provides a kind of independent energy management method for microgrid for considering stochastic prediction error, the independent microcapacitance sensor includes windpowered electricity generationphotovoltaicmicro turbineenergystorage battery and Energy Management System EMS, the SOC state of EMS realtime monitoring energystorage battery, the actual generation power of windpowered electricity generation, photovoltaic is measured, the actual power of micro turbine and energystorage battery is measured；According to the power of prediction and actual monitoring, net load stochastic prediction error is obtained；According to the size of net load stochastic prediction error, the power output of controllable micro turbine and energystorage battery is arranged and adjusted by multivariable, the Mathematics Optimization Method of multiple constraint and setting process, so that energystorage battery operates normally.Using technical solution of the present invention, overcome load and renewable energy power prediction error bring adverse effect, stable, the reliable and economic operation of microcapacitance sensor is realized by Mathematics Optimization Method to the power output reasonable arrangement in controllable micro source and energy storage according to the size of net load stochastic prediction error.
Description
Technical field
The invention belongs to power scheduling and administrative skill fields, are related to a kind of independent microcapacitance sensor for considering stochastic prediction error
Energy management method more particularly to a kind of independent microgrid energy for considering load and renewable energy source power stochastic prediction error
Management method.
Background technique
Microcapacitance sensor can easily access distribution type renewable energy, the reliably working in networking and island state, be intelligence
A kind of basic composed structure of power grid.To realize uncontrollable micro battery, micro turbine and the energy storage such as photovoltaic, windpower electricity generation etc. in microgrid
Steady in a longterm, the economical operation of controllable micro battery and customer charge, it usually needs Energy Management System is coordinated and managed.Mesh
Before, microcapacitance sensor is determining after optimized to plan a few days ago often according to the renewable energy power generation power and load power of prediction, to reach
The purpose of the lowest coursing cost or renewable energy utilization maximize.However, due to the random fluctuation category of windforce, illumination and load
Property, often there is error between predicted value and actual value, and error degree deteriorates with the increasing at predicted time interval.Larger prediction
The presence of error not only directly affects the power quality of microcapacitance sensor, will also result in the micro battery economical operation plan of EMS formulation
Validity decline, even jeopardizes the stable operation of microcapacitance sensor when serious.With in microcapacitance sensor, renewable energy specific gravity is constantly mentioned
Height predicts that the influence of error can be more serious.
Currently, having done some researchs in microgrid energy management aspect both at home and abroad, some documents propose stochastic programming
Method converts certain problem processing for uncertain problem by generating several scenes using Monte Carlo simulation.However,
Such methods are computationally intensive more than the scene, are not suitable for the fast occasion of fluctuating change；Some researchers then propose standby by reserving
The impact of fluctuating power bring is mitigated with the method for power.Some documents propose the error level system by considering intermittent energy
Surely there is the plan a few days ago of nonfirm power, further according to two layers of scheduling scheme of realtime power error correction operational plan, but those sides
The determination of nonfirm power coefficient is mainly by experience in method, and also not accounting for energy storage device, actually charged capacity can be by power error
Cumulative effect.Some researches show that determining spare capacity according to year power supply reliability index, but energy storage is not accounted for；In addition,
Researcher also explores other methods.Some researchers propose by using the higher shortterm renewable energy power output prediction of precision
+ online rolling optimization improves the method for operational plan.Also some researchers mitigate prediction by introducing, controlling schedulable load
The influence of error.Though there is above many research achievements, people grind the summation of prediction error and dysgenic improvement
Study carefully it is but still few, it is especially seldom to load and the research of renewable energy source power stochastic prediction error.
Summary of the invention
Against the above technical problems, the invention discloses a kind of independent microgrid energy management for considering stochastic prediction error
Method overcomes load and renewable energy power prediction error and gives independent microcapacitance sensor operation bring adverse effect, to realize
Reliable, the economical operation of independent microcapacitance sensor.
In this regard, the technical solution adopted by the present invention are as follows:
A kind of independent energy management method for microgrid considering stochastic prediction error, the independent microcapacitance sensor includes windpowered electricity generation
Photovoltaicmicro turbineenergystorage battery comprising the Energy Management System EMS of microcapacitance sensor uses following steps to be managed:
Step S1, Energy Management System EMS predict following a period of time internal loading and windpowered electricity generation, photovoltaic power generation renewable energy
Power；
The SOC state of step S2, EMS realtime monitoring energystorage battery, the actual generation power of measurement windpowered electricity generation, photovoltaic, measurement
The actual power of micro turbine and energystorage battery；
Step S3 obtains net load stochastic prediction error according to the power of prediction and actual monitoring；It is random according to net load
The size for predicting error, by multivariable, multiple constraint Mathematics Optimization Method to the power output of controllable micro turbine and energystorage battery into
Row arranges and adjustment, so that energystorage battery operates normally；Then step S1~step S3 is repeated；
The multivariable, multiple constraint Mathematics Optimization Method include following operational objective function and one group of equation/differ
Formula constrains formula:
In formula, x is micro battery and the optimized variable that energy storage link power output arranges；c^{T}X is objective function；Ax=b is equation
Constraint；Dx < d is inequality constraints；X is the codomain of variable；Wherein, A is microcapacitance sensor active power balance constraint coefficient matrix,
Value is the matrix of 0,1 value, micro battery, energy storage device or the load being attached on microcapacitance sensor voltage bus, then its corresponding positions
Value is 1.If certain equipment or load are departing from microcapacitance sensor voltage bus, then it is constant that its corresponding positions value, which is 0b, in wattful power
Value is 0 when rate balances；D is the power limit comprising micro turbine and energystorage battery link, the charged capacity SOC limit of energystorage battery
The constraint matrix that system, micro turbine rate of power change limit, the matrix of value 0,1 value are attached to microcapacitance sensor voltage mother
Micro battery, energy storage device or load on line, then its corresponding positions value is 1.If certain equipment or load are departing from microcapacitance sensor voltage
Bus, then its corresponding positions value is 0；D is the constant in inequality, by micro turbine, the product specification of energy storage device
Listed power capacity, allows the parameters such as rate of power change to determine at energy storage SOC limit value.Further change as of the invention
Into objective function c^{T}X includes the secondary cost function C of micro turbine powerfuel_{Fuel}, micro turbine start and stop cost function C_{StartShut}
And energy storage charge and discharge punishment cost function C_{esspenalty}, specifically:
In formula, i and I_{set}Respectively micro turbine index and index set, t and T_{set}Respectively runing time index and index
Set.
Since the intermittence, fluctuation and randomness of the renewable energy such as windpowered electricity generation, photovoltaic power generation power output are prominent, cause to predict
Error is larger.The prediction error causes microcapacitance sensor actual motion point that can deviate daily planning operating point, and in the SOC of energy storage link
Accumulation, causes the deviation of energy storage SOC actual value and planned value to increase at any time.
As a further improvement of the present invention, the energy management of independent microcapacitance sensor at interval of 3~5 minutes to microcapacitance sensor can
Control micro turbine and the power output of energystorage battery are adjusted and arrange.
As a further improvement of the present invention, in step S3, when being arranged and being adjusted, make the practical SOC of energystorage battery
Maintain higher extreme value SOC_{max}With low extreme value SOC_{min}Between.
As a further improvement of the present invention, in step S3, according to prediction error to micro turbine, energy storage link in microcapacitance sensor
The size that power and SOC influence, determines net load stochastic prediction error threshold ε；Wherein stochastic prediction error threshold ε desirable 10%
Or it is bigger, specifically determined by microcapacitance sensor user.
As net load stochastic prediction error≤ε, the prediction of microgrid energy management system EMS realtime monitoring net load is missed
Difference, if error is in limits of error ε, and the practical SOC of energystorage battery is also in the up/down limit value (SOC of energystorage battery_{high}/SOC_{low})
It is interior, then it runs according to original plan；If the practical SOC of energystorage battery has crossed the up/down limit value of energystorage battery, then to micro turbine with
The power output of energystorage battery is arranged and is adjusted, and updates plan.
As a further improvement of the present invention, as the practical SOC of energystorage battery has crossed the up/down limit value of energystorage battery,
It is carried out using power output of the Rolling optimal strategy (CPLEX Rolling Optimization, CRO) to micro turbine and energystorage battery
It arranges and adjustment, the Rolling optimal strategy includes:
In moment t_{k}, when the practical SOC of energystorage battery crosses its lower limit SOC_{low}Or upper limit SOC_{high}, EMS according to micro turbine,
The current operating conditions information of energystorage battery and net load are from t_{k}To the predicted value of T, IBM Corporation CPLEX derivation algorithm is called, it is right
The operational plan of remaining period micro turbine, energystorage battery is newly solved, and updates t_{k}To T operational plan.
As a further improvement of the present invention, when calling IBM CPLEX derivation algorithm to solve, worked as using micro turbine, energy storage
Preceding actual power p_{i}[t_{k}]、p_{ess}[t_{k}] and micro turbine, energy storage current state v_{i}[t_{k}]、E_{ess}[t_{k}] it is to calculate primary condition, make new
Operational plan original state with former operational plan end state is smooth is connected.
As a further improvement of the present invention, when net load stochastic prediction error > ε, the practical SOC of energystorage battery also cross storage
The up/down limit value SOC of energy battery_{high}/SOC_{low}When, microgrid energy management system EMS controls micro turbine and energystorage battery
System is restored to the SOC of energystorage battery in up/down limit range, energystorage battery is maintained to operate normally.
As a further improvement of the present invention, using maintain Stable Control Strategy (Keep Stable Operation,
KSO) micro turbine and energystorage battery are controlled, the maintenance Stable Control Strategy includes:
As practical SOC≤SOC of energystorage battery_{low}, EMS first detects the power flow direction of energystorage battery and the switch of micro turbine
Machine state, if the power of energystorage battery is outflow and micro turbine MT shuts down, starting micro turbine at once is that energystorage battery is filled
Electricity；
If the power of energystorage battery is outflow and micro turbine has been switched on, the power output for increasing micro turbine is filled to energystorage battery
Electricity；If net load is too big, micro turbine power output has reached its maximum valueAnd the charge power of energystorage battery is still below its maximum value
P_{max}, then micro turbine power output is set as its rated powerThe charge power of energystorage battery is accordingly changed with net load power,
Its value is the difference of micro turbine rated power and net load power；
If the power of energystorage battery is inflow and micro turbine is shut down, energy storage is carried out using windpowered electricity generation, photovoltaic renewable energy
Charging；If energy storage power is inflow and micro turbine is switched on, the power output of micro turbine is incrementally increased, the maximum charge allowed with energy storage
Power charges to energystorage battery；When micro turbine power output has reached its maximum value and the charge power of energystorage battery is still below permission most
When big value charge power, micro turbine power output is set as its rated power；
As practical SOC >=SOC of energystorage battery_{high}, EMS detects the power flow direction of energystorage battery first and micro turbine switchs
Machine state, if the power flow direction of energystorage battery is outflow, micro turbine and energystorage battery continue that original operational plan is followed to instruct；
If the power flow direction of energystorage battery is inflow and micro turbine is switched on, EMS, which reduces micro turbine power output, makes the charge power of energystorage battery
Decline；If micro turbine power output has reached its minimumP_{i} , and energystorage battery is still charging, then cutout renewable energy is abandoned
Part renewable energy source power, makes energystorage battery discharge；Whole renewable energy source power are abandoned if having cut off, but energystorage battery is still
It is charging, is then closing combustion engine；If energystorage battery persistently charges and SOC is caused to cross storage in excision renewable energy power process
The maximum permissible value SOC of energy battery_{max}, then directly close micro turbine and cut off all renewable energy.
As a further improvement of the present invention, when starting micro turbine, its power output is in a cycle of micro turbine starting
Its specified minimum power, when second period, the power output of micro turbine follows load or operational plan to instruct.
Compared with prior art, the invention has the benefit that
Technical solution of the present invention, which considers load and renewable energy source power stochastic prediction error, can make micro battery practical
Operating point and operational plan a few days ago generate deviation, and it is more than it that the deviation longterm accumulation, which can lead to energy storage SOC at the unplanned moment,
Work limit value, influences microcapacitance sensor stable operation；Technical solution of the present invention overcomes load and renewable energy power prediction error
Independent microcapacitance sensor operation bring adverse effect is given, according to the size of net load stochastic prediction error, passes through Mathematics Optimization Method
To the power output reasonable arrangement in controllable micro source and energy storage, stable, the reliable and economic operation of microcapacitance sensor is realized.
Specifically, the present invention proposes under the small stochastic prediction error of net load, when the SOC of energystorage battery transfinites, lead to
Rolling optimization CRO strategy is crossed to make the microcapacitance sensor EMS stable control method of energy storage SOC holding in the reasonable scope, so that whole
Optimum results are more preferable, more feasible, also make independent microcapacitance sensor operation more economical；Under the big stochastic prediction error of net load, work as storage
When energy SOC transfinites, stablizing preferential KSO strategy by maintenance makes energy storage SOC quickly recover to the method in zone of reasonableness, makes solely
Vertical microcapacitance sensor operation is more stable.
Detailed description of the invention
Fig. 1 is a kind of general flow chart for the independent energy management method for microgrid for considering stochastic prediction error of the present invention.
Fig. 2 is the flow chart of CRO Rolling optimal strategy in the present invention.
Fig. 3 is that CRO energy management rolls update timing diagram in the present invention.
Fig. 4 is that KSO maintains to stablize EMS strategic process figure in the present invention.
Fig. 5 is that KSO maintains stable strategy timing diagram in the present invention.
Fig. 6 is under the small stochastic prediction error of the present invention using CRO micro battery operation result exemplary diagram, wherein a) is micro combustion
The actual power operating status figure of machine, b) be energystorage battery actual power operating status figure, c) be micro turbine actual power
And the difference of operational plan, d) be the actual power of energystorage battery and the difference of operational plan, e) be energystorage battery plan SOC and more
SOC change curve after changing plan.
Fig. 7 is under big stochastic prediction error of the invention using KSO micro battery operation result exemplary diagram, wherein a) is micro combustion
The actual power operating status figure of machine, b) be energystorage battery actual power operating status figure, c) be micro turbine actual power
And the difference of operational plan, d) be the actual power of energystorage battery and the difference of operational plan, e) be energystorage battery plan SOC and more
SOC change curve after changing plan.
Specific embodiment
Preferably embodiment of the invention is described in further detail below.
As shown in Figure 1, a kind of independent energy management method for microgrid for considering stochastic prediction error comprising following step
It is rapid:
(1) Energy Management System EMS carries out the power of following a period of time internal loading and the renewable sources of energy (windpowered electricity generation, photovoltaic)
Prediction；
(2) it is optimized using CPLEX, specifies operational plan a few days ago, micro battery (micro turbine and energystorage battery) is according to meter
It rows row；
(3) the SOC state of EMS realtime monitoring energystorage battery, the actual generation power of measurement windpowered electricity generation, photovoltaic, measures micro combustion
The actual power of machine and energystorage battery；According to the power of prediction and actual monitoring, it is i.e. practical to obtain net load stochastic prediction error
Kinematic error；
(4) size that micro turbine, energy storage link power and SOC influence in microcapacitance sensor is determined net negative according to prediction error
Lotus stochastic prediction error threshold ε；
As net load stochastic prediction error≤ε, the prediction of microgrid energy management system EMS realtime monitoring net load is missed
Difference, if error is in limits of error ε, and the practical SOC of energystorage battery is also in the up/down limit value (SOC of energystorage battery_{high}/SOC_{low})
It is interior, then it runs according to original plan；If the practical SOC of energystorage battery has crossed the up/down limit value of energystorage battery, using rolling optimization
Tactful (CPLEX Rolling Optimization, CRO) is arranged and is adjusted to the power output of micro turbine and energystorage battery, institute
Stating Rolling optimal strategy CRO includes:
In moment t_{k}, when the practical SOC of energystorage battery crosses its lower limit SOC_{low}Or upper limit SOC_{high}, EMS according to micro turbine,
The current operating conditions information of energystorage battery and net load are from t_{k}To the predicted value of T, IBM CPLEX derivation algorithm is called, to surplus
The operational plan of remaining period micro turbine, energystorage battery is newly solved, and updates t_{k}To T operational plan.IBM CPLEX is called to ask
When resolving Algorithm solves, micro turbine, the currently practical power p of energy storage are used_{i}[t_{k}]、p_{ess}[t_{k}] and micro turbine, energy storage current state v_{i}
[t_{k}]、E_{ess}[t_{k}] be to calculate primary condition, make new operational plan original state with original operational plan end state is smooth is connected.
As net load stochastic prediction error > ε, using maintain Stable Control Strategy (Keep Stable Operation,
KSO) micro turbine and energystorage battery are controlled, the SOC of energystorage battery is restored in up/down limit range, maintains storage
It can battery normal operation.
The maintenance Stable Control Strategy KSO includes:
As practical SOC≤SOC of energystorage battery_{low}, EMS first detects the power flow direction of energystorage battery and the switch of micro turbine
Machine state, if the power of energystorage battery is outflow and micro turbine MT shuts down, starting micro turbine at once is that energystorage battery is filled
Electricity；When starting micro turbine, its power output is its specified minimum power in a cycle of micro turbine starting, when second period,
The power output of micro turbine follows load or operational plan to instruct.
If the power of energystorage battery is outflow and micro turbine has been switched on, the power output for increasing micro turbine is filled to energystorage battery
Electricity；If net load is too big, micro turbine power output has reached its maximum valueAnd the charge power of energystorage battery is still below its maximum value
P_{max}, then micro turbine power output is set as its rated powerThe charge power of energystorage battery is accordingly changed with net load power,
Its value is the difference of micro turbine rated power and net load power；
If the power of energystorage battery is inflow and micro turbine is shut down, energy storage is carried out using windpowered electricity generation, photovoltaic renewable energy
Charging；If energy storage power is inflow and micro turbine is switched on, the power output of micro turbine is incrementally increased, the maximum charge allowed with energy storage
Power charges to energystorage battery；When micro turbine power output has reached its maximum value and the charge power of energystorage battery is still below permission most
When big value charge power, micro turbine power output is set as its rated power；
As practical SOC >=SOC of energystorage battery_{high}, EMS detects the power flow direction of energystorage battery first and micro turbine switchs
Machine state, if the power flow direction of energystorage battery is outflow, micro turbine and energystorage battery continue that original operational plan is followed to instruct；
If the power flow direction of energystorage battery is inflow and micro turbine is switched on, EMS, which reduces micro turbine power output, makes the charge power of energystorage battery
Decline；If micro turbine power output has reached its minimumP_{i} , and energystorage battery is still charging, then abandons part renewable energy by excision
Source power makes energystorage battery discharge；If having cut off whole renewable energy source power, but energystorage battery is still charging, then combustion is closed
Machine；If energystorage battery persistently charges and SOC is caused to cross maximum permissible value SOC in excision renewable energy power process_{max}, then
It directly closes micro turbine and cuts off all renewable energy.
Above scheme is based on rolling optimization (CRO) and maintains to stablize two kinds of new E MS strategies of (KSO), it is intended to reduce negative
Lotus and renewable energy power prediction error give independent microcapacitance sensor operation bring adverse effect, can with realize independent microcapacitance sensor
It leans on, economical operation.Technical solution of the present invention first according to random theory, to prediction prediction error stochastic behaviour in microgrid and its
Communication process carries out mathematical modeling, with its specific influence on the controllable micro battery of EMS and energy storage link operational plan of post analysis；Into
And will cause according to the size of prediction error makes energy storage SOC cross thereon/lower limit value speed difference, has separately designed rolling
Optimize CRO and maintains to stablize two kinds of control strategies of KSO, to make energy storage SOC in operation remain at normal operation range, thus
Improve microcapacitance sensor longplay stability.
Technical solution of the present invention is suitable for using windlightmicro turbinebattery energy storage as the micro electricity of the independent operating of main composition
Net.The Energy Management System EMS of microcapacitance sensor passes through on predicting following a period of time internal loading and renewable energy power level
Mathematics Optimization Method is to the controllably power output reasonable arrangement of micro source and energy storage, to reach the stabilization and economy of microcapacitance sensor operation.
The mathematic optimal model of microgrid energy management system EMS is usually by operational objective function and one group of equation/differ
Formula constrains formula and constitutes, specifically:
In formula, x is micro battery and the optimized variable that energy storage link power output arranges；c^{T}X is objective function；Ax=b is equation
Constraint；Dx < d is inequality constraints；X is the codomain of variable.Wherein, A is active power balance constraint matrix, and b is constant, and D is
Constraint matrixes, the d such as the power capacity limit of micro source and energy storage link, the limitation of micro source power rate of change are some in inequality
Constant value.To the mixedinteger nonlinear programming model, Dynamic Programming, mixed integer linear programming (MILP), particle can be used
The methods of group (PSO) solves.
The objective function of independent microcapacitance sensor includes the secondary cost function C of micro turbine powerfuel_{Fuel}, micro turbine start and stop
Cost function C_{StartShut}And energy storage charge and discharge punishment cost function C_{esspenalty}, specifically:
In formula, i and I_{set}Respectively micro turbine index and index set, t and T_{set}Respectively runing time index and index
Set.
In constraint condition, the sum of micro turbine and energy storage power in this microcapacitance sensor want the moment to be equal to net load power, come
Meet the requirement of powerbalance equation；In addition, micro turbine and energy storage link are also divided because of the limitation of its physical structure and manufacture level
Do not need to meet multiple groups operation constraint condition.As micro turbine needs to meet: (1) maximum available power is limited in unit up/down power
Interior and spinning reserve capacity requirement；(2) requirement of the climbing rate of maximum available power, starting climbing rate and climbing rate of shutting down；
(3) micro turbine starting and shutdown will meet minimum available machine time and minimum unused time limitation, to prolong the service life.It is similar
, since the service life of energy storage link is influenced by factors such as chargedischarge electric power, charge and discharge conversion frequency and depth of discharge, storage
Energy link normal operation needs to meet: (1) chargedischarge electric power and charge and discharge change rate limit；(2) charge and discharge conversion frequency limits；
(3) continuous wave high power charge and discharge time and SOC highlow limit limit；(4) to maximize energy storage link service life, once
Charging is then charged to always the regulation maximum value of SOC as far as possible, and the regulation for then discharging into SOC always as far as possible once electric discharge is minimum
Value.Since inequality is more, the unlisted expression in this place.
Prominent for the intermittence, fluctuation and randomness of renewable energy power output, Accurate Prediction modeling is difficult, prediction misses
The larger feature of difference, there has been proposed a variety of probability density methods such as normal distribution, Gaussian function, beta distribution to be fitted wind
The prediction error of electricity, photovoltaic power generation.Although the error distribution of normal distribution and windpowered electricity generation actual measurement yet has some differences, such as practical
Slower than normal distribution curve, Density Function of Normal Distribution variable the positive minus infinity value range of error curve ending has exceeded
Practical renewable energy power output range, but since error appears in probability very little, the prediction error existence range of curve tail end
It is limited.
Being used uniformly normal distribution below, renewable energy is contributed in real time and the probability density of load electricity consumption is divided to describe
Cloth.
Enabling the predicted value of load and renewable energy is mathematical expectation, then the prediction of windpowered electricity generation, photovoltaic power generation, load misses
This poor stochastic variable Normal Distribution, specifically:
In formula, p_{θ}[t] and p_{θ} ^{*}[t] is respectively the real output and pre measurement of power of load and renewable energy θ in moment t
Rate, N indicate normal distyribution function, μ_{θ}[t] and δ_{θ}[t] is respectively p_{θ}[t] is in moment t mathematic expectaion and variance, T_{set}When to predict
The set at quarter has T element, p_{θ} ^{*}[t]=μ_{θ}[t], Θ indicate the set of load, renewable energy.According to probability theory normal state
Distribution character, the value of stochastic variable fall in ( 3 σ_{θ}[t],+3σ_{θ}[t]) probability in section is 99.74%, therefore can consider micro electricity
Net in operation in following 24 hours, the random error between load and renewable energy source power actual value and predicted value also fall in (
3σ_{θ}[t],+3σ_{θ}[t]) within the limits of error.
Random error in the present invention between microgrid load actual power and prediction power is set as that mean value is 0, variance isNormal distribution, standard deviation calculate specifically:
In formula, k value is 1, p_{load} ^{*}[t] is load in moment t shortterm forecast value.
It is 0 just that random error between windpower electricity generation, the practical power output of photovoltaic power generation and shortterm forecast power output, which is set as mean value,
State distribution, standard deviation calculate specifically:
In formula, p_{θrate}For photovoltaic, blower installed capacity, p_{θ} ^{*}[t] is photovoltaic, blower in moment t shortterm forecast value.
The net load power of microcapacitance sensor is the difference of load power and renewable energy power generation power, formula specifically:
The random error variable p of net load power_{net}[t]p_{net} ^{*}[t] Normal Distribution, specifically:
For convenient for load, photovoltaic and wind turbine power generation power respectively predict error it is random variation be compared, if at random
Variable p_{θ}[t]p_{θ} ^{*}[t] has identical coefficient of variation C [t], specifically:
In formula, K is constant；Then it can obtain:
σ_{load}[t]+σ_{solar}[t]+σ_{wind}[t]=K^{2}p_{load} ^{*}[t]+K^{2}p_{solar} ^{*}[t]+K^{2}p_{wind} ^{*}[t]
The prediction error stochastic variable of net load powerVariance ratio load, photovoltaic and power of fan
Respectively prediction error variance of a random variable is much greater, shows that the prediction error of load, photovoltaic and wind turbine power generation power can pass
It is delivered in net load, and becomes much larger.Therefore if the predicted value of load, photovoltaic and power of fan is not quasi enough, it is calculated
Net load predicted value may differ greatly with actual value.
Due to load, renewable energy changed power actually or by some common factors, such as temperature, atmospheric density
With the influence of humidity etc., thus there is also certain correlations on various discrete time point for power measured value, predicted value, and
And time interval is shorter, the power dependency on the discrete time point of front and back 2 is stronger, and changed power is smaller.Therefore, net load
Stochastic variable p_{net}[t]p_{net} ^{*}[t] is also that T ties up random vector on the whole, specifically:
P_{net}=(P_{net}[t_{1}],...,P_{net}[t_{k}],...,P_{net}[t_{T}])=(p_{net}[t_{1}]p_{net} ^{*}[t_{1}],...,p_{net}[t_{k}]
p_{net} ^{*}[t_{k}],...,p_{net}[t_{T}]p_{net} ^{*}[t_{T}])
If stochastic variable p_{net}[t]p_{net} ^{*}[t] joint probability distribution also obeys T dimension normal distribution, each discrete point performance number
Between degree of correlation by error of covariance matrix nondiagonal term element reflect, specifically:
In formula, the T member population mean vector μ of net load_{net}Specifically:
μ_{net}=(μ_{net}[t_{1}],...,μ_{net}[t_{k}],...,μ_{net}[t_{T}])
E_{net}For P_{net}T member normal distribution error of covariance matrix, and E_{net}Real symmetric tridiagonal matrices, tool are tieed up for T × T
Body are as follows:
In formula, Cov (P_{net}[t_{i}],P_{net}[t_{j} ^{]}) it is P_{net}[t] is in moment t_{i}And t_{j}Between covariance.ρ_{ij}For related coefficient,
Its value are as follows:
The prediction error of net load can be such that micro battery and the actual motion point deviation of energy storage link in microcapacitance sensor runs a few days ago
The set point of plan.Microcapacitance sensor uses load and renewable energy power prediction value as defeated when carrying out EMS plan solution
Enter data, calculated by mathematical optimization, obtains micro turbine and energy storage in the operation meter of the discretetime series of following a period of time
It draws.
It is run in microcapacitance sensor and in the works, net load and micro battery, energy storage link keeps powerbalance relationship, specifically
Are as follows:
In formula, p_{i} ^{*}[t] is ith micro turbine moment t power；p_{ess} ^{*}[t] is power of the energy storage in moment t.
The stateofcharge of energy storage link then determines by the integral of energy storage power, specifically:
E_{ess} ^{*}[t]=E_{ess} ^{*}[t1]η(p_{ess} ^{*}[t1])·p_{ess} ^{*}[t1]
In formula, E_{ess} ^{*}[t] is the SOC of energy storage；η is sign function.
In each t ∈ T_{set}The net load predicted value error at moment can be all delivered in micro battery and energy storage, and the product in energy storage
Tire out.That is the T member random error vector P of net load_{net}It is transmitted to the T member operational plan vector P of micro turbine and energy storage_{i} ^{*}With
P_{ess} ^{*}In.The net load T member predicted value vector that microgrid EMS model uses specifically:
P_{net} ^{*}=(p_{net} ^{*}[t_{1}],...,p_{net} ^{*}[t_{k}],...,p_{net} ^{*}[t_{T}])
After Optimization Solution EMS model, it is assumed that by P_{net} ^{*}Coefficient matrices A is tieed up by ith of T × T_{i}Obtain ith micro turbine
T member operational plan vector P_{i} ^{*}, and matrix number B is maintained by a T × T and obtains the T member operational plan vector P of energy storage_{ess} ^{*}, tool
Body are as follows:
P_{ess} ^{*}=BP_{net} ^{*}
Micro turbine set I_{set}In ith micro turbine T member operational plan vector P_{i} ^{*}With energy storage T member operational plan vector
P_{ess} ^{*}Specifically:
P_{ess} ^{*}=(p_{ess} ^{*}[t_{1}],...,p_{ess} ^{*}[t_{k}],...,p_{ess} ^{*}[t_{T}])
In P_{net}In random error pass through A_{i}It is transmitted to P respectively with B_{i} ^{*}And P_{ess} ^{*}In.Wherein P_{i} ^{*}And P_{ess} ^{*}Corresponding T × T
Tie up error of covariance matrix specifically:
E_{pess}=BE_{net}·B^{T}
The value of storage energy operation power set point is according to P_{ess} ^{*}Setting, since energy storage actual motion point and set point be not in operation
Unanimously, in random error by P_{net}It is transmitted to P_{ess} ^{*}Afterwards, random error can be transmitted to energy storage SOC by energy storage energy conservation equation
In, can all error be made to increase after iterating to calculate energy storage SOC every time, after end of run between energy storage practical SOC and operational plan SOC
Error specifically:
Wherein,With Cov (p_{ess} ^{*}[t], p_{es}s^{*}[l]) it is respectively P_{ess} ^{*}T × T tie up error of covariance matrix E_{pess}'s
Diagonal item element and nondiagonal term element；T is the total number of cycles of runing time.
The restriction that energy storage SOC operation has up/down to limit is contained in microcapacitance sensor EMS optimization computation model, is made
Storage energy operation plan can make energy storage SOC keep over/under limit range in.However, the prediction error of net load then make micro turbine,
Energy storage link actual motion power deviates planned value, which constantly accumulates in energy storage SOC, can make energy storage SOC be more than thereon/
Lower limit value.For avoid overcharging/overdischarge and damage the service life, energy storage link can voluntarily limit charge/discharge or stoppage in transit, this just gives microgrid steady
Determine economical operation and brings potential impact.
Method by increasing stored energy capacitance merely can bring microgrid cost to rise, in practice and undesirable.It can by analysis
To know, prediction deviation is of different sizes, and it is different from the severe degree that storage energy operation power, state change to micro turbine, energy storage SOC is got over
The speed for crossing up/down limit is also different.Therefore, the present invention proposes a kind of microcapacitance sensor energy based on prediction error and energy storage SOC safety
Measure management strategy.Its on project basis a few days ago, according to prediction error and energy storage SOC different conditions carry out according to original plan,
Rolling optimization plan or energy storage SOC restore stabilization plan operation, so that energy storage SOC be made to maintain in microgrid economical operation rationally
Limit range in.
The shortterm forecast error of renewable energy power generation power is smaller in microgrid, and confidence interval of the error less than 10% is
95%.That is in microgrid one day most times, the random error of net load will fall in ( 3 σ_{θ}[t],+3σ_{θ}[t]) limits of error
Within.The difference of size is influenced on micro turbine, energy storage link power and SOC in microgrid according to prediction error, it may be determined that one suitable
When net load random error threshold epsilon.As stochastic prediction error≤ε, it is believed that it is small error, it is on the contrary then be considered as big error.
Since the time span of operational plan a few days ago is big, small stochastic prediction error it is also possible that energy storage link variable capacity not
Foot influences microgrid and stablizes.EMS realtime monitoring net load of the present invention predicts error, and if error is in limits of error ε, and energy storage is practical
SOC is also in the upper limit/lower limit value (SOC_{high}/SOC_{low}) in, then by original (a few days ago) plan operation；As the practical SOC of energy storage has passed past
Up/down limit value, then start Rolling optimal strategy CRO, formulate and update plan, restore energy storage SOC gradually.
It is illustrated in figure 2 CRO rolling optimization EMS strategic process figure.Its entry condition specifically:
E_{ess} ^{*}[t_{k}]≤SOC_{low} OR E_{ess} ^{*}[t_{k}]≥SOC_{high}
In moment t_{k}The practical SOC of energy storage crosses its lower limit SOC_{low}Or upper limit SOC_{high}, EMS is according to micro turbine, energy storage link
Current operating conditions information and net load are from t_{k}To the predicted value of T, IBM CPLEX derivation algorithm is called, to the micro combustion of remaining period
Machine, energy storage operational plan newly solved, and update t_{k}To T operational plan.Due in EMS to energy storage link overshoot/overdischarge
Provided with penalty function, the operational plan newly formulated can correct micro turbine, energy storage power output, and energy storage SOC is made to be gradually recovered normal operation
In range.
There is great fluctuation process to avoid micro turbine and energy storage power or state, when CRO calls CPLEX to solve, using micro turbine,
The currently practical power p of energy storage_{i}[t_{k}]、p_{ess}[t_{k}] and state v_{i}[t_{k}]、E_{ess}[t_{k}] it is to calculate primary condition, at the beginning of making new operational plan
Beginning state with former operational plan end state is smooth is connected.It is illustrated in figure 3 CRO energy management operational plan and updates timing diagram.
When the random error of net load is greater than threshold epsilon, micro turbine in microgrid, energy storage link changed power can be larger,
The practical SOC of energy storage also changes acceleration.If the error last longer, the practical SOC of energy storage may be reached in original plan SOC
Up/down crossed limit value before limit time point, energy storage is that safety will limitation charge/discharge or stoppage in transit.Renewable energy when if SOC reaches the upper limit
Micro turbine is just shut down when source is sufficient or SOC reaches lower limit, and the powerbalance of microgrid will be made to be impacted.The present invention designs thus
It maintains to stablize (Keep Stable Operation, KSO) energy management strategies, micro turbine and energy storage is controlled, it is excellent
It is restored to energy storage SOC in up/down limit range, so that energy storage be maintained to operate normally.
As shown in Figure 4, left side dashed box is the broad flow diagram that KSO maintains stable strategy.EMS realtime detection net load is pre
Survey error, such as t_{k}Moment its be more than threshold epsilon, but energy storage SOC also over/under limit in, then former operational plan is still pressed in micro turbine, energy storage
Operation；If the practical SOC of energy storage at this time has passed past up/down limit value, then KSO strategy, i.e. its entry condition are enabled specifically:
E_{ess} ^{*}[t_{k}]≤SOC_{low} OR E_{ess} ^{*}[t_{k}]≥SOC_{high}
When KSO is controlled, micro turbine in microcapacitance sensor, energy storage link main control flow be described below:
1)SOC≤SOC_{low}Energy storage electricity is insufficient at this time, to avoid energy storage overdischarge, need to limit electric discharge, fill as early as possible to energy storage
Electricity.EMS system first detects the onoff state of energy storage power flow direction and micro turbine MT.If energy storage power is outflow (p_{ess}It bears to put
Electricity is just being charging) and micro turbine MT shutdown, then emergency start micro turbine is energy storage charging.For protect micro turbine, the first of starting
Its power output is its specified minimum power in a period, and starting second period can just follow load or operational plan to instruct, in figure
Ontime parameter represents the periodicity of micro turbine starting, and Disp parameter represents the operational plan of each micro battery of microcapacitance sensor.If energy storage
Power be outflow and micro turbine have been switched on, then increase micro turbine contribute give energy storage charging.If net load is too big, micro turbine power output
Its maximum value is reachedAnd energy storage charge power is still below its maximum value P_{max}, then micro turbine power output is set as its rated powerThe charge power of energy storage is accordingly changed with net load power, and value is the difference of micro turbine rated power and net load power；If
Energy storage power is inflow and micro turbine is shut down, and shows that renewable energy power generation power is abundant at this time, can make full use of renewable
The energy charges to energy storage；If energy storage power be flow into and micro turbine be switched on, incrementally increase micro turbine power output, as far as possible with
The maximum charge power that energy storage allows charges；When micro turbine power output reach its maximum value and energy storage charge power is still below and allows most
When big value charge power, micro turbine power output is set as its rated power.For the service life for extending energy storage link, energy storage is once
It starts to charge, is charged to SOC always as far as possible_{high}。
2)SOC≥SOC_{high}Show that energy storage electric energy is sufficient, at this time to protect energy storage not damage service life, palpus because overcharging
Limit its charging.EMS detects the power flow direction and micro turbine onoff state of energy storage first.If energy storage power flow direction is outflow,
Illustrate that energy storage is being discharged, then micro turbine and energy storage continue that original operational plan is followed to instruct；If energy storage power flow direction be flow into and
Micro turbine booting, shows that energy storage still is continuing to charge, and EMS, which reduces micro turbine power output, declines energy storage charge power.If micro combustion
Machine power output has reached its minimum P_{i}, and energy storage is still being charged, then cutout renewable energy P_{RES}Abandon part renewable energy
Source power is so that energy storage starts to discharge.If having cut off whole renewable energy source power, but energy storage is still being charged, then closes combustion engine.
If energy storage persistently charges and SOC is caused to cross maximum permissible value SOC in excision renewable energy power process_{max}, then directly close
Close micro turbine and renewable energy.KSO maintains stable strategy timing diagram as shown in Figure 5.
Energy storage SOC outoflimit situation is handled when KSO strategy is for net load big stochastic prediction error.When big error disappears
It loses, energy storage SOC is more handled with CRO strategy in limited time under small error.Two kinds of strategic substitute cooperations of CRO and KSO, it is ensured that energy storage
The SOC interior work of limits over/under substantially, maintains microcapacitance sensor stable and economical operation.It is used under small stochastic prediction error
CRO micro battery operation result example is as shown in fig. 6, wherein ε value is the 25% of microcapacitance sensor capacity.It can be seen that being missed in small stochastic prediction
Difference is lower to use CRO Rolling optimal strategy, can will maintain higher extreme value SOC in the practical SOC formula of energy storage_{max}With low extreme value SOC_{min}
Between.
The micro source operation result example of KSO is used under big stochastic prediction error as shown in fig. 7, wherein ε value is microcapacitance sensor appearance
The 25% of amount.It can be seen that maintaining stable strategy using KSO under big stochastic prediction error, energy storage SOC can maintain pole in formula
Limit value SOC_{max}With low extreme value SOC_{min}Between.
The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be said that
Specific implementation of the invention is only limited to these instructions.For those of ordinary skill in the art to which the present invention belongs, exist
Under the premise of not departing from present inventive concept, a number of simple deductions or replacements can also be made, all shall be regarded as belonging to of the invention
Protection scope.
Claims (10)
1. a kind of independent energy management method for microgrid for considering stochastic prediction error, it is characterised in that: the independent microcapacitance sensor
Including windpowered electricity generationphotovoltaicmicro turbineenergystorage battery and Energy Management System EMS, following steps is used to carry out energy management:
Step S1, Energy Management System EMS predict the power of following a period of time internal loading and windpowered electricity generation, photovoltaic renewable energy；
The SOC state of step S2, EMS realtime monitoring energystorage battery, the actual generation power of measurement windpowered electricity generation, photovoltaic, measures micro combustion
The actual power of machine and energystorage battery；
Step S3 obtains net load stochastic prediction error according to the power of prediction and actual monitoring；According to net load stochastic prediction
The size of error pacifies the power output of controllable micro turbine and energystorage battery by the Mathematics Optimization Method of multivariable, multiple constraint
Row and adjustment, so that energystorage battery operates normally；Then step S1~step S3 is repeated；
The multivariable, multiple constraint Mathematics Optimization Method include following operational objective function and one group of equation/inequality about
Beam formula:
In formula, x is micro battery and the optimized variable that energy storage link power output arranges；c^{T}X is objective function；Ax=b is equality constraint；
Dx < d is inequality constraints；X is the codomain of variable；Wherein, A is microcapacitance sensor active power balance constraint coefficient matrix, and value is
0, the matrix of 1 value；B is constant, and in active power balance, value is 0；D is the function comprising micro turbine Yu energystorage battery link
The constraint matrix of rate limitation, the charged capacity SOC limitation of energystorage battery, the limitation of micro turbine rate of power change, value 0,1 value
Matrix；D is the constant in inequality, by power capacity listed in micro turbine, the product specification of energy storage device, storage
Energy SOC limit value allows the parameters such as rate of power change to determine.
2. the independent energy management method for microgrid according to claim 1 for considering stochastic prediction error, it is characterised in that:
Objective function c^{T}X includes the secondary cost function C of micro turbine powerfuel_{Fuel}, micro turbine start and stop cost function C_{StartShut}And storage
It can charge and discharge punishment cost function C_{esspenalty}, specifically:
In formula, i and I_{set}Respectively micro turbine index and index set, t and T_{set}Respectively runing time index and index set.
3. the independent energy management method for microgrid according to claim 1 for considering stochastic prediction error, it is characterised in that:
The energy management of independent microcapacitance sensor adjusted the controllable micro turbine of microcapacitance sensor and the power output of energystorage battery at interval of 3~5 minutes
Whole and arrangement.
4. the independent energy management method for microgrid according to any one of claims 1 to 3 for considering stochastic prediction error,
It is characterized by: when being arranged and being adjusted, the practical SOC of energystorage battery is made to maintain the upper pole of energystorage battery in step S3
Between limit value and low extreme value.
5. the independent energy management method for microgrid according to claim 4 for considering stochastic prediction error, it is characterised in that:
In step S3, according to prediction error on the size that micro turbine, energy storage link power and SOC influence in microcapacitance sensor, net load is determined
Stochastic prediction error threshold ε；
As net load stochastic prediction error≤ε, the prediction error of microgrid energy management system EMS realtime monitoring net load,
If error is in limits of error ε, and the practical SOC of energystorage battery is also in up/down limit value, that is, SOC of energystorage battery_{high}/SOC_{low}It is interior,
Then run according to original plan；If the practical SOC of energystorage battery has crossed the up/down limit value of energystorage battery, then to micro turbine and storage
The power output of energy battery is arranged and is adjusted, and updates plan.
6. the independent energy management method for microgrid according to claim 5 for considering stochastic prediction error, it is characterised in that:
If the practical SOC of energystorage battery has crossed the up/down limit value of energystorage battery, using Rolling optimal strategy to micro turbine and energy storage electricity
The power output in pond is arranged and is adjusted, and the Rolling optimal strategy includes:
In moment t_{k}, when the practical SOC of energystorage battery crosses its lower limit value or upper limit value, EMS is according to micro turbine, energystorage battery
Current operating conditions information and net load are from t_{k}To the predicted value of T, CPLEX derivation algorithm is called, to remaining period micro turbine, storage
The operational plan of energy battery is newly solved, and updates t_{k}To T operational plan.
7. the independent energy management method for microgrid according to claim 6 for considering stochastic prediction error, it is characterised in that:
When IBM CPLEX derivation algorithm being called to solve, micro turbine, the currently practical power p of energy storage are used_{i}[t_{k}]、p_{ess}[t_{k]}With micro turbine,
Energy storage current state v_{i}[t_{k}]、E_{ess}[t_{k}] it is to calculate primary condition, make new operational plan original state and former operational plan end
The smooth linking of state.
8. the independent energy management method for microgrid according to claim 5 for considering stochastic prediction error, it is characterised in that:
When net load stochastic prediction error > ε, the practical SOC of energystorage battery also cross the up/down limit value SOC of energystorage battery_{high}/SOC_{low}
When, microgrid energy management system EMS controls micro turbine and energystorage battery, is preferentially restored to the SOC of energystorage battery
Up/down limits in range, and energystorage battery is maintained to operate normally.
9. the independent energy management method for microgrid according to claim 8 for considering stochastic prediction error, it is characterised in that:
Using maintaining Stable Control Strategy to control micro turbine and energystorage battery, the maintenance Stable Control Strategy includes: when storage
Practical SOC≤SOC of energy battery_{low}, EMS first detects the power flow direction of energystorage battery and the onoff state of micro turbine, if energy storage
The power of battery is outflow and micro turbine MT shuts down, then starting micro turbine is that energystorage battery charges at once；
If the power of energystorage battery is outflow and micro turbine has been switched on, the power output for increasing micro turbine charges to energystorage battery；Such as
Fruit net load is too big, and micro turbine power output has reached its maximum value and the charge power of energystorage battery is still below its maximum value, then will be micro
Combustion engine power output is set as its rated power, and the charge power of energystorage battery is accordingly changed with net load power, and value is micro turbine
The difference of rated power and net load power；
If the power of energystorage battery be flow into and micro turbine shut down, using include windpowered electricity generation, photovoltaic renewable energy to energy storage into
Row charging；If energy storage power is inflow and micro turbine is switched on, the power output of micro turbine is incrementally increased, is filled with the maximum that energy storage allows
Electrical power charges to energystorage battery；When micro turbine power output has reached its maximum value and the charge power of energystorage battery is still below permission
When maximum value charge power, micro turbine power output is set as its rated power；
As practical SOC >=SOC of energystorage battery_{high}, EMS detects the power flow direction and micro turbine switching on and shutting down shape of energystorage battery first
State, if the power flow direction of energystorage battery is outflow, micro turbine and energystorage battery continue that original operational plan is followed to instruct；If storage
The power flow direction of energy battery is inflow and micro turbine is switched on, and EMS, which reduces micro turbine and contributes, declines the charge power of energystorage battery；
If micro turbine power output has reached its minimum, and energystorage battery is still charging, then abandons portion by cutout renewable energy
Divide renewable energy source power, energystorage battery is made to discharge；If having cut off whole renewable energy, but energystorage battery is still charging, then
Close combustion engine；If energystorage battery persistently charges and SOC is caused to cross energystorage battery most in excision renewable energy power process
Big permissible value SOC_{max}, then directly close micro turbine and cut off all renewable energy.
10. the independent energy management method for microgrid according to claim 9 for considering stochastic prediction error, feature exist
In: when starting micro turbine, its power output is its specified minimum power in a cycle of micro turbine starting, when second period,
The power output of micro turbine follows load or operational plan to instruct.
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CN110261673A (en) *  20190514  20190920  哈尔滨工业大学  It is a kind of based on voltage, the dummy burst power measuring system of electric current dipulse signal and method 
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WO2020219078A1 (en) *  20190426  20201029  Pason Power, Inc.  Intelligent energy management system for distributed energy resources and energy storage systems using machine learning 
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