CN109617138A - A kind of independent energy management method for micro-grid considering stochastic prediction error - Google Patents

A kind of independent energy management method for micro-grid considering stochastic prediction error Download PDF

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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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energy
micro
power
storage battery
micro turbine
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陈亚红
和军平
陶耀东
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Shenzhen Graduate School Harbin Institute of Technology
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Shenzhen Graduate School Harbin Institute of Technology
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46Controlling of the sharing of output between the generators, converters, or transformers
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/50Photovoltaic [PV] energy
    • Y02E10/56Power conversion systems, e.g. maximum power point trackers
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/70Wind energy
    • Y02E10/76Power conversion electric or electronic aspects
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30Systems combining energy storage with energy generation of non-fossil origin

Abstract

The present invention provides a kind of independent energy management method for micro-grid for considering stochastic prediction error, the independent micro-capacitance sensor includes wind-powered electricity generation-photovoltaic-micro turbine-energy-storage battery and Energy Management System EMS, the SOC state of EMS real-time monitoring energy-storage battery, the actual generation power of wind-powered electricity generation, photovoltaic is measured, the actual power of micro turbine and energy-storage 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 energy-storage battery is arranged and adjusted by multivariable, the Mathematics Optimization Method of multiple constraint and setting process, so that energy-storage 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 micro-capacitance 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

A kind of independent energy management method for micro-grid considering stochastic prediction error
Technical field
The invention belongs to power scheduling and administrative skill fields, are related to a kind of independent micro-capacitance 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
Micro-capacitance 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, wind-power electricity generation etc. in microgrid Steady in a long-term, the economical operation of controllable micro battery and customer charge, it usually needs Energy Management System is coordinated and managed.Mesh Before, micro-capacitance 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 wind-force, 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 micro-capacitance sensor, will also result in the micro battery economical operation plan of EMS formulation Validity decline, even jeopardizes the stable operation of micro-capacitance sensor when serious.With in micro-capacitance 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 non-firm power, further according to two layers of scheduling scheme of realtime power error correction operational plan, but those sides The determination of non-firm 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 short-term 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 micro-capacitance sensor operation bring adverse effect, to realize Reliable, the economical operation of independent micro-capacitance sensor.
In this regard, the technical solution adopted by the present invention are as follows:
A kind of independent energy management method for micro-grid considering stochastic prediction error, the independent micro-capacitance sensor includes wind-powered electricity generation- Photovoltaic-micro turbine-energy-storage battery comprising the Energy Management System EMS of micro-capacitance sensor uses following steps to be managed:
Step S1, Energy Management System EMS predict following a period of time internal loading and wind-powered electricity generation, photovoltaic power generation renewable energy Power;
The SOC state of step S2, EMS real-time monitoring energy-storage battery, the actual generation power of measurement wind-powered electricity generation, photovoltaic, measurement The actual power of micro turbine and energy-storage 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 energy-storage battery into Row arranges and adjustment, so that energy-storage 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;cTX is objective function;Ax=b is equation Constraint;Dx < d is inequality constraints;X is the codomain of variable;Wherein, A is micro-capacitance 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 micro-capacitance sensor voltage bus, then its corresponding positions Value is 1.If certain equipment or load are departing from micro-capacitance 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 energy-storage battery link, the charged capacity SOC limit of energy-storage battery The constraint matrix that system, micro turbine rate of power change limit, the matrix of value 0,1 value are attached to micro-capacitance 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 micro-capacitance 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 cTX includes the secondary cost function C of micro turbine power-fuelFuel, micro turbine start and stop cost function CStartShut And energy storage charge and discharge punishment cost function Cesspenalty, specifically:
In formula, i and IsetRespectively micro turbine index and index set, t and TsetRespectively runing time index and index Set.
Since the intermittence, fluctuation and randomness of the renewable energy such as wind-powered electricity generation, photovoltaic power generation power output are prominent, cause to predict Error is larger.The prediction error causes micro-capacitance 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 micro-capacitance sensor at interval of 3~5 minutes to micro-capacitance sensor can Control micro turbine and the power output of energy-storage 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 energy-storage battery Maintain higher extreme value SOCmaxWith low extreme value SOCminBetween.
As a further improvement of the present invention, in step S3, according to prediction error to micro turbine, energy storage link in micro-capacitance 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 micro-capacitance sensor user.
As net load stochastic prediction error≤ε, the prediction of microgrid energy management system EMS real-time monitoring net load is missed Difference, if error is in limits of error ε, and the practical SOC of energy-storage battery is also in the up/down limit value (SOC of energy-storage batteryhigh/SOClow) It is interior, then it runs according to original plan;If the practical SOC of energy-storage battery has crossed the up/down limit value of energy-storage battery, then to micro turbine with The power output of energy-storage battery is arranged and is adjusted, and updates plan.
As a further improvement of the present invention, as the practical SOC of energy-storage battery has crossed the up/down limit value of energy-storage battery, It is carried out using power output of the Rolling optimal strategy (CPLEX Rolling Optimization, CRO) to micro turbine and energy-storage battery It arranges and adjustment, the Rolling optimal strategy includes:
In moment tk, when the practical SOC of energy-storage battery crosses its lower limit SOClowOr upper limit SOChigh, EMS according to micro turbine, The current operating conditions information of energy-storage battery and net load are from tkTo the predicted value of T, IBM Corporation CPLEX derivation algorithm is called, it is right The operational plan of remaining period micro turbine, energy-storage battery is newly solved, and updates tkTo 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 pi[tk]、pess[tk] and micro turbine, energy storage current state vi[tk]、Eess[tk] 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 energy-storage battery also cross storage The up/down limit value SOC of energy batteryhigh/SOClowWhen, microgrid energy management system EMS controls micro turbine and energy-storage battery System is restored to the SOC of energy-storage battery in up/down limit range, energy-storage 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 energy-storage battery are controlled, the maintenance Stable Control Strategy includes:
As practical SOC≤SOC of energy-storage batterylow, EMS first detects the power flow direction of energy-storage battery and the switch of micro turbine Machine state, if the power of energy-storage battery is outflow and micro turbine MT shuts down, starting micro turbine at once is that energy-storage battery is filled Electricity;
If the power of energy-storage battery is outflow and micro turbine has been switched on, the power output for increasing micro turbine is filled to energy-storage battery Electricity;If net load is too big, micro turbine power output has reached its maximum valueAnd the charge power of energy-storage battery is still below its maximum value Pmax, then micro turbine power output is set as its rated powerThe charge power of energy-storage 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 energy-storage battery is inflow and micro turbine is shut down, energy storage is carried out using wind-powered 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 energy-storage battery;When micro turbine power output has reached its maximum value and the charge power of energy-storage 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 energy-storage batteryhigh, EMS detects the power flow direction of energy-storage battery first and micro turbine switchs Machine state, if the power flow direction of energy-storage battery is outflow, micro turbine and energy-storage battery continue that original operational plan is followed to instruct; If the power flow direction of energy-storage battery is inflow and micro turbine is switched on, EMS, which reduces micro turbine power output, makes the charge power of energy-storage battery Decline;If micro turbine power output has reached its minimumPi , and energy-storage battery is still charging, then cut-out renewable energy is abandoned Part renewable energy source power, makes energy-storage battery discharge;Whole renewable energy source power are abandoned if having cut off, but energy-storage battery is still It is charging, is then closing combustion engine;If energy-storage battery persistently charges and SOC is caused to cross storage in excision renewable energy power process The maximum permissible value SOC of energy batterymax, 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 long-term accumulation, which can lead to energy storage SOC at the unplanned moment, Work limit value, influences micro-capacitance sensor stable operation;Technical solution of the present invention overcomes load and renewable energy power prediction error Independent micro-capacitance 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 micro-capacitance sensor is realized.
Specifically, the present invention proposes under the small stochastic prediction error of net load, when the SOC of energy-storage battery transfinites, lead to Rolling optimization CRO strategy is crossed to make the micro-capacitance 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 micro-capacitance 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 micro-capacitance 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 micro-grid 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 energy-storage battery actual power operating status figure, c) be micro turbine actual power And the difference of operational plan, d) be the actual power of energy-storage battery and the difference of operational plan, e) be energy-storage 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 energy-storage battery actual power operating status figure, c) be micro turbine actual power And the difference of operational plan, d) be the actual power of energy-storage battery and the difference of operational plan, e) be energy-storage 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 micro-grid 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 (wind-powered electricity generation, photovoltaic) Prediction;
(2) it is optimized using CPLEX, specifies operational plan a few days ago, micro battery (micro turbine and energy-storage battery) is according to meter It rows row;
(3) the SOC state of EMS real-time monitoring energy-storage battery, the actual generation power of measurement wind-powered electricity generation, photovoltaic, measures micro- combustion The actual power of machine and energy-storage 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 micro-capacitance 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 real-time monitoring net load is missed Difference, if error is in limits of error ε, and the practical SOC of energy-storage battery is also in the up/down limit value (SOC of energy-storage batteryhigh/SOClow) It is interior, then it runs according to original plan;If the practical SOC of energy-storage battery has crossed the up/down limit value of energy-storage battery, using rolling optimization Tactful (CPLEX Rolling Optimization, CRO) is arranged and is adjusted to the power output of micro turbine and energy-storage battery, institute Stating Rolling optimal strategy CRO includes:
In moment tk, when the practical SOC of energy-storage battery crosses its lower limit SOClowOr upper limit SOChigh, EMS according to micro turbine, The current operating conditions information of energy-storage battery and net load are from tkTo the predicted value of T, IBM CPLEX derivation algorithm is called, to surplus The operational plan of remaining period micro turbine, energy-storage battery is newly solved, and updates tkTo T operational plan.IBM CPLEX is called to ask When resolving Algorithm solves, micro turbine, the currently practical power p of energy storage are usedi[tk]、pess[tk] and micro turbine, energy storage current state vi [tk]、Eess[tk] 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 energy-storage battery are controlled, the SOC of energy-storage 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 energy-storage batterylow, EMS first detects the power flow direction of energy-storage battery and the switch of micro turbine Machine state, if the power of energy-storage battery is outflow and micro turbine MT shuts down, starting micro turbine at once is that energy-storage 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 energy-storage battery is outflow and micro turbine has been switched on, the power output for increasing micro turbine is filled to energy-storage battery Electricity;If net load is too big, micro turbine power output has reached its maximum valueAnd the charge power of energy-storage battery is still below its maximum value Pmax, then micro turbine power output is set as its rated powerThe charge power of energy-storage 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 energy-storage battery is inflow and micro turbine is shut down, energy storage is carried out using wind-powered 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 energy-storage battery;When micro turbine power output has reached its maximum value and the charge power of energy-storage 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 energy-storage batteryhigh, EMS detects the power flow direction of energy-storage battery first and micro turbine switchs Machine state, if the power flow direction of energy-storage battery is outflow, micro turbine and energy-storage battery continue that original operational plan is followed to instruct; If the power flow direction of energy-storage battery is inflow and micro turbine is switched on, EMS, which reduces micro turbine power output, makes the charge power of energy-storage battery Decline;If micro turbine power output has reached its minimumPi , and energy-storage battery is still charging, then abandons part renewable energy by excision Source power makes energy-storage battery discharge;If having cut off whole renewable energy source power, but energy-storage battery is still charging, then combustion is closed Machine;If energy-storage battery persistently charges and SOC is caused to cross maximum permissible value SOC in excision renewable energy power processmax, 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 micro-capacitance sensor operation bring adverse effect, can with realize independent micro-capacitance 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 micro-capacitance sensor long-play stability.
Technical solution of the present invention is suitable for using wind-light-micro turbine-battery energy storage as the micro- electricity of the independent operating of main composition Net.The Energy Management System EMS of micro-capacitance 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 micro-capacitance 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;cTX 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 mixed-integer 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 micro-capacitance sensor includes the secondary cost function C of micro turbine power-fuelFuel, micro turbine start and stop Cost function CStartShutAnd energy storage charge and discharge punishment cost function Cesspenalty, specifically:
In formula, i and IsetRespectively micro turbine index and index set, t and TsetRespectively runing time index and index Set.
In constraint condition, the sum of micro turbine and energy storage power in this micro-capacitance sensor want the moment to be equal to net load power, come Meet the requirement of power-balance 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 charge-discharge electric power, charge and discharge conversion frequency and depth of discharge, storage Energy link normal operation needs to meet: (1) charge-discharge 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 high-low 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 wind-powered 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 wind-powered electricity generation, photovoltaic power generation, load misses This poor stochastic variable Normal Distribution, specifically:
In formula, pθ[t] and pθ *[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, μθ[t] and δθ[t] is respectively pθ[t] is in moment t mathematic expectaion and variance, TsetWhen to predict The set at quarter has T element, pθ *[t]=μθ[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 σθ[t],+3σθ[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 (- 3σθ[t],+3σθ[t]) within the limits of error.
Random error in the present invention between micro-grid 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, pload *[t] is load in moment t short-term forecast value.
It is 0 just that random error between wind-power electricity generation, the practical power output of photovoltaic power generation and short-term forecast power output, which is set as mean value, State distribution, standard deviation calculate specifically:
In formula, pθrateFor photovoltaic, blower installed capacity, pθ *[t] is photovoltaic, blower in moment t short-term forecast value.
The net load power of micro-capacitance sensor is the difference of load power and renewable energy power generation power, formula specifically:
The random error variable p of net load powernet[t]-pnet *[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 pθ[t]-pθ *[t] has identical coefficient of variation C [t], specifically:
In formula, K is constant;Then it can obtain:
σload[t]+σsolar[t]+σwind[t]=K2pload *[t]+K2psolar *[t]+K2pwind *[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 pnet[t]-pnet *[t] is also that T ties up random vector on the whole, specifically:
Pnet=(Pnet[t1],...,Pnet[tk],...,Pnet[tT])=(pnet[t1]-pnet *[t1],...,pnet[tk]- pnet *[tk],...,pnet[tT]-pnet *[tT])
If stochastic variable pnet[t]-pnet *[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 loadnetSpecifically:
μnet=(μnet[t1],...,μnet[tk],...,μnet[tT])
EnetFor PnetT member normal distribution error of covariance matrix, and EnetReal symmetric tridiagonal matrices, tool are tieed up for T × T Body are as follows:
In formula, Cov (Pnet[ti],Pnet[tj ]) it is Pnet[t] is in moment tiAnd tjBetween covariance.ρijFor 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 micro-capacitance sensor runs a few days ago The set point of plan.Micro-capacitance 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 discrete-time series of following a period of time It draws.
It is run in micro-capacitance sensor and in the works, net load and micro battery, energy storage link keeps power-balance relationship, specifically Are as follows:
In formula, pi *[t] is i-th micro turbine moment t power;pess *[t] is power of the energy storage in moment t.
The state-of-charge of energy storage link then determines by the integral of energy storage power, specifically:
Eess *[t]=Eess *[t-1]-η(pess *[t-1])·pess *[t-1]
In formula, Eess *[t] is the SOC of energy storage;η is sign function.
In each t ∈ TsetThe 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 loadnetIt is transmitted to the T member operational plan vector P of micro turbine and energy storagei *With Pess *In.The net load T member predicted value vector that microgrid EMS model uses specifically:
Pnet *=(pnet *[t1],...,pnet *[tk],...,pnet *[tT])
After Optimization Solution EMS model, it is assumed that by Pnet *Coefficient matrices A is tieed up by i-th of T × TiObtain i-th micro turbine T member operational plan vector Pi *, and matrix number B is maintained by a T × T and obtains the T member operational plan vector P of energy storageess *, tool Body are as follows:
Pess *=BPnet *
Micro turbine set IsetIn i-th micro turbine T member operational plan vector Pi *With energy storage T member operational plan vector Pess *Specifically:
Pess *=(pess *[t1],...,pess *[tk],...,pess *[tT])
In PnetIn random error pass through AiIt is transmitted to P respectively with Bi *And Pess *In.Wherein Pi *And Pess *Corresponding T × T Tie up error of covariance matrix specifically:
Epess=BEnet·BT
The value of storage energy operation power set point is according to Pess *Setting, since energy storage actual motion point and set point be not in operation Unanimously, in random error by PnetIt is transmitted to Pess *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 (pess *[t], pess*[l]) it is respectively Pess *T × T tie up error of covariance matrix Epess'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 micro-capacitance 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/over-discharge 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 micro-capacitance 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 short-term 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 σθ[t],+3σθ[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 real-time 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 (SOChigh/SOClow) 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:
Eess *[tk]≤SOClow OR Eess *[tk]≥SOChigh
In moment tkThe practical SOC of energy storage crosses its lower limit SOClowOr upper limit SOChigh, EMS is according to micro turbine, energy storage link Current operating conditions information and net load are from tkTo 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 tkTo T operational plan.Due in EMS to energy storage link overshoot/over-discharge 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 storagei[tk]、pess[tk] and state vi[tk]、Eess[tk] 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 power-balance 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 real-time detection net load is pre- Survey error, such as tkMoment 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:
Eess *[tk]≤SOClow OR Eess *[tk]≥SOChigh
When KSO is controlled, micro turbine in micro-capacitance sensor, energy storage link main control flow be described below:
1)SOC≤SOClowEnergy storage electricity is insufficient at this time, to avoid energy storage over-discharge, need to limit electric discharge, fill as early as possible to energy storage Electricity.EMS system first detects the on-off state of energy storage power flow direction and micro turbine MT.If energy storage power is outflow (pessIt 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 micro-capacitance 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 Pmax, 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 possiblehigh
2)SOC≥SOChighShow 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 on-off 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 Pi, and energy storage is still being charged, then cut-out renewable energy PRESAbandon 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 processmax, then directly close Close micro turbine and renewable energy.KSO maintains stable strategy timing diagram as shown in Figure 5.
Energy storage SOC out-of-limit 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 micro-capacitance 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 micro-capacitance 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 storagemaxWith low extreme value SOCmin 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 micro-capacitance 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 SOCmaxWith low extreme value SOCminBetween.
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 micro-grid for considering stochastic prediction error, it is characterised in that: the independent micro-capacitance sensor Including wind-powered electricity generation-photovoltaic-micro turbine-energy-storage 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 wind-powered electricity generation, photovoltaic renewable energy;
The SOC state of step S2, EMS real-time monitoring energy-storage battery, the actual generation power of measurement wind-powered electricity generation, photovoltaic, measures micro- combustion The actual power of machine and energy-storage 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 energy-storage battery by the Mathematics Optimization Method of multivariable, multiple constraint Row and adjustment, so that energy-storage 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;cTX is objective function;Ax=b is equality constraint; Dx < d is inequality constraints;X is the codomain of variable;Wherein, A is micro-capacitance 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 energy-storage battery link The constraint matrix of rate limitation, the charged capacity SOC limitation of energy-storage 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 micro-grid according to claim 1 for considering stochastic prediction error, it is characterised in that: Objective function cTX includes the secondary cost function C of micro turbine power-fuelFuel, micro turbine start and stop cost function CStartShutAnd storage It can charge and discharge punishment cost function Cesspenalty, specifically:
In formula, i and IsetRespectively micro turbine index and index set, t and TsetRespectively runing time index and index set.
3. the independent energy management method for micro-grid according to claim 1 for considering stochastic prediction error, it is characterised in that: The energy management of independent micro-capacitance sensor adjusted the controllable micro turbine of micro-capacitance sensor and the power output of energy-storage battery at interval of 3~5 minutes Whole and arrangement.
4. the independent energy management method for micro-grid 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 energy-storage battery is made to maintain the upper pole of energy-storage battery in step S3 Between limit value and low extreme value.
5. the independent energy management method for micro-grid 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 micro-capacitance 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 real-time monitoring net load, If error is in limits of error ε, and the practical SOC of energy-storage battery is also in up/down limit value, that is, SOC of energy-storage batteryhigh/SOClowIt is interior, Then run according to original plan;If the practical SOC of energy-storage battery has crossed the up/down limit value of energy-storage 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 micro-grid according to claim 5 for considering stochastic prediction error, it is characterised in that: If the practical SOC of energy-storage battery has crossed the up/down limit value of energy-storage 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 tk, when the practical SOC of energy-storage battery crosses its lower limit value or upper limit value, EMS is according to micro turbine, energy-storage battery Current operating conditions information and net load are from tkTo 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 tkTo T operational plan.
7. the independent energy management method for micro-grid 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 usedi[tk]、pess[tk]With micro turbine, Energy storage current state vi[tk]、Eess[tk] 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 micro-grid 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 energy-storage battery also cross the up/down limit value SOC of energy-storage batteryhigh/SOClow When, microgrid energy management system EMS controls micro turbine and energy-storage battery, is preferentially restored to the SOC of energy-storage battery Up/down limits in range, and energy-storage battery is maintained to operate normally.
9. the independent energy management method for micro-grid according to claim 8 for considering stochastic prediction error, it is characterised in that: Using maintaining Stable Control Strategy to control micro turbine and energy-storage battery, the maintenance Stable Control Strategy includes: when storage Practical SOC≤SOC of energy batterylow, EMS first detects the power flow direction of energy-storage battery and the on-off 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 energy-storage battery charges at once;
If the power of energy-storage battery is outflow and micro turbine has been switched on, the power output for increasing micro turbine charges to energy-storage battery;Such as Fruit net load is too big, and micro turbine power output has reached its maximum value and the charge power of energy-storage 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 energy-storage 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 energy-storage battery be flow into and micro turbine shut down, using include wind-powered 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 energy-storage battery;When micro turbine power output has reached its maximum value and the charge power of energy-storage 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 energy-storage batteryhigh, EMS detects the power flow direction and micro turbine switching on and shutting down shape of energy-storage battery first State, if the power flow direction of energy-storage battery is outflow, micro turbine and energy-storage 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 energy-storage battery; If micro turbine power output has reached its minimum, and energy-storage battery is still charging, then abandons portion by cut-out renewable energy Divide renewable energy source power, energy-storage battery is made to discharge;If having cut off whole renewable energy, but energy-storage battery is still charging, then Close combustion engine;If energy-storage battery persistently charges and SOC is caused to cross energy-storage battery most in excision renewable energy power process Big permissible value SOCmax, then directly close micro turbine and cut off all renewable energy.
10. the independent energy management method for micro-grid 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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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110034570A (en) * 2019-05-16 2019-07-19 阳光电源股份有限公司 Control method, device and the photovoltaic plant of energy storage device
CN110261673A (en) * 2019-05-14 2019-09-20 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
WO2020219078A1 (en) * 2019-04-26 2020-10-29 Pason Power, Inc. Intelligent energy management system for distributed energy resources and energy storage systems using machine learning
WO2021103357A1 (en) * 2019-11-28 2021-06-03 山东理工大学 Power distribution network mobile energy storage configuration method based on fourier-legendre series

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020219078A1 (en) * 2019-04-26 2020-10-29 Pason Power, Inc. Intelligent energy management system for distributed energy resources and energy storage systems using machine learning
CN110261673A (en) * 2019-05-14 2019-09-20 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
CN110034570A (en) * 2019-05-16 2019-07-19 阳光电源股份有限公司 Control method, device and the photovoltaic plant of energy storage device
WO2021103357A1 (en) * 2019-11-28 2021-06-03 山东理工大学 Power distribution network mobile energy storage configuration method based on fourier-legendre series

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