CN107392395A - A kind of power distribution network and micro electric network coordination optimization method based on price competition mechanism - Google Patents
A kind of power distribution network and micro electric network coordination optimization method based on price competition mechanism Download PDFInfo
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The present invention relates to a kind of power distribution network based on price competition mechanism and micro electric network coordination optimization method, power distribution network and micro-capacitance sensor interaction mechanism are established：Each micro-capacitance sensor is using the exchange power of day part in final trading scheme and power distribution network as known parameters, optimization obtains coordinated scheduling scheme, and this interaction mechanism includes economic load dispatching optimization and power distribution network optimization based on micro-capacitance sensor scheduling result of the micro-capacitance sensor based on electricity price a few days ago；In terms of micro-capacitance sensor economic load dispatching optimization：The linear economy scheduling model of micro-capacitance sensor is established, for nonlinear terms therein, is handled using linearization technique, 0/1 variable and each equipment power output continuous variable are included in model, turns into Mixed integer linear programming.In terms of power distribution network micro-capacitance sensor optimizing scheduling：The operating cost of power distribution network under current day-ahead power market electricity price is obtained according to each micro-capacitance sensor economic dispatch program result, the day-ahead power market electricity price of power distribution network and each micro-capacitance sensor is optimized, obtains the minimum pricing scheme of power distribution network operating cost.
Description
Technical field
The present invention relates to a kind of power distribution network and micro electric network coordination optimization method, belongs to active distribution network Optimized Operation field.
Background technology
Along with increasingly exhausted and problem of environmental pollution the increasingly exacerbation of traditional fossil energy, renewable energy is developed
Source, realize that economic sustainable development turns into the common recognition of national governments.It is micro- as the effective carrier for efficiently utilizing regenerative resource
Electric power network technique has obtained development energetically in recent years.It is contemplated that along with micro-capacitance sensor technology maturation and application it is extensive, by
Multiple integrated active distribution networks formed of interconnection micro-capacitance sensor are by as the important component of following intelligent grid.Therefore, how
The coordinated operation between multiple micro-capacitance sensors and power distribution network is realized, play more micro-grid systems turns into newly in the advantage that the energy is mutually filled
Study hotspot.For this problem, the challenge of two aspects is primarily present：1) micro-capacitance sensor is faced with many not true in the process of running
Qualitatively influence, such as the renewable distributed power source such as photovoltaic, blower fan is contributed, local load power and market are real-time in micro-capacitance sensor
Electricity price etc., these uncertain factors bring challenge, it is necessary to reasonable in design, effective energy management side to the operation of micro-capacitance sensor
Method, realize the economical operation of micro-capacitance sensor under uncertain environment；2) power distribution network and micro-capacitance sensor adhere to different Interest Main Bodies separately, are running
During both be intended to maximize the interests of itself, it is therefore desirable to market mechanism reasonable in design, ensure the flat of each side income
Weighing apparatus.In addition, power distribution network needs to carry out rationally effective management to accessing micro-capacitance sensor therein, it is ensured that each node voltage of system, branch
Road power etc. is in the range of security constraint.
For the economic load dispatching method of micro-capacitance sensor under uncertain environment, method using based on scene main at present and random
Planing method.Wherein, performance of the method based on scene using typical scene to alternatives, such as economy are carried out
Assess, final scheme needs have preferable performance under each scene；Stochastic programming method is then based on the general of each scene
Rate obtains the performance desired value of alternative, so as to be screened, determines preferred plan.Either the method based on scene is still
Stochastic programming method, both keys are all to generate typical scene to describe the uncertain information in micro-capacitance sensor, therefore
The performance of scheme depends on the selection of scene, is primarily present following problem：
1) in micro-capacitance sensor actual motion, the probability of the uncertain variables such as load power and renewable distributed power source output
Curve is difficult accurately to obtain, and causes final model not accurate enough；
2) uncertain variables information is described using substantial amounts of scene, needs to utilize scene reduction technology before calculating
Scene is reasonably screened so that algorithm complex improves, and amount of calculation increases.
On the other hand, for the coordination optimization problem of power distribution network and micro-capacitance sensor, in current research or it have ignored distribution
The trend distribution of net, the out-of-limit problem of trend caused by the Power Exchange possibility between micro-capacitance sensor and power distribution network is not considered；Or neglect
The uncertainty in micro-capacitance sensor has been omited, the economic load dispatching of micro-capacitance sensor is considered with deterministic models.
The content of the invention
In view of the above-mentioned problems, the purpose of the present invention is overcome the deficiencies in the prior art, it is actual with reference to power distribution network and micro-capacitance sensor
The needs of operation, there is provided a kind of power distribution network and micro electric network coordination optimization method, the present invention have been considered micro- based on price incentive
The uncertainty of operation of power networks and the safe operation of power distribution network constrain, and can realize that the coordination optimization of power distribution network and micro-capacitance sensor is adjusted
Degree.Technical scheme is as follows
1. a kind of power distribution network and micro electric network coordination optimization method based on price competition mechanism, it is characterised in that
(1) power distribution network and micro-capacitance sensor interaction mechanism framework are as follows：
1) power distribution network announces the bilateral transaction electricity price with each micro-capacitance sensor；
2) each micro-capacitance sensor, according to the risk tolerance of itself, is chosen suitable robust and adjusted after electricity price a few days ago is received
Parameter area is saved, prediction and corresponding prediction deviation based on renewable distributed power source output and non-resilient load power, really
Fixed optimal economic dispatch program, and report the exchange power bound with power distribution network day part；
3) power distribution network control centre is submitted according to each micro-capacitance sensor trading scheme, the information on load of itself and system electricity
Pressure, trend constraint etc., are optimized to system load flow, obtain the minimum purchase sale of electricity scheme of active power loss, afterwards according to higher level's electricity
The electricity price of net and the result of tide optimization, with the bilateral electricity price of the minimum target update of operating cost and each micro-capacitance sensor；
4) return to step 1), until power distribution network determines final electricity price a few days ago and trading scheme；
5) each micro-capacitance sensor optimizes using the exchange power of day part in final trading scheme and power distribution network as known parameters
To the coordinated scheduling scheme of miniature gas turbine, energy storage and demand response load, this interaction mechanism includes micro-capacitance sensor and is based on a few days ago
The economic load dispatching optimization and optimization of the power distribution network based on micro-capacitance sensor scheduling result of electricity price；
(2) in terms of micro-capacitance sensor is based on the economic load dispatching optimization of electricity price a few days ago：By the fortune for analyzing each equipment in micro-capacitance sensor
Row characteristic and operation constrain, and the linear economy scheduling model of micro-capacitance sensor are established, for nonlinear terms therein, using linearisation side
Method is handled, and 0/1 variable and each equipment power output continuous variable are included in model, MILP is established and asks
Topic；For further consider micro-capacitance sensor in stochastic variable wave characteristic influence, using it is uncertain collection describe uncertain variables with
Machine characteristic, stochastic variable has an opportunity to get the uncertain arbitrary value concentrated in optimization process；Determined with reference to robust optimization the worst
The essence of optimal scheduling scheme under scene, micro-capacitance sensor two benches Robust Optimization Model is built, to 0/1 variable and continuous variable sublevel
Section solves, while finds the most severe Run-time scenario faced in the given uncertain collection of micro-capacitance sensor by optimization means, final to obtain
Economic dispatch program optimal under day-ahead power market electricity price is given to power distribution network.
(3) in optimization of the power distribution network based on micro-capacitance sensor scheduling result：According to each micro-capacitance sensor economic dispatch program result, with reference to
The operation constraint of itself, including node voltage constraint and branch power constraint, determine the minimum scheduling scheme of active power network loss,
And then the operating cost of power distribution network under current day-ahead power market electricity price is obtained, afterwards by genetic algorithm to power distribution network and each micro-capacitance sensor
Day-ahead power market electricity price optimize, obtain the minimum pricing scheme of power distribution network operating cost.
The present invention substantive distinguishing features be：Bottom optimization with the minimum target of micro-capacitance sensor operating cost, each micro-capacitance sensor according to
The a few days ago bilateral electricity price and the risk tolerance of itself that power distribution network is announced, are not known using two benches robust Optimal methods
The economic dispatch program of micro-capacitance sensor under environment；In the optimization of upper strata, trading scheme and system that power distribution network is submitted according to each micro-capacitance sensor
Voltage, trend constraint etc., obtain the minimum scheduling scheme of system losses, while by the transaction of price incentive adjustment micro-capacitance sensor
Strategy, and the scheme to that may cause system congestion is adjusted, and finally gives the minimum bilateral transaction electricity price of operating cost.
Consider probabilistic in micro-capacitance sensor meanwhile, it is capable to ensure that the trading scheme of micro-capacitance sensor and power distribution network does not cause the trend of power distribution network
It is out-of-limit, meet the safe operation constraint of power distribution network, realize the coordination optimization operation of power distribution network and micro-capacitance sensor.The present invention is due to taking
Above technical scheme, compared with prior art with advantages below：
(1) using the Economic Dispatch Problem of two benches robust Optimal methods processing micro-capacitance sensor, may be applicable to become to 0/1
While amount and continuous variable optimize, the application scenarios for the most harsh conditions that the system of determination may face.
(2) interaction mechanism of power distribution network and micro-capacitance sensor is devised, can be real while power distribution network and micro-capacitance sensor interests is taken into account
The safety and economic operation of existing power distribution network.
Brief description of the drawings
Fig. 1 is the power distribution network and micro-capacitance sensor interaction mechanism that the present invention applies.
Fig. 2 is that the double-deck dispatching method that the present invention applies solves structure.
Fig. 3 is the load and photovoltaic prediction power curve of the embodiment of the present invention.
Fig. 4 is the voltage curve of the embodiment of the present invention.
Fig. 5 is the miniature gas turbine power output and energy storage charge-discharge electric power of the embodiment of the present invention.
Fig. 6 is the demand response load scheduling power of the embodiment of the present invention and it is expected power.
Table 1 is the micro-capacitance sensor operational factor of the embodiment of the present invention.
Table 2 is that the micro-capacitance sensor of the embodiment of the present invention does not know adjustment parameter scope.
Table 3 is the optimum results of the embodiment of the present invention.
Embodiment
The present invention is described in detail with reference to the accompanying drawings and examples.
Power distribution network and micro-capacitance sensor interaction mechanism framework designed by the present invention is as shown in Figure 1.Interactive flow is as follows：
1) power distribution network announces the bilateral transaction electricity price with each micro-capacitance sensor；
2) each micro-capacitance sensor, according to the risk tolerance of itself, is chosen suitable robust and adjusted after electricity price a few days ago is received
Parameter area is saved, prediction and corresponding prediction deviation based on renewable distributed power source output and non-resilient load power, really
Fixed optimal economic dispatch program, and report the exchange power bound with power distribution network day part；
3) power distribution network control centre is submitted according to each micro-capacitance sensor trading scheme, the information on load of itself and system electricity
Pressure, trend constraint etc., are optimized to system load flow, obtain the minimum purchase sale of electricity scheme of active power loss, afterwards according to higher level's electricity
The electricity price of net and the result of tide optimization, with the bilateral electricity price of the minimum target update of operating cost and each micro-capacitance sensor；
4) return to step 1), until power distribution network determines final electricity price a few days ago and trading scheme；
5) each micro-capacitance sensor optimizes using the exchange power of day part in final trading scheme and power distribution network as known parameters
To the coordinated scheduling scheme of miniature gas turbine, energy storage and demand response load.
Two optimization process are contained in above-mentioned interactive flow：Economic load dispatching of the micro-capacitance sensor based on electricity price a few days ago optimizes and matched somebody with somebody
Optimization of the power network based on micro-capacitance sensor scheduling result.Modeling below for two optimization problems carries out necessary elaboration.
In micro-capacitance sensor comprising controlled distribution formula power supply, renewable distributed power source, energy storage, demand response load and local often
Advise load.Wherein, controlled distribution formula power supply is thought of as miniature gas turbine, and its cost function is represented by：
CG(t)=(aPG(t)+b)Δt (1)
In formula, CG(t) expression miniature gas turbine is cost coefficient in the cost of electricity-generating of t periods, a, b；PG(t) it is the t periods
The power output of miniature gas turbine；Δ t is to dispatch step-length, value 1h.The constraints of consideration constrains for power output：
Wherein,WithRepresent the maximum/minimum power output of miniature gas turbine.
To the energy-storage units in micro-capacitance sensor, its cost function is：
Wherein, KSFor the unit discharge and recharge cost after conversion；WithThe exchange of t periods energy storage inverter is represented respectively
The charge/discharge power of side input/output；η is the efficiency for charge-discharge of energy-storage units.For realize micro-capacitance sensor to energy storage it is long-term,
Round-robin scheduling, energy storage need to meet following operation constraint：
Formula (4) and formula (5) are respectively the charging and discharging power constraint of energy storage,The maximum discharge and recharge allowed for energy storage
Power, mainly by the capacity limit of energy storage parallel network reverse device.US(t) charging and discharging state of energy storage is represented, value represents when being 1
Electric discharge, charging is represented when value is 0；Formula (6) ensure that energy storage is equal in the whole story moment capacity of scheduling, be advantageous to following for energy storage
Ring is dispatched, NTFor dispatching cycle, value 24h；Formula (7) represents the residual capacity constraint of energy storage day part, ES(0) exist for energy storage
The capacity of initial time is dispatched,WithThe maximum/minimum residual capacity allowed for energy storage in scheduling process.
For the demand response load in micro-capacitance sensor, it is believed that it is steady state value in intraday total electric power, but each
The electric power of period can be adjusted within the specific limits, can be used to lower constraint representation：
Wherein, PDR(t) for t periods micro-capacitance sensor to the actual schedule power of demand response load, DDRFor demand response load
Total power demand within dispatching cycle.WithFor demand response load the t periods maximum/minimum power demand.
Micro-capacitance sensor require demand response load service process is provided needed for the scheduling cost paid be：
Wherein, KDRCost is dispatched for the unit of demand response load；Used for the expectation of t period demand response loads
Electrical power.Absolute value term in formula (10) is used to represent actual schedule power and it is expected the deviation between electric power, by drawing
Enter auxiliary variable PDR1(t)、PDR2(t) and (12), (13) are constrained, the linear forms shown in formula (11) can be turned to：
CDR(t)=KDR(PDR1(t)+PDR2(t))Δt (11)
PDR1(t)≥0,PDR2(t)≥0 (13)
When each generator unit can not meet workload demand in micro-capacitance sensor, it is necessary to power distribution network power purchase；Conversely, micro-capacitance sensor can
Electric energy more than needed is sold to power distribution network, obtains income.Interaction power between micro-capacitance sensor and power distribution network need to meet to balance as follows
Constraint：
Wherein,The power that respectively t periods micro-capacitance sensor is bought and sold to power distribution network；PL(t)、PRES(t)
Respectively the conventional load power in t period micro-capacitance sensors and renewable distributed power source output power.Micro-capacitance sensor and power distribution network
Exchanging power should meet：
Wherein,Represent that micro-capacitance sensor and power distribution network exchange the maximum of power.UM(t) it is purchase of the micro-capacitance sensor to power distribution network
Sale of electricity state, represent that micro-capacitance sensor to power distribution network power purchase, represents micro-capacitance sensor to power distribution network sale of electricity when value is 0 when value is 1.In t
The interaction cost C of period, micro-capacitance sensor and power distribution networkM(t) it is represented by：
With reference to above-mentioned model, the object function that can obtain micro-capacitance sensor economic load dispatching model is：
The uncertainty that renewable distributed power source is contributed with conventional load power in micro-capacitance sensor is further considered, with formula
(19) stochastic behaviour of both uncertain set representations shown in：
Wherein, uRESAnd u (t)L(t) the renewable distributed power source introduced for consideration after uncertain is contributed and load work(
Rate uncertain variables；WithThe maximum fluctuation that respectively renewable distributed power source is contributed and load power allows
Deviation, it is both positive number.The prediction that t periods renewable distributed power source is contributed with load power is represented respectively
Value.
After introducing uncertain collection, the two benches Robust Optimization Model that can obtain micro-capacitance sensor is as follows：
Wherein, outer layer is minimised as first stage problem, optimized variable x, binary variable is represented, such as energy storage charge and discharge
Electricity condition and micro-capacitance sensor purchase sale of electricity state；The minimax of internal layer turns to second stage problem, and optimized variable is u and y.Ω(x,
Optimized variable y feasible zone, expression are as follows when u) representing to give one group (x, u)：
Wherein, dual variable corresponding to each constraint in the minimization problem of γ, λ, ν, π expression second stage.
For each group of given uncertain variables u, formula (20) can abbreviation be deterministic optimization model, it is and of the invention
The purpose of max structures, which is that to find, in constructed two benches robust Model second stage optimization problem causes operating cost most
Big most severe scene.
After above-mentioned model is obtained, column vector constraint generating algorithm can be used to be solved.Wherein, by after former PROBLEM DECOMPOSITION
Obtained primal problem form is：
Wherein, k is current iterations；ylFor the solution of subproblem after the l times iteration；For what is obtained after the l times iteration
Uncertain variables u value under most severe scene.
Subproblem form after decomposition is：
By linear duality theory, above formula can be converted into corresponding dual problem：
In the present invention, renewable distributed power source output gets the minimum value in section and load power gets section most
During big value, the operating cost of micro-capacitance sensor is higher, more meets the definition of " most severe " scene, therefore can be rewritten into formula (19) as follows
Form：
Wherein, B=(BRES(t),BL(t))TFor binary variable, value is that 1 phase answers the uncertain variables of period to take
To the border in section.ΓRESAnd ΓLRespectively present invention introduces renewable distributed power source contribute and load power " robust
Adjustment parameter ", available for the conservative of regulation optimal solution, the scheme that value obtains more greatly is more conservative, conversely, scheme then more emits
Danger.Its physical meaning is：Renewable distributed power source is contributed within dispatching cycle and load power is got described by formula (25)
The minimum value of waving interval or the period sum of maximum.Finally, formula (25) is substituted into (24), can obtained：
B '=(B'RES(t),B'L(t))TFor the continuous auxiliary variable of introducing,For the upper bound of dual variable, can be taken as enough
Big arithmetic number.
By above-mentioned derivation and conversion, finally decoupling is the examination in chief with MIXED INTEGER linear forms to two benches robust Model
Topic formula (22) and subproblem formula (26), primal problem and subproblem can be handed over using MILP method afterwards
For iterative.
For the Optimal Scheduling of power distribution network, its operating cost is included to micro-capacitance sensor power purchase and superior power network power purchase
Cost, income then come from the income to micro-capacitance sensor sale of electricity and superior power network sale of electricity, and its object function is represented by：
Wherein, the first row of formula (27) represents the power distribution network purchase sale of electricity cost of one day；Second system of behavior trend is out-of-limit
Penalty term.In above-mentioned optimization problem, optimized variable is power distribution network and micro-capacitance sensor m bilateral electricity price.In order to more rational simultaneous
The interests of power distribution network and micro-capacitance sensor are cared for, the bound of setting power distribution network day part electricity price is constrained to：
Power distribution network can pass through in the exchange power of day part and micro-capacitance sensor m exchange power and power distribution network and higher level's power network
Tide optimization model shown in solution formula (29)-(36) obtains：
Vmin≤Vi≤Vmax i∈N (32)
Wherein, formula (29) represents that the target of tide optimization problem is minimum for the active power loss of system, Ploss(t) distribution is represented
The active power loss of net；Formula (30)-formula (31) be distribution system power flow equation, PDiAnd QDiRespectively represent node i at it is active and
Load or burden without work.PGiAnd QGiThe active and reactive power of generator unit output at node i is represented respectively.GijAnd BijRespectively node i
Conductance and susceptance between node j；Formula (32)-formula (36) represents the constraint of node i voltage bound, circuit l trends about respectively
Beam, power distribution network purchase the power constraint of sale of electricity to the power constraint and power distribution network superior power network of micro-capacitance sensor m sales of electricity and power purchase.Its
In, VmaxAnd VminRepresent the upper voltage limit and lower limit of node i；Pl maxRepresent the branch road l transimission power upper limit.
The bound of optimized variable, which is constrained to each micro-capacitance sensor and reported to, in tide optimization problem, in formula (34) and formula (35) matches somebody with somebody
The interactive information of grid dispatching center, its economic load dispatching model is solved by micro-capacitance sensor and obtained.Trend shown in formula (29)-(36) is excellent
Change the nonlinear optimal problem that model is belt restraining, can be solved using tracking center track interior point method.Asked in tide optimization
After topic solves, the voltage and branch power of each node of power distribution network can be obtained, and then can join as the input of optimization problem (27)
It is several that the problem is solved.
Double-deck dispatching method structure proposed by the invention is as shown in Figure 2.Bottom optimizes the economy for realizing micro-capacitance sensor
Scheduling, by foregoing two benches Robust Optimization Model and corresponding model inference, can use MILP method
Solved；Upper strata optimizes the formulation for realizing the optimal electricity price a few days ago of power distribution network, optimizes two comprising tide optimization and electricity price
Part, wherein tide optimization solve to obtain the exchange for exchanging power and higher level's power network of power distribution network and each micro-capacitance sensor using interior point method
Power, electricity price optimization are selected, intersected and made a variation using genetic algorithm, and it is minimum a few days ago to finally give power distribution network operating cost
Pricing.
The present invention combines Fig. 3 to Fig. 6 and table 1 to table 3 to being proposed the power distribution network based on price competition mechanism and micro- electricity
The embodiment of net coordination optimizing method is introduced.The present invention is by taking distribution net work structure shown in Fig. 1 as an example, to power distribution network and micro-capacitance sensor
Coordination optimizing method is verified.Three micro-capacitance sensors are connected to respectively in node 12,24 and 30.Fig. 3 show the negative of each micro-capacitance sensor
Lotus and renewable distributed power source are contributed.Wherein, renewable distributed power source is photovoltaic in micro-capacitance sensor 1 and micro-capacitance sensor 2, micro-capacitance sensor
Renewable distributed power source is blower fan in 3.Dash area is the load power that considers in the embodiment of the present invention and can be again in Fig. 3
The fluctuation deviation that the uncertain collection that raw distributed power source is contributed, load power and renewable distributed power source are contributed is respectively to predict
The 10% and 15% of value.The operational factor of micro-capacitance sensor, such as miniature gas turbine unit cost of electricity-generating, energy storing and electricity generating cost such as table
Shown in 1.The robust adjustment parameter scope of each micro-capacitance sensor is as shown in table 2, and value is bigger to represent that corresponding scheme is more conservative.Emulated
Cheng Zhong, the rated capacity of energy storage are set to 2MWh.It is corresponding that the upper and lower bound of power distribution network electricity price a few days ago is respectively set as higher level's power network
1.2 times of period electricity price and 0.8 times, the voltage magnitude of each node need to be limited in the range of 0.95p.u.-1.05p.u..
Table 3 show power distribution network and the simulation result of micro electric network coordination optimization, and the 2nd is classified as the node limit electricity of higher level's power network
Valency；3-6 row, 7-10 row and 11-14 row are respectively micro-capacitance sensor 1, micro-capacitance sensor 2 and the final pricing of micro-capacitance sensor 3, handed over
Change the upper limit of the power, exchange the lower limit of the power and conclusion of the business power, micro-capacitance sensor is represented to power distribution network sale of electricity, negative value on the occasion of expression micro-capacitance sensor
To power distribution network power purchase.Last is classified as the exchange power of power distribution network and higher level's power network, on the occasion of expression power distribution network superior power network purchase
Electricity, on the contrary represent power distribution network superior power network sale of electricity.As can be seen from Table 3：
1) in the exchange upper limit of the power and lower range that micro-capacitance sensor is submitted, power distribution network can optimize to obtain loss minimization,
And meet voltage, the scheduling scheme of trend constraint.For example, in 11h, 13h and 19h, to prevent the voltage of node 12 from exceeding the upper limit, match somebody with somebody
Power network is below the upper limit of the power of the submission of micro-capacitance sensor 1 to the schedule power of micro-capacitance sensor 1.Fig. 4 is shown in the embodiment of the present invention respectively
The voltage max and minimum value of period all nodes, it can be seen that system voltage meets given safe operation constraint all the time；
2) in 1h-7h and 24h there is power shortage, it is necessary to power distribution network power purchase in micro-capacitance sensor 1 and micro-capacitance sensor 2.Now, match somebody with somebody
The electricity price of power network is the maximum allowed, passes through electricity of being merchandised between higher level's power network electricity price and the micro-capacitance sensor 2 of power distribution network and micro-capacitance sensor 1/
The price difference of valency, power distribution network can obtain income.In remaining period, micro-capacitance sensor 1 and micro-capacitance sensor 2 (except 22h) are to power distribution network sale of electricity.
Now, except 19h-21h, power distribution network is with the price less than higher level's power network from micro-capacitance sensor 1 and the power purchase of micro-capacitance sensor 2.In 19h-21h,
Power distribution network is ready with the price higher than higher level's power network that from micro-capacitance sensor 1 and the power purchase of micro-capacitance sensor 2 reason is by higher price,
Micro-capacitance sensor segment call energy storage at these can be encouraged to discharge.For on the whole, power distribution network can be roused by this price incentive
Encourage micro-capacitance sensor scheduling energy storage and carry out peak load shifting, reduce the operating cost of itself.
3) it is 69kW to the power purchase power of power distribution network in 22h, micro-capacitance sensor 2, power distribution network can be increased by improving price in theory
Add sale of electricity income.However, in the sale of electricity electricity price Jin Wei $1.35/kWh of the period power distribution network, its reason is that the raising of price will
The scheduling that micro-capacitance sensor 2 responds load to its internal demands is influenceed, so as to change the exchange power of micro-capacitance sensor 2 and power distribution network, is caused
The raising of power distribution network operating cost.
4) in addition to 24h, micro-capacitance sensor 3 is in remaining period all to power distribution network sale of electricity.Different to micro-capacitance sensor 1 and micro-capacitance sensor 2
Bilateral electricity price, power distribution network are supplied to minimum value of the electricity price of micro-capacitance sensor 3 all to allow in block of purchase electricity.Under the electricity price, micro- electricity
Net 3 will not dispatch energy storage and carry out peak load shifting, that is to say, that power distribution network is not thought to allow micro-capacitance sensor by the means of price incentive
3 scheduling energy storage are more beneficial for reducing the operating cost of itself.
The 6th, 10,14 row in table 3 represent power distribution networks and the final trading scheme of each micro-capacitance sensor, using the trading scheme as
Known parameters are substituted into the economic load dispatching model of micro-capacitance sensor, can obtain the final scheduling scheme of each micro-capacitance sensor.It is with micro-capacitance sensor 2
Example, under the trading scheme shown in the row of table 3 the 10th, the schedule power of its inside micro gas turbine and energy storage as shown in figure 5, its
Value be negative during middle energy storage charging, is just during electric discharge.The actual schedule power and expectation electric power such as Fig. 6 of demand response load
It is shown.
In Fig. 5, when the bilateral day-ahead power market electricity price of power distribution network and micro-capacitance sensor 2 is less than miniature gas turbine unit cost of electricity-generating
When, miniature gas turbine is run with minimum output power, such as 1h-7h and 24h；In remaining period, miniature gas turbine is then with most
Big power output operation.Energy-storage units are charged in 6h-7h and 24h, are discharged in 19h-21h, so as to by paddy electricity valency
The power storage of period is got up, and at peak, rate period is sold, and realizes peak load shifting.In Fig. 6, the expectation electricity consumption of demand response load
Plan is similar to non-resilient load, and electricity consumption is concentrated mainly on electricity price peak period.Meeting total electricity consumption demand and day part use
On the premise of Constraint, micro-capacitance sensor distributes 19h-21h power demand to 1h-8h and 24h, exists so as to reduce micro-capacitance sensor
Peak rate period needs the electric energy bought.
As can be seen that being optimized based on power distribution network proposed by the invention and micro electric network coordination from the analysis of above-described embodiment
Method, power distribution network can pass through tide optimization and price adjustment mechanism, it is ensured that the safety of system, economical operation, anti-locking system occur
Obstruction.By price incentive reasonable in design, power distribution network can make full use of the ability of micro-capacitance sensor peak load shifting, improve systematic economy
Property.
The micro-capacitance sensor operational factor of table 1
The micro-capacitance sensor uncertainty adjustment parameter of table 2
The power distribution network the best electric price of table 3 and trading scheme simulation result
Claims (1)
1. a kind of power distribution network and micro electric network coordination optimization method based on price competition mechanism, it is characterised in that
(1) power distribution network and micro-capacitance sensor interaction mechanism framework are as follows：
1) power distribution network announces the bilateral transaction electricity price with each micro-capacitance sensor；
2) each micro-capacitance sensor, according to the risk tolerance of itself, chooses suitable robust regulation ginseng after electricity price a few days ago is received
Number scope, prediction and corresponding prediction deviation based on renewable distributed power source output and non-resilient load power, it is determined that most
Excellent economic dispatch program, and report the exchange power bound with power distribution network day part；
3) power distribution network control centre is submitted according to each micro-capacitance sensor trading scheme, itself information on load and system voltage, tide
Stream constraint etc., is optimized to system load flow, the minimum purchase sale of electricity scheme of active power loss is obtained, afterwards according to the electricity of higher level's power network
The result of valency and tide optimization, with the bilateral electricity price of the minimum target update of operating cost and each micro-capacitance sensor；
4) return to step 1), until power distribution network determines final electricity price a few days ago and trading scheme；
5) each micro-capacitance sensor obtains micro- using the exchange power of day part in final trading scheme and power distribution network as known parameters, optimization
The coordinated scheduling scheme of type gas turbine, energy storage and demand response load, this interaction mechanism include micro-capacitance sensor and are based on electricity price a few days ago
Economic load dispatching optimization and optimization of the power distribution network based on micro-capacitance sensor scheduling result；
(2) in terms of micro-capacitance sensor is based on the economic load dispatching optimization of electricity price a few days ago：It is special by the operation for analyzing each equipment in micro-capacitance sensor
Property and operation constraint, establish the linear economy scheduling model of micro-capacitance sensor, for nonlinear terms therein, entered using linearization technique
Row is handled, and is included 0/1 variable and each equipment power output continuous variable in model, is established Mixed integer linear programming；For
Further consider the influence of stochastic variable wave characteristic in micro-capacitance sensor, the random spy of uncertain variables is described using uncertain collection
Property, stochastic variable has an opportunity to get the uncertain arbitrary value concentrated in optimization process；The worst scene is determined with reference to robust optimization
The essence of lower optimal scheduling scheme, micro-capacitance sensor two benches Robust Optimization Model is built, 0/1 variable and continuous variable are asked stage by stage
Solution, while the most severe Run-time scenario faced in the given uncertain collection of micro-capacitance sensor is found by optimization means, finally give and match somebody with somebody
Power network gives economic dispatch program optimal under day-ahead power market electricity price.
(3) in terms of power distribution network is based on the optimization of micro-capacitance sensor scheduling result：According to each micro-capacitance sensor economic dispatch program result, with reference to
The operation constraint of itself, including node voltage constraint and branch power constraint, determine the minimum scheduling scheme of active power network loss,
And then the operating cost of power distribution network under current day-ahead power market electricity price is obtained, afterwards by genetic algorithm to power distribution network and each micro-capacitance sensor
Day-ahead power market electricity price optimize, obtain the minimum pricing scheme of power distribution network operating cost.
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