CN109861309A - A kind of isolated operation micro-capacitance sensor group energy amount scheduling distributed optimization method - Google Patents
A kind of isolated operation micro-capacitance sensor group energy amount scheduling distributed optimization method Download PDFInfo
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The present invention discloses a kind of isolated operation micro-capacitance sensor group energy amount scheduling distributed optimization method, comprising: obtains electric load caused by prediction error existing for the existing prediction error of photovoltaic, wind-powered electricity generation and load random fluctuation and predicts error;And photovoltaic power output model, blower power output model and load model are established according to each prediction error;According to the three of foundation models, safety margin model is established;According to each prediction error, the limit value of safety margin model is determined;According to the three of foundation models, Optimal Operation Model is established;According to the limit value of safety margin model, the constraint condition of the Optimal Operation Model is determined;Optimal Operation Model is split, multiple distributed optimization scheduling models are obtained;Multiple distributed optimization scheduling models are solved, the optimized operation plan of each micro-capacitance sensor is obtained.Performance driving economy can be improved as far as possible on the basis of guaranteeing property safe and reliable to operation using the present invention.
Description
Technical field
The present invention relates to operation of power networks fields, distributed excellent more particularly to a kind of scheduling of isolated operation micro-capacitance sensor group energy amount
Change method.
Background technique
Each isolated operation micro-capacitance sensor is by photovoltaic, blower, conventional distributed generation resource, load and Energy Management System (EMS)
Composition.The Optimal Scheduling of each isolated operation micro-capacitance sensor is completed in EMS, can carry out a few days ago electric load according to historical data
It is predicted with renewable energy power outputs such as photovoltaic, blowers, predicts that micro-capacitance sensor electric load and renewable energy power output situation, decision go out
Generating set generated energy etc..In view of existing because of the renewable energy such as load random fluctuation and photovoltaic power output predicted value and true value
Error, EMS need to adjust controllable power output (conventional distribution unit), and there are enough safety margins, come at any time
Cope with because load random fluctuation and renewable energy go out force prediction method it is not perfect caused by error, guarantee power supply reliability.
For being protected to cope with the fluctuation of itself load with the fluctuation that renewable energy is contributed for each isolated island micro-capacitance sensor of stand-alone mode
Testimony electricity is safe and reliable, and conventional distributed generation resource need to will lead to unit operating point and receive limitation there are enough safety margins,
Influence performance driving economy.
Summary of the invention
The object of the present invention is to provide a kind of isolated operation micro-capacitance sensor group energy amounts to dispatch distributed optimization method, can protect
On the basis of demonstrate,proving property safe and reliable to operation, performance driving economy is improved as far as possible.
To achieve the above object, the present invention provides following schemes:
A kind of isolated operation micro-capacitance sensor group energy amount scheduling distributed optimization method, comprising:
It is pre- to obtain electric load caused by prediction error existing for the existing prediction error of photovoltaic, wind-powered electricity generation and load random fluctuation
Survey error;
Error is predicted according to existing for the photovoltaic, establishes photovoltaic power output model;
Error is predicted according to existing for the wind-powered electricity generation, establishes blower power output model;
Error is predicted according to electric load caused by the load random fluctuation, establishes load model;
According to photovoltaic power output model, blower power output model and the load model, safety margin model is established;
The safety margin model is the unit output upper limit and the practical power output difference of unit;
Prediction error existing for prediction error, the wind-powered electricity generation according to existing for the photovoltaic and the load random fluctuation are drawn
The electric load risen predicts error, determines the limit value of safety margin model;
Based on photovoltaic power output model, blower power output model and the load model, with isolated island micro-capacitance sensor group fortune
Row cost is minimum, establishes Optimal Operation Model;
According to the limit value of the safety margin model, the constraint condition of the Optimal Operation Model is determined;
The Optimal Operation Model is split, multiple distributed optimization scheduling models are obtained;
Multiple distributed optimization scheduling models are solved, the optimized operation of each isolated operation micro-capacitance sensor group is obtained
Plan.
Optionally, described to predict error according to existing for the photovoltaic, photovoltaic power output model is established, is specifically included:
Error is predicted according to existing for the photovoltaic, establishes photovoltaic power output model
Wherein,For micro-capacitance sensor i t moment photovoltaic power generation output forecasting value,It is missed for the photovoltaic power generation output forecasting of t moment
Difference.
Optionally, described to predict error according to existing for the wind-powered electricity generation, blower power output model is established, is specifically included:
Error is predicted according to existing for the wind-powered electricity generation, establishes blower power output model
For micro-capacitance sensor i t moment Wind turbines contribute predicted value,For the Wind turbines power output prediction of t moment
Error amount.
Optionally, the electric load according to caused by the load random fluctuation predicts error, establishes load model, specifically
Include:
Error is predicted according to electric load caused by the load random fluctuation, establishes load model
Wherein,It is micro-capacitance sensor i in t moment electric load predicted value,For t moment because of load random fluctuation caused by
Electric load prediction error value.
Optionally, the prediction error according to existing for the photovoltaic, prediction error existing for the wind-powered electricity generation and described negative
Electric load caused by lotus random fluctuation predicts error, determines the limit value of safety margin model, specifically includes:
Prediction error existing for prediction error, the wind-powered electricity generation according to existing for the photovoltaic and the load random fluctuation are drawn
The electric load risen predicts error, determines the limit value of safety margin model
Wherein,For the photovoltaic power generation output forecasting error amount of t moment,For the Wind turbines power output prediction error of t moment
Value,It is t moment because of electric load prediction error value caused by load random fluctuation.
Optionally, described according to photovoltaic power output model, blower power output model and the load model, it establishes excellent
Change scheduling model, specifically include:
According to photovoltaic power output model, blower power output model and the load model, Optimal Operation Model is established
Wherein,For the conventional distributed unit operating cost of each isolated operation micro-capacitance sensor;It is handed between micro-capacitance sensor
The wheeling rates that easy electricity generates,It is micro-capacitance sensor i to the purchase of electricity of micro-capacitance sensor j, A is adjacency matrix, right
Angle element is 0, remaining element is 1;eiIt is N-dimensional column vector, i-th of element is 1, remaining is 0,For electricity consumption effect
Use function;kiFor electricity consumption utilization coefficient;N is micro-capacitance sensor number.
Optionally, the limit value according to the safety margin model, determines the constraint condition of the Optimal Operation Model,
It specifically includes:
According to the limit value of the safety margin model, the constraint condition of the Optimal Operation Model is determined:
Wherein, A is adjacency matrix, and diagonal element 0, remaining element is 1.
Optionally, described to split the Optimal Operation Model, multiple distributed optimization scheduling models are obtained, specifically
Include:
The Optimal Operation Model is split, multiple distributed optimization scheduling models are obtained:
If
Wherein,It is micro-capacitance sensor i to the purchase of electricity of micro-capacitance sensor j;It is micro-
Purchase from power grid i to micro-capacitance sensor j margin amount; Represent isolated operation micro-capacitance sensor i t moment as its
He provides the unit price of nargin ancillary service by isolated operation micro-capacitance sensor;Represent isolated operation micro-capacitance sensor i
It is monovalent to other isolated operation micro-capacitance sensor sales of electricity in t moment;Sale of electricity for from micro-capacitance sensor i to micro-capacitance sensor j
Amount;For micro-capacitance sensor i the margin amount of (sale) can be provided to micro-capacitance sensor j;
The constraint condition of the distributed optimization scheduling model:
Wherein, ifIt is micro-
Purchase of electricity of the power grid i to micro-capacitance sensor j;For purchase from micro-capacitance sensor i to micro-capacitance sensor j margin amount;It is micro-capacitance sensor i to the electricity sales amount of micro-capacitance sensor j;It can be to micro- for micro-capacitance sensor i
The margin amount of the offer (sale) of power grid j, A are adjacency matrix, and diagonal element 0, remaining element is 1, eiIt is N-dimensional column vector,
I-th of element is 1, remaining is 0,For the conventional distributed unit output maximum value of micro-capacitance sensor.
Optionally, described that multiple distributed optimization scheduling models are solved, obtain the optimal fortune of each micro-capacitance sensor
Row plan, specifically includes:
Multiple distributed optimization scheduling models are solved using distribution iterative algorithm, obtain the optimal fortune of each micro-capacitance sensor
Row plan.
The specific embodiment provided according to the present invention, the invention discloses following technical effects: the present invention provides a kind of orphan
Island runs micro-capacitance sensor group energy amount and dispatches distributed optimization method, comprising: obtains pre- existing for the existing prediction error of photovoltaic, wind-powered electricity generation
It surveys electric load caused by error and load random fluctuation and predicts error;And according to each prediction error establish photovoltaic power output model,
Blower power output model and load model;According to the three of foundation models, safety margin model is established;According to each prediction error, really
Determine the limit value of safety margin model;Three models based on foundation, it is minimum with isolated operation micro-capacitance sensor group's operating cost, it establishes excellent
Change scheduling model;According to the limit value of safety margin model, the constraint condition of the Optimal Operation Model is determined;By Optimized Operation mould
Type is split, and multiple distributed optimization scheduling models are obtained;Multiple distributed optimization scheduling models are solved, are obtained each
The optimized operation plan of micro-capacitance sensor.Fortune can be improved as far as possible on the basis of guaranteeing property safe and reliable to operation using the present invention
Row economy.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is that isolated operation of embodiment of the present invention micro-capacitance sensor group energy amount dispatches distributed optimization method flow diagram.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of isolated operation micro-capacitance sensor group energy amounts to dispatch distributed optimization method, can protect
On the basis of demonstrate,proving property safe and reliable to operation, performance driving economy is improved as far as possible.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is that isolated operation of embodiment of the present invention micro-capacitance sensor group energy amount dispatches distributed optimization method flow diagram.Such as Fig. 1 institute
Show, a kind of isolated operation micro-capacitance sensor group energy amount scheduling distributed optimization method, comprising:
Step 101: caused by obtaining prediction error existing for the existing prediction error of photovoltaic, wind-powered electricity generation and load random fluctuation
Electric load predicts error;
Step 102: predicting error according to existing for the photovoltaic, establish photovoltaic power output model;
Step 103: predicting error according to existing for the wind-powered electricity generation, establish blower power output model;
Step 104: error being predicted according to electric load caused by the load random fluctuation, establishes load model;
Step 105: according to photovoltaic power output model, blower power output model and the load model, establishing safety
Nargin model;The safety margin model is the unit output upper limit and the practical power output difference of unit;
Step 106: prediction error, prediction error and the load existing for the wind-powered electricity generation according to existing for the photovoltaic with
Electric load caused by machine fluctuates predicts error, determines the limit value of safety margin model;
Step 107: based on photovoltaic power output model, blower power output model and the load model, being transported with isolated island
The minimum target of row micro-capacitance sensor group's operating cost, establishes Optimal Operation Model;
Step 108: according to the limit value of the safety margin model, determining the constraint condition of the Optimal Operation Model;
Step 109: the Optimal Operation Model being split, multiple distributed optimization scheduling models are obtained;
Step 110: multiple distributed optimization scheduling models being solved, the optimized operation meter of each micro-capacitance sensor is obtained
It draws.
Step 102, it specifically includes:
Error is predicted according to existing for the photovoltaic, establishes photovoltaic power output model
Wherein,For micro-capacitance sensor i t moment photovoltaic power generation output forecasting value,For the photovoltaic power generation output forecasting error of t moment
Value.
Step 103, it specifically includes:
Error is predicted according to existing for the wind-powered electricity generation, establishes blower power output model
For micro-capacitance sensor i t moment Wind turbines contribute predicted value,For the Wind turbines power output prediction of t moment
Error amount.
There are random fluctuations according to user demand for electric load, and in actual moving process, load cannot be fully according to preparatory
Dispatch situation carries out, and there are certain errors.Step 104, it specifically includes:
Error is predicted according to electric load caused by the load random fluctuation, establishes load model
Wherein,It is micro-capacitance sensor i in t moment electric load predicted value,For t moment because of load random fluctuation caused by
Electric load prediction error value.
In the establishment process of load model, each micro-capacitance sensor has a certain proportion of translatable load, has certain need
Seek responding ability.The electricity consumption effectiveness of user may be expressed as:
In formula: uiFor the electricity consumption effectiveness of micro-capacitance sensor i;For the electricity consumption of micro-capacitance sensor i;kiBeing is electricity consumption effectiveness parameter,
Its value is adjusted according to user in the consumption habit of day part.It should guarantee base load just during adjusting electricity consumption
Often power supply can not be more than the upper limit of distribution line, i.e.,
Safety margin definition is the unit output upper limit and the practical power output difference of unit, i.e.,To ensure to power
Securely and reliably, controllable (conventional distribution unit) need to there are enough safety margins to go out to cope with load and renewable energy
Fluctuation.
When micro-capacitance sensor isolated operation:
Because load fluctuation and the presence of prediction error make:
System is because of the error ε that renewable energy goes out fluctuation and load random fluctuation generatesi,t
So the conventional distributed unit of controllable is that guarantee system is securely and reliably powered, can be existed according to the photovoltaic
Prediction error, electric load predicts error caused by the existing prediction error of the wind-powered electricity generation and the load random fluctuation, determine
The limit value of safety margin model
Wherein,For the photovoltaic power generation output forecasting error amount of t moment,For the Wind turbines power output prediction error of t moment
Value,It is t moment because of electric load prediction error value caused by load random fluctuation.
The operating cost of conventional distribution unit may be expressed as:
In formula, αi, βi, γiFor fuel cost coefficient,For the output power of conventional distributed generation resource.
Transaction electric energy, will generate wheeling rates, electric energy wheeling rates is modeled as cubic polynomial:
γe(x)=a1x+b1x3
In formula, a1,b1For coefficient, x is transaction electric energy.
Step 107, it specifically includes:
Based on photovoltaic power output model, blower power output model and the load model, with isolated operation micro-capacitance sensor
Group's minimum target of operating cost, establishes Optimal Operation Model
Wherein,For the conventional distributed unit operating cost of each isolated operation micro-capacitance sensor;It is handed between micro-capacitance sensor
The wheeling rates that easy electricity generates,It is micro-capacitance sensor i to the purchase of electricity of micro-capacitance sensor j, A is adjacency matrix, right
Angle element is 0, remaining element is 1;eiIt is N-dimensional column vector, i-th of element is 1, remaining is 0.For electricity consumption effect
Use function;kiFor electricity consumption utilization coefficient;N is micro-capacitance sensor number.
Consider that the Optimized Operation target of the interconnection isolated operation micro-capacitance sensor group of safety margin is in guarantee system in the present invention
Safe and reliable operation, i.e., for controllable unit there are under conditions of enough safety margins, system total operating cost is minimum, wherein including
Power generation, wheeling rates, electricity consumption effectiveness cost are not required to the abundant of micro-capacitance sensor error where every conventional distributed unit is both needed to reserved meet
Degree, but the sum of interconnection isolated operation micro-capacitance sensor group system entirety nargin meets global error requirement.
Step 108, it specifically includes:
According to the limit value of the safety margin model, the constraint condition of the Optimal Operation Model is determined:
Wherein, A is adjacency matrix, and diagonal element 0, remaining element is 1.Wherein,
Step 109, it specifically includes:
The Optimal Operation Model is split, multiple distributed optimization scheduling models are obtained:
If
Wherein,It is micro-capacitance sensor i to the purchase of electricity of micro-capacitance sensor j;It is micro-
Purchase from power grid i to micro-capacitance sensor j margin amount; Represent isolated operation micro-capacitance sensor i t moment as its
He provides the unit price of nargin ancillary service by isolated operation micro-capacitance sensor;Represent isolated operation micro-capacitance sensor i
It is monovalent to other isolated operation micro-capacitance sensor sales of electricity in t moment;Sale of electricity for from micro-capacitance sensor i to micro-capacitance sensor j
Amount;For micro-capacitance sensor i the margin amount of (sale) can be provided to micro-capacitance sensor j;
The constraint condition of the distributed optimization scheduling model:
Wherein, ifIt is micro-
Purchase of electricity of the power grid i to micro-capacitance sensor j;For purchase from micro-capacitance sensor i to micro-capacitance sensor j margin amount;It is micro-capacitance sensor i to the electricity sales amount of micro-capacitance sensor j;It can be to micro- for micro-capacitance sensor i
The margin amount of the offer (sale) of power grid j, A are adjacency matrix, and diagonal element 0, remaining element is 1, eiIt is N-dimensional column vector,
I-th of element is 1, remaining is 0,For the conventional distributed unit output maximum value of micro-capacitance sensor.
Step 110, it specifically includes:
Multiple distributed optimization scheduling models are solved using distribution iterative algorithm, obtain each isolated operation micro-capacitance sensor
Optimized operation plan.
Distributed iterative algorithm:
Lagrange multiplier updates as follows when each round is initial:
ηt[k] is the kth time iteration in solution procedureIsolated operation micro-capacitance sensor i is represented to exist
T moment provides the unit price of nargin ancillary service for other isolated operation micro-capacitance sensors;λt[k] is the kth time iteration in solution procedure
'sIt is monovalent to other isolated operation micro-capacitance sensor sales of electricity in t moment to represent isolated operation micro-capacitance sensor i;For the kth time iteration in solution procedure For the kth time iteration in solution procedure
'sIt is micro-capacitance sensor i to the electricity sales amount of micro-capacitance sensor j;For micro-capacitance sensor i the margin amount of (sale) can be provided to micro-capacitance sensor j.A is adjacency matrix, diagonal element
Element is 0, remaining element is 1.eiIt is N-dimensional column vector, i-th of element is 1, remaining is 0.
By solving the generated energy of the available each micro-capacitance sensor of distributed optimization algorithm, electricity of trading with other micro-capacitance sensors
Amount, transaction margin amount, trade electricity price, nargin transaction value, so that it is safe and reliable to operation in guarantee to obtain each micro-capacitance sensor
On the basis of optimized operation plan and operating cost.
It is limited by traditional prediction technique, photovoltaic power output is difficult to obtain Accurate Prediction, practical power generating value and prediction power generating value
Between there are certain errors;Load is affected by many factors, and there are random fluctuations, therefore in scheduling, need to reserve controllable unit
Certain safety margin come cope with photovoltaic power output with load random fluctuation generate error, guarantee power supply safety and reliability.
In recent years, with China's distributed energy in power grid permeability lasting increase, micro-capacitance sensor as integrate it is a variety of
The control unit of distributed energy and load is come into being.Currently, isolated island micro-capacitance sensor tool is there are two types of the method for operation: isolated island and simultaneously
Net.With the appearance of micro-capacitance sensor group's form, there is the new method of operation in micro-capacitance sensor group: more micro-capacitance sensor isolated island interconnected operations.It is real
Source lotus Optimized Operation in the operational process of border about micro-capacitance sensor is the essential link of micro-capacitance sensor, and dispatcher needs according to micro-
The actual conditions such as network load, renewable energy power output, determine unit output, nargin and transaction electricity and nargin situation.It is logical
Energy-optimised scheduling is crossed, micro-capacitance sensor power supply economics and reliability are improved.
Method of the invention considers safety margin, can be applied to the isolated island micro-capacitance sensor group of specific interconnected operation, root
According to each isolated island micro-capacitance sensor actual distribution formula unit output situation and load condition, renewable energy prediction error and load are being considered
In the case where random fluctuation, electricity and the safety margin value, transaction electricity price, friendship traded between each isolated island micro-capacitance sensor of optimization
Easy safety margin price and each controllable unit output.Apply the present invention in isolated island micro-capacitance sensor group energy amount Optimized Operation, transports
Administrative staff can be according to optimization as a result, interconnection isolated island micro-capacitance sensor group's operational plan is formulated, in the guarantee interacted system reliability
On the basis of, so that operation is most economical.
Method of the invention has following advantage:
(1) in the scheduling of each microgrid energy, considering security nargin improves each micro-capacitance sensor reply renewable energy and goes out
Fluctuation and load fluctuation ability improve power supply reliability, reduce caused by going out fluctuation because of load fluctuation and renewable energy
Loss of outage.
(2) it by interconnection isolated operation micro-capacitance sensor group's combined dispatching, determines controllable unit operating point, makes each isolated operation
Micro-capacitance sensor is under the method for operation of most safety economy, reduces Gas Generator Set, fired power generating unit fuel consumption.
(3) this dispatching method is easy to operate, calculates rapidly, significantly reduces dispatcher's work complexity.
(4) this dispatching method, the charge value for only needing between each isolated island micro-capacitance sensor interaction to need to buy and safety margin value,
Each isolated island micro-capacitance sensor dispatcher can go out corresponding electricity consumption according to this dispatching method Optimal Decision-making, electricity production, electricity sales amount, sell
The numerical value such as safety margin value carry out optimal scheduling.Greatly protect the privacy of each isolated island micro-capacitance sensor.Each reality in this specification
It applies example to be described in a progressive manner, each embodiment focuses on the differences from other embodiments, Ge Geshi
Applying same and similar part between example may refer to each other.
Used herein a specific example illustrates the principle and implementation of the invention, and above embodiments are said
It is bright to be merely used to help understand method and its core concept of the invention;At the same time, for those skilled in the art, foundation
Thought of the invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (9)
1. a kind of isolated operation micro-capacitance sensor group energy amount dispatches distributed optimization method characterized by comprising
Electric load prediction caused by prediction error existing for the existing prediction error of photovoltaic, wind-powered electricity generation and load random fluctuation is obtained to miss
Difference;
Error is predicted according to existing for the photovoltaic, establishes photovoltaic power output model;
Error is predicted according to existing for the wind-powered electricity generation, establishes blower power output model;
Error is predicted according to electric load caused by the load random fluctuation, establishes load model;
According to photovoltaic power output model, blower power output model and the load model, safety margin model is established;It is described
Safety margin model is the unit output upper limit and the practical power output difference of unit;
Caused by prediction error existing for prediction error, the wind-powered electricity generation according to existing for the photovoltaic and the load random fluctuation
Electric load predicts error, determines the limit value of safety margin model;
Based on photovoltaic power output model, blower power output model and the load model, with isolated operation micro-capacitance sensor group fortune
The minimum target of row cost, establishes Optimal Operation Model;
According to the limit value of the safety margin model, the constraint condition of the Optimal Operation Model is determined;
The Optimal Operation Model is split, multiple distributed optimization scheduling models are obtained;
Multiple distributed optimization scheduling models are solved, the optimized operation plan of each isolated operation micro-capacitance sensor is obtained.
2. isolated operation micro-capacitance sensor group energy amount according to claim 1 dispatches distributed optimization method, which is characterized in that institute
It states and predicts error according to existing for the photovoltaic, establish photovoltaic power output model, specifically include:
Error is predicted according to existing for the photovoltaic, establishes photovoltaic power output model
Wherein,For micro-capacitance sensor i t moment photovoltaic power generation output forecasting value,For the photovoltaic power generation output forecasting error amount of t moment.
3. isolated operation micro-capacitance sensor group energy amount according to claim 2 dispatches distributed optimization method, which is characterized in that institute
It states and predicts error according to existing for the wind-powered electricity generation, establish blower power output model, specifically include:
Error is predicted according to existing for the wind-powered electricity generation, establishes blower power output model It is micro-
Power grid i t moment Wind turbines contribute predicted value,For the Wind turbines power output prediction error value of t moment.
4. isolated operation micro-capacitance sensor group energy amount according to claim 3 dispatches distributed optimization method, which is characterized in that institute
The prediction error of the electric load according to caused by the load random fluctuation is stated, load model is established, specifically includes:
Error is predicted according to electric load caused by the load random fluctuation, establishes load model
Wherein,It is i in t moment electric load predicted value,For t moment because electric load prediction caused by load random fluctuation misses
Difference.
5. isolated operation micro-capacitance sensor group energy amount according to claim 4 dispatches distributed optimization method, which is characterized in that institute
State electricity caused by prediction error existing for prediction error, the wind-powered electricity generation according to existing for the photovoltaic and the load random fluctuation
Load prediction error determines the limit value of safety margin model, specifically includes:
Caused by prediction error existing for prediction error, the wind-powered electricity generation according to existing for the photovoltaic and the load random fluctuation
Electric load predicts error, determines the limit value of safety margin model
Wherein,For the photovoltaic power generation output forecasting error amount of t moment,For t moment Wind turbines contribute prediction error value,It is t moment because of electric load prediction error value caused by load random fluctuation.
6. isolated operation micro-capacitance sensor group energy amount according to claim 5 dispatches distributed optimization method, which is characterized in that institute
It states based on photovoltaic power output model, blower power output model and the load model, with isolated operation micro-capacitance sensor group operation
The minimum target of cost, establishes Optimal Operation Model, specifically includes:
According to photovoltaic power output model, blower power output model and the load model, Optimal Operation Model is established
Wherein,For the conventional distributed unit operating cost of each isolated operation micro-capacitance sensor;It trades between micro-capacitance sensor electric
The wheeling rates generated are measured,It is micro-capacitance sensor i to the purchase of electricity of micro-capacitance sensor j, A is adjacency matrix, diagonal element
Element is 0, remaining element is 1;eiIt is N-dimensional column vector, i-th of element is 1, remaining is 0,For electricity consumption effectiveness letter
Number;kiFor electricity consumption utilization coefficient;N is micro-capacitance sensor number.
7. isolated operation micro-capacitance sensor group energy amount according to claim 6 dispatches distributed optimization method, which is characterized in that institute
The limit value according to the safety margin model is stated, the constraint condition of the Optimal Operation Model is determined, specifically includes:
According to the limit value of the safety margin model, the constraint condition of the Optimal Operation Model is determined:
Wherein, A is adjacency matrix, and diagonal element 0, remaining element is 1.
8. isolated operation micro-capacitance sensor group energy amount according to claim 7 dispatches distributed optimization method, which is characterized in that institute
It states and splits the Optimal Operation Model, obtain multiple distributed optimization scheduling models, specifically include:
The Optimal Operation Model is split, multiple distributed optimization scheduling models are obtained:
If
Wherein,It is micro-capacitance sensor i to the purchase of electricity of micro-capacitance sensor j;For micro-capacitance sensor
Purchase from i to micro-capacitance sensor j margin amount; It is lonely as other in t moment to represent isolated operation micro-capacitance sensor i
Island runs micro-capacitance sensor and provides the unit price of nargin ancillary service; Isolated operation micro-capacitance sensor i is represented in t
It carves to other isolated operation micro-capacitance sensor sale of electricity unit prices;It is micro-capacitance sensor i to the electricity sales amount of micro-capacitance sensor j;For micro-capacitance sensor i the margin amount of (sale) can be provided to micro-capacitance sensor j;
The constraint condition of the distributed optimization scheduling model:
Wherein, ifFor micro-capacitance sensor i
To the purchase of electricity of micro-capacitance sensor j;For purchase from micro-capacitance sensor i to micro-capacitance sensor j margin amount;It is micro-capacitance sensor i to the electricity sales amount of micro-capacitance sensor j;It can be to micro- for micro-capacitance sensor i
The margin amount of the offer (sale) of power grid j, A are adjacency matrix, and diagonal element 0, remaining element is 1, eiIt is N-dimensional column vector,
I-th of element is 1, remaining is 0,For the conventional distributed unit output maximum value of micro-capacitance sensor.
9. isolated operation micro-capacitance sensor group energy amount according to claim 1 dispatches distributed optimization method, which is characterized in that institute
It states and multiple distributed optimization scheduling models is solved, obtain the optimized operation plan of each isolated operation micro-capacitance sensor, have
Body includes:
Multiple distributed optimization scheduling models are solved using distribution iterative algorithm, obtain each isolated operation micro-capacitance sensor most
Excellent operational plan.
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