CN109687442A - A kind of new energy Optimal capacity of area's spot exchange transprovincially appraisal procedure and device - Google Patents
A kind of new energy Optimal capacity of area's spot exchange transprovincially appraisal procedure and device Download PDFInfo
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Abstract
The invention discloses a kind of new energy Optimal capacity of area's spot exchange transprovincially appraisal procedure and device, belongs to and new energy transprovincially area's electric power spot exchange scale and purchases strategies technical field is quantitatively evaluated comprising the steps of: S1: building input data library module；S2: building interconnection Security Checking module；S3: building is by end regions electro-load forecast module and this area new energy power output prediction module；S4: building is by end regions normal power supplies peak regulation requirement forecasting module；S5: building peak modulation capacity checks module；S6: building this area peak regulation forecasting of cost module；S7: the transregional spot exchange cost of building new energy checks module.The present invention can be used for that receiving end power grid is instructed rationally to mention in the new energy transprovincially spot exchange of area's electric power to report and submit electricity demanding and quotation, under the premise of meeting the consumption of this province new energy and peak regulation demand, it maximizes consumption and meets new energy outside the area of channel constraint, it is final to realize new energy marketization consumption to the greatest extent in wider scope.
Description
Technical Field
The invention relates to the technical field of quantitative evaluation of new energy trans-provincial electric power spot transaction scale and electricity purchasing cost, in particular to an optimal scale evaluation method for new energy trans-provincial spot transaction.
Background
Under the influence of natural resources, wind power generation and solar power generation installed machines in China are intensively distributed in the three-north area. The problems of wind abandoning and light abandoning exist under the restriction of factors such as limited local absorption space, insufficient system peak regulation capacity, unsound trans-provincial absorption mechanism and the like. The wind power, the photovoltaic and other new energy sources fluctuate randomly, the current technology cannot realize accurate prediction in a medium-long term, is difficult to participate in medium-long term transaction in a trans-provincial region, and the consumption of electric quantity in the trans-provincial region is influenced. The cross-provincial spot-shipment transaction based on short-term and ultra-short-term power generation prediction can effectively solve the contradiction between the traditional electric quantity transaction and the random fluctuation of the new energy output, expand the new energy consumption space in a wider region, fully play the investment and environmental protection benefits of a new energy unit and an ultra-high voltage power grid and reduce the fuel cost of the whole society. The rich renewable energy cross-provincial spot transaction aiming at the wind and light electricity abandonment quantity is formally started, and the scale of the new energy cross-provincial spot transaction in the future is further expanded.
The electric power spot transaction fully embodies the characteristics of autonomous participation and decision of a trading subject, and can realize the optimal allocation of resources by the market. On one hand, the balance problem of the new energy electricity purchasing cost outside the area and the peak shaving cost possibly brought by the new energy electricity purchasing cost and the average electricity purchasing cost of the local unit needs to be focused. On the other hand, from the viewpoint of system conditions and physical constraints, the adjustment performance of the conventional units in the receiving end region, the installation and output of new energy in the local region, the interconnection and intercommunication condition of the power grid, the scale of regional loads and the peak-valley difference are also several key factors influencing the consumption of new energy across provinces and regions. Therefore, the method for evaluating the optimal scale of the spot transaction of the new energy across provincial regions is provided.
Patent document No. CN108520315A discloses a power grid active real-time control method considering medium and long term transaction and spot transaction constraints, and belongs to the technical field of power system operation and control. Aiming at power plant grid-connected active real-time control under the power market environment with coexistence of medium-long term transaction and spot transaction, the invention provides that the ratio of transaction electric quantity completion progress and transaction time progress is taken as a transaction electric quantity execution rate index, the spot transaction electric quantity execution rate index is adjusted by introducing a parameter smaller than 1, a power plant grid-connected active power adjustment speed and adjustable space, power balance, power transmission channel capacity, frequency modulation peak regulation constraint and the like are considered, a power grid active power control optimization model which takes the product of the medium-long term transaction electric quantity execution rate index and the spot transaction electric quantity execution rate index as a weight and takes the power plant grid-connected active power sum minimum as a target is constructed, and the power grid active power control which simultaneously meets the medium-long term transaction constraint and the spot transaction constraint requirements is realized. However, the method only optimizes the active real-time control decision of the power grid by taking the product of the medium-and-long-term transaction electric quantity execution rate index and the spot transaction electric quantity execution rate index as a weight, cannot realize medium-and-long-term accurate prediction, is difficult to participate in the cross-provincial medium-and-long-term transaction, and affects cross-provincial electric quantity consumption.
Patent document No. CN107832911A discloses a demand side node electricity price partition settlement method in a spot market environment. The method comprises the following steps: s1, partitioning a power system according to electricity prices, and acquiring data of each partitioned price area; s2, calculating all power consumption of users in each price area; s3, calculating a weight value Ai of the electric quantity of each node; s4, calculating the electricity price of each partition average node; and S5, calculating the electric charge due by market users in the spot market. The demand side node electricity price partition settlement method provided by the invention combines a spot market operation mechanism and a partition electricity price principle, and is simple in calculation process, on one hand, the advantage of node electricity price pricing can be exerted, an electric power market price signal in a spot market can be accurately reflected, meanwhile, an electric power consumer can be prevented from being exposed to an overhigh price fluctuation risk, the stable development of an electric power market can be promoted in an electric power market construction transition period, and the method has reference significance for construction of a spot market. However, the method does not consider factors such as limited space, insufficient system peak regulation capacity, incomplete cross-province clearing mechanism and the like, and can not realize cross-province spot transaction.
Disclosure of Invention
The invention aims to provide a method and a device for calculating the optimal scale of new energy cross-provincial spot transaction.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a new energy cross-provincial spot transaction optimal scale evaluation method comprises the following steps:
step S1: arranging data, constructing an input database module, and making a day-ahead new energy cross-provincial region trading plan;
step S2: building a tie line safety check module, checking the transaction plan in the step S1, returning to the step S1 if the check is unqualified, and readjusting the transaction plan;
step S3: constructing a receiving end area power load prediction module and a local area new energy output prediction module, and predicting the receiving end area power load and the local area new energy output condition after checking in the step S2;
step S4: performing conventional power supply peak regulation demand prediction on the receiving end region in the step S3, and constructing a conventional power supply peak regulation demand prediction module of the receiving end region to obtain a conventional power supply output curve of the local region;
step S5: a peak regulation capability checking module is constructed, the peak regulation capability of the local area conventional power output curve in the step S4 is checked, if the checking is unqualified, the step S1 is returned, and the transaction plan is readjusted;
step S6: a local region peak shaving cost prediction module is constructed, and after the local region peak shaving cost prediction module is checked to be qualified in the step S5, the local region peak shaving cost is predicted to obtain the local region conventional unit peak shaving cost;
step S7: constructing a new energy cross-regional spot shipment transaction cost check module, checking the peak shaving cost of the local conventional unit in the step S6, and executing the check if the check is qualified; and if the verification is not qualified, returning to the step S1 to readjust the transaction plan.
Preferably, in step S1, the regional new energy transprovincial and regional electricity is reported based on the power price curve formed in the spot market before the dayInitial size of force spot transactionAnd calculating the electricity purchasing cost based on the electricity purchasing price。
Preferably, in step S2, the tie line power must satisfy the channel capability constraint:
in the formula、Is connected with a connecting lineThe minimum limit and the maximum limit of the transmission power at any moment;the method is that the medium and long term electric power trade scale agreed by the tie line, if the safety check of the tie line is not satisfied, the initial scale of spot trade needs to be adjusted in time。
Preferably, in step S3, the daily electrical load prediction is performed based on short-term and ultra-short-term prediction methods such as load derivation, gray correlation, and least-squares support vector machinePhotovoltaic output predictionPrediction of wind power output。
Preferably, in step S4, the power supply and the power utilization of the power system are completed simultaneously, and the power load exhibits a time-varying characteristic; new forms of energy electric power outside the district is introduced through the spot transaction, superpose this regional wind-powered electricity generation, photovoltaic and exert oneself, has increased the regulation burden of local area conventional power, and conventional power not only will follow the load change, still need balance the new forms of energy exert oneself undulant, obtains local area conventional power curve of exerting oneself:
in the formula:、the feed-out time is positive.
Preferably, in step S5, the peak shaving capability of the local conventional unit is determined by the power supply regulation performance, and is also related to the power supply structure, and the conventional power supply output needs to satisfy the peak shaving capability of the local area:
in the formula,is a local areaMaximum technical output of a conventional unit; i is the number of the conventional units in the local area;is as followsAnd (3) adjusting the peak regulation depth of the conventional unit, and if the peak regulation capacity check is not met, adjusting the spot trade initial scale P (t) in time.
Preferably, in step S6, according to the peak shaving requirement and the daily power generation plan of the conventional unit, in combination with the relevant provision of the local peak shaving auxiliary service, if the organic unit performs peak shaving for the new energy outside the absorption area, the peak shaving cost of the system generated thereby is calculated。
Preferably, in step S7, the electricity purchase cost and the peak shaving cost caused by the new energy cross-regional spot transaction are balanced with the local regional average electricity purchase cost:
in the formula,the average electricity purchasing cost of the conventional unit in the local area is calculated, and if the average electricity purchasing cost does not meet the transaction cost check, the spot transaction initial scale P (t) needs to be adjusted in time.
A new energy trans-provincial spot transaction optimal scale evaluation device comprises a database module, a tie line safety check module, a receiving end region power utilization load prediction module, a local region new energy output prediction module, a receiving end region conventional power supply peak regulation demand prediction module, a peak regulation capacity check module, a local region peak regulation cost prediction module and a new energy trans-regional spot transaction cost check module; the database module is used for inputting data and making a day-ahead new energy cross-provincial region trading plan; the tie line safety check module is used for checking a transaction plan; the receiving end area power load prediction module and the local area new energy output prediction module are used for predicting the receiving end area power load and the local area new energy output condition; the receiving end region conventional power supply peak regulation demand prediction module is used for predicting the conventional power supply peak regulation demand of the receiving end region to obtain a local region conventional power supply output curve; the peak regulation capability checking module is used for checking the peak regulation capability of the output curve of the conventional power supply in the local area; the local region peak regulation cost prediction module is used for predicting the local region peak regulation cost to obtain the local region conventional unit peak regulation cost; the new energy cross-regional spot goods transaction cost check module is used for checking the peak shaving cost of the local conventional unit.
A computer readable storage medium comprising a memory and a processor, the memory for storing one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the new energy cross-provincial spot transaction optimal size assessment method.
The invention has the beneficial effects that:
comparing data in the database module in the step S1, wherein the data comprises market power unit price data, historical statistical data and the like, and making a current new energy cross-provincial region trading plan; and the tie line safety check module in the step S2 checks the plan in the step S1, a certain constraint condition is required to be met, otherwise, the check is unqualified, and the step S1 is returned to readjust the transaction plan. Steps S3 and S4 are carried out on the power load of the receiving end region, the output condition of the new energy of the local region and the peak shaving requirement of the conventional power supply of the receiving end region to predict, and a conventional power supply output curve of the local region is obtained; the peak regulation capability checking module in the step S5 checks the peak regulation capability of the conventional power output curve of the local area, and if the peak regulation capability of the conventional power output curve of the local area must meet a certain constraint condition, otherwise, the checking is unqualified, the step S1 is returned, and the transaction plan is readjusted; step S6, the peak shaving cost of the local area is predicted to obtain the peak shaving cost of the conventional unit of the local area; the new energy transregional spot shipment transaction cost checking module of the step S7 checks the peak shaving cost of the local conventional unit in the step S6, and if the check is qualified, the process can be executed after the process is finished; and if the verification is not qualified, returning to the step S1 to readjust the transaction plan.
The assessment method can be used for guiding a receiving-end power grid to reasonably report power transmission requirements and quotations in the spot-stock transaction of new energy cross-provincial electric power, and maximally consumes the extra-regional new energy meeting the channel constraint on the premise of meeting the consumption and peak regulation requirements of the new energy of the province, so that the marketized consumption of the new energy in a wider range is finally realized.
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The present invention will be described in further detail with reference to the accompanying drawings.
FIG. 1 is a flow chart of an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to fig. 1 of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention, are within the scope of the invention.
Example 1
Referring to fig. 1, the embodiment provides a method for calculating an optimal scale of a spot transaction of new energy across provincial regions.
Step S1: arranging data, constructing an input database module, and making a day-ahead new energy cross-provincial region trading plan;
electric power price curve formed based on current market in the day, and new energy of this region is reportedInitial scale for source-to-provincial region electric power spot transactionAnd calculating the electricity purchasing cost based on the electricity purchasing price。
Step S2: building a tie line safety check module, checking the transaction plan in the step S1, returning to the step S1 if the check is unqualified, and readjusting the transaction plan;
the tie line power must meet the channel capability constraint:
in the formula、Is connected with a connecting lineThe minimum limit and the maximum limit of the transmission power at any moment;is the medium and long term electric power trade scale agreed by the junctor. If the link line safety check is not satisfied, the initial scale of spot transaction needs to be adjusted in time。
Step S3: constructing a receiving end area power load prediction module and a local area new energy output prediction module, and predicting the receiving end area power load and the local area new energy output condition after checking in the step S2;
short-term and ultra-short-term prediction methods based on load derivation, grey correlation, least square support vector machine and the like are used for completing daily power load predictionPhotovoltaic output predictionPrediction of wind power output。
In this embodiment, a prediction method of load derivation is adopted, as follows:
in the formulaIs as followsLoad prediction values of the points;is as followsActual load value of the point;is as followsPredicted load change rate values for the points.
The load changes in different or even violent magnitude at every moment, but the change rate of the load has a certain rule. By fitting historySampling the load curve, and performing derivation once to obtain the history corresponding to the first stepLoad change rate of a point. Wherein,，the number of days sampled. In order to improve the prediction accuracy, the historical load change rate is averaged to obtainThe predicted value of (c):
。
step S4: performing conventional power supply peak regulation demand prediction on the receiving end region in the step S3, and constructing a conventional power supply peak regulation demand prediction module of the receiving end region to obtain a conventional power supply output curve of the local region;
the power supply, the power supply and the use of the power system are completed simultaneously, and the power load has the characteristic of time variation. Due to the resource characteristics of wind and light, the output of new energy also has randomness and fluctuation. New energy electric power outside the area is introduced through spot transaction, wind power and photovoltaic output of the area are superposed, the adjusting burden of a conventional power supply of the area is increased, the conventional power supply is required to change along with the load, and output fluctuation of the new energy is required to be balanced. Obtaining a local conventional power output curve:
in the formula:、the feed-out time is positive.
Step S5: a peak regulation capability checking module is constructed, the peak regulation capability of the local area conventional power output curve in the step S4 is checked, if the checking is unqualified, the step S1 is returned, and the transaction plan is readjusted;
the peak regulation capability of the conventional unit in the local area is determined by the power supply regulation performance and is also related to the power supply structure. The regulation performance of the heat supply thermal power generating unit is poor, and the regulation performance of power supplies such as gas, pumping storage, water and electricity is good. The conventional power output needs to satisfy the peak shaving capability of the local region:
in the formula,is a local areaMaximum technical output of a conventional unit; i is the number of the conventional units in the local area;is as followsAnd (4) peak shaving depth of a conventional unit. If the peak regulation capability check is not met, the spot transaction initial scale P (t) needs to be adjusted in time.
Step S6: a local region peak shaving cost prediction module is constructed, and after the local region peak shaving cost prediction module is checked to be qualified in the step S5, the local region peak shaving cost is predicted to obtain the local region conventional unit peak shaving cost;
and according to the peak shaving requirement and the daily power generation plan of the conventional unit, the relevant regulation of the local peak shaving auxiliary service is combined. If the organic group carries out peak regulation for new energy outside the digestion area, calculating the peak regulation cost of the system generated by the peak regulation cost。
Step S7: constructing a new energy cross-regional spot shipment transaction cost check module, checking the peak shaving cost of the local conventional unit in the step S6, and executing the check if the check is qualified; and if the verification is not qualified, returning to the step S1 to readjust the transaction plan.
The electricity purchasing cost and peak shaving cost brought by the cross-regional spot transaction of the new energy are balanced with the average electricity purchasing cost of the local region:
in the formula,the average electricity purchasing cost of the conventional units in the local area is obtained. If the transaction cost check is not satisfied, the spot transaction initial scale P (t) needs to be adjusted in time.
Step S1 of the invention is based on the power price curve formed by the spot market in the day, the initial scale of the local area new energy cross-provincial region power spot transaction is reported, the power purchasing cost is calculated based on the power purchasing price, and the day-ahead new energy cross-provincial region transaction plan is made; step S2 provides that the tie line power must meet the channel capacity constraint condition, and the safety check is carried out on the tie line; step S3, based on short-term and ultra-short-term prediction methods such as cluster analysis, grey correlation, least square support vector machine and the like, completing daily power load prediction, photovoltaic output prediction and wind power output prediction, and predicting power load of a receiving end region and new energy output of a local region; step S4, the power generation, the supply and the use of the power system are simultaneously completed, the power load presents the time-varying characteristic, the output of new energy also has randomness and volatility due to the resource characteristics of wind and light, the output of the new energy is introduced outside the area through the spot transaction, the wind power and the photovoltaic output of the area are superposed, the adjusting burden of the conventional power supply of the local area is increased, the conventional power supply not only needs to change along with the load, but also needs to balance the output fluctuation of the new energy, the output curve of the conventional power supply of the local area is obtained, and the peak regulation demand of the conventional power supply of the receiving end area is predicted; step S5, because the peak regulation capability of the local conventional unit is determined by the power supply regulation performance and is related to the power supply structure, the peak regulation capability is checked, because the regulation performance of the heat supply thermal power unit is poor and the regulation performance of the power supplies such as gas, extraction and storage, water and electricity is good; step S6, according to the peak regulation demand and the generation daily plan of the conventional unit, the local peak regulation cost is predicted by combining the relevant regulations of the local peak regulation auxiliary service; step S7 is to balance the electricity purchasing cost and peak shaving cost brought by the new energy cross-regional spot shipment transaction with the local average electricity purchasing cost, and check the new energy cross-regional spot shipment transaction cost.
Example 2
Referring to fig. 1, the present embodiment provides a method for calculating an optimal scale of a spot transaction of new energy across provincial regions, which is different from embodiment 1 in that: in the present embodiment, the first and second electrodes are,
step S3: constructing a receiving end area power load prediction module and a local area new energy output prediction module, and predicting the receiving end area power load and the local area new energy output condition after checking in the step S2;
short-term and ultra-short-term prediction methods based on load derivation, grey correlation, least square support vector machine and the like are used for completing daily power load predictionPhotovoltaic output predictionPrediction of wind power output。
The prediction method by using the least square support vector machine comprises the following steps:
given training sample setWherein,counting the number of samples;is an input vector, n isA spatial dimension;is the output vector. Taking into account the non-linearity of the sample, use is made of non-linear functionsMapping each sample point toDimension (k)) Constructing a regression function for the feature space
（1）
In the formula:in order to weight the vector, the weight vector,(ii) a b is a constant value,。
substitution of linear operations with high-dimensional feature spacesAndthe dot product operation of (1). The LS-SVM optimization target error estimation part adopts a square term, the constraint condition is also constrained by inequality in the SVM as equality constraint, and the equations (2) and (3) are shown as
(2)
(3)
In the formula:is an error variable; penalty parameterControl over and overThe degree of penalty of the sample. Parameter of formula (1)And b can be estimated from equations (2) and (3).
Introducing lagrange multipliers（) Constructor function
(4)
Solving an optimal solution according to a KKT condition, and simplifying to obtain a prediction model:
（5）
wherein, K (x, x)i）=φ(χ)Tφ(xi) Is a kernel function.
A new energy trans-provincial spot transaction optimal scale evaluation device comprises a database module, a tie line safety check module, a receiving end region power utilization load prediction module, a local region new energy output prediction module, a receiving end region conventional power supply peak regulation demand prediction module, a peak regulation capacity check module, a local region peak regulation cost prediction module and a new energy trans-regional spot transaction cost check module; the database module is used for inputting data and making a day-ahead new energy cross-provincial region trading plan; the tie line safety check module is used for checking a transaction plan; the receiving end area power load prediction module and the local area new energy output prediction module are used for predicting the receiving end area power load and the local area new energy output condition; the receiving end region conventional power supply peak regulation demand prediction module is used for predicting the conventional power supply peak regulation demand of the receiving end region to obtain a local region conventional power supply output curve; the peak regulation capability checking module is used for checking the peak regulation capability of the output curve of the conventional power supply in the local area; the local region peak regulation cost prediction module is used for predicting the local region peak regulation cost to obtain the local region conventional unit peak regulation cost; the new energy cross-regional spot goods transaction cost check module is used for checking the peak shaving cost of the local conventional unit.
A computer readable storage medium comprising a memory and a processor, the memory for storing one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the new energy cross-provincial spot transaction optimal size assessment method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Claims (10)
1. A new energy cross-provincial spot transaction optimal scale assessment method is characterized by comprising the following steps: comprises the following steps:
step S1: arranging data, constructing an input database module, and making a day-ahead new energy cross-provincial region trading plan;
step S2: building a tie line safety check module, checking the transaction plan in the step S1, returning to the step S1 if the check is unqualified, and readjusting the transaction plan;
step S3: constructing a receiving end area power load prediction module and a local area new energy output prediction module, and predicting the receiving end area power load and the local area new energy output condition after checking in the step S2;
step S4: performing conventional power supply peak regulation demand prediction on the receiving end region in the step S3, and constructing a conventional power supply peak regulation demand prediction module of the receiving end region to obtain a conventional power supply output curve of the local region;
step S5: a peak regulation capability checking module is constructed, the peak regulation capability of the local area conventional power output curve in the step S4 is checked, if the checking is unqualified, the step S1 is returned, and the transaction plan is readjusted;
step S6: a local region peak shaving cost prediction module is constructed, and after the local region peak shaving cost prediction module is checked to be qualified in the step S5, the local region peak shaving cost is predicted to obtain the local region conventional unit peak shaving cost;
step S7: constructing a new energy cross-regional spot shipment transaction cost check module, checking the peak shaving cost of the local conventional unit in the step S6, and executing the check if the check is qualified; and if the verification is not qualified, returning to the step S1 to readjust the transaction plan.
2. The method according to claim 1, wherein the method comprises the following steps: in step S1, the initial scale of the local area new energy cross-provincial area electric power spot transaction is reported based on the electric power price curve formed in the spot market before the dayAnd calculating the electricity purchasing cost based on the electricity purchasing price。
3. The method according to claim 1, wherein the method comprises the following steps: in step S2, the tie line power must satisfy the channel capability constraint:
in the formula、Is connected with a connecting lineThe minimum limit and the maximum limit of the transmission power at any moment;the method is that the medium and long term electric power trade scale agreed by the tie line, if the safety check of the tie line is not satisfied, the initial scale of spot trade needs to be adjusted in time。
4. The method according to claim 1, wherein the method comprises the following steps: in step S3, the prediction of the daily electrical load is completed based on short-term and ultra-short-term prediction methods such as load derivation, gray correlation, and least square support vector machinePhotovoltaic output predictionPrediction of wind power output。
5. The method according to claim 1, wherein the method comprises the following steps: in step S4, the power supply and the power consumption of the power system are completed simultaneously, and the power load has a time-varying characteristic; new forms of energy electric power outside the district is introduced through the spot transaction, superpose this regional wind-powered electricity generation, photovoltaic and exert oneself, has increased the regulation burden of local area conventional power, and conventional power not only will follow the load change, still need balance the new forms of energy exert oneself undulant, obtains local area conventional power curve of exerting oneself:
in the formula:、the feed-out time is positive.
6. The method according to claim 1, wherein the method comprises the following steps: in step S5, the peak shaving capability of the local conventional unit is determined by the power supply regulation performance, and is also related to the power supply structure, and the output of the conventional power supply needs to satisfy the peak shaving capability of the local area:
in the formula,is a local areaMaximum technical output of a conventional unit; i is the number of the conventional units in the local area;is as followsAnd (3) adjusting the peak regulation depth of the conventional unit, and if the peak regulation capacity check is not met, adjusting the spot trade initial scale P (t) in time.
7. The method according to claim 1, wherein the method comprises the following steps: in step S6, according to the peak shaving demand and the daily power generation plan of the conventional unit, in combination with the relevant regulations of the local peak shaving auxiliary service, if the organic unit performs peak shaving for the new energy outside the consumption area, the peak shaving cost of the system generated thereby is calculated。
8. The method according to claim 1, wherein the method comprises the following steps: in step S7, the electricity purchase cost and peak shaving cost caused by the new energy cross-regional spot purchase transaction are balanced with the average electricity purchase cost of the local region:
in the formula,the average electricity purchasing cost of the conventional unit in the local area is calculated, and if the average electricity purchasing cost does not meet the transaction cost check, the spot transaction initial scale P (t) needs to be adjusted in time.
9. A new energy cross-provincial region spot transaction optimal scale evaluation device is characterized in that: the system comprises a database module, a tie line safety check module, a receiving end region power load prediction module, a local region new energy output prediction module, a receiving end region conventional power supply peak regulation demand prediction module, a peak regulation capacity check module, a local region peak regulation cost prediction module and a new energy cross-region spot transaction cost check module; the database module is used for inputting data and making a day-ahead new energy cross-provincial region trading plan; the tie line safety check module is used for checking a transaction plan; the receiving end area power load prediction module and the local area new energy output prediction module are used for predicting the receiving end area power load and the local area new energy output condition; the receiving end region conventional power supply peak regulation demand prediction module is used for predicting the conventional power supply peak regulation demand of the receiving end region to obtain a local region conventional power supply output curve; the peak regulation capability checking module is used for checking the peak regulation capability of the output curve of the conventional power supply in the local area; the local region peak regulation cost prediction module is used for predicting the local region peak regulation cost to obtain the local region conventional unit peak regulation cost; the new energy cross-regional spot goods transaction cost check module is used for checking the peak shaving cost of the local conventional unit.
10. A computer-readable storage medium comprising a memory and a processor, characterized in that: the memory is to store one or more computer program instructions, wherein the one or more computer program instructions are to be executed by the processor to implement the method of any of claims 1-8.
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