CN-115809735-B - Method, system, storage medium and equipment for creating spare market clearing model

CN115809735BCN 115809735 BCN115809735 BCN 115809735BCN-115809735-B

Abstract

The application relates to a method for creating a reserve market clearing model, which comprises the steps of obtaining actual net loads and predicted net load numbers of a power dispatching system in the same period of daily for one year, obtaining a deviation rate distribution probability table, drawing a net load prediction error distribution function according to the deviation rate distribution probability table, determining loss load cost with reserve shortage due to positive and negative errors of net load prediction, drawing a reserve value curve with reserve shortage due to the net load prediction error by combining the net load prediction error distribution function, and building a combined clearing model according to quotation and winning information in an electric energy market, reserve capacity in the reserve market and the reserve value curve. Compared with the prior art, the method considers the influence of the net load prediction accuracy on reserve, combines the reserve demand elasticity, and jointly clears the reserve market and the electric energy market, so that the clearing result of the reserve market clearing model is more feasible and reliable, and the practical application demands are met.

Inventors

ZHAO YUE
WU GUOBING
CAI QIUNA
WANG LONG
YU JUE
SONG HUI
YU PENG

Assignees

广东电网有限责任公司
广东电网有限责任公司电力调度控制中心

Dates

Publication Date: 20260512
Application Date: 20221206

Claims (7)

1. A method for creating a reserve market clearing model, adapted to a power dispatching system, comprising the steps of: Acquiring actual payload and predicted payload data of the power dispatching system in the same period of time every day in a history of one year; calculating a net load prediction deviation rate according to the actual net load of the power dispatching system in the same period every day in a history of one year and the predicted net load data to obtain a deviation rate distribution probability table, and drawing a net load prediction error distribution function according to the deviation rate distribution probability table; determining loss load cost with insufficient reserve due to positive and negative errors of the payload prediction, and drawing a demand value curve with insufficient reserve due to the payload prediction error by combining the payload prediction error distribution function; the calculation formula of the demand value in the demand value curve is as follows: Wherein, the And The required costs for positive and negative spare capacities, respectively; RPRC and RNRC respectively represent reference costs when positive standby is insufficient and negative standby is insufficient, A% represents probability of occurrence of the positive standby and the negative standby, and corresponds to occurrence probability of different payload prediction error intervals, PC is upper limit of bidding cost of electric energy spot market, PF is upper limit of cost of deep peak shaving auxiliary service market or upper limit of deep peak shaving compensation cost, and PF is lower limit of bidding cost of electric energy spot market if the electric energy spot market allows to declare negative electricity price; establishing a combined clearing model according to quotation and winning bid information in the electric energy market, spare capacity in the spare market and the demand value curve so as to determine electric energy and spare winning bid results of each unit; the combined clearing model is as follows: Wherein, the The output of the unit i corresponding to the quotation segment k in the period t is provided; The declaration cost of the quotation segment k in the period t is set i; Is the cumulative probability value; the positive standby capacity of the unit i corresponding to the period t is set; For a positive standby capacity demand of period t, The negative standby capacity corresponding to the period t of the unit i is set; negative reserve capacity demand for period t; The output of the unit i in the period t is given; And The upper and lower limits of the output of the unit i in the period t are respectively set.
2. The spare market clearing model creation method according to claim 1, wherein the model for calculating a payload prediction deviation rate from actual payload and predicted payload data is: Where η represents the predicted deviation rate of the payload, L actual represents the actual payload, and L forecast represents the predicted payload.
3. The spare market clearing model creation method according to claim 2, wherein the deviation rate distribution probability table acquisition method specifically comprises: Dividing a plurality of payload prediction error intervals with a deviation rate of 1% as an interval; And classifying the calculated payload prediction deviation rate in one year of the history according to the payload prediction error ranges of different sections to obtain a deviation rate distribution probability table.
4. A backup market clearing model creation system adapted to a power dispatching system, said system comprising: the load data acquisition module is used for acquiring the actual payload and predicted payload data of the power dispatching system in the same period of time every day for one year; The error distribution drawing function module is used for calculating a net load prediction deviation rate according to the actual net load of the power dispatching system in the same period every day of a year and the predicted net load data to obtain a deviation rate distribution probability table, and drawing a net load prediction error distribution function according to the deviation rate distribution probability table; The demand value curve drawing module is used for determining the loss load cost with insufficient reserve due to the positive and negative errors of the net load prediction, and drawing a demand value curve with insufficient reserve due to the net load prediction error by combining the net load prediction error distribution function; the calculation formula of the demand value in the demand value curve is as follows: Wherein, the And The required costs for positive and negative spare capacities, respectively; RPRC and RNRC respectively represent reference costs when positive standby is insufficient and negative standby is insufficient, A% represents probability of occurrence of the positive standby and the negative standby, and corresponds to occurrence probability of different payload prediction error intervals, PC is upper limit of bidding cost of electric energy spot market, PF is upper limit of cost of deep peak shaving auxiliary service market or upper limit of deep peak shaving compensation cost, and PF is lower limit of bidding cost of electric energy spot market if the electric energy spot market allows to declare negative electricity price; The combined clearing module creation module is used for creating a combined clearing model according to quotation and winning bid information in the electric energy market, spare capacity in the spare market and the demand value curve so as to determine electric energy and spare winning bid results of each unit; the combined clearing model is as follows: Wherein, the The output of the unit i corresponding to the quotation segment k in the period t is provided; The declaration cost of the quotation segment k in the period t is set i; Is the cumulative probability value; the positive standby capacity of the unit i corresponding to the period t is set; For a positive standby capacity demand of period t, The negative standby capacity corresponding to the period t of the unit i is set; negative reserve capacity demand for period t; The output of the unit i in the period t is given; And The upper and lower limits of the output of the unit i in the period t are respectively set.
5. The reserve market inventory model creation system of claim 4, wherein the model for calculating a payload prediction bias rate from actual payload and predicted payload data is: Where η represents the predicted deviation rate of the payload, L actual represents the actual payload, and L forecast represents the predicted payload.
6. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the method of creating a spare market clearing model according to any one of claims 1 to 5.
7. An electrical power apparatus comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the reserve market clearing model creation method of any of claims 1-5 when the computer program is executed.

Description

Method, system, storage medium and equipment for creating spare market clearing model Technical Field The application relates to the technical field of power dispatching, in particular to a method and a system for creating a reserve market clearing model, a storage medium and power equipment. Background The electric power standby market is an important mechanism for guaranteeing the operation safety of a short-term system of the system. From an economic perspective, the back-up market needs to offset the opportunistic costs of the unit due to the failure of reserved capacity to participate in the electrical energy market. From the system perspective, the spare market mainly guarantees the adequacy of the short-term capacity of the system. The load standby refers to the capacity and capacity reserved by the grid-connected main body under the dispatching demand instruction, and the power balance is maintained in response to the dispatching instruction within a specified time, but the load standby is mainly used for coping with the net load change caused by load prediction deviation. However, current spare markets employ reporting modes that are either set reporting offers or reporting no offers. The reserve lacks demand flexibility, does not incorporate actual electric energy market operating conditions, and does not reflect reserve value at different time periods. Therefore, the reserve market and the electric energy market are combined to be clear by combining the reserve demand elasticity and the supply and demand conditions of the electric energy market, the value of the reserve service can be effectively embodied, the clear result of the reserve market is more closely related to the actual supply and demand conditions of the electric power system, the reserve capacity can be provided according to the actual demand, the operation efficiency of the electric power system can be improved, and the safe and stable operation of the electric power system can be ensured. Disclosure of Invention In view of the foregoing, it is desirable to provide a method, a system, a storage medium, and a power device for creating a reserve market clearing model, which consider the influence of the accuracy of the payload prediction on reserve, combine reserve demand elasticity, and clear the reserve market and the electric energy market together, so that the clearing result of the reserve market clearing model is more feasible and reliable. The embodiment of the invention provides a method for creating a spare market clearing model, which is suitable for a power dispatching system and comprises the following steps: Acquiring actual payload and predicted payload data of the power dispatching system in the same period of time every day in a history of one year; calculating a net load prediction deviation rate according to the actual net load of the power dispatching system in the same period every day in a history of one year and the predicted net load data to obtain a deviation rate distribution probability table, and drawing a net load prediction error distribution function according to the deviation rate distribution probability table; determining loss load cost with insufficient reserve due to positive and negative errors of the payload prediction, and drawing a demand value curve with insufficient reserve due to the payload prediction error by combining the payload prediction error distribution function; and establishing a joint clearing model according to quotation and winning bid information in the electric energy market, reserve capacity in the reserve market and the demand value curve. Further, the model for calculating the predicted deviation rate of the payload from the actual payload and the predicted payload data is: Where η represents the predicted deviation rate of the payload, L actual represents the actual payload, and L forecast represents the predicted payload. Further, the method for acquiring the deviation rate distribution probability table specifically comprises the following steps: Dividing a plurality of payload prediction error intervals with a deviation rate of 1% as an interval; And classifying the calculated payload prediction deviation rate in one year of the history according to the payload prediction error ranges of different sections to obtain a deviation rate distribution probability table. Further, the calculation formula of the demand value in the demand value curve is as follows: θP=min{RPRC,A%·PC} θN=min{RNRC,A%·PF} The method comprises the steps of determining a positive standby capacity and a negative standby capacity, wherein theta P and theta N are respectively required cost of the positive standby capacity and the negative standby capacity, RPRC and RNRC respectively represent reference cost when the positive standby is insufficient and the negative standby is insufficient, A% represents probability of occurrence of the positive standby and the negative standby, probability of occurrence