CN110415138B - Electric heating combined day-ahead scheduling planning method based on peak shaving capacity bidding - Google Patents
Electric heating combined day-ahead scheduling planning method based on peak shaving capacity bidding Download PDFInfo
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y04S50/00—Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
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Abstract
The invention belongs to the field of power system dispatching automation, and particularly relates to an electrothermal combined day-ahead dispatching planning method based on peak shaving capacity bidding. The wind power station sends wind power prediction to the dispatching control system, and the photovoltaic power station sends photovoltaic power prediction to the dispatching control system; the scheduling control system receives the load prediction, formulates the load rate to be adjusted down according to the received information and sends the load rate to the peak shaving capacity bidding system; the peak shaving capacity bidding system performs information interaction with all power supplies to form bidding results; the peak shaving capacity bidding system sends bidding results to the scheduling control system, and the scheduling control system completes daily power generation planning and issues the bidding results to all power supplies. Under the condition of obtaining load prediction and uncontrollable power supply power generation prediction, the invention applies a market price mechanism to bid the peak shaving capacity of the power supply, more precisely formulates the next day power generation plan, forms a more perfect power market mechanism, and is suitable for reasonably formulating the peak shaving subsidy price.
Description
Technical Field
The invention belongs to the field of power system dispatching automation, and particularly relates to an electrothermal combined day-ahead dispatching planning method based on peak shaving capacity bidding.
Background
With the great development of new energy construction in China, the new energy power generation installed capacity in the northern area is rapidly increased in recent years due to the abundant wind energy and solar energy resources. The heating requirement in winter causes that a large number of cogeneration units cannot reduce the output of the cogeneration units because of bearing the heating task, which is an important reason for serious wind-discarding phenomenon in winter. In order to accommodate more renewable energy sources for power generation, the thermal electric unit is flexibly transformed, and an electric boiler and a heat storage system are established to consume the abandoned wind power. The existing subsidy price participating in peak shaving is formulated by an auxiliary service market, and although the method has reduced the wind abandoning rate to a certain extent, the rationality of price formulation is still to be questionable.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an electrothermal joint day-ahead scheduling planning method based on peak shaving capacity bidding. The method aims to realize that under the condition of obtaining load prediction and uncontrollable power supply power generation prediction, a market price mechanism is applied to bid the power peak shaving capacity, so that a next day power generation plan is formulated more accurately, and a more perfect power market mechanism is formed.
In order to achieve the above object, the present invention is achieved by the following technical scheme:
an electrothermal joint day-ahead scheduling planning method based on peak shaving capability bidding is characterized by comprising the following steps: the wind power station sends wind power prediction to the dispatching control system, and the photovoltaic power station sends photovoltaic power prediction to the dispatching control system; the scheduling control system receives the load prediction, formulates the load rate to be adjusted down according to the received information and sends the load rate to the peak shaving capacity bidding system; the peak shaving capacity bidding system performs information interaction with all power supplies to form bidding results; the peak shaving capacity bidding system sends bidding results to the scheduling control system, and the scheduling control system completes daily power generation planning and issues the bidding results to all power supplies.
The peak shaving capacity bidding system performs information interaction with all power supplies, and means that: the peak shaving capacity bidding system sends the load factors to be reduced to a nuclear power station, a photovoltaic power station, a wind power station, a thermoelectric unit and a pure condensing unit, each power supply carries out peak shaving capacity analysis according to the actual situation, the power supply with insufficient peak shaving capacity sends peak shaving shortages to the peak shaving capacity bidding system, and the peak shaving capacity bidding system gathers all reported peak shaving shortages to form total peak shaving shortages and sends the total peak shaving shortages to all power supplies.
All the power supplies include: nuclear power stations, photovoltaic power stations, wind power plants, thermoelectric units, pure condensing units, electric heat storage and electric energy storage.
After the load rate is reduced to the load rate to be reduced, the peak shaving capacity bidding system performs peak shaving capacity bidding on power supplies still having surplus peak shaving capacity, the peak shaving capacity bidding system performs summarizing analysis on all the bidding, arranges the bidding according to the bidding from low to high, and makes a power generation plan before the day by the capacity of total peak shaving shortage, the bidding is sold with the planned peak shaving capacity to form a total peak shaving price, and the power supplies with insufficient peak shaving capacity are distributed according to the shortage capacity to form bidding results.
The electrothermal combined day-ahead scheduling planning method based on peak shaving capacity bidding comprises the following steps:
step 1, calculating the lowest total output under the condition of no depth peak shaving in each period of the next day, and setting the lowest total output as a;
step 2, load prediction of each time period of the next day is accessed, and the total load is set as b;
step 3, finding out the time period that the total output of the lowest output is still larger than the total load (namely a > b) under the condition of no depth peak shaving, calculating the total load rate required to be adjusted downwards when the depth peak shaving is carried out, wherein r% = (a-b)/a is 100%, all power supplies in the time period have the capacity of adjusting the expected output downwards by r%, the power supplies with the capacity of not adjusting the peak shaving less than r% need to purchase the peak shaving capacity, and the redundant peak shaving capacity is required to be adjusted downwards by more than r%;
step 4, the regulation center sends the total load rate r% which needs to be regulated down in each period to a peak regulation capacity bidding system, a power supply lacking peak regulation capacity reports the peak regulation deficiency to the peak regulation capacity bidding system, and the system gathers the peak regulation deficiency to form the total peak regulation deficiency;
step 5, using the thermal power unit and the thermoelectric unit with the electric energy storage, the electric heat storage and the surplus peak shaving capacity as power supplies with the surplus peak shaving capacity to offer the total peak shaving shortage, arranging the prices from low to high, forming an offer list until the peak shaving capacity reaches the total peak shaving shortage, and selling the offers to the power supplies with the shortage peak shaving capacity;
step 6, the power supply with surplus peak regulation capacity, which is excessively high in quotation and does not enter the peak regulation range, only needs to ensure that the peak regulation capacity reaches r percent, and the surplus peak regulation capacity is reserved for standby except electric energy storage and electric heat storage and is not considered in the planning of a scheduling plan before the day;
step 7, in the next day of actual scheduling, if the actual output of power supplies without peak shaving capability such as wind power is larger than the predicted output, continuing to purchase the peak shaving capability from the surplus peak shaving capability power supplies which are excessively high and do not enter the peak shaving range, arranging the prices from low to high, and allocating the cost by the power supplies with inaccurate prediction according to the predicted error;
and 8, in the actual scheduling of the next day, if the actual load is smaller than the load prediction, further increasing the total load rate r needed to be adjusted downwards, purchasing peak shaving capacity from the power supply with surplus peak shaving capacity which is excessively high and does not enter the peak shaving range, arranging the price from low to high, and allocating the cost from the power supply which is not adjusted downwards to r% according to peak shaving shortage electric quantity.
Step 1, calculating the lowest total output under the condition of no depth peak shaving in each period of the next day: the pure thermal power generating unit and the thermoelectric unit are calculated according to 50% of load rate, the nuclear power is calculated according to 77% of load rate, and the wind power and the photovoltaic are calculated according to predicted power generation.
The invention has the advantages and beneficial effects that:
the invention provides an electrothermal combined day-ahead scheduling planning method based on peak shaving capacity bidding, which uses a market price mechanism to bid the peak shaving capacity of a power supply under the condition of obtaining load prediction and uncontrollable power supply power generation prediction, so as to more accurately formulate a next day power generation plan and form a more perfect power market mechanism. The method is suitable for reasonably formulating the peak regulation patch price.
Drawings
In order to facilitate the understanding and practice of the invention, those of ordinary skill in the art will now make further details with reference to the drawings and detailed description, it being understood that the scope of the invention is not limited to the specific description.
FIG. 1 is a schematic diagram of a system architecture of the present invention;
FIG. 2 is a schematic flow chart of the present invention;
FIG. 3 is a schematic diagram showing the calculation of the total load factor to be adjusted downward according to the present invention;
FIG. 4 is a schematic diagram of a total peak shaving deficiency calculation according to the present invention;
FIG. 5 is a schematic diagram of a total peak shaving absence schedule;
fig. 6 is a schematic diagram of an example of the total peak shaving and absence schedule of the present invention.
In the figure: the system comprises a dispatching control system 1, wind power prediction 2, photovoltaic power prediction 3, electric heat storage 4, peak shaving capacity bidding system 5, electric energy storage 6, nuclear power station 7, photovoltaic power station 8, wind power plant 9, thermoelectric unit 10, pure condensing unit 11, bidding result 12, load factor 13 to be adjusted downwards and load prediction 14.
Detailed Description
The invention relates to an electrothermal combined day-ahead scheduling planning method based on peak shaving capacity bidding, which comprises the following steps:
1. calculating the lowest total output under the condition of no deep peak shaving in each period of the next day, calculating the pure condensing power unit and the thermoelectric unit according to 50% load rate, calculating the nuclear power according to 77% load rate, calculating the wind power and the photovoltaic according to predicted power generation, and setting the lowest total output as a;
2. accessing load prediction of each time period of the next day, and setting the total load as b;
3. finding out the time period that the minimum total output is still greater than the total load (namely a > b) under the condition of no depth peak shaving, calculating the total load rate required to be adjusted downwards when the depth peak shaving is carried out, wherein r% = (a-b)/a is 100%, all power supplies in the time period have the capacity of adjusting the predicted output downwards by r%, the power supplies with the insufficient peak shaving capacity less than r% need to purchase the peak shaving capacity, and the redundant peak shaving capacity can be adjusted downwards by more than r%; as shown in fig. 3.
4. The regulation center sends the total load rate r% which needs to be regulated down in each period to a peak regulation capacity bidding system, a power supply lacking peak regulation capacity reports own peak regulation deficiency to the peak regulation capacity bidding system, and the system gathers the peak regulation deficiency to form total peak regulation deficiency; as shown in fig. 4.
5. The thermal power unit and the thermoelectric unit with the electric energy storage, the electric heat storage and the surplus peak shaving capacity are used as power supplies with the surplus peak shaving capacity to bid the total peak shaving shortage, the price is arranged from low to high to form a quotation table until the peak shaving capacity reaches the total peak shaving shortage, and the quotation table is sold to the power supplies with the shortage peak shaving capacity; as shown in fig. 5.
6. The power supply with surplus peak regulation capacity, which is excessively high in quotation and does not enter the peak regulation range, only needs to ensure that the peak regulation capacity reaches r percent, and the surplus peak regulation capacity is reserved for standby except electric energy storage and electric heat storage and is not considered in the planning of a scheduling plan before the day;
7. in the next day actual scheduling, if the actual output of a power supply without peak shaving capability, such as wind power, is larger than the predicted output, the peak shaving capability is required to be purchased from a surplus peak shaving power supply which is excessively high and does not enter the peak shaving range, the price is arranged from low to high, and the cost is shared by power supplies with inaccurate prediction according to the prediction error;
8. in the actual scheduling of the next day, if the actual load is smaller than the load prediction, the total load rate r needed to be adjusted is further increased, the peak shaving capacity is purchased from the power supply with the surplus peak shaving capacity, which is excessively high and does not enter the peak shaving range, the price is arranged from low to high, and the cost is shared by the power supply which is not adjusted to r% from low according to the peak shaving shortage electric quantity.
The invention provides an electrothermal combined day-ahead scheduling planning method based on peak shaving capacity bidding, which mainly comprises the following mechanisms: the system comprises a dispatching control system 1, wind power prediction 2, photovoltaic power prediction 3, electric heat storage 4, peak shaving capacity bidding system 5, electric energy storage 6, nuclear power station 7, photovoltaic power station 8, wind power plant 9, thermoelectric unit 10, pure condensing unit 11, bidding result 12, load factor 13 to be adjusted downwards and load prediction 14.
Firstly, a wind power plant 9 sends wind power prediction 2 to a dispatching control system 1, a photovoltaic power station 8 sends photovoltaic power prediction 3 to the dispatching control system 1, the dispatching control system 1 receives load prediction 14, and then establishes a load factor 13 to be regulated down according to the received information and sends the load factor 13 to a peak shaving capacity bidding system 5. And then, the peak shaving capacity bidding system 5 sends the load ratio 13 to be reduced to all power supplies, including a nuclear power station 7, a photovoltaic power station 8, a wind power plant 9, a thermoelectric unit 10 and a pure condensing unit 11, each power supply analyzes the peak shaving capacity according to the actual situation, the power supplies with insufficient peak shaving capacity send the peak shaving deficiency to the peak shaving capacity bidding system 5, and the peak shaving capacity bidding system 5 gathers all the reported peak shaving deficiency to form a total peak shaving deficiency and send the total peak shaving deficiency to all the power supplies, including the nuclear power station 7, the photovoltaic power station 8, the wind power plant 9, the thermoelectric unit 10, the pure condensing unit 11, the electric heat storage 4 and the electric energy storage 6. Finally, after the load factor is reduced to the load factor 13 to be reduced, the power supply with surplus peak regulation capacity carries out peak regulation capacity quotation, the peak regulation capacity bidding system 5 carries out summarization analysis on all quotations, the quotations are arranged from low to high, the capacity from the total peak regulation to the shortage is cut off to be brought into the power generation plan formulation before the day, the planned peak regulation capacity is sold in the respective quotations, the total peak regulation price is formed, and the power supply with insufficient peak regulation capacity is allocated according to the shortage capacity, so as to form the bidding result 12. The peak shaving capacity bidding system 5 sends the bidding result 12 to the dispatching control system 1, and the dispatching control system 1 completes the daily power generation planning and issues all power sources.
As shown in fig. 2, the wind power of the wind farm 9 in the period X predicts that 2 is 200MW, and sends it to the dispatch control system 1; the photovoltaic power station 8 predicts that the photovoltaic power 3 in the X period is 100MW and sends the power to the dispatching control system 1; the load forecast 14 for period X is 800MW, which is sent to the dispatch control system 1. The scheduling control system 1 establishes the load factor 13 to be adjusted down to 20% according to the received information and sends the load factor to the peak shaving capacity bidding system 5. The peak shaving capacity bidding system 5 sends a command for reducing the load factor by 20% to all power sources including a nuclear power station 7, a photovoltaic power station 8, a wind farm 9, a thermoelectric unit 10 and a pure condensing unit 11. The peak regulation capacity analysis is carried out on each power supply according to the actual situation, the power shortage of the nuclear power station 7 is 20MW, the power shortage of the photovoltaic power station 8 is 20MW, the power shortage of the wind power station 9 is 40MW, the thermoelectric unit 10 and the pure condensing unit 11 are free from power shortage, the peak regulation capacity bidding system 5 gathers all reported peak regulation shortage to form total peak regulation shortage 80MW, and then the total peak regulation shortage is sent to all power supplies (including the nuclear power station 7, the photovoltaic power station 8, the wind power station 9, the thermoelectric unit 10, the pure condensing unit 11, the electric heat storage 4 and the electric energy storage 6). After the load factor is reduced to the load factor 13 to be reduced, the power supply with the surplus peak shaving capacity carries out peak shaving capacity quotation, and the quotation of the thermoelectric unit 10 is 0-20MW:0.6 yuan/kW; 20MW-40MW:1.2 yuan/kW; 40MW-60MW:2.2 yuan/kW, price of pure condensing unit 11 is 0-20MW:0.5 yuan/kW; 20MW-30MW:1 yuan/kW; 30MW-50MW:2 yuan/kW, and the quotation of the electric heat storage 4 is 0-10MW:0.7 yuan/kW, the quotation of the electric energy storage 6 is 0-10MW:0.8 yuan/kW. The peak shaving capacity bidding system 5 performs a summary analysis on all the offers, ranks the offers from low to high, and the capacity up to 80MW of the total peak shaving shortage is included in the day-ahead power generation plan, the peak shaving capacity listed in the plan is sold as the respective offer to form the total peak shaving price, and the power supply with insufficient peak shaving capacity is shared according to the shortage capacity to form the bidding result 12. As shown in fig. 6.
The peak shaving capacity bidding system 5 sends the bidding result 12 to the dispatching control system 1, and the dispatching control system 1 completes the daily power generation planning and issues the power. Wherein the total peak regulation cost is 59000 yuan, the average cost is 737.5 yuan/MW, the wind power plant 9 bears 29500 yuan, the photovoltaic power station 8 bears 14750 yuan, and the nuclear power station 7 bears 14750 yuan.
Claims (1)
1. An electrothermal joint day-ahead scheduling planning method based on peak shaving capability bidding is characterized by comprising the following steps: the wind power plant (9) sends wind power prediction (2) to the dispatching control system (1), and the photovoltaic power station (8) sends photovoltaic power prediction (3) to the dispatching control system (1); the scheduling control system (1) receives the load prediction (14), formulates a load rate (13) to be adjusted downwards according to the received information and sends the load rate to the peak shaving capacity bidding system (5); the peak shaving capacity bidding system (5) performs information interaction with all power supplies to form a bidding result (12); the peak shaving capacity bidding system (5) sends bidding results (12) to the scheduling control system (1), the scheduling control system (1) completes the daily power generation planning and issues the bidding results to all power supplies; the peak shaving capacity bidding system (5) performs information interaction with all power supplies, which means that: the peak shaving capacity bidding system (5) sends a load ratio (13) to be reduced to a nuclear power station (7), a photovoltaic power station (8), a wind power station (9), a thermoelectric unit (10) and a pure condensing unit (11), each power supply analyzes the peak shaving capacity according to the actual situation, the power supply with insufficient peak shaving capacity sends peak shaving shortage to the peak shaving capacity bidding system (5), and the peak shaving capacity bidding system (5) gathers all reported peak shaving shortage to form total peak shaving shortage and sends the total peak shaving shortage to all the power supplies; all the power supplies include: a nuclear power station (7), a photovoltaic power station (8), a wind power station (9), a thermoelectric unit (10), a pure condensing unit (11), electric heat storage (4) and electric energy storage (6); after the load rate is reduced to the load rate (13) to be reduced, the peak shaving capacity bidding system (5) performs peak shaving capacity quotation on the power supply with the surplus peak shaving capacity, the peak shaving capacity bidding system (5) performs summarization analysis on all quotations, arranges the quotations from low to high, and the capacity from the total peak shaving to the shortage is brought into the day-ahead power generation plan, the planned peak shaving capacity is sold in the respective quotations to form the total peak shaving price, and the power supply with the shortage of the peak shaving capacity is allocated according to the shortage capacity to form a bidding result (12);
the electrothermal combined day-ahead scheduling planning method based on peak shaving capacity bidding comprises the following steps:
step 1, calculating the lowest total output under the condition of no depth peak shaving in each period of the next day, and setting the lowest total output as a; the calculation of the lowest total output under the condition of no depth peak shaving in each period of the next day is as follows: the pure thermal power generating unit and the thermoelectric unit are calculated according to 50% load rate, the nuclear power is calculated according to 77% load rate, and the wind power and the photovoltaic are calculated according to predicted power generation; step 2, load prediction of each time period of the next day is accessed, and the total load is set as b; step 3, finding out the time period that the lowest total output is still larger than the total load under the condition of no depth peak shaving, namely a > b, calculating the total load rate required to be adjusted downwards when the depth peak shaving is carried out, wherein r% = (a-b)/a is 100%, all power supplies in the time period have the capacity of adjusting the expected output downwards by r%, the power supplies with the capacity of not adjusting the peak shaving less than r% need to purchase the peak shaving capacity, and the redundant peak shaving capacity is required to be compared with the capacity of adjusting the peak shaving more than r%; step 4, the regulation center sends the total load rate r% which needs to be regulated down in each period to a peak regulation capacity bidding system, a power supply lacking peak regulation capacity reports the peak regulation deficiency to the peak regulation capacity bidding system, and the system gathers the peak regulation deficiency to form the total peak regulation deficiency; step 5, using the thermal power unit and the thermoelectric unit with the electric energy storage, the electric heat storage and the surplus peak shaving capacity as power supplies with the surplus peak shaving capacity to offer the total peak shaving shortage, arranging the prices from low to high, forming an offer list until the peak shaving capacity reaches the total peak shaving shortage, and selling the offers to the power supplies with the shortage peak shaving capacity; step 6, the power supply with surplus peak regulation capacity, which is excessively high in quotation and does not enter the peak regulation range, only needs to ensure that the peak regulation capacity reaches r percent, and the surplus peak regulation capacity is reserved for standby except electric energy storage and electric heat storage and is not considered in the planning of a scheduling plan before the day; step 7, in the actual scheduling of the next day, if the actual output of the power supply with the peak shaving capability is larger than the predicted output, continuing to purchase the peak shaving capability from the power supply with the surplus peak shaving capability, which is excessively high and does not enter the peak shaving range, wherein the price is arranged from low to high, and the cost is shared by the power supply with inaccurate prediction according to the prediction error; and 8, in the actual scheduling of the next day, if the actual load is smaller than the load prediction, further increasing the total load rate r needed to be adjusted downwards, purchasing peak shaving capacity from the power supply with surplus peak shaving capacity which is excessively high and does not enter the peak shaving range, arranging the price from low to high, and allocating the cost from the power supply which is not adjusted downwards to r% according to peak shaving shortage electric quantity.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103824235A (en) * | 2014-03-18 | 2014-05-28 | 国家电网公司 | Method for making power generation absorption scheme for new energy power stations based on price bidding |
| CN107153986A (en) * | 2017-05-09 | 2017-09-12 | 西安交通大学 | A kind of Generation Rights Trade method for promoting new energy to dissolve |
| WO2018059096A1 (en) * | 2016-09-30 | 2018-04-05 | 国电南瑞科技股份有限公司 | Combined decision method for power generation plans of multiple power sources, and storage medium |
| CN109360030A (en) * | 2018-11-13 | 2019-02-19 | 清华大学 | Electricity transaction go out clearly with pricing method and system |
| CN109829624A (en) * | 2018-12-29 | 2019-05-31 | 华北电力大学 | A kind of wind-powered electricity generation cooperative game climbing control method and device |
-
2019
- 2019-06-17 CN CN201910521409.0A patent/CN110415138B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103824235A (en) * | 2014-03-18 | 2014-05-28 | 国家电网公司 | Method for making power generation absorption scheme for new energy power stations based on price bidding |
| WO2018059096A1 (en) * | 2016-09-30 | 2018-04-05 | 国电南瑞科技股份有限公司 | Combined decision method for power generation plans of multiple power sources, and storage medium |
| CN107153986A (en) * | 2017-05-09 | 2017-09-12 | 西安交通大学 | A kind of Generation Rights Trade method for promoting new energy to dissolve |
| CN109360030A (en) * | 2018-11-13 | 2019-02-19 | 清华大学 | Electricity transaction go out clearly with pricing method and system |
| CN109829624A (en) * | 2018-12-29 | 2019-05-31 | 华北电力大学 | A kind of wind-powered electricity generation cooperative game climbing control method and device |
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