CN112598481B - Computer implementation method for inter-provincial short-term clean energy power transaction recommendation - Google Patents
Computer implementation method for inter-provincial short-term clean energy power transaction recommendation Download PDFInfo
- Publication number
- CN112598481B CN112598481B CN202011611604.1A CN202011611604A CN112598481B CN 112598481 B CN112598481 B CN 112598481B CN 202011611604 A CN202011611604 A CN 202011611604A CN 112598481 B CN112598481 B CN 112598481B
- Authority
- CN
- China
- Prior art keywords
- power
- short
- term
- recommendation
- rate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0206—Price or cost determination based on market factors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0611—Request for offers or quotes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
-
- 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
- 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
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- 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
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S50/00—Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
- Y04S50/10—Energy trading, including energy flowing from end-user application to grid
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S50/00—Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
- Y04S50/14—Marketing, i.e. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Human Resources & Organizations (AREA)
- Tourism & Hospitality (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Technology Law (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Data Mining & Analysis (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention relates to a computer implementation method for recommending short-term clean energy electric power trading among provinces, which is characterized in that short-term power generation prediction information and weather forecast information are used as a basis for establishing short-term clean energy electric power trading recommendation among the provinces, an inter-province short-term clean energy electric power trading recommendation database and a clean energy basic database which can be stored/read by a computer are generated, inter-province historical trading information, power transmission channel space capacity and clean energy consumption conditions are analyzed, and surplus trading electric power curves recommended by inter-province short-term wind power and photovoltaic power are predicted; meanwhile, considering the delay characteristic of water resource power generation, a subentry index is established for the hydropower transaction recommendation rate, and a clean energy recommendation result is generated. The method can obtain quantitative recommendation information of wind power and photovoltaic short-term trading power curves of each province, can obtain qualitative recommendation information of each province and hydropower short-term trading, can obtain time-sharing average electricity price information of inter-province clean energy trading, improves the consumption level of clean energy, and improves the peak regulation capability of a power grid.
Description
Technical Field
The invention belongs to the technical field of inter-provincial clean energy electric power trading, and particularly relates to a computer implementation method for inter-provincial short-term clean energy electric power trading recommendation.
Background
At present, provincial short-term clean energy power trading is mainly based on a spot system to conduct trading organization. The spot market mainly develops day-ahead, day-within and real-time electric energy trading, is an important component of a complete electric power market system, provides a marketization means for electric power short-term supply and demand balance, realizes electric power short-term supply and demand balance, helps further stabilize medium and long term market, realizes connection and coordination of medium and long term market and system operation, and ensures safe and efficient operation of a power grid. The short-term clean energy electric power transaction between provinces is beneficial to solving the phenomenon that renewable resources in China are not matched with loads, relieving the problems of wind power abandonment, photovoltaic abandonment and water and electricity abandonment, and simultaneously being beneficial to obtaining more preferential electric power and electricity supply.
The provincial short-term clean energy electric power transaction needs to be compatible with the characteristics of clean energy volatility, randomness and the like, and needs to be close to real time as much as possible and closely track the running state and possible changes of an electric power system. However, the construction of the cross-provincial electric power spot market in China is still in the initial stage of construction, on one hand, due to the lack of predictive analysis of inter-provincial meteorological information and clean energy power generation information and the lack of analysis and dynamic perception of short-term power generation and power transmission capability of an external network, surplus high-quality electric power resources in the provinces are difficult to be absorbed effectively, the problem that a large amount of clean energy cannot be generated but is not used exists, and the situations of clean energy fluctuation and power supply and demand surplus are not formed; on the other hand, effective excavation of transaction space is lacked, the available power transmission space in the current area is not dynamically grasped in real time, and the power transmission channel space is difficult to be fully and reasonably utilized.
Therefore, how to recommend short-term clean energy transactions among provinces, overall network adjustment resources are planned, wind power abandonment, water power abandonment and photovoltaic abandonment are reduced, scientificity and rationality of the spot market transactions of clean energy electric power among provinces are effectively improved, and the method is a subject which needs to be researched and solved urgently.
Disclosure of Invention
Aiming at the technical problems, the invention mainly aims to solve the problems that the transaction organization is not high in timely effectiveness and lacks of effective recommendation means to carry out assistant decision analysis in the provincial short-term power transaction organization, and secondly solves the problem of low effective utilization rate of a power transmission channel. The technical scheme adopted by the invention is as follows:
a computer implementation method for inter-provincial short-term clean energy electric power transaction recommendation is characterized in that short-term weather forecast information and short-term power generation forecast information are used as a basis for establishing inter-provincial short-term clean energy electric power transaction recommendation, a database which can be stored/read by a computer is generated, inter-provincial electric power historical transaction information, power transmission channel space capacity and clean energy consumption conditions are analyzed, and inter-provincial wind power and photovoltaic short-term surplus generated power transaction electric power curves are predicted and recommended; considering the delay characteristic of water resource power generation, establishing and calculating a hydropower transaction recommendation rate index; analyzing inter-provincial power transaction historical information, and recommending the node average transaction electricity price of inter-provincial clean energy; and finally, generating a recommendation result of the inter-provincial clean energy electric power transaction.
Preferably, the method comprises:
generating a short-term clean energy power transaction recommendation database which can be stored/read by a computer on the basis of basic information of a power transmission channel, overhaul information of the power transmission channel and historical transaction curve information of the power transmission channel; generating a clean energy basic database which can be stored/read by a computer based on the historical contemporaneous wind curtailment rate and the historical contemporaneous curtailment rate of wind power and photovoltaic, the historical contemporaneous electricity load, the short-term predicted electricity load, the wind power predicted power generation power and the photovoltaic predicted power generation power of the wind power and photovoltaic, and the short-term predicted data of water resources, the historical contemporaneous rainfall, the early rainfall accumulation data and the water and electricity consumption data;
calculating the residual available power transmission space of a power transmission channel and calculating the node average trading power price of each province and each type of clean energy by using an inter-province short-term clean energy power trading recommendation database; and (c) a second step of,
calculating a predicted wind abandoning rate, a predicted light abandoning rate, time-sharing wind power short-term surplus generated power and time-sharing photovoltaic short-term surplus generated power by utilizing a clean energy basic database; and (c) a second step of,
calculating wind power recommended generating power and photovoltaic recommended generating power by utilizing the time-sharing wind power short-term surplus generating power, the time-sharing photovoltaic short-term surplus generating power and the remaining available power transmission space of the power transmission channel; and the number of the first and second groups,
calculating the short-term transaction recommendation rate of provincial hydropower by utilizing a clean energy basic database; and (c) a second step of,
and generating a clean energy recommendation result by utilizing the wind power recommended generated power, the photovoltaic recommended generated power and the hydropower short-term transaction recommendation rate.
The invention discloses a computer implementation method for recommending provincial short-term clean energy electric power trading. The technical terms involved in the present invention are explained as follows:
1. the transmission channel has the available transmission space.
The used power transmission space of the power transmission channels is the space distribution situation of the used power in time sharing every day.
The remaining available power transmission space of the power transmission channel is the daily time-sharing available power space distribution condition.
2. The node average trades the electricity prices.
The calculation of the node average transaction electricity price of wind power, photovoltaic and hydropower is helpful for mastering the transaction electricity price conditions of different resources in different time periods, the generation and power utilization resources are effectively promoted to participate in peak shaving through price signals, the scheduling operation pressure is reduced by giving excess income to a market main body with flexible adjustment capacity, and therefore the consumption of new energy is promoted.
3. Wind power short-term surplus generated power and photovoltaic short-term surplus generated power.
The short-term surplus generated power of the inter-provincial wind power is calculated based on the predicted generated power of the wind power and the predicted wind abandoning rate, the calculation result is the daily wind power time-sharing surplus generated power, and the time interval is generally 15 minutes by one point; the wind abandon rate is predicted in time-sharing mode every day, and the wind abandon rate is calculated according to the change of the electric load and the historical wind abandon rate condition and is the wind abandon condition in time-sharing mode.
Calculating the photovoltaic short-term surplus generated power based on the predicted light rejection rate and the photovoltaic predicted generated power, wherein the calculation result is the daily photovoltaic time-sharing surplus generated power, and the time interval is generally 15 minutes by one point; the light abandonment rate is predicted in time-sharing mode every day, calculation is carried out according to the change of the electric load and the historical light abandonment rate, and the result is the predicted light abandonment rate in time-sharing mode.
4. Wind power recommended power generation power and photovoltaic recommended power generation power.
The generated power which can be transmitted by wind power and photovoltaic is closely related to the residual available power transmission space of the power transmission channel, and the utilization conditions of different channels in different time periods determine whether the transmission of the surplus generated power can be met. Therefore, the surplus generated power is compared with the remaining available power transmission space of the power transmission channel every day in a time-sharing manner, and the generated power in the transmittable range is the transmittable wind power recommended generated power and photovoltaic recommended generated power.
5. Hydroelectricity short term trade recommendation rate.
And respectively calculating five subentries, namely short-term rainfall forecast change rate, early-stage rainfall accumulated change rate, forecast water abandon rate, water and power installed capacity ratio and power transmission capacity recommendation rate of a power transmission channel, and finally performing weighted calculation.
Short-term predicted rate of change of rainfall: the change condition is analyzed by taking the day as a unit, a time difference between rainfall and power generation needs to be considered during recommendation, after the rainfall is finished, the rainfall needs to flow into a reservoir, and a certain time is needed in the middle to enable the power generation to be carried out, so that the recommendation time of hydropower is the recommendation of the next few days after the water resource is generated greatly.
Rainfall accumulation rate at the early stage: the early rainfall change condition is embodied, the later power generation condition can be influenced, the early rainfall is large, the later hydroelectric power can be increased, and the early accumulation time is configured to be 7 days.
Predicting the water abandoning rate: under the condition of monthly water resource consumption level, the lower the predicted value is, the better the consumption is; the higher the predicted value is, the worse the consumption is, and the higher the inter-provincial electric power trade recommendation degree is.
The ratio of installed capacity of water to installed capacity: the proportion of the water-saving electric machine capacity to the total installed capacity of the water-saving electric machine is higher, and the recommendation degree is higher.
Power transmission channel power transmission capacity recommendation rate: converting the electric power into electric power, and calculating according to the ratio of the residual transmissible electric power to the total transmitted electric power.
The method is characterized in that weather forecast information and power generation forecast information of short-term clean energy are more helpful for people to know the characteristic of rapid change of clean energy, therefore, the method takes the short-term power generation forecast information and the weather forecast information as a basis for establishing inter-provincial short-term clean energy power trading recommendation, analyzes inter-provincial historical trading information, power transmission channel space capacity and clean energy consumption conditions on the basis, predicts and recommends surplus trading power curves recommended by inter-provincial short-term wind power and photovoltaic, and meanwhile, fully considers the delay characteristic of water resource power generation, and provides a qualitative recommendation method for the hydropower short-term trading recommendation through a hydropower specific recommendation algorithm. The short-term power transaction recommendation model established by the method enables the tradable situation of the clean energy between the provinces of a market main body to be changed from unknown to known, can acquire quantitative recommendation information of wind power and photovoltaic short-term transaction power curves of the provinces, can acquire qualitative recommendation information of water power short-term transactions of the provinces, and can acquire time-sharing average power price information of the clean energy transaction between the provinces, so that the method has important value for promoting positive organization of delivery transaction of the clean energy, realizing short-term supply and demand balance of power, improving the consumption level of the clean energy, improving the peak regulation capability of a power grid, and comprehensively exerting economic, social and environmental benefits of the power transaction.
The invention has the beneficial effects that:
in the past, the short-term clean energy power transaction between provinces is totally dependent on experience, and an auxiliary analysis means is not provided. The invention provides a method for recommending inter-provincial short-term clean energy electric power trading, which has important effects on improving the scientificity and rationality of inter-provincial clean energy electric power spot market trading, improving the consumption of clean energy, improving the peak regulation capacity of a power grid, improving the utilization rate of a power transmission space, reducing the electricity purchasing cost and realizing win-win of electricity generation and electricity utilization. The main advantages are as follows:
1) A method for recommending short-term wind power and photovoltaic power generation in provinces is provided, and auxiliary decision analysis means and quantitative decision basis are provided for short-term new energy trading in provinces by analyzing surplus recommended power generation and node average trading price.
2) The short-term hydropower trading recommendation method between provinces is provided, the storability of water resources and the generating hysteresis are fully considered, a specific short-term trading recommendation method is provided for hydropower trading, and a qualitative aid decision analysis means is provided for the short-term hydropower trading between provinces.
3) The transaction recommendation method fully analyzes and effectively utilizes the power transmission space of the power transmission channel, and has important values for guaranteeing the operation of the channel and managing the blockage of the channel.
4) And calculating the node average trading power price of each province of clean energy according to the historical trading price, and providing a price wind vane for the organization trading.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are specific embodiments of the invention, and that other drawings within the scope of the present application can be obtained by those skilled in the art without inventive effort.
FIG. 1 is a logic block diagram of steps of an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention.
FIG. 1 is a logic block diagram of steps of an embodiment of the present invention. A computer-implemented method of inter-provincial short-term clean energy electricity trade recommendation, comprising the steps of:
step 1, generating a short-term clean energy electric power transaction recommendation database in province which can be stored/read by a computer based on basic information of a power transmission channel, overhaul information of the power transmission channel and historical transaction curve information of the power transmission channel; and analyzing and calculating the used power transmission space of the power transmission channel and the residual available power transmission space of the power transmission channel.
The method for calculating the residual available power transmission space of the power transmission channel comprises the following steps: and analyzing the transaction curve information in the transaction plan, and performing time-sharing accumulation on the daily 24-hour transaction result curve to obtain the used power transmission space of each power transmission channel, wherein the area between the maximum power transmission space of the power transmission channel and the used power transmission space of the power transmission channel is the residual available power transmission space of the power transmission channel. The calculation formula is as follows:
in the formula: n- -number of transactions completed for the transmission channel, PA k -at the kth moment, the transmission channel has a remaining available transmission space, PM k -kth instant, power transmission channel maximum power transmission space, PC k -at the kth moment, the transmission channel occupied by the power having completed the transaction is used for transmission space.
The calculation method of the node average trading electricity price comprises the following steps: and (4) counting historical spot transaction information, and analyzing and calculating node average transaction electricity prices of various provinces and various clean energy sources based on inter-province historical transaction and settlement data. The calculation formula of the node average transaction electricity price is as follows:
in the formula: n- -all provinces number, pr i - -at the ith moment, the average trade price of electricity, fe i -at the ith moment, each province deals with the electricity charge, eq i -at the ith moment, each province deals with the electricity.
By utilizing the formula, the average trading power price of each province wind power node, the average trading power price of each province photovoltaic node, the average trading power price of each province water and power node and the average trading power price of each province clean energy node can be respectively calculated.
And 2, generating a clean energy basic database which can be stored/read by a computer based on the historical synchronous wind abandoning rate and the historical synchronous light abandoning rate of the wind power and the photovoltaic, the historical synchronous power load, the short-term predicted power load, the wind power predicted power generation power and the photovoltaic predicted power generation power.
For wind power and photovoltaic, calculating a predicted wind abandoning rate and a predicted light abandoning rate based on a historical synchronous wind abandoning rate, a historical synchronous light abandoning rate, a historical synchronous power load and a short-term predicted power load; and calculating the short-term surplus power generation power of wind power and the short-term surplus power generation power of photovoltaic at the time of province by taking the day as a recommendation unit and taking one value every 15 minutes based on the predicted power generation power and the predicted light rejection rate of wind power and photovoltaic at each province.
1) The short-term surplus generated power of the wind power is calculated as follows:
WR j ＝WRH j *(PLH j /PL j )；
PWR j ＝PWF j *WR j ；
in the formula: WR (pulse Width modulation) j -predicting the wind curtailment rate at the jth moment; WRH j -at the jth moment, historical contemporaneous wind abandonment rates; PLH j -historical contemporaneous electrical load at time jth; PL j -a short-term prediction of the electricity load at the jth instant; PWR j -wind short-term surplus generated power at jth moment; PWF j -the wind power predicts the generated power at the jth moment.
2) The photovoltaic short-term surplus generated power is calculated as follows:
SR j ＝WSH j *(PLH j /PL j )；
PSR j ＝PSF j *SR j ；
in the formula: SR j -predicting the light rejection at the jth moment; WSH j -the historical contemporaneous extinction rate at the jth moment; PLH j -the jth moment, historical contemporaneous electrical load; PL j -a j-th moment, short-term prediction of the electrical load; PSR j At the jth moment, photovoltaic short-term surplus generated power; PSF j And the photovoltaic prediction power generation power at the jth moment.
For wind power and photovoltaic, according to the short-term surplus generated power and the remaining available transmission space of the transmission channel, taking a day as a recommendation unit, taking one value every 15 minutes at 96 points every day, comparing the short-term surplus generated power of the wind power and the short-term surplus generated power of the photovoltaic with the remaining available transmission space of the transmission channel at the corresponding moment, and calculating the recommended generated power of the wind power and the recommended generated power of the photovoltaic. The wind power recommended power generation power and the photovoltaic recommended power generation power are calculated as follows:
PW k ＝min(PWR k ，PA k )；
PS k ＝min(PSR k ，PA k )；
in the formula: PWR k At the kth moment, the short-term surplus generated power of the wind power is generated; PA k -at a kth moment, the transmission channel has a remaining available transmission space; PW (pseudo wire) k -at the kth moment, the wind power recommended generated power; PSR k -at the kth moment, photovoltaic short-term surplus generated power; PS (polystyrene) with high sensitivity k -at the kth moment, the photovoltaic recommended generated power.
And 3, generating a clean energy basic database which can be stored/read by a computer based on short-term forecast data of water resources, historical contemporaneous rainfall, early rainfall accumulation data and hydropower consumption data.
For hydropower, comprehensive recommendation evaluation is carried out on the basis of short-term prediction data and historical contemporaneous rainfall of water resources, consideration is given to the retrogradation of water resource power generation, early rainfall accumulation data and hydropower consumption data, a percentage evaluation mode is adopted, and a hydropower short-term transaction recommendation rate model is established by taking a day as a unit. One primary index and five secondary indexes are established. The first-level index recommendation rate is the sum of the second-level index recommendation rates; and each level of index is provided with corresponding weight, and the first level index weight is the sum of the second level index weights.
And establishing a provincial hydropower short-term trading recommendation rate as a first-level index (L1).
Establishing a secondary index of the short-term trading recommendation degree of hydropower:
the rainfall capacity prediction method comprises the following steps of (1P 1) a rainfall capacity short-term prediction change rate (L1P 1), a rainfall capacity early accumulation change rate (L1P 2), a prediction water abandon rate (L1P 3), a transmission channel transmission capacity recommendation rate (L1P 4) and a water and electricity installed capacity ratio (L1P 5).
Short-term predicted rate of change of rainfall (L1P 1): L1P1= (short term forecast rainfall-historical contemporaneous average rainfall)/historical contemporaneous average rainfall.
Cumulative change rate at early stage of rainfall (L1P 2): L1P2= (accumulation of rainfall in the last 7 days-historical contemporaneous average rainfall)/historical contemporaneous average rainfall.
Predicted water rejection (L1P 3): L1P3= (historical contemporaneous electrical load/short term electrical load forecast) historical contemporaneous water abandonment rate.
Power transmission channel power transmission capacity recommendation rate (L1P 4): L1P4= power transmission channel remaining available power transmission space/power transmission channel total power transmission space.
Water installed capacity ratio (L1P 5): L1P5= water installed capacity/total installed capacity of clean energy of this province.
Provincial hydropower short-term transaction recommendation rate (L1): l1= (L1P 1 × k31+ L1P2 × k32+ L1P3 × k 33) × L1P4 × L1P5;
k31: a rainfall short-term prediction change rate weighting coefficient;
k32: the rainfall early-stage accumulated change rate weighting coefficient;
k33: and predicting a water abandon rate weighting coefficient.
And 4, generating a clean energy recommendation result by utilizing the wind power recommended generated power, the photovoltaic recommended generated power and the short-term hydropower transaction recommendation rate. The rules of the clean energy recommendation result are as follows:
for wind power and photovoltaic, the day is taken as a recommendation unit, the province is taken as a recommendation unit, and the transmittable daily time-of-day recommended power generation power and the node average trading electricity price are taken as recommendation results.
For hydropower, a day is taken as a recommending unit, a province is taken as a recommending unit, and the short-term trading recommendation rate of the hydropower and the average trading electricity price of a node are taken as recommendation results.
Finally, it is to be noted that: the above examples are only specific embodiments of the present invention, and are used to illustrate the technical solutions of the present invention, but not to limit the technical solutions, and the scope of the present invention is not limited thereto. Those skilled in the art will understand that: modifications and variations of the embodiments described above may be apparent to those skilled in the art, or equivalent arrangements of parts of the technical features may be substituted, without departing from the scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein.
Claims (7)
1. The computer implementation method for inter-provincial short-term clean energy electric power transaction recommendation is characterized in that short-term weather forecast information and short-term power generation forecast information are used as a basis for establishing inter-provincial short-term clean energy electric power transaction recommendation, a database which can be stored/read by a computer is generated, the space capacity of a power transmission channel and the consumption condition of clean energy are analyzed, and inter-provincial wind power and photovoltaic short-term surplus generated power transaction electric power curves are predicted and recommended; considering the delay characteristic of water resource power generation, establishing and calculating a hydropower transaction recommendation rate index; analyzing inter-provincial power transaction history information, and recommending the node average transaction electricity price of inter-provincial clean energy; finally, generating a recommendation result of inter-provincial clean energy electric power trading;
the method comprises the following steps:
generating a short-term clean energy electric power transaction recommendation database which can be stored/read by a computer based on the basic information of the power transmission channel, the overhaul information of the power transmission channel and the historical transaction curve information of the power transmission channel; generating a clean energy basic database which can be stored/read by a computer on the basis of the historical contemporaneous wind curtailment rate and the historical contemporaneous light curtailment rate of wind power and photovoltaic, the historical contemporaneous electricity load, the short-term predicted electricity load, the wind power predicted electricity generation power and the photovoltaic predicted electricity generation power, and the short-term predicted data, the historical contemporaneous rainfall, the early rainfall accumulation data and the water and electricity consumption data of water resources;
calculating the residual available power transmission space of a power transmission channel and calculating the node average trading power price of each province and each type of clean energy by using a short-term clean energy power trading recommendation database; and (c) a second step of,
calculating a predicted wind abandoning rate, a predicted light abandoning rate, time-sharing wind power short-term surplus generated power and time-sharing photovoltaic short-term surplus generated power by utilizing a clean energy basic database; and (c) a second step of,
calculating wind power recommended generating power and photovoltaic recommended generating power by utilizing the time-sharing wind power short-term surplus generating power, the time-sharing photovoltaic short-term surplus generating power and the remaining available power transmission space of the power transmission channel; and (c) a second step of,
calculating the short-term transaction recommendation rate of provincial hydropower by utilizing a clean energy basic database; and the number of the first and second groups,
generating an inter-provincial clean energy trading recommendation result by utilizing the wind power recommended generating power, the photovoltaic recommended generating power and the short-term trading recommendation rate of hydropower;
the short-term surplus generated power of the wind power is calculated as follows:
WR j ＝WRH j *(PLH j /PL j )；
PWR j ＝PWF j *WR j ；
in the formula: WR (pulse Width modulation) j -predicting the wind abandon rate at the jth moment; WRH j -the jth moment, historical contemporaneous wind abandonment rate; PLH j -the jth moment, historical contemporaneous electrical load; PL j -a short-term prediction of the electricity load at the jth instant; PWR j -wind power short-term surplus generated power at jth moment; PWF j -the wind power forecasted generated power at the jth moment;
the photovoltaic short-term surplus generated power is calculated as follows:
SR j ＝WSH j *(PLH j /PL j )；
PSR j ＝PSF j *SR j ；
in the formula: SR j -predicting the rejection at a jth instant; WSH j -the historical contemporaneous extinction rate at the jth moment; PLH j -the jth moment, historical contemporaneous electrical load; PL J -a j-th moment, short-term prediction of the electrical load; PSR j -a j-th moment, photovoltaic short-term surplus generated power; PSF j -photovoltaic predicted generated power at time j;
the wind power recommended power generation power and the photovoltaic recommended power generation power are calculated as follows:
PW k ＝min(PWR k ，PA k )；
PS k ＝min(PSR k ，PA k )；
in the formula: PWR k At the kth moment, the wind power is short-term surplus generated power; PA k -at the kth instant, the transmission channel has remaining available transmission space; PW (pseudo wire) k -at the kth moment, the wind power recommended generated power; PSR k -at the kth moment, photovoltaic short-term surplus generated power; PS (polystyrene) with high sensitivity k -at the kth moment, the photovoltaic recommended power generation power;
establishing a provincial hydropower short-term transaction recommendation rate as a first-level index (L1);
establishing a secondary index of the short-term trading recommendation degree of hydropower:
the rainfall capacity prediction method comprises the following steps of (1) predicting a short-term rainfall change rate (L1P 1), an early-stage rainfall accumulated change rate (L1P 2), a predicted water abandoning rate (L1P 3), a power transmission channel power transmission capacity recommendation rate (L1P 4) and a water and power installed capacity ratio (L1P 5);
short-term predicted rate of change of rainfall (L1P 1): L1P1= (short term forecast rainfall-historical contemporaneous average rainfall)/historical contemporaneous average rainfall;
cumulative rate of change in rainfall earlier stage (L1P 2): L1P2= (accumulation of rainfall in last 7 days-historical contemporaneous average rainfall)/historical contemporaneous average rainfall;
predicted water rejection (L1P 3): L1P3= (historical contemporaneous electrical load/short-term electrical load prediction) × historical contemporaneous water abandonment rate;
power transmission channel power transmission capacity recommendation rate (L1P 4): L1P4= remaining available transmission space/total transmission space of transmission channel;
water installed capacity ratio (L1P 5): L1P5= water installed capacity/total installed capacity of clean energy in this province;
provincial hydropower short-term transaction recommendation rate (L1): l1= (L1P 1 × k31+ L1P2 × k32+ L1P3 × k 33) × L1P4 × L1P5;
k31: a rainfall short-term prediction change rate weighting coefficient;
k32: the rainfall early-stage accumulated change rate weighting coefficient;
k33: and predicting a water abandon rate weighting coefficient.
2. The computer-implemented method of inter-provincial short term clean energy electricity trade recommendation according to claim 1, wherein the method of calculating the remaining available transmission space of a transmission corridor: accumulating the daily 24-hour transaction result curves in a time-sharing manner to obtain the used power transmission space of each power transmission channel, wherein the area between the maximum power transmission space of each power transmission channel and the used power transmission space of each power transmission channel is the remaining available power transmission space of each power transmission channel;
the calculation method of the node average transaction electricity price comprises the following steps: and (4) counting historical spot transaction information, and calculating node average transaction electricity prices of various provinces and various clean energy sources based on inter-province historical transaction and settlement data.
3. The computer-implemented method of inter-provincial short term clean energy electricity trade recommendation according to claim 2, wherein the remaining available transmission space of the transmission corridor is calculated as follows:
in the formula: n- -number of transactions completed by the transmission channel, PA k -at the kth moment, the transmission channel has a remaining available transmission space, PM k -the kth time, power transmission channel maximum power transmission space, PC k -at the kth moment, the electricity transmission channel occupied by the electricity having completed the transaction has used electricity transmission space;
the calculation formula of the node average transaction electricity price is as follows:
in the formula: n- -all provinces number, pr i - -at the ith moment, the average trade price of electricity, fe i -at the ith moment, each province deals with the electricity charge, eq i -at the ith moment, the transaction amount is saved.
4. The inter-provincial short-term clean energy electricity transaction recommendation computer-implemented method according to claim 1, wherein the predicted wind curtailment rate and the predicted light curtailment rate are calculated based on a historical contemporaneous wind curtailment rate and a historical contemporaneous light curtailment rate, a historical contemporaneous electricity load and a short-term predicted electricity load; based on the predicted generated power of wind power and the predicted generated power of photovoltaic power of each province, the predicted abandoned wind rate and the predicted abandoned light rate are combined, a day is taken as a recommendation unit, and the short-term surplus generated power of wind power and the short-term surplus generated power of photovoltaic power at the time of the province are calculated by taking one value every 15 minutes; and comparing the short-term surplus generated power of the wind power and the short-term surplus generated power of the photovoltaic with the remaining available transmission space of the transmission channel at the corresponding moment by taking the day as a recommendation unit, taking a value every 15 minutes and 96 points every day, and calculating the recommended generated power of the wind power and the recommended generated power of the photovoltaic.
5. The computer-implemented method for recommending inter-provincial short-term clean energy electric power trading according to claim 1, wherein comprehensive recommendation evaluation is performed based on short-term forecast data of water resources and historical contemporaneous rainfall, considering postponement of power generation of water resources, accumulated data of rainfall in the early period and water and electricity consumption data, and a model for recommending short-term trading rate of water and electricity is established in a daily unit by adopting a percentage evaluation mode.
6. The computer-implemented method of inter-provincial short-term clean energy electricity trading recommendation according to claim 5, wherein the hydropower short-term trading recommendation rate model establishes a first-level index and a fifth-level index; the first-level index recommendation rate is the sum of the second-level index recommendation rates; and each level of index is provided with corresponding weight, and the first level index weight is the sum of the second level index weights.
7. The method of any of claims 1-6, wherein the recommendation is for wind power, photovoltaic, taking a day as a recommending unit, a province as a recommending unit, and a transmittable daily time-of-day recommended generating power and a node average trading electricity price as a recommending result;
for hydropower, a day is taken as a recommending unit, a province is taken as a recommending unit, and the short-term trading recommendation rate of hydropower and the node average trading electricity price are taken as recommendation results.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011611604.1A CN112598481B (en) | 2020-12-30 | 2020-12-30 | Computer implementation method for inter-provincial short-term clean energy power transaction recommendation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011611604.1A CN112598481B (en) | 2020-12-30 | 2020-12-30 | Computer implementation method for inter-provincial short-term clean energy power transaction recommendation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112598481A CN112598481A (en) | 2021-04-02 |
| CN112598481B true CN112598481B (en) | 2022-12-20 |
Family
ID=75206534
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011611604.1A Active CN112598481B (en) | 2020-12-30 | 2020-12-30 | Computer implementation method for inter-provincial short-term clean energy power transaction recommendation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112598481B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2015153346A (en) * | 2014-02-19 | 2015-08-24 | 辰之 岩崎 | Small-amount power aggregation trade support system and small-amount power aggregation trade support method |
| 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 |
| CN109345335A (en) * | 2018-09-06 | 2019-02-15 | 中国电力科学研究院有限公司 | The method of commerce and system of optical quantum are abandoned in a kind of abandonment |
| CN109948872A (en) * | 2017-12-20 | 2019-06-28 | 中国电力科学研究院有限公司 | A kind of real-time scheduling method and system of the transaction of abandonment electricity |
| CN111027756A (en) * | 2019-11-22 | 2020-04-17 | 国家电网有限公司 | New energy transaction curve decomposition method, system and server considering medium and long term contracts |
-
2020
- 2020-12-30 CN CN202011611604.1A patent/CN112598481B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2015153346A (en) * | 2014-02-19 | 2015-08-24 | 辰之 岩崎 | Small-amount power aggregation trade support system and small-amount power aggregation trade support method |
| 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 |
| CN109948872A (en) * | 2017-12-20 | 2019-06-28 | 中国电力科学研究院有限公司 | A kind of real-time scheduling method and system of the transaction of abandonment electricity |
| CN109345335A (en) * | 2018-09-06 | 2019-02-15 | 中国电力科学研究院有限公司 | The method of commerce and system of optical quantum are abandoned in a kind of abandonment |
| CN111027756A (en) * | 2019-11-22 | 2020-04-17 | 国家电网有限公司 | New energy transaction curve decomposition method, system and server considering medium and long term contracts |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112598481A (en) | 2021-04-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107665378B (en) | Multi-objective optimization scheduling method for power system based on demand side bidding transaction mechanism | |
| Pinson et al. | Dynamic sizing of energy storage for hedging wind power forecast uncertainty | |
| JP2015531585A (en) | Method and system for distributing and / or controlling energy flow taking into account constraints on electrical networks | |
| Giulietti et al. | Analyzing the potential economic value of energy storage | |
| CN107565585A (en) | Energy storage device peak regulation report-back time Forecasting Methodology and its model creation method | |
| Khalid | Wind power economic dispatch–impact of radial basis functional networks and battery energy storage | |
| Khalid et al. | A market‐oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage | |
| Argiolas et al. | Optimal battery energy storage dispatch in energy and frequency regulation markets while peak shaving an EV fast charging station | |
| Wang et al. | Optimal energy management of integrated energy systems for strategic participation in competitive electricity markets | |
| Reddy et al. | Cloud energy storage management system with price fluctuations and distributed generation intermittency | |
| Kim et al. | Economical energy storage systems scheduling based on load forecasting using deep learning | |
| CN112598481B (en) | Computer implementation method for inter-provincial short-term clean energy power transaction recommendation | |
| Park et al. | Optimal VPP Operation Considering Network Constraint Uncertainty of DSO | |
| Chen et al. | Available transfer capability calculations considering demand response | |
| CN111539547A (en) | Optimal spare capacity decision method considering market acquisition mode and cost | |
| CN113255957A (en) | Quantitative optimization analysis method and system for uncertain factors of comprehensive service station | |
| Obersteiner et al. | Influence of market rules on the economic value of wind power: an Austrian case study | |
| Mihaela et al. | Smart Hub Electric Energy Data Aggregation Platform for Prosumers Grid Integration | |
| Cheng et al. | Power and energy balance of active distribution network considering operation-control strategy | |
| Legalov et al. | Hydro generation scheduling with electricity price calculation | |
| Razak et al. | Forecasting cost saving through solar system installation | |
| Abran et al. | Battery Storage for Grid Application: A case study of implementing a Lithium-ion storage system for power peak shaving and energy arbitrage | |
| Xuan et al. | Research on short-term load forecasting model of integral energy system considering demand side response | |
| Zhang et al. | Research on Demand Side Resources Planning Strategy of Load Aggregator Considering CVaR | |
| Hjelmeland et al. | Coordination of hydro and wind power in a transmission constrained area using SDDP |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |