CN113222422A - Method and system for coordinating and scheduling demand response resources - Google Patents
Method and system for coordinating and scheduling demand response resources Download PDFInfo
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Abstract
The demand response resource coordination scheduling method comprises the steps of constructing an objective function based on a stock market bidding trading clearance model of a demand side, outputting a response capacity variable possessed by a user side according to the objective function based on the stock market bidding trading clearance model of the demand side, constructing an objective function based on a day-ahead power stock market clearance model of a supply side, inputting the response capacity variable possessed by the user side into an objective function output unit variable based on the day-ahead power stock market clearance model of the supply side, and determining the current stock market price according to the unit variable. The effect of demand side in the market is increased through price signal and incentive mechanism to this application to carry out comprehensive resource coordination optimization with the resource of supply side and demand side, play the decisive role of market in resource allocation, ensure that electric power supply and demand are balanced and the electric wire netting safety and stability is moved.
Description
Technical Field
The application belongs to the technical field of power systems and automation thereof, and particularly relates to a demand response resource coordination scheduling method and system.
Background
In recent years, the power supply and demand situation of the power grid is biased, power gaps exist in part of time intervals, demand response is introduced in power market competition, the effect of a demand side in the market is increased through price signals and an incentive mechanism, resources of a supply side and the demand side are subjected to comprehensive resource coordination optimization, and the method is an inevitable requirement for adapting to power market development. At present, the domestic demand response function is developed by taking a power demand side management system of a marketing department of a power grid company as a technical platform, and the system is constructed to reduce energy consumption and power load of a user side under the condition of keeping the energy service level, help an enterprise to improve the power consumption management level, improve the utilization efficiency of electric energy, promote the enterprise to continuously improve the investment of energy-saving technical equipment, reduce the cost through energy conservation, increase the benefit and reduce the power supply pressure of the power grid at the peak time. At present, an electric power demand side management system and an electric power spot goods support system are not integrated and associated, and a demand response mechanism for collaborative optimization interaction of resources on two sides of power generation and utilization cannot be supported.
Disclosure of Invention
In order to overcome the problem that a demand response mechanism for collaborative optimization interaction of resources on both sides of power generation and power utilization cannot be supported due to the fact that a power demand side management system and a power spot support system are not integrated and associated at least to a certain extent, the application provides a demand response resource coordination scheduling method and system.
In a first aspect, the present application provides a method for coordinating and scheduling demand response resources, including:
constructing an objective function of a spot market bidding trading clearing model based on a demand side;
outputting a response capability variable possessed by a user side according to an objective function of the spot market bidding trading clearing model based on the demand side;
constructing an objective function based on a supply side day-ahead electric power spot market clearing model;
and inputting the response capability variable possessed by the user side into the objective function based on the supply side day-ahead electric power spot market clearing model to obtain a unit variable so as to determine the current spot market price according to the unit variable.
Further, the method also comprises the following steps:
establishing at least one constraint condition of a demand side objective function;
and carrying out constraint solving on the objective function of the demand-side-based spot market bid trading clearing model through the at least one demand-side objective function constraint condition.
Further, the at least one demand-side objective function constraint includes:
at least one of load balance constraint, system positive reserve capacity constraint, system negative reserve capacity constraint, output upper and lower limit constraint, demand response resource power upper and lower limit constraint, unit climbing constraint, demand side resource climbing constraint, unit group output upper and lower limit constraint, unit output and quotation segment constraint, demand side resource power and quotation segment constraint and section trend constraint.
Further, the objective function based on the demand-side spot market bid trading clearing model is a minimum function of total electricity purchasing cost.
Further, the method also comprises the following steps:
establishing at least one supply-side objective function constraint;
and carrying out constraint solving on the objective function of the supply-side-based day-ahead power spot market clearing model through the at least one supply-side objective function constraint condition.
Further, the at least one supply-side objective function constraint includes:
the system issues at least one of an electrical balance constraint, a rotating reserve capacity constraint, a network security constraint, a unit operation constraint, a unit climbing constraint, a fairness constraint, a pragmatization constraint, and a specified output constraint.
Further, the objective function based on the supply-side day-ahead power spot market clearing model is a minimum function of total power generation cost.
Further, the response capability variable of the user side comprises at least one of a scalar variable and a demand side resource contribution variable in a demand side resource quotation section;
and/or the presence of a gas in the gas,
the unit variables comprise at least one of unit start-stop state variables, unit output variables and scalar variables in a unit quotation section.
Further, the method also comprises the following steps:
acquiring sample data;
calculating the whole income of a demand side and the whole income of a supply side according to the sample data;
and verifying the demand response resource coordination scheduling method according to the demand side overall income and the supply side overall income.
In a second aspect, the present application provides a demand response resource coordination scheduling system, including:
the system comprises a first construction module, a second construction module and a third construction module, wherein the first construction module is used for constructing an objective function based on a stock market bidding trading clearing model on a demand side;
the output module is used for outputting a response capability variable possessed by a user side according to an objective function of the spot market bidding trading clearing model based on the demand side;
the second construction module is used for constructing an objective function based on a supply side day-ahead electric power spot market clearing model;
and the determining module is used for inputting the response capability variable possessed by the user side into the objective function based on the supply side day-ahead electric power spot market clearing model to obtain a unit variable so as to determine the current spot market price according to the unit variable.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
the demand response resource coordination scheduling method and system provided by the embodiment of the invention construct an objective function based on a stock market bidding trading clearance model of a demand side, output a response capability variable possessed by a user side according to the objective function based on the stock market bidding trading clearance model of the demand side, construct an objective function based on a day-ahead power stock market clearance model of a supply side, input the response capability variable possessed by the user side into the objective function based on the day-ahead power stock market clearance model of the supply side to obtain a unit variable, determine the current stock market price according to the unit variable, introduce demand response resources in power market competition, increase the effect of the demand side in the market through price signals and an excitation mechanism, perform comprehensive resource coordination optimization on resources of the supply side and the demand side, and play a decisive role of the market in resource configuration, the balance of power supply and demand and the safe and stable operation of a power grid are ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart of a method for coordinating and scheduling demand response resources according to an embodiment of the present application.
Fig. 2 is a flowchart of a method for coordinating and scheduling demand response resources according to another embodiment of the present application.
Fig. 3 is a flowchart of a method for coordinating and scheduling demand response resources according to another embodiment of the present application.
Fig. 4 is a flowchart of a method for coordinating and scheduling demand response resources according to another embodiment of the present application.
Fig. 5 is a functional block diagram of a demand response resource coordination scheduling system according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail below. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a flowchart of a demand response resource coordination scheduling method according to an embodiment of the present application, and as shown in fig. 1, the demand response resource coordination scheduling method includes:
s11: constructing an objective function of a spot market bidding trading clearing model based on a demand side;
s12: outputting a response capability variable possessed by a user side according to an objective function of a spot market bidding trading clearing model based on a demand side;
s13: constructing an objective function based on a supply side day-ahead electric power spot market clearing model;
s14: and inputting the response capability variable possessed by the user side into an objective function based on a day-ahead electric power spot market clearing model of the supply side to obtain a unit variable so as to determine the current spot market price according to the unit variable.
At present, an electric power demand side management system and an electric power spot goods support system are not integrated and associated, and a demand response mechanism for collaborative optimization interaction of resources on two sides of power generation and utilization cannot be supported. For example, the price of electricity in the existing electric power spot market is constant, and the power consumption enterprise can not adjust the production time according to the spot price is nimble, reduces the power consumption cost of enterprise, and the power generation enterprise also does not in time control the unit and opens and stop, and the output of control generated energy is unfavorable for the decisive role of full play market in resource allocation.
In the embodiment, by constructing the objective function based on the spot market bidding trading clearing model on the demand side, outputting a response capability variable possessed by a user side according to an objective function of a spot market bidding trading clearance model based on a demand side, constructing an objective function of a day-ahead electric power spot market clearance model based on a supply side, inputting the response capability variable possessed by the user side into the objective function of the day-ahead electric power spot market clearance model based on the supply side to obtain a unit variable so as to determine the current spot market price according to the unit variable, the demand response resource is introduced in the competition of the power market, the role of the demand side in the market is increased through price signals and incentive mechanisms, and the resources of the supply side and the demand side are subjected to comprehensive resource coordination optimization, the decisive role of the market in resource allocation is played, and the balance of power supply and demand and the safe and stable operation of a power grid are ensured.
Fig. 2 is a flowchart of a demand response resource coordination scheduling method according to another embodiment of the present application, and as shown in fig. 2, the demand response resource coordination scheduling method includes:
s21: establishing at least one constraint condition of a demand side objective function;
s22: and carrying out constraint solving on an objective function based on the spot market bidding trading clearing model on the demand side through at least one demand side objective function constraint condition.
In some embodiments, the at least one demand-side objective function constraint comprises:
at least one of load balance constraint, system positive reserve capacity constraint, system negative reserve capacity constraint, output upper and lower limit constraint, demand response resource power upper and lower limit constraint, unit climbing constraint, demand side resource climbing constraint, unit group output upper and lower limit constraint, unit output and quotation segment constraint, demand side resource power and quotation segment constraint and section trend constraint.
For each time period t, the load balancing constraint may be:
wherein, Pi,tRepresenting the output, PR, of the unit i during a time period tj,tRepresenting the power, D, of the demand-side resource j during time period ttThe system payload (planned exchange power of the trip link) for time period t.
On the premise of ensuring the power balance of the system, in order to prevent the system load prediction deviation and the unbalanced fluctuation of the system supply and demand caused by various actual operation accidents, a certain capacity needs to be reserved in the whole system generally.
It is necessary to ensure that the total boot capacity of each day meets the minimum spare capacity of the system. The system positive spare capacity constraint may be:
wherein v isi,tShowing the starting and stopping states of the unit i in the time period t, vi,t0 denotes a unit shutdown, vi,t1 represents the starting of the unit; pi,t maxThe maximum output of the unit i in the time period t is obtained; PRj,t maxThe maximum power of the demand side resource j in the time period t; rt UThe system positive spare capacity requirement for time period t.
The system negative spare capacity constraint may be:
wherein v isi,tShowing the starting and stopping states of the unit i in the time period t, vi,t0 denotes a unit shutdown, vi,t1 represents the starting of the unit; pi,t minThe minimum output of the unit i in the time period t is obtained; PRj,t minMinimum power for the demand side resource j in time period t; rt DThe system negative spare capacity requirement for time period t.
The constraint of the upper and lower output limits means that the output of the unit should be within the maximum/minimum output range, and the constraint conditions can be as follows:
the power of the demand response resource should be within its maximum/minimum capacity, and the constraint may be:
the unit climbing restraint refers to the capacity of the unit for increasing and decreasing output, is a physical restraint and can be expressed as follows:
wherein, Rampi UAnd Rampi DRespectively showing the up-down climbing capability of the unit i.
The demand side resource climbing constraint refers to the capacity of increasing and decreasing the output of the demand side, is a physical constraint, and can be expressed as:
wherein the content of the first and second substances,
and
respectively representing the up-down climbing capability of the demand response resource j.
The upper and lower limit constraints of the output of the machine group mean that the output of the machine group should be in the maximum/minimum output range, and the constraint conditions can be as follows:
wherein G isk,t min、Gk,t maxThe minimum and maximum output of the machine group k in the time period t.
The unit output and quotation segment constraint means that when the unit has multi-segment quotation, the sum of the bid amounts in each segment is equal to the unit output, and can be expressed as:
wherein PSi,t,gRepresents the bid amount, seg of the unit i quoted in the time period t and the g-th periodiAnd indicating the number of quotation sections of the unit i.
The constraint of the resource power and the quotation section at the demand side is that when the unit has multi-section quotation, the sum of the bid amounts in each section is equal to the output of the unit, and can be expressed as:
wherein the PRSj,t,gRepresents the bid amount, segR, of the demand side resource j in the period t and the g th quotejIndicating the number of segments quoted for the demand-side resource j.
Considering the flow constraint of a critical section (including a single line), the section flow constraint may be:
wherein the content of the first and second substances,
respectively the tidal current transmission limit of the section s; gs-iThe generator output power of the section s is transferred to a distribution factor for the node where the unit i is located; gs-jA generator output power transfer distribution factor of a section s is output by a node where a demand response resource j is located; gs-kThe generator output power transfer distribution factor is node k to section s. SL (Long-side)s +And SLs -Respectively the positive and reverse tide relaxation variables of the section s.
In some embodiments, the objective function based on the demand-side spot market bid trading closeout model is a minimum function of total electricity purchase cost. The formula is as follows:
wherein T represents the total number of considered time periods, generally one time period every 15 minutes, and 1-3 days are considered;
n represents the total number of the units, and NR represents the total number of the demand response resources;
Pi,trepresents the output of the unit i in the time period t, PRj,tRepresenting the output of the demand response resource j in the period t;
Ci,t(Pi,t)、Ci,t U、Ci,t Nthe operation cost, the starting cost and the no-load cost of the unit i in the time period t are distinguished, wherein the unit operation cost Ci,t(Pi,t) Is a multi-segment linear function related to each segment of output interval declared by the unit and the corresponding energy price; unit start-up cost Ci,t UIs a function related to the unit down time to represent the start-up cost of the unit under different states (cold/warm/hot); cost C for no-load operation of uniti,t NRepresenting the no-load cost (including the starting and stopping processes) of the unit in the running state; for demand response resources, only the operating costs CR thereof need to be consideredj,t(PRj,t)。
M is a network flow constraint relaxation penalty factor for market clearing optimization;
SLs+ and SLs-positive and negative current relaxation variables, respectively, of section (comprising a single line) s; NS is the total number of sections.
The response capacity variable of the user side is obtained by solving the objective function of the spot market bidding trading clearance model based on the demand side, and the response capacity variable of the user side comprises at least one of a scalar variable and a demand side resource clearance variable in the resource quotation section of the demand side, so that the solving result of the objective function of the spot market clearance model based on the supply side can be influenced by the response capacity variable of the user side.
In this embodiment, the minimum function of the total electricity purchasing cost is constructed and at least one constraint condition is established to solve the minimum function of the total electricity purchasing cost so as to obtain a response capability variable possessed by the user side, influence is generated on the supply side, resources of the supply side and the demand side are subjected to comprehensive resource coordination optimization, and integration and cooperation of a demand response technology and a clearing model of the electric power spot inventory support system are realized.
Fig. 3 is a flowchart of a demand response resource coordination scheduling method according to another embodiment of the present application, and as shown in fig. 3, the demand response resource coordination scheduling method includes:
s31: establishing at least one supply-side objective function constraint;
s32: and carrying out constraint solving on an objective function based on a supply-side day-ahead power spot market clearing model through at least one supply-side objective function constraint condition.
In some embodiments, the at least one supply-side objective function constraint comprises:
the system issues at least one of an electrical balance constraint, a rotating reserve capacity constraint, a network security constraint, a unit operation constraint, a unit climbing constraint, a fairness constraint, a pragmatization constraint, and a specified output constraint.
The system electricity generation and utilization balance constraint comprises load balance constraint, power balance is required to be kept between electricity generation and utilization in each time period in the power spot market in the day ahead, and line loss of a connecting line, station service electricity and the like are comprehensively considered.
In the formula, DtThe demand of the spot goods of the power in the province before the time t is met.
The rotation reserve capacity constraint comprises ensuring that the up-regulation capacity sum and the down-regulation capacity sum of the output of the generator set meet the up-regulation and down-regulation rotation reserve requirements set by the actual operation (the up-regulation capacity sum and the down-regulation capacity sum are more than or equal to the up-regulation and down-regulation rotation reserve requirements set by the actual operation).
The power grid safety constraint comprises power transmission line and section flow constraint, the power transmission capacity of the power transmission channel is determined to be within a limit value according to the power generation combined transfer distribution factor, and corresponding power limit constraint is added.
In the formula, Xj,tThe active power flow of the power transmission channel j in the t period;
is the active power flow limit of the transmission channel j; and L is a power transmission channel, namely a line or a section.
The unit operation constraint and the unit adjustable output constraint comprise a unit output upper limit constraint and a unit output lower limit constraint, and each time interval can be independently set.
In the formula (I), the compound is shown in the specification,
the upper limit of the output of the unit i is set; piAnd (4) providing a lower output limit for the unit i.
The unit climbing restraint comprises unit output rate restraint and output rate reduction restraint, and each time interval can be set independently. And the connection between the planned output in the early day period and the planned output or the actual output in the last day period of the unit can be ensured.
In the formula (I), the compound is shown in the specification,
representing the uphill limit of the unit i in a time period; iΔPrepresenting the down-hill limit of the unit i over a period of time.
The unit start-up and shut-down time constraints comprise minimum start-up time, minimum shut-down time constraints and the like of the unit.
The unit startup and shutdown times constraint comprises the maximum startup times of the unit, the maximum shutdown times constraint and the like.
The stop-and-start constraint refers to the constraint that the unit must be in a stop state or a start state for reasons (heat supply or maintenance) in certain time periods.
Fairness constraints ensure that the output of the same quotation section is balanced.
The specified output constraints may specify that a portion of the units operate with a fixed output curve.
In some embodiments, the objective function based on the supply-side, day-ahead, power spot market clearing model is a minimum function of total generation cost.
And in the current spot market clearing, according to the market demand of the power spot transaction and declaration data of the power generation enterprise, carrying out market clearing, and calculating the starting and stopping arrangement of the power generation enterprise unit, the winning result in each time period and the node marginal price.
The method comprises the steps of optimizing a target by minimizing the total power generation cost of a day-ahead market system, carrying out market clearing calculation based on a power demand prediction curve, a tie line day-ahead planned power curve, declared data of power generation enterprises, transmission capacity constraints of power transmission lines and the like, determining unit combination arrangement, bid winning results of spot goods transactions of all units, a total power generation planned curve of the units, calculating node time-sharing power price of the day-ahead market and the like. For example, one electricity rate is formed every 1 hour (or every 15 minutes), and 24 different electricity rates are formed every day, which sufficiently represents the different values of electricity as a commodity at different times. Under the action of a price mechanism, the power utilization enterprises can flexibly adjust the production time according to the spot price and the medium and long term transaction price, so that the power utilization cost of the enterprises is reduced; the power generation enterprise can flexibly select the number of the units to be started, stopped, adjusted and maintained and generated energy, the decisive role of the market in resource allocation is fully played, and the balance of power supply and demand and the safe and stable operation of a power grid are ensured.
The export model of the spot market at the day before is implemented based on a crew assembly program with safety constraints, as follows.
The objective function of the current electric power spot market clearing in the day is the minimization of the total power generation cost of the system, and specifically comprises the following steps:
wherein T is the number of transaction time segments, I is the total unit number, Pi tThe active power output of the unit i in the time period t is obtained; ci(Pi t) And the generating cost declared by the unit i in the time period t.
The first two items are the running cost of the unit, wherein the no-load cost is the fixed cost per hour during the running period of the unit and is irrelevant to the output; the third item is the one-time compensation of the unit startup or shutdown.
The method comprises the steps of solving an objective function of a day-ahead power spot market clearing model based on a supply side to obtain a unit variable, wherein the unit variable comprises at least one of a unit start-stop state variable, a unit output variable and a unit quotation section scalar variable, and determining the current spot market price according to the unit variable, so that the solving result of the objective function of the spot market bidding trading clearing model based on a demand side is influenced through the current spot market price.
In this embodiment, the total power generation cost minimum function is solved by constructing the total power generation cost minimum function and establishing at least one constraint condition to determine the current spot market price, so as to affect the demand side, perform comprehensive resource coordination optimization on the resources of the supply side and the demand side, and realize integration and cooperation between the demand response technology and the clearing model of the electric power spot support system.
Fig. 4 is a flowchart of a demand response resource coordination scheduling method according to another embodiment of the present application, and as shown in fig. 4, the demand response resource coordination scheduling method includes:
s41: acquiring sample data;
s42: calculating the whole income of a demand side and the whole income of a supply side according to the sample data;
s43: and verifying the demand response resource coordination scheduling method according to the demand side overall income and the supply side overall income.
And verifying the research model and analyzing the data by combining the sample data, and evaluating the optimization benefit of the demand side response participating in the power market. Under the same external boundary condition, after the demand side participates in the market, the increase and decrease of the electricity purchasing cost of a user and the increase of the deviation checking cost are considered comprehensively, the whole income of the demand side is calculated quantitatively, so that the income of the demand side participating in spot goods is analyzed, and the space-time distribution rule of the income is analyzed.
The demand response resource participates in the real-time electric energy market demonstration, the user agent load integrator is L1, the grid node connected with the end user is also provided with two other load service enterprises L2 and L3, and the loads of the three service enterprises in the project participation period of the end user respectively account for 66.67%, 16.67% and 16.67% of the total load. The load size of the terminal user is 25MW, the retail electricity price is fixed to 35 yuan/MWh, the load of 5MW can be reduced, the minimum load stop time is 6 hours, and the load stop cost is 1500 yuan. The marginal cost for the end user to participate in the real-time demand response is as follows:
the user predicts that the real-time node marginal price (LMP) is greater than 85 yuan/MWh at 12:00-18:00, and then decides to cut down the load in the real-time market, and the user will inform the market operating agency 2 hours before the start of the load reduction.
Through the three seed scenes, the example settlement is respectively carried out.
TABLE 1 real-time market calculation of one
| Numbering | Plan reduction (MW) | Actual load reduction (MW) | Actual node electricity price LMP (Yuan) |
| 1 | 5 | 4 | 40 |
| 2 | 5 | 4 | 90 |
| 3 | 5 | 0 | 90 |
(1) After the end user notifies the market operating agency, only 4MW is cut in the real-time market, and the real-time electricity rate is lower than the expected electricity rate, at which time the market operating agency will pay the user (real-time node electricity rate-retail electricity rate) × actual load reduction, i.e., (40-35) × 4 ═ 2 yuan/MWh, while the market operating agency will charge L120 yuan.
(2) The real-time LMP is higher than the expected electricity price, the market operator will pay the user the real-time node electricity price x actual load reduction, i.e. 90 x 4-360 x, where (real-time node electricity price-retail electricity price) actual load reduction, i.e. (90-35) × 4-220, will be charged from L1, the other 140 x will be shared according to the load proportion of 3 load integrators.
(3) The end user notifies the market operator that the load is to be reduced, but does not act in real time, does not assume responsibility, and has zero revenue.
Or the same end user, who, after participating in the real-time market, decides to accept the dispatch of the market operator in the real-time market. The user's bid is 87 meta >85 meta. The market operator predicts that the LMP is greater than 87 bins from 12 to 18 points, and then schedules the load to be reduced by 5 MW.
TABLE 2 real-time market calculation two
| Numbering | Plan reduction (MW) | Actual load reduction (MW) | Actual node electricity price LMP (Yuan) |
| 1 | 5 | 4 | 40 |
| 2 | 5 | 4 | 90 |
| 3 | 5 | 0 | 40 |
(1) The real-time LMP is lower than the user's price, the market operator will pay the user price x real load reduction, i.e. 87 x 4 ═ 348 dollars, while the market operator will collect from L1 (real-time node electricity price-retail electricity price) x real load reduction, i.e. 5 x 4 ═ 20 dollars. The additional 328 dollars will be collected from the running standby market.
(2) The real-time LMP is higher than the user price, the market operator reduces the real-time LMP x actual load paid to the user, i.e. 90 x 4 ═ 360, and in addition, the market operator reduces the real-time node electricity price-retail electricity price x actual load, i.e. 55 x 4 ═ 220 to L1, and the rest is distributed according to the load proportion of each load integrator.
(3) The end user does not follow the schedule without shedding load and it does not assume responsibility.
All scenarios can be summarized as follows.
TABLE 3 summary of real-time electric energy market examples
| Real-time market scenarios | 1 | 2 | 3 | 4 | 5 | 6 |
| Marginal cost (Yuan) | 85 | 85 | 85 | 85 | 85 | 85 |
| Real-time LMP (Yuan) | 40 | 90 | 40 | 90 | ||
| Real-time reduction (MW) | 4 | 4 | 0 | 4 | 4 | 0 |
| Payment load user (Yuan) | 20 | 360 | 348 | 360 | ||
| From load user income (Yuan) | ||||||
| Receive from the load integrator 1 (Yuan) | 20 | 220+93.34 | 20 | 220+93.34 | ||
| Receive from the load integrator 2 (Yuan) | 23.34 | 23.34 | ||||
| Receive from the load integrator 3 (Yuan) | 23.34 | 23.34 | ||||
| Operational reserve market collection (Yuan) | 328 |
The demand response resource participates in the day-ahead electric energy market demonstration, and assuming that 1 Shandong demand response user participates in the day-ahead electric energy market, the node where the user is located has three load integrators, wherein L1 serves the user. The user consumes 0.5MW of electric energy, the retail price of the electric energy is 35/MWh, the user load plan is reduced by 0.5MW, the minimum load stop time is 8 hours, and the load stop cost is 175 yuan. The marginal cost to the user is
The user predicts that the real-time marginal node electricity price (LMP) is greater than 78.75 dollars from 12 o 'clock to 20 o' clock on the day of operation, and decides to submit a bid in the day-ahead market, indicating a willingness to reduce the load by 0.5MW if the LMP is greater than $ 78.75 in the day-ahead market.
Assuming that the market today is 80 dollars LMP and above 78.75 dollars, the customer is offering, the operator will pay the end user or represent 80 dollars 0.5 dollars to 40 dollars, and the operator will collect (current LMP-retail price) from L1 with a reduced load, i.e., 45 dollars 0.5 dollars to 22.50 dollars. And the other 17.50 yuan is distributed to each load integrator. After the quote is cleared, the end user is responsible for reducing the load according to the quote quantity in real time, if not, the end user is charged, and the charging amount is the calculation of the real-time node marginal price (LMP) multiplied by the clear load reduction quantity.
TABLE 4 day ago electric energy market calculation example
In the embodiment, the verification and data analysis of a research model are performed by combining sample data, a marketized operation mechanism is established for demand response users, the admission management capacity of the power grid to various market subjects is remarkably improved, and the optimization benefit of interaction between the adjustable load and the power grid is effectively evaluated.
An embodiment of the present invention provides a demand response resource coordination scheduling system, which is a functional structure diagram shown in fig. 5, and includes:
a first construction module 51, configured to construct an objective function based on a demand-side stock market bidding trading clearing model;
the output module 52 is used for outputting a response capability variable possessed by the user side according to an objective function of the stock market bidding trading clearing model based on the demand side;
a second construction module 53, configured to construct an objective function based on a supply-side, day-ahead, power spot market outlook model;
and the determining module 54 is used for inputting the response capability variable possessed by the user side into the objective function based on the supply side day-ahead electric power spot market clearing model to obtain a unit variable so as to determine the current spot market price according to the unit variable.
In the embodiment, an objective function based on a stock market bidding trading clearance model on a demand side is constructed through a first construction module, an output module outputs a response capacity variable possessed by a user side according to the objective function based on the stock market bidding trading clearance model on the demand side, a second construction module constructs an objective function based on a day-ahead power stock market clearance model on the supply side, a determination module inputs the response capacity variable possessed by the user side into an objective function output unit variable based on the day-ahead power stock market clearance model on the supply side to determine the current stock market price according to the unit variable, demand response resources are introduced in power market competition, the function of the demand side in the market is increased through a price signal and an excitation mechanism, and the resources on the supply side and the demand side are subjected to comprehensive resource coordination optimization to play a decisive role of the market in resource allocation, the balance of power supply and demand and the safe and stable operation of a power grid are ensured.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional component mode. The integrated module, if implemented in the form of a software functional component and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
It should be noted that the present invention is not limited to the above-mentioned preferred embodiments, and those skilled in the art can obtain other products in various forms without departing from the spirit of the present invention, but any changes in shape or structure can be made within the scope of the present invention with the same or similar technical solutions as those of the present invention.
Claims (10)
1. A method for coordinated scheduling of demand response resources, comprising:
constructing an objective function of a spot market bidding trading clearing model based on a demand side;
outputting a response capability variable possessed by a user side according to an objective function of the spot market bidding trading clearing model based on the demand side;
constructing an objective function based on a supply side day-ahead electric power spot market clearing model;
and inputting the response capability variable possessed by the user side into the objective function based on the supply side day-ahead electric power spot market clearing model to obtain a unit variable so as to determine the current spot market price according to the unit variable.
2. The demand response resource coordinated scheduling method of claim 1, further comprising:
establishing at least one constraint condition of a demand side objective function;
and carrying out constraint solving on the objective function of the demand-side-based spot market bid trading clearing model through the at least one demand-side objective function constraint condition.
3. The demand-response resource coordinated scheduling method of claim 2, wherein the at least one demand-side objective function constraint comprises:
at least one of load balance constraint, system positive reserve capacity constraint, system negative reserve capacity constraint, output upper and lower limit constraint, demand response resource power upper and lower limit constraint, unit climbing constraint, demand side resource climbing constraint, unit group output upper and lower limit constraint, unit output and quotation segment constraint, demand side resource power and quotation segment constraint and section trend constraint.
4. The demand-response resource coordinated scheduling method according to claim 1 or 2, wherein the objective function based on the demand-side spot market bid trading clearing model is a minimum function of total electricity purchase cost.
5. The demand response resource coordinated scheduling method of claim 1, further comprising:
establishing at least one supply-side objective function constraint;
and carrying out constraint solving on the objective function of the supply-side-based day-ahead power spot market clearing model through the at least one supply-side objective function constraint condition.
6. The demand-response resource coordinated scheduling method of claim 5, wherein the at least one supply-side objective function constraint comprises:
the system issues at least one of an electrical balance constraint, a rotating reserve capacity constraint, a network security constraint, a unit operation constraint, a unit climbing constraint, a fairness constraint, a pragmatization constraint, and a specified output constraint.
7. The demand-response resource coordinated scheduling method according to claim 1 or 5, wherein the objective function based on the supply-side day-ahead power spot market clearing model is a total generation cost minimum function.
8. The method for coordinated scheduling of demand response resources according to claim 1, wherein the response capability variable possessed by the user side includes at least one of a scalar variable and a demand side resource contribution variable in a demand side resource quotation section;
and/or the presence of a gas in the gas,
the unit variables comprise at least one of unit start-stop state variables, unit output variables and scalar variables in a unit quotation section.
9. The demand response resource coordinated scheduling method of claim 1, further comprising:
acquiring sample data;
calculating the whole income of a demand side and the whole income of a supply side according to the sample data;
and verifying the demand response resource coordination scheduling method according to the demand side overall income and the supply side overall income.
10. A demand response resource coordinated scheduling system, comprising:
the system comprises a first construction module, a second construction module and a third construction module, wherein the first construction module is used for constructing an objective function based on a stock market bidding trading clearing model on a demand side;
the output module is used for outputting a response capability variable possessed by a user side according to an objective function of the spot market bidding trading clearing model based on the demand side;
the second construction module is used for constructing an objective function based on a supply side day-ahead electric power spot market clearing model;
and the determining module is used for inputting the response capability variable possessed by the user side into the objective function based on the supply side day-ahead electric power spot market clearing model to obtain a unit variable so as to determine the current spot market price according to the unit variable.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116307500A (en) * | 2023-01-13 | 2023-06-23 | 南方电网调峰调频发电有限公司鲁布革水力发电厂 | Power resource allocation optimization method and system for power spot market |
| CN116720885A (en) * | 2023-08-07 | 2023-09-08 | 国网安徽省电力有限公司经济技术研究院 | Distributed virtual power plant control method and system in electric power spot market environment |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116307500A (en) * | 2023-01-13 | 2023-06-23 | 南方电网调峰调频发电有限公司鲁布革水力发电厂 | Power resource allocation optimization method and system for power spot market |
| CN116720885A (en) * | 2023-08-07 | 2023-09-08 | 国网安徽省电力有限公司经济技术研究院 | Distributed virtual power plant control method and system in electric power spot market environment |
| CN116720885B (en) * | 2023-08-07 | 2023-10-20 | 国网安徽省电力有限公司经济技术研究院 | Distributed virtual power plant control method and system in electric power spot market environment |
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