CN114928052A

CN114928052A - High-permeability new energy power grid dispatching method and system considering deep peak shaving

Info

Publication number: CN114928052A
Application number: CN202210767325.7A
Authority: CN
Inventors: 宋福龙; 汪洋子; 梁才浩; 余潇潇; 孟婧; 倪煜; 陈正曦; 陈晨; 刘怀远; 燕志宇; 李隽�; 周原冰; 聂坤月; 赵盛楠; 王志军; 王晓辉; 丁磊
Original assignee: Global Energy Internet Group Ltd; Shandong University
Current assignee: Global Energy Internet Group Ltd; Shandong University
Priority date: 2022-07-01
Filing date: 2022-07-01
Publication date: 2022-08-19

Abstract

The invention provides a high-permeability new energy power grid dispatching method and system considering deep peak shaving, which comprises the following steps: constructing a rolling scheduling model considering the deep peak shaving market in which the wind power participates, wherein the model comprises a day-ahead scheduling model and a day-in scheduling model; the target function of the day-ahead scheduling model takes the minimum sum of the unit start-stop cost, the running cost and the deep peak-shaving resource scheduling cost as a target, and takes various day-ahead related constraint conditions into consideration; the objective function of the day scheduling model is to minimize the total operation cost and consider various constraint conditions in the day; and the wind power participates in each level of scheduling by utilizing the rolling scheduling model, and the day-ahead and day-inside real-time scheduling coordination is carried out. The rolling scheduling model can fully utilize the day-to-day and real-time wind power and load prediction results, and improve the accuracy of decision. Compared with a day-ahead scheduling model, the rolling scheduling model can supplement the reserve capacity from the market in time, so that the total operation cost is reduced.

Description

High-permeability new energy power grid dispatching method and system considering deep peak shaving

Technical Field

The invention belongs to the technical field of power grid dispatching, and particularly relates to a high-permeability new energy power grid dispatching method and system considering deep peak shaving.

Background

The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.

Under the existing mechanism of forming the price of the on-line electricity, peak shaving is an important work for realizing the balance of the electricity generation and utilization by tracking load shared by all power generation enterprises. With the improvement of the permeability of the renewable energy, the peak shaving not only needs to satisfy the periodic change of the load, but also needs to satisfy the fluctuation change of the output of the renewable energy, however, the cost corresponding to the increment requirement of the peak shaving part is not fully compensated in most areas in China at present.

The mature electric power market in foreign countries depends on the electric energy spot market, realizes the matching of supply and demand, determines the output plan of the generator set, and solves the problem of peak shaving by forming the time sequence electricity price through market competition. In the market environment, in order to better meet the change trend of time sequence electricity price, the academic community continuously tries to combine the water, electricity and energy storage devices with better controllability, even demand side resources and renewable energy power generation, and better economic benefit is obtained by changing the time distribution characteristic of the whole power generation output.

Because a complete power spot market system is not established in China, the peak regulation authority is still shared among conventional power supplies mainly through a planning means at present, and different from the areas where the power spot market is established, the peak regulation pointed in China pays more attention to the power reduction capacity in the valley period of the load. Because the power resources in China lack quick adjustment resources such as gas turbine units and the like, and the coal-fired thermal power generating units in the supernatant of the market at present cannot be started and stopped frequently, deep peak shaving is still an urgent auxiliary service product. With the construction of a spot market, deep peak regulation is combined with a power day-ahead market, and a thermal power generating unit declares deep peak regulation gears and quotations day-ahead. When the generated energy of the new energy is high, the system calls the peak reduction capability of the thermal power generating unit, but the current new energy does not participate in deep peak regulation, so that excessive deep peak regulation resources can be called for absorbing the new energy, and the total electricity purchasing cost is increased. Therefore, new energy is introduced into the paid peak-shaving market to participate in market bidding, which is an inevitable development trend of the peak-shaving auxiliary service market.

The peak regulation has more definite responsibility and benefit, and with the diversification of the power generation energy types, the peak regulation reflects the requirement of improving the flexibility of the system more. At present, the research on a peak regulation compensation mechanism is mainly based on cost analysis statistics to obtain a relatively reasonable compensation standard, and the calculation is mainly based on the economic characteristics of the hydroelectric generating set. Besides the method based on the cost, a part of research is carried out on a peak regulation right transaction mechanism from the common responsibility of peak regulation, and the requirement of the system on the peak regulation effect is reflected to a certain extent. In addition, based on the analysis of peak shaving responsibility, how to divide the boundaries of the gratuitous and paid peak shaving is also a concern.

Under certain conditions, renewable energy can also become a peak regulation provider, and by means of actively reducing output and the like, additional economic loss and safety risk caused by forced low-voltage low-load rate and even shutdown of traditional energy generating units such as thermal power units and the like in short-time load valley are avoided.

Due to uncertainty of generated output, renewable energy represented by wind power is generally considered as peak shaving consumers, and when the capacity of the renewable energy exceeds the peak shaving capacity of a conventional unit, the renewable energy can only passively receive scheduling instructions of wind and light abandonment, so that the economic consideration of the operation of the renewable energy is insufficient.

Disclosure of Invention

In order to overcome the defects of the prior art, the invention provides the high-permeability new energy power grid dispatching method considering deep peak shaving, so that the coordination of day-ahead-day-in-real-time dispatching is realized, and the overall economy of wind power and a system is improved.

In order to achieve the above object, one or more embodiments of the present invention provide the following technical solutions:

in a first aspect, a high-permeability new energy power grid dispatching method considering deep peak shaving is disclosed, which comprises the following steps:

constructing a rolling scheduling model considering the deep peak shaving market in which the wind power participates, wherein the model comprises a day-ahead scheduling model and a day-in scheduling model;

the target function of the day-ahead scheduling model takes the minimum sum of the start-stop cost of a unit, the running cost and the scheduling cost of deep peak-shaving resources as a target, and various constraint conditions related to the day-ahead are considered;

the objective function of the day scheduling model is to minimize the total operation cost and consider various constraint conditions in the day;

and the wind power participates in each level of scheduling by utilizing the rolling scheduling model, and the day-ahead and day-inside real-time scheduling coordination is carried out.

As a further technical scheme, a day-ahead scheduling model is executed in a day-ahead market, the day-in scheduling model of the invention is executed in a day-in market, and the rolling scheduling model is executed in a real-time scheduling process.

As a further technical scheme, the slow machine set operation arrangement and the daily deep peak shaving resource purchase quantity obtained by the day-ahead scheduling model are used as input quantities of the day-interior scheduling model; and the running arrangement of the fast machine set and the daily deep peak shaving resource purchase quantity obtained by the daily scheduling model are used as input quantities of the rolling scheduling model.

As a further technical scheme, the day-ahead scheduling model constraint conditions comprise power balance constraint, line power flow constraint, constraint of a system for meeting rotating standby requirement and climbing requirement, output constraint after a fan participates in peak shaving, upper and lower limit constraint of output of a thermal power generating unit, constraint of starting and stopping of the unit, constraint of output climbing of a conventional unit considering deep peak shaving, reference output limit of the unit participating in peak shaving market, constraint of upward/downward climbing provided by the unit at the previous moment and downward/upward climbing provided by the unit at the next moment, constraint of participation of the deep peak shaving unit in peak shaving, and constraint of starting and stopping variables and state variables.

As a further technical scheme, the intra-day scheduling in the intra-day scheduling model is scheduled in a rolling manner according to a scheduling period, and in each scheduling period, a scheduling step length and the number of scheduling time periods are set.

As a further technical solution, the constraint conditions of the intra-day scheduling model include: the method comprises the following steps of daily power balance constraint, daily traditional slow machine operation constraint, daily fast machine operation constraint, daily cleaning machine set standby output adjustment constraint, daily fan standby output constraint, line power flow constraint, thermal power unit output upper and lower limit constraint and rotary standby constraint which needs to be met by the system.

As a further technical scheme, in day-ahead scheduling, calculating and submitting a deep peak regulation resource calling price and a predicted power generation amount, and the output price, the deep peak regulation price, the power generation capacity, the deep peak regulation segment capacity, the climbing rate, the minimum start-stop time and the minimum power generation amount submitted by other units;

scheduling according to the reported calling prices, calling capacities, unit parameters and load predicted value information of all units, performing day-ahead output arrangement according to a target function formula and a constraint condition formula of a scheduling model in the day, and sending the following information of each 24-hour period to the units 24 hours in advance by the scheduling according to the calculated result: the system comprises a control system, a control system and a control system, wherein the control system comprises a slow machine set, a fast machine set, a slow machine set, a standby safety displacement and a deep peak-regulation safety displacement of the fast machine and the slow machine. According to the calculation result;

and the unit sends calling information to the unit in a scheduling mode.

As a further technical scheme, in the daily scheduling, the unit scheduling amount arranged in the day ahead is regarded as a resource which can be used in the day;

when the total power utilization deviation in the day is positive and small, the power generation instruction dispatched to the unit is a superposition value of the output dispatching quantity arranged in the day before and the dispatching quantity of the spare dispatching quantity arranged in the day before;

when the deviation is positive and large, a new unit needs to be started;

when the total power utilization deviation is negative, calling the depth peak-shaving quantity scheduled in the day ahead, and if the depth peak-shaving quantity scheduled in the day ahead is insufficient, supplementing new depth peak-shaving resources in the day;

the scheduling output value is the following information which is transmitted to the unit 2h in advance, takes 15min as a scheduling step length and has 8 scheduling time periods: the method comprises the following steps of slow machine output regulation amount, fast machine set start-stop arrangement, fast machine set output regulation amount, daily deep peak regulation supplement arrangement and standby arrangement.

In a second aspect, a high-permeability new energy power grid dispatching system considering deep peak shaving is disclosed, which comprises:

a rolling scheduling model building module configured to: constructing a rolling scheduling model considering the deep peak shaving market in which the wind power participates, wherein the model comprises a day-ahead scheduling model and a day-in scheduling model;

a scheduling module configured to: and the wind power participates in each level of scheduling by utilizing the rolling scheduling model, and the day-ahead and day-in real-time scheduling coordination is carried out.

The above one or more technical solutions have the following beneficial effects:

the rolling scheduling model for calculating the wind power participation deep peak shaving market allows wind power to participate in market quotation, so that the capability of the wind power for providing peak shaving resources is fully exerted, the wind power participates in scheduling at each level, the day-ahead-day-in-real-time scheduling coordination is realized, and the overall economy of the wind power and the system is improved.

By adopting a day-ahead-day-in-real-time rolling scheduling model, the peak-shaving resource supply is increased for the wind power resources, the peak-shaving resources provided by the traditional unit with higher quotation are fully replaced, the market does not need to call expensive peak-shaving resources for consuming more wind power, but can abandon the wind at a lower price, and therefore the total scheduling cost of the system is reduced; and the wind power can obtain higher income from the paid wind abandoning.

The rolling scheduling model can fully utilize the daily and real-time wind power and load prediction results, and improves the accuracy of decision. Compared with a day-ahead scheduling model, the rolling scheduling model can supplement the spare capacity from the market in time, so that the total operation cost is reduced.

Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.

FIG. 1 is a diagram of a PJM5-bus system according to an embodiment of the present invention;

2(a) -2 (b) are schematic diagrams of load and wind power prediction curves according to the embodiment of the invention;

FIG. 3 is a schematic diagram of a market clearing situation when wind power does not participate in the auxiliary service market according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a market clearing situation when wind power participates in a peak shaving market according to an embodiment of the present invention;

5(a) -5 (b) are schematic diagrams of peak shaving resource purchase according to the embodiment of the present invention;

6(a) -6 (b) are schematic diagrams of marginal prices of market resources at the time of liquidation according to an embodiment of the invention;

FIG. 7 is a schematic diagram of a situation that a fan participates in peak shaving 24-hour market resource real-time calling in an embodiment of the present invention;

FIG. 8 is a schematic diagram of adjustment amounts of a medium-voltage generator set and wind power in scheduling within a day and in real time according to an embodiment of the present invention;

FIG. 9 is a schematic diagram of the call volume of the medium-power generator set and the wind power peak shaving service in real-time scheduling according to the embodiment of the invention;

FIG. 10 is a diagram illustrating scheduling results of various resources in 24 hours in a conventional scheduling model according to an embodiment of the present invention;

FIG. 11 is a flowchart illustrating a method according to an embodiment of the present invention.

Detailed Description

It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.

The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.

Example one

The embodiment discloses a high-permeability new energy power grid scheduling method considering deep peak shaving, which comprises the following steps of:

constructing a rolling scheduling model considering the deep peak-shaving market participated by wind power, wherein the model comprises a day-ahead scheduling model and a day-in scheduling model;

At present, the quotation rule of new energy participating in the peak regulation auxiliary service in China is the same as that of a thermal power unit and other units, renewable energy sources such as wind power and photovoltaic declare the quotation of the peak regulation auxiliary service, the quotation can be in a step shape, but in order to ensure that a market clearing model is a convex problem, the quotation needs to be increased progressively.

At present, two feasible modes are available, one mode is the same as thermal power, renewable energy sources report the quotation of the output reduction, and the economic significance of the method is that the renewable energy sources are willing to abandon wind for compensation, and the output is actively reduced so as to reduce the deep peak regulation cost. For example, if the peak reduction quote of the wind farm (50-100 MW) is 0.2 yuan/kWh, it means that when the uncompensated peak regulation resource has been called and the compensated peak regulation part needs to be called, the wind farm is willing to actively abandon the wind at the price of 0.2 yuan/kW, and the output and the load of other units are equal.

The second is the mode of mountain and west peak shaving market, and renewable energy sources declare a volume-price quotation for avoiding wind and light abandonment. For example, when the down-regulation quotation of the wind power station (50-100 MW) is 0.2 yuan/kWh, and when the wind power curtailment reaches the range of 50-100 MW, the wind power station is willing to reduce the power generation price of the part by 0.2 yuan/kWh; if the market energy clearing price is 0.5 yuan/kWh, and the reduction settlement price is avoided to be 0.2 yuan/kWh, the scalar settlement price in the part is 0.3 yuan/kWh (if the market is not participated, wind is directly abandoned, and the settlement price is 0). When the system generates renewable energy source reduction, the higher the reduction price-reduction price is, the cheaper the electric energy is, and the higher the priority of power generation internet surfing is. The difference between the actual reduction amount and the required reduction amount of the renewable energy is the reduction avoidance amount of the renewable energy. The deep peak regulation market price is based on the average value of the marginal price of the thermal power generating unit and the marginal price of the renewable energy generating unit. At the moment, the total output and the load of the wind power plant and other units are equal.

The quotation of the renewable energy resource reduced power peak regulation service comprises the following steps:

fixing cost: the fixed cost of peak shaving services refers to the increased equipment cost of fans and the like needed to provide peak shaving. The cost is calculated according to the investment cost and the annual depreciation coefficient:

where rho _dps The unit fixed cost in the peak shaving cost; a. the _y The annual depreciation amount of the equipment; a. the _mt And S _avet Annual maintenance costs and personnel costs due to the duty of peak shaving; p is _ps Putting scalar quantities for annual expected peak shaving service of the unit; and kappa is the winning probability of the historical peak shaving service of the unit.

Opportunity cost: according to scheduling, when the generator set reduces output and operates in a peak shaving mode, installed capacity cannot completely participate in trading of an electric energy market due to peak shaving, and the opportunity that the generated capacity gains in the trading of the electric energy is lost. For example, the unit is falling at a certain momentThe output peak regulation operation is carried out, and the actual generated output is P _i,t And the rated generating capacity of the unit is P _i,N For this purpose, the unit has a power loss Δ P ═ P (P) at this time period _i,N -P _i,t ) Delta t, if the price of electricity for the unit is rho _clear,t The cost of opportunity for unsold power generation is:

and (3) clearing rules: currently, there is a view in the industry that the introduction of deep peak shaving will make the quotation curve of the unit in the market in the future descend first and then ascend, and further make the market clearing model become non-convex. Therefore, how to solve the problem from the aspects of mechanism design and model construction and realize the practicability of the day-ahead market clearing is the key of the integration of deep peak shaving and the day-ahead market. It is also thought that after spot transactions are carried out in the future, market transactions before the day can be started first, and deep peak shaving transactions can be started. If the market and the deep peak shaving are respectively cleared in the day ahead, the output of the unit must be subjected to the deep peak shaving on the basis of the clear result of the market in the day ahead, when the unit climbs upwards from the minimum output, some units which can carry out the deep peak shaving in the valley period originally lose the capacity of the deep peak shaving in the valley period due to the climbing constraint of the unit. The climbing constraint of a certain 600MW unit is assumed to be 150 MW/h. When the day-ahead energy market and the deep peak-shaving market are respectively cleared, the clearing amount in the period 1 of the day-ahead market is 300MW, the clearing amount in the period 2 is 450MW, when the deep peak-shaving transaction is carried out, the unit is supposed to have lower quotation, the deep peak-shaving of 50MW can be carried out, but the unit loses the deep peak-shaving capability in the period 1 due to the climbing constraint; when the day-ahead market and the deep peak regulation market are jointly cleared, the clear result is that the day-ahead market clearing amount of the unit in the period 1 is 300MW, the deep peak regulation market clearing amount is 50MW, and the energy market in the period 2 is 400MW, so that the climbing constraint can be met. Therefore, the current sequential scheduling mode cannot realize the optimal configuration of resources, and if the current market and the deep peak shaving are jointly scheduled, the space for optimal configuration of resources can be expanded. For example, the PJM market in the united states schedules power jointly with backup.

Day-ahead scheduling model:

the unit needs to obtain the dispatching instruction of the dispatching center when generating electricity, and if the parameters are not provided, the dispatching center can not arrange the unit into the schedulable resource.

Objective function

min f＝C _G,str +C _G,ope +C _G,dps (3)

In the formula: c _G,str 、C _G,ope 、C _G,adj The unit start-stop cost, the operation cost and the deep peak-shaving scheduling cost are respectively accumulated by the start-stop cost, the operation cost and the deep peak-shaving scheduling cost of each unit. The starting cost, the running cost and the auxiliary service cost of deep peak shaving of a single unit in one running period (24h) in the day before are calculated as follows.

In the formula: a is _i 、b _i 、c _i A quadratic coefficient, a primary coefficient and a constant coefficient of a power generation cost curve of the unit i respectively, c _i For the unit startup cost u _i In order to increase the start-up cost of the unit,

and (4) the four constant parameters are reported for the kth section of the unit i by deep peak regulation, and are reported information of each schedulable unit and known quantity of the scheduling model. N is a radical of _T The value is 24. C _G,str,i For the start-up cost of unit i in one operating cycle,

a variable 0-1 indicating whether the unit i is started or not at the time t,

is composed of

Variable 0-1 for judging whether there is shutdown action for unit i at time t

The output variable of the unit i at the moment t; c _G,ope,i The operation cost of the unit i in one operation period is calculated; c _G,dps,i Auxiliary service cost is added for deep peak shaving of the unit i in one operation period,

and

the purchase price (constant, unit declaration information) and purchase quantity (variable) of the deep peak shaving service of the kth section of the unit i at the time t,

and K is a quotation subsection number, wherein the quotation is a variable 0-1 which indicates whether the service of the kth quotation of the deep peak-shaving unit i at the moment t is successful in winning the bid.

Constraint conditions are as follows:

and (4) power balance constraint. The output arrangement of the unit needs to meet the predicted load requirement, see formula (7). The predicted load demand is predicted by the dispatching center according to information such as historical electricity utilization data and weather, and is a known quantity of the model.

In the formula:

for the reference output schedule of the unit i at time t,

the predicted load contribution for node m at time t. N is a radical of _G The total number of the generating sets (including thermal power and wind power). N is a radical of hydrogen _M Is the total number of loads.

And secondly, constraint of circuit power flow. And (5) assuming that the system has sufficient reactive power, only considering the active power flow, and calculating the line power flow based on the direct current power flow, see the formula (8).

In the formula:

to take account of the maximum active power that the line L is allowed to flow after the margin, this value is determined by the model, the model, the operating age, the temperature, etc. G is a power transfer distribution factor matrix which is determined by a power grid structure and is a known quantity. G _m,L And G _i,L The power transfer factors corresponding to the line L in the matrix and the node i and the node m, respectively.

And thirdly, the system needs to meet the constraint of the rotation standby requirement and the climbing requirement, namely (9) - (13).

The constraint aims at conventional units such as thermal power units, the output of the units can be controlled, and a standby is required to be arranged to deal with uncertainty of wind power and load. In the formula:

the number of the thermal power generating units comprises a fast machine with fast start and stop and a slow machine with slow start and stop,

setting the demand of the positive and negative spare capacity of the system according to historical experience by the dispatching center, wherein the demand is a known quantity of the model;

the variable is the running state 0-1 variable of the unit i at the moment t, 0 is shutdown, and 1 is running;

and setting the rotation standby requirements for the system up-regulation and down-regulation at the moment t according to the predicted load and the wind power output by the dispatching center, wherein the rotation standby requirements are known quantities of the model.

The variable of the climbing rate and the descending rate which can be provided by the unit i at the moment t is related to the characteristics of the unit and the clearing amount in the deep peak regulation market. Equation (13) shows that the deep peak shaving must be the sequential clearing of the quotes of different segments of the running unit, which is the quote rule of the current deep peak shaving market.

Fourthly, the output constraint after the fan participates in peak shaving is as follows:

wherein the content of the first and second substances,

for the bid amount of the wind power in the energy market,

and predicting output for wind power.

Is a 0-1 variable for judging whether the wind power depth peak regulation market wins the bid,

the method is a medium-bid amount of wind power in a deep peak regulation market. The constraint is to illustrate that the scalar in the wind power depth peak shaving cannot be more than the electric quantity of the wind power grid, because the wind power depth peak shaving is realized by paying wind abandon.

Thermal power generating unit output upper and lower limit constraints, see formula (16)

In the formula:

the maximum technical output and the minimum technical output of the unit i are respectively, and the output of the unit is in the range.

Sixthly, the unit needs to meet the start and stop constraint, see the formulas (16) and (17);

equation (16) shows that the startup time of the unit is not less than the minimum startup time T _ON Equation (17) states that the unit down time must not be less than the minimum down time T _OFF 。

Seventhly, considering the conventional unit output climbing restriction of depth peak regulation

In the formula (I), the compound is shown in the specification,

and

the maximum upward and downward slope that can be provided by the unit i for time t is a fixed parameter, a known quantity, related to the unit performance. The formulas (18) and (19) show that the up-down climbing capability of the unit cannot exceed the maximum up-down climbing capability. Equation (20) shows that the current capacity of the unit and the uphill slope provided are limited by the maximum capacity of the unit.

The unit reference output limits participating in the peak shaving market are shown in formulas (21) to (22) in relevant constraint.

Wherein the content of the first and second substances,

is part of the gratuitous offering of peak shaving services,

is a set of units participating in the deep peak shaving market. Equation (21) shows that the ramp-down of the unit participating in the deep peak shaving must not exceed the depth peak shaving callable part. Equation (22) shows that the output of the deep peak shaving unit after providing the downhill slope must be larger than the minimum output allowed by the unit.

Ninthly, considering that the previous time unit provides upward/downward climbing and the next time unit provides restriction between downward/upward climbing, see formula (23)

In the formula:

the maximum climbing rate of the unit i 1min is a known constant number. T is a unit of ₆₀ Indicating a time interval of 60 minutes.

And (c) constraint equation (24) of starting and stopping peak regulation is considered in the (r) direction.

In the formula (I), the compound is shown in the specification,

is a variable 0-1 for judging whether the unit i has a shutdown action at the moment t.

The constraints between the start-stop variables and the state variables are (25) (26):

scheduling model in day:

the intra-day scheduling refers to rolling scheduling with a scheduling period of 2h, which is performed 12 times in 24h of a day. In each scheduling period, the scheduling step length is 15min, the number of scheduling time segments is 8, and the scheduling objective function minimizes the total operating cost, namely:

an objective function:

min f＝C _ope,Δ +C _fast,st +C _fast,ope +C _adj,Δ (26)

in the formula: c _ope,Δ For the daily call cost of the day-ahead clearing unit, C _fast,st 、C _fast,ope Starting and running costs, C, for a fast day-start unit, respectively _adj,Δ For the daily spare cost.

In the formula (I), the compound is shown in the specification,

calling unit calling cost corresponding to the difference value of the output arranged in the day before for the unit in the i day;

and the difference value of the adjustment amount in the day and the adjustment amount before the day is the unit. n is _T The number of scheduled time periods in a day is 8.

In order to deal with the difference between the prediction before the day and the prediction in the day, the start and stop of the quick start unit need to be rearranged in the day. C _fast,st Start-stop cost and C of fast machine in the sun _fast,ope The running cost of the fast machine in the day. In the formula u _k 、

a _k 、b _k 、c _k The starting cost, the stopping cost, the secondary term coefficient, the primary term coefficient and the constant coefficient of the fast machine k are known quantities.

A variable 0-1 for whether the unit k is started at time t,

the output of the unit k arranged in the day at the moment t is a variable. N is a radical of hydrogen _FG The number of units which can be adjusted quickly is a known quantity.

In the formula, d _i The unit is subjected to deep peak regulation within a day, and the unit is a known quantity;

scalar (variable) in-daily depth peak shaver scheduled for scheduling; d _ju 、d _jd The wind power generation capacity is a known capacity for the intraday up-regulation output and the down-regulation peak quotation submitted by the wind power generation according to the new prediction data in the daytime,

and scalar quantities (variable quantities) in the daily up-regulation output and down-regulation peak regulation quantity of the fan arranged for scheduling.

Constraint conditions are as follows:

similar to the day-ahead scheduling constraints, the day-ahead scheduling needs to satisfy the operational constraints, including: the system comprises an intra-day power balance constraint, a line power flow constraint, a thermal power unit output upper and lower limit constraint, a system rotation standby constraint and the like. It should be noted that:

and (6) power balance constraint in a day.

The intra-day power balance constraint requires that the output of the unit scheduled by intra-day scheduling is equal to the predicted load value. In the formula:

the output is output after the machine set is adjusted,

the scheduling instruction is a scheduling instruction which is given to the unit in the day by the system scheduling after the output arranged in the day is superposed with the output adjusted in the day.

The predicted value of the net load in the day,

and predicting output for the daily load and the wind power respectively. Δ L ^t 、ΔW ^t The load is cut and the wind is abandoned.

Secondly, the traditional slow machine operation constraint in the day:

in the formula:

respectively the maximum and minimum technical output of the unit i,

the slow unit start and stop arrangement (the value solved in the day-ahead model) obtained by solving the day-ahead scheduling model is a known quantity in the day-ahead scheduling model.

Is the output of adjacent stages of the unit (one stage every 15min, T) ₁₅ )

The ramp rate is set i.

Thirdly, fast machine operation restraint in the sun:

in the formula:

the maximum and minimum technical output of the fast machine k are respectively.

Is the variable of the on-off state 0-1 of the fast machine k at the time t.

Fourthly, adjusting and restraining the standby output of the out-of-date unit:

equation (39) shows that the deviation of the unit in-day output from the pre-day schedule cannot be higher than the maximum value of the downward adjustment amount, wherein the downward adjustment amount is equation (40) and represents that the sum of the capacity of the pre-day and in-day deep peak shaving schedules cannot be exceeded. Equation (41) is the scheduling price for the deviation, which is the daily generated energy quote when the deviation is positive

(known amount); when the deviation is between the depth peak regulation arranged in the day ahead and 0, no additional payment is needed, and the unit cost of calling is 0; when the negative deviation absolute value is larger than the depth peak-shaving quantity arranged in the day ahead, the depth peak-shaving resource needs to be supplemented in the day, and the price is the quoted price of the depth peak-shaving resource in the day

(known amount).

The traditional slow machine operation constraint, the fast machine operation constraint and the fast and slow machine climbing rate requirement constraint in the day are the same as those in the day before, but the time scale is shortened to be step length 15min, and the scheduling period is 2 h.

And in addition, the standby output of the fan in the day needs to be supplemented as follows:

in the formula:

and (4) according to the new output prediction and the positive deviation and the negative deviation of the output clearance of the market in the day ahead, the fan is subjected to capacity up-regulation/down-regulation bidding in the corresponding day.

The calling model of the real-time scheduling stage is the same as the existing scheduling model.

The process of rolling scheduling before-in-day-in-real time is as follows:

in day-ahead scheduling, the wind generation set calculates and submits a deep peak regulation resource calling price and a predicted generated energy according to a formula (1) and a formula (2), and information such as an output (power generation) price, a deep peak regulation price, a power generation capacity, a deep peak regulation subsection capacity, a climbing rate, minimum startup and shutdown time and minimum generated energy submitted by other sets is the same as that of an existing scheduling method of a power grid company. Scheduling according to information such as the reported calling prices, calling capacities, unit parameters and load predicted values of all units, performing day-ahead output arrangement according to a target function formula (1) and constraint condition formulas (7) - (26), and sending the following information of each 24-h time period to the units 24h in advance by the scheduling according to the calculated result: the system comprises a control system, a control system and a control system, wherein the control system comprises a slow machine set, a fast machine set, a slow machine set, a standby safety displacement and a deep peak-regulation safety displacement of the fast machine and the slow machine. According to the calculation result, the unit sends the calling information to the unit in a scheduling mode, and the unit can be regarded as purchasing the resources from the unit because the corresponding price needs to be paid to the unit.

In the day scheduling, the unit scheduling amount arranged in the day ahead is regarded as a resource which can be used in the day, but due to the uncertainty of the load and the wind power output, the actual output of the fan, the actual demand of the load and the predicted value have deviation, and the unit needs to purchase additional resources from a generator to deal with the deviation. The day-ahead schedule is disturbed, wherein the start-stop schedule of the slow unit cannot be changed due to the unit characteristics, and other call volumes are corrected according to the quotation information (the value can be different from the day-ahead) resubmitted by the unit in the day: when the deviation of the total power utilization in a day is positive and small, the power generation instruction dispatched to the unit is a superposed value of the output dispatching quantity arranged in the day ahead and the dispatching quantity of the standby dispatching quantity arranged in the day ahead, and when the deviation is positive and large, a new unit (fast unit) needs to be started, so that the power generation quantity of the fast unit, the start and stop of the fast unit and the power generation quantity of the fast unit and the slow unit need to be rearranged. When the total power utilization deviation is negative, the depth peak-shaving amount scheduled in the day-ahead is called, and if the depth peak-shaving amount scheduled in the day-ahead is insufficient, new depth peak-shaving resources (generally more expensive) need to be supplemented in the day. The output predicted value of the fan in the time interval in the day is far more accurate than the predicted value in the day, the deviation between the predicted value in the day and the predicted value in the day can be used as a called resource, if the load demand is larger than the predicted value in the day and the deviation of the wind power is a positive value (more power generation), the resource of the wind power can be scheduled by scheduling; and if the load demand is less than the estimation before the day and the wind power deviation is negative, scheduling deep peak shaving resources after deducting the wind power deviation. The above process still performs the solution of the scheduling scheme through an optimization model, the objective function is formula (26), and the constraint conditions are formulas (31) - (43). The output value is the following information which is transmitted to the unit 2h in advance, takes 15min as a scheduling step length and has 8 scheduling time periods: the method comprises the following steps of slow machine output adjusting quantity (day-ahead output arrangement and day-inside output arrangement), fast machine set start-stop arrangement, fast machine set output adjusting quantity (day-ahead output arrangement and day-inside output arrangement), deep peak regulation supplement arrangement in a day and standby arrangement.

The real-time period is once every 5min, economic dispatching is carried out according to the schedulable resources (output arrangement, standby, deep peak regulation and the starting state of the unit) which are arranged for 15min, and the output arrangement of each unit with 5min as a scale is obtained in the same way as the existing dispatching method.

In specific implementation, fig. 11 shows that in an application scenario of the scheduling center, according to a scheduling process of the scheduling center, the scheduling center acquires information (power generation cost, start/stop cost, etc.) of a market trading subject in the day ahead in the market, and implements day ahead scheduling; performing scheduling within a day 2h in advance according to the latest short-term load prediction result and trading subject information (power generation cost and quotation) of the market within the day; and carrying out real-time scheduling according to the ultra-short-term load prediction result of 15min by taking 5min as a step length at the real-time 15 min. The deep peak shaving and energy are jointly scheduled in day-ahead scheduling, in-day scheduling and in real-time scheduling, the day-ahead scheduling model of the invention is executed in a day-ahead market, the in-day scheduling model of the invention is executed in a day-ahead market, and the real-time scheduling model of the invention is executed in a real-time scheduling process. The slow machine set operation arrangement and the deep peak shaving resource purchase amount in the day-ahead obtained by the day-ahead scheduling model are used as input quantities of the scheduling model in the day; the operation arrangement of the fast machine set and the daily deep peak shaving resource purchase quantity obtained by the daily scheduling model are used as input quantities for implementing the scheduling model.

Analysis by calculation example:

the invention verifies the proposed scheduling model based on the PJM5-bus system design example, and the structure of the PJM5-bus system is shown in FIG. 1. The model contains 5 generators and 3 load nodes, parameter references of the generator set. Suppose that wind power is connected to bus _ 5. The model is solved by CPLEX software.

Market clearing cost analysis:

fig. 2(a) -fig. 2(b) show the prediction curves of the total load at 48 hours and the wind power. And the prediction errors of the wind power and load curves at the day-ahead, day-inside and real-time scheduling stages are gradually decreased. Assuming that the day-ahead prediction error of wind power is 20%, the day-ahead wind power prediction curve is obtained by adding white noise with the expectation of 0 and the standard deviation of 0.2 to an actual wind power curve (assuming that the prediction error obeys normal distribution). Similarly, it is assumed that the daily, real-time prediction errors of wind power are respectively 5% and 2%, and the daily, real-time prediction errors of load are respectively 3%, 1%, and 0.5%, and the prediction curve is obtained by adding corresponding white noise to the actual curve. The wind power has high uncertainty, and in order to verify the effect of the fan participating in peak shaving frequency modulation, a north area wind power curve with strong anti-peak shaving characteristics is selected as the wind power curve.

To study the scheduling of all resources during a day, the effect of day-ahead-day-real-time rolling scheduling on day-ahead market clearing was first studied in the following example. FIGS. 3 and 4 show the market clearing condition when the wind power does not participate in the auxiliary service market and the market clearing condition when the wind power only participates in the peak shaving market, which shows that

Fig. 5(a) -5 (b) show peak shaving resource purchase situations when the wind turbine participates in the peak shaving market, wherein fig. 5(a) shows that the wind turbine does not participate, and fig. 5(b) shows that when the wind turbine provides the peak shaving resource, the peak shaving resource supply is more sufficient, and therefore a considerable part of the resource provided by the slow turbine is replaced.

The electric energy clearing price of the electric power market is shown in fig. 6(a), and it can be seen that the wind turbine participates in the peak shaving market to effectively reduce the electricity price, because as can be seen from comparison between fig. 3 and fig. 4, the wind power entering the peak shaving market effectively reduces the requirement for high-price flexibility adjustment resources (typically, the wind turbine exits from the G4 unit from 10 to 12 points). Peak shaving market clearing price As shown in FIG. 6(b), it can be seen that more resource supply reduces the clearing price of the peak shaving market.

The system scheduling cost and the income of electric energy sold by the fan and auxiliary service products when the fan participates in the peak shaving market are shown in table 1, and it can be seen that the wind power participating in the peak shaving market can effectively reduce the total scheduling cost of the market, because the market does not need to call expensive peak shaving resources for consuming more wind power, but can abandon the wind at a lower price, thereby reducing the total system cost; and the wind power is equivalent to the paid abandoned wind at the moment, so that higher benefits can be obtained.

TABLE 1 Total System Dispatch cost for fans participating in the auxiliary service market (48h)

TABLE 2 income from fans participating in the auxiliary service market (48h)

Fig. 7 shows the configuration conditions of electric energy, standby and frequency modulation of the thermal power generating unit and the wind power generating unit 24 hours a day when the wind turbine participates in peak shaving, and peak shaving resource purchase amount before and during the day.

FIG. 8 shows the adjustment quantities of the thermal power generating unit and the wind power generating unit in the scheduling stage before the day and in the scheduling stage in the day when the fan participates in the peak regulation service. It can be seen that the wind turbine bears a part of power adjustment, which plays an important role in maintaining the power balance of the system.

Fig. 9 shows the amount of the peak shaving service of the wind power generator and the wind power generator in real-time scheduling. It can be seen that 1) the timely adjustment of the wind power replaces the adjustment of part of the thermal power. 2) The fan provides a certain peak shaving capacity. 3) Due to uncertainty of prediction in the day-ahead, part of peak-shaving products in the day market win the bid, and the peak-shaving products are used as supplement and protection systems of day-ahead resources to stably operate. However, in real-time scheduling, because the wind power marginal cost is low, in order to save the cost, the priority of peak shaving calling of the fan is set back.

In order to compare the influence of whether the wind turbine generator participates in the auxiliary service market on resource scheduling, the 24-hour resource scheduling results of the traditional scheduling model in fig. 10 are obtained.

And comparing the scheduling results of the conventional Shandong scheduling model with the text rolling scheduling model. It can be seen that compared with the rolling scheduling model, the frequency modulation and the standby are called much more in the scheduling result of the existing scheduling model than in the rolling scheduling model. And because the total rotating reserve capacity required by the system is large, the adjustment of various powers needs to be borne by the thermal power generating unit. When the existing scheduling model is adopted, all resources of the system need to be purchased in the market at the present day, and the required total spare capacity is 1963.4MW respectively; when the rolling scheduling model is adopted, the total capacity required by the system purchased in the day ahead is only 1076.8MW, the peak shaving resources are purchased according to the upper wind power limit and the lower load prediction limit, the total purchase quantity is 3303.28MW, the peak shaving resource quantity purchased according to the rolling scheduling model is 2182.7MW, and both the total purchase quantity and the peak shaving resource quantity are lower than the auxiliary service capacity required by the system only by adopting the day ahead scheduling model. The prediction accuracy of wind power and load is greatly improved in the day scheduling stage of the rolling scheduling model compared with the day-ahead scheduling stage, so that the spare capacity can be supplemented in the day market at a lower price, and the resource of the real-time market scheduling at a higher compensation price is greatly reduced.

Example two

It is an object of this embodiment to provide a computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the program.

EXAMPLE III

An object of the present embodiment is to provide a computer-readable storage medium.

A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.

Example four

The purpose of this embodiment is to provide a high permeability new forms of energy electric wire netting dispatch system of considering degree of depth peak regulation, includes:

a scheduling module configured to: and the wind power participates in each level of scheduling by utilizing the rolling scheduling model, and the day-ahead and day-inside real-time scheduling coordination is carried out.

Aiming at the fact that the renewable energy source is regarded as the peak regulation resource of the system for a long time, the consumer can not actively participate in power peak regulation, an ideal peak regulation curve is used as a reference standard of peak regulation contribution, the up-and-down adjustment power in a unit time interval is used as a trading target, and a peak regulation model considering the participation of the renewable energy source is designed so as to stimulate various resources to provide peak regulation through peak regulation trading and promote the consumption of the renewable energy source. An example analysis shows the effectiveness and feasibility of the model.

The steps involved in the apparatuses of the above second, third and fourth embodiments correspond to the first embodiment of the method, and the detailed description thereof can be found in the relevant description section of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media containing one or more sets of instructions; it should also be understood to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any of the methods of the present invention.

Those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using general purpose computer means, or alternatively, they can be implemented using program code that is executable by computing means, such that they are stored in memory means for execution by the computing means, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps of them are fabricated into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.

Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.

Claims

1. The high-permeability new energy power grid dispatching method considering deep peak shaving is characterized by comprising the following steps of:

the target function of the day-ahead scheduling model takes the minimum sum of the unit start-stop cost, the running cost and the deep peak-shaving resource scheduling cost as a target, and takes various day-ahead related constraint conditions into consideration;

2. The deep peaking-considered high permeability new energy grid dispatching method as claimed in claim 1, wherein a day-ahead dispatching model is executed on a day-ahead market, the day-in dispatching model of the present invention is executed on a day-in market, and a rolling dispatching model is executed in a real-time dispatching process.

3. The high-permeability new energy power grid dispatching method considering deep peak shaving as claimed in claim 1, wherein the slow machine set operation arrangement and the deep peak shaving resource purchase amount before the day obtained by the scheduling model before the day are used as input amounts of the scheduling model in the day; and the running arrangement of the fast machine set and the daily deep peak shaving resource purchase quantity obtained by the daily scheduling model are used as input quantities of the rolling scheduling model.

4. The high-permeability new energy power grid scheduling method considering deep peak shaving according to claim 1, wherein the day-ahead scheduling model constraint conditions include power balance constraint, line flow constraint, constraint that a system needs to meet spinning standby requirement constraint and climbing requirement, output constraint after a fan participates in peak shaving, upper and lower limit constraint of output of a thermal power unit, constraint that a unit needs to meet start and stop, conventional unit output climbing constraint considering deep peak shaving, unit reference output limit participating in peak shaving market, constraint that a unit provides upward/downward climbing at a previous moment and a unit provides downward/upward climbing at a next moment, constraint that a unit considers deep peak shaving participates in start and stop peak shaving, and constraint between start and stop variables and state variables;

preferably, the intra-day scheduling in the intra-day scheduling model is scheduled in a rolling manner according to a scheduling period, and in each scheduling period, a scheduling step length and the number of scheduling periods are set.

5. The deep peaking-considered high permeability new energy grid dispatching method according to claim 1, wherein the constraint conditions of the intra-day dispatching model include: the method comprises the following steps of daily power balance constraint, daily traditional slow machine operation constraint, daily fast machine operation constraint, daily cleaning machine set standby output adjustment constraint, daily fan standby output constraint, line power flow constraint, thermal power unit output upper and lower limit constraint and rotary standby constraint which needs to be met by the system.

6. The method for dispatching the high-permeability new energy power grid considering the deep peak shaving according to claim 1, wherein in day-ahead dispatching, a deep peak shaving resource calling price and a predicted power generation amount are calculated and submitted, and an output price, a deep peak shaving price, a power generation capacity, a deep peak shaving segmented capacity, a climbing rate, a minimum start-stop time and a minimum power generation amount are submitted by other units;

scheduling according to the reported calling prices, calling capacities, unit parameters and load predicted value information of all units, performing day-ahead output arrangement according to a target function formula and a constraint condition formula of a scheduling model in the day, and sending the following information of each 24-hour period to the units 24 hours in advance by the scheduling according to the calculated result: starting and stopping and outputting each slow machine set, starting and stopping and outputting each fast machine, power generation capacity of each fan on the internet, standby safe discharge capacity of each fast machine and each slow machine, and deep peak-shaving safe discharge capacity. According to the calculation result;

and the unit sends calling information to the unit in a scheduling mode.

7. The deep peaking-considered high permeability new energy grid dispatching method according to claim 1, wherein in the day scheduling, the unit scheduling amount arranged in the day ahead is regarded as a resource which can be used in the day;

when the deviation is positive and large, a new unit needs to be started;

when the total power utilization deviation is negative, calling the depth peak-shaving amount scheduled in the day ahead, and if the depth peak-shaving amount scheduled in the day ahead is insufficient, supplementing new depth peak-shaving resources in the day;

the scheduling output value is the following information which is transmitted to the unit 2h in advance, takes 15min as a scheduling step length and has 8 scheduling time periods: the method comprises the following steps of slow machine output adjusting amount, fast machine set start and stop arrangement, fast machine set output adjusting amount, deep peak regulation supplement arrangement in the day and standby arrangement.

8. High-permeability new energy power grid dispatching system considering deep peak shaving is characterized by comprising the following steps:

9. A computing device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method of any one of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, is adapted to carry out the steps of the method according to any one of the preceding claims 1 to 7.