CN111047077A - New energy annual transaction electric quantity optimization decomposition method and system - Google Patents

New energy annual transaction electric quantity optimization decomposition method and system Download PDF

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CN111047077A
CN111047077A CN201911157261.3A CN201911157261A CN111047077A CN 111047077 A CN111047077 A CN 111047077A CN 201911157261 A CN201911157261 A CN 201911157261A CN 111047077 A CN111047077 A CN 111047077A
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许彦平
黄越辉
耿天翔
王跃峰
蔡乾
王晶
李峰
刘志斌
马天东
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
State Grid Ningxia Electric Power Co Ltd
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China Electric Power Research Institute Co Ltd CEPRI
State Grid Ningxia Electric Power Co Ltd
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Abstract

The invention provides a new energy annual transaction electric quantity optimization decomposition method, which comprises the following steps: predicting annual theoretical generating capacity of the new energy based on incoming wind and incoming light resource conditions of the power grid and new energy layout conditions; calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical electric generation quantity of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan; and calculating the decomposed electric quantity of each month based on the transaction electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan. The technical scheme provided by the invention realizes the introduction of trading electric quantity execution degree and monthly electric quantity decomposition factors to control the execution progress of the new energy contract electric quantity, and generates a monthly electric quantity trading decomposition plan in a rolling manner, thereby providing a means for a dispatching department to formulate a reasonable dispatching plan.

Description

New energy annual transaction electric quantity optimization decomposition method and system
Technical Field
The invention relates to a transaction electric quantity optimizing and decomposing method, in particular to a new energy annual transaction electric quantity optimizing and decomposing method and system.
Background
By the end of 2017, the installed capacities of wind power generation and photovoltaic power generation in China respectively reach 168.4GW and 130.3GW, which are at the first position in the world. However, the installed specific gravity of new energy in northwest areas is large, and the long-term high of wind and light abandonment is constant. In order to solve the problem of new energy consumption, the electric power market innovation is further promoted, the specific gravity of electric power such as power generation right replacement transactions of new energy medium-long term transaction electric quantity, new energy, thermal power and the like is increasingly large, and the transaction electric quantity in part of months accounts for more than 10% of the generated energy.
Medium and long term electricity quantity trading is an effective means for promoting new energy consumption, but the fluctuation characteristic of new energy output brings great difficulty to the decomposition of trading electricity quantity, the decomposition of electricity quantity in electric power market trading comprises a part of free trading electricity quantity, and the uncertainty of the free electricity quantity increases the deviation of the decomposition result. At present, most of the decomposition methods adopted by power grid enterprises are simpler decomposition methods, such as direct simple average decomposition, and annual generated energy is distributed to monthly contract electric quantity according to the same proportion. However, as the proportion of annual transaction electric quantity is gradually increased, the simple decomposition method may cause wind power, the wind power is generated for a long time, the power generation capacity of the wind power plant far exceeds the preset level, the decomposition electric quantity is too small in the time period, and the completion of annual transaction electric quantity is not facilitated; in a wind power low wind period, the actual power generation capacity of wind power may not reach a preset average value, so that the decomposed power in the period may be too large, and a short-term scheduling space is narrowed, which brings risks to the safe and stable operation of a power system.
Disclosure of Invention
Based on the problems in the prior art, the invention provides a new energy annual transaction electric quantity optimization decomposition method, which comprises the following steps:
predicting annual theoretical generating capacity of the new energy based on incoming wind and incoming light resource conditions of the power grid and new energy layout conditions;
calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical electric generation quantity of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan;
and calculating the decomposed electric quantity of each month based on the transaction electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan.
Preferably, the calculating of the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical electric energy production of the new energy comprises the following steps:
and calculating the acceptable electric quantity of the new energy in each month based on the annual theoretical electric energy production of the new energy, the collected minimum output of the conventional power supply, the junctor plan, the load prediction, the electric quantity trading curve and a pre-constructed new energy time sequence production model under the medium and long term scale.
Preferably, the construction of the new energy time series production model comprises:
partitioning the predicted system, and calculating wind power output and photovoltaic output of each partition in a prediction time period;
constructing a target function based on the wind power output and the photovoltaic output of each partition in the prediction time period;
setting a constraint condition for the objective function;
the sum of the wind power output and the photovoltaic output of each partition in the prediction time period is not greater than the annual theoretical generated energy of the new energy;
the constraint conditions include: the method comprises the following steps of unit optimization power and total power constraint, unit optimization power climbing rate constraint, unit minimum starting and stopping time constraint, heat supply unit heat supply period output characteristic constraint, inter-area line transmission capacity constraint, partition load balance constraint and system positive/negative rotation reserve capacity constraint.
Preferably, the objective function is represented by the following formula:
Figure BDA0002285135500000021
in the formula, Pw(t, n) is the wind power output of the nth subarea in the time period of t; ppv(t, n) is the photovoltaic output of the nth partition at the time period of t; t: the total length of the scheduling time can be the total duration of one month/year; n: the total number of all partitions in the system.
Preferably, the calculating of the decomposed electric quantity of each month based on the trading electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan comprises
Calculating a transaction contract execution deviation degree based on the transaction electric quantity execution degree and the monthly electric quantity decomposition factor;
selecting a monthly electric quantity decomposition factor by taking the minimum deviation of the execution degree of the trading contract as a target and considering the electric quantity supply and demand balance constraint, the power plant generated energy constraint and the contract completion rate constraint;
revising the transaction electric quantity execution degree based on the selected monthly electric quantity decomposition factor;
and calculating contract decomposition electric quantity of each month based on the revised execution degree of the transaction electric quantity.
Preferably, the monthly decomposition plan is calculated as:
Figure BDA0002285135500000031
in the formula, Dm: a monthly decomposition plan for annual trading electricity; l ism'The m' can accept the electric quantity for the new energy; qYThe annual contract electric quantity; l ismThe new energy can accept electric quantity in the mth month; n: the total number of all partitions in the system.
Preferably, the transaction power execution degree is calculated according to the following formula:
Figure BDA0002285135500000032
in the formula: rhom: the transaction electric quantity execution degree in the mth month; qm: the contract in the mth month decomposes the electric quantity; qY: annual contract electricity quantity.
Preferably, the monthly electricity decomposition factor is calculated according to the following formula:
Figure BDA0002285135500000033
in the formula, σm: monthly electricity decomposition factor; qσ m: contract electric quantity executed in the mth month in the historical years; qσ year: and actually trading the total electric quantity in the historical years.
Preferably, the degree of deviation of the trade contract is calculated according to the following formula:
Figure BDA0002285135500000034
wherein η is the deviation of execution degree of trade contract, rhom: trading electric quantity execution degree in the mth month; sigmam: mth month electrical quantity decompositionThe factor, T, is the total length of the scheduling time.
Preferably, the power supply and demand balance constraint is as follows:
Dm*90％≤Qm≤Dm*110％
Qm: the contract of the m month decomposes the electric quantity.
Preferably, after calculating the decomposed electric quantity of each month based on the trading electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition that the electric quantity and demand balance constraint constructed by the monthly decomposition plan is met, the method further comprises the following steps:
after the monthly operation is finished, the annual contract electric quantity is subtracted by the actual consumed electric quantity of the operation finished month to obtain the residual electric quantity, and the residual electric quantity is used as the given annual contract electric quantity to calculate the decomposed electric quantity of each remaining month.
A new energy annual transaction electric quantity optimizing and decomposing system comprises:
the prediction module is used for predicting annual theoretical generating capacity of new energy based on the incoming wind and incoming light resource conditions of the power grid and the layout condition of the new energy;
the first calculation module is used for calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical generated energy of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan;
and the second calculation module is used for calculating the decomposed electric quantity of each month on the basis of the transaction electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan.
Preferably, the first calculation module includes: a first calculation unit and a second calculation unit;
the first calculating unit is used for calculating the acceptable electric quantity of the new energy in each month based on the annual theoretical electric energy production of the new energy, the minimum output of a conventional power supply, a tie line plan, load prediction, an electric quantity transaction curve and a pre-constructed new energy time sequence production model under the medium and long term scale;
and the second calculating unit is used for decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan.
Preferably, the second calculation module includes:
the execution deviation calculation unit is used for calculating a transaction contract execution deviation degree based on the transaction electric quantity execution degree and the monthly electric quantity decomposition factor;
the revision unit is used for selecting a monthly electric quantity decomposition factor by taking the minimum deviation of the transaction contract execution degree as a target and considering the electric quantity supply and demand balance constraint, the power plant power generation amount constraint and the contract completion rate constraint, and revising the transaction electric quantity execution degree based on the selected monthly electric quantity decomposition factor;
and the contract decomposition electric quantity calculating unit is used for calculating the contract decomposition electric quantity of each month based on the revised execution degree of the transaction electric quantity.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention provides a new energy annual transaction electric quantity optimization decomposition method, which comprises the steps of predicting the annual theoretical electric quantity of new energy based on the conditions of incoming wind and incoming light resources of a power grid and the layout condition of the new energy; calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical generated energy of the new energy; the monthly planned electric quantity is generated in a rolling mode based on the transaction electric quantity execution degree and the monthly electric quantity decomposition factor, and the probability of completing annual transaction electric quantity is greatly increased.
2. The invention utilizes a time sequence production simulation method to evaluate the new energy consumption electric quantity of each month, introduces trading electric quantity execution degree and monthly electric quantity decomposition factors on the basis of the calculation result, controls the execution progress of the new energy contract electric quantity by utilizing the actual execution condition of the trading electric quantity and the execution condition of historical contemporaneous trading, and provides a means for a scheduling department to make a reasonable scheduling plan.
3. The invention adopts rolling generation of the monthly electric quantity transaction decomposition plan, which is beneficial to the completion of annual transaction electric quantity.
Drawings
FIG. 1 is a flowchart of a new energy annual transaction power optimization decomposition method according to the present invention;
fig. 2 is a schematic diagram of a specific application of the annual transaction electric quantity optimization decomposition method for new energy according to the present invention.
Detailed Description
The invention discloses a new energy annual transaction electric quantity optimizing decomposition method and a system.
Example 1:
the invention provides a new energy annual transaction electric quantity optimization decomposition method, as shown in fig. 1, the method comprises the following steps:
step 1: predicting annual theoretical generating capacity of the new energy based on incoming wind and incoming light resource conditions of the power grid and new energy layout conditions;
step 2: calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical electric generation quantity of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan;
and step 3: and calculating the decomposed electric quantity of each month based on the transaction electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan.
Specifically, as shown in fig. 2:
step 1: predicting the annual theoretical generating capacity of the new energy based on the incoming wind and light resource conditions of the power grid and the layout condition of the new energy:
predicting annual theoretical generating capacity of new energy according to incoming wind and incoming light resource conditions of a demonstration power grid and new energy layout conditions;
step 2: calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical electric generation quantity of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan:
searching a conventional power supply minimum output, a tie line plan, load prediction and an electric quantity trading curve under a centralized long-term scale, and calculating the acceptable electric quantity of the new energy in each month by utilizing a time sequence production simulation model;
an objective function:
the maximization of the new energy generated energy is realized under the condition of meeting the basic constraint conditions of the system:
Figure BDA0002285135500000061
in the formula: n is the total number of all the partitions of the system; n represents a partition; t represents the total length of the scheduling time; t is the simulation time step length; pw(t, n) is the wind power output of the nth subarea in the time period of t; ppvAnd (t, n) is the photovoltaic output of the nth subarea in the t period.
Constraint conditions are as follows:
(1) optimized power and total power constraint of unit
0≤Pj(t)≤[TPj,max(t)-TPj,min(t)]·Xj(t) (2)
TPj(t)＝TPj,min(t)·Xj(t)+Pj(t) (3)
In the formula: j is the number of units; pj(t) power participating in optimization for the jth unit in the t time period; TP is the total power of the unit; TPj,max、TPj,minRespectively setting the upper output limit and the lower output limit of the jth unit; xjAnd (t) represents the running state of the jth unit in the time period t, the running state is a binary variable, 0 represents that the unit is stopped, and 1 represents that the unit is running.
(2) Unit optimized power ramp rate constraint
Pj(t+1)-Pj(t)≤ΔPj,up(4)
Pj(t)-Pj(t+1)≤ΔPj,down(5)
In the formula: pj(t +1) is the power participating in optimization of the jth unit in the t +1 time period; delta Pj,up，ΔPj,downRespectively the climbing rate and the descending rate of the jth unit.
(3) Minimum start-stop time constraint of unit
Yj(t)+Zj(t+1)+Zj(t+2)+...+Zj(t+k)≤1 (6)
Zj(t)+Yj(t+1)+Yj(t+2)+...+Yj(t+k)≤1 (7)
In the formula: y isj(t) and ZjAnd (t) is the starting state and the stopping state of the jth unit in the time period t, and both the starting state and the stopping state are binary variables. Y isj(t + k) and ZjAnd (t + k) is the starting state and the stopping state of the jth unit set in the t + k period. Y is the sum of the total weight of the components,
0 indicates not in the activated state, 1 indicates being activated; for Z, 0 indicates not in shutdown, 1 indicates shutdown; k is determined by the unit minimum startup or shutdown time parameter, which reflects the time step of the minimum startup or shutdown.
(4) Output characteristic constraint of heat supply unit in heat supply period
TPj,BY(t)＝Cj,b·Hj(t) (8)
Hj(t)·Cj,b≤TPj,CQ(t)≤TPj,max-Hj(t)·Cj,v(9)
In the formula: cj,b、Cj,vIs the thermoelectric ratio coefficient; hj(t) Heat output for a period of t, Pj,CQ(t) is the output of the air extractor set in the time period t.
(5) Inter-area line transfer capacity constraints
-Li,max≤Li≤Li,max(10)
In the formula: l isiThe transmission power of the ith transmission line; and L isi,maxand-Li,minRespectively the upper and lower limits of the transmission capacity of the ith transmission line.
(6) Partition load balancing constraints
TPall,n(t)+Pw,n(t)+Ppv,n(t)+Li(t)＝Pl,n(t) (11)
In the formula: TPall,n(t) the sum of the total power of all conventional units in the n region in the t period; pl,n(t) represents the electric load of the n region in the t period; pw,n(t): the output of the wind power plant in the n area in the t time period; ppv,n(t): and (5) photovoltaic output of an n region in the t period.
(7) System positive/negative rotation reserve capacity constraints
Figure BDA0002285135500000081
Figure BDA0002285135500000082
In the formula: pre and Nre are respectively positive rotation standby and negative rotation standby; pl(t) load of the whole system for a certain period of time; cpwThe credible capacity of each time period of wind power generation is obtained; pre: the system is ready for use; nre negative system backup.
New energy acceptable electric quantity L in each month obtained based on optimization solutionmDecomposing annual trading electric quantity contract according to the proportion of receivable electric quantity of new energy in each month to obtain monthly decomposition plan D of annual trading electric quantitym；
Figure BDA0002285135500000083
In the formula, QYThe annual contract electric quantity; l ism'The electric quantity can be accepted for the mth' of the new energy.
And step 3: calculating the decomposed electricity quantity of each month based on the transaction electricity quantity execution degree, the monthly electricity quantity decomposition factor and the given annual contract electricity quantity under the condition of meeting the electricity quantity supply and demand balance constraint constructed by the monthly decomposition plan:
introducing transaction electric quantity execution degree rhomAnd monthly electrical quantity decomposition factor sigmamControlling the execution progress H of the transaction electric quantitymAnd the completion of monthly transactions is guaranteed. Wherein, the transaction electric quantity execution degree rhomMonthly electric quantity decomposition factorSub sigmamAnd transaction power execution progress HmRespectively as follows:
Figure BDA0002285135500000084
Figure BDA0002285135500000085
Figure BDA0002285135500000091
in the formula: qmFor contract resolution in month m, QYFor annual contract electric quantity, HmFor the execution progress of annual contract electricity quantity in the mth month, Qσ mContract power for execution in the mth month of the historical year, Qσ yearThe total electric quantity is actually traded for the historical years.
Further, with the goal of minimizing deviation of the execution degree of the trading contract,
Figure BDA0002285135500000092
where ρ ismFor transaction capacity, σmIs a monthly coulomb decomposition factor.
The following constraints are considered:
(1) and electric quantity supply and demand balance constraint:
Dm*90％≤Qm≤Dm*110％ (18)
in the formula: dmThe total electric quantity can be received for the new energy sources receivable in the mth month; the constraint means that the contract electric quantity decomposed in each month is related to the receivable electric quantity of the new energy.
(2) Power plant generated energy constraint
Figure BDA0002285135500000093
In the formula (I), the compound is shown in the specification, mQ、
Figure BDA0002285135500000094
the upper and lower limits of monthly generated energy of the power plant; the upper and lower limits of the monthly power generation of the power plant are determined according to factors such as the overhaul condition of the power plant, the predicted power generation and the like.
(3) Contract completion rate constraints
Figure BDA0002285135500000095
In the formula:
Figure BDA0002285135500000096
completing a deviation rate for a preset maximum allowable contract of the power plant i; since it is considered that a deviation is allowed in the contract electric quantity to be completed, the deviation exceeds the allowed value and is punished, and the constraint sets that the contract completion rate can be floated within a certain range.
The invention adopts a rolling adjustment mode to adjust the subsequent months, namely, the annual contract electric quantity subtracts the actual consumed electric quantity of the month after the operation, and the obtained residual electric quantity is used as the given annual contract electric quantity to calculate the decomposed electric quantity of each month left.
Example 2:
the invention based on the same inventive concept also provides a new energy annual transaction electric quantity optimizing and decomposing system, which comprises:
the prediction module is used for predicting annual theoretical generating capacity of new energy based on the incoming wind and incoming light resource conditions of the power grid and the layout condition of the new energy;
and the first calculation module is used for calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical generated energy of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan.
And the second calculation module is used for calculating the decomposed electric quantity of each month on the basis of the transaction electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan.
The first computing module includes: a first calculation unit and a second calculation unit;
the first calculating unit is used for calculating the acceptable electric quantity of the new energy in each month based on the annual theoretical electric energy production of the new energy, the minimum output of a conventional power supply, a tie line plan, load prediction, an electric quantity transaction curve and a pre-constructed new energy time sequence production model under the medium and long term scale;
the new energy time sequence production model comprises an objective function and a constraint condition, wherein the objective function is shown as the following formula:
Figure BDA0002285135500000101
in the formula, Pw(t, n) is the wind power output of the nth subarea in the time period of t; ppv(t, n) is the photovoltaic output of the nth partition at the time period of t; t: the total length of the schedule time may be a total length of one month/year.
The constraint conditions are specifically as follows:
(1) optimized power and total power constraint of unit
0≤Pj(t)≤[TPj,max(t)-TPj,min(t)]·Xj(t) (2)
TPj(t)＝TPj,min(t)·Xj(t)+Pj(t) (3)
In the formula: j is the number of units; pj(t) power participating in optimization for the jth unit in the t time period; TP is the total power of the unit; TPj,max、TPj,minRespectively setting the upper output limit and the lower output limit of the jth unit; xjAnd (t) represents the running state of the jth unit in the time period t, the running state is a binary variable, 0 represents that the unit is stopped, and 1 represents that the unit is running.
(2) Unit optimized power ramp rate constraint
Pj(t+1)-Pj(t)≤ΔPj,up(4)
Pj(t)-Pj(t+1)≤ΔPj,down(5)
In the formula: pj(t +1) is the power participating in optimization of the jth unit in the t +1 time period; delta Pj,up，ΔPj,downRespectively the climbing rate and the descending rate of the jth unit.
(3) Minimum start-stop time constraint of unit
Yj(t)+Zj(t+1)+Zj(t+2)+...+Zj(t+k)≤1 (6)
Zj(t)+Yj(t+1)+Yj(t+2)+...+Yj(t+k)≤1 (7)
In the formula: y isj(t) and ZjAnd (t) is the starting state and the stopping state of the jth unit in the time period t, and both the starting state and the stopping state are binary variables. Y isj(t + k) and Zj(t+k)The starting state and the shutdown state of the jth unit set in the t + k period are opposite. Y, 0 indicates not in the start state, 1 indicates being started; for Z, 0 indicates not in shutdown, 1 indicates shutdown; k is determined by the unit minimum startup or shutdown time parameter, which reflects the time step of the minimum startup or shutdown.
(4) Output characteristic constraint of heat supply unit in heat supply period
TPj,BY(t)＝Cj,b·Hj(t) (8)
Hj(t)·Cj,b≤TPj,CQ(t)≤TPj,max-Hj(t)·Cj,v(9)
In the formula: cj,b、Cj,vIs the thermoelectric ratio coefficient; hj(t) Heat output for a period of t, Pj,CQ(t) is the output of the air extractor set in the time period t.
(5) Inter-area line transfer capacity constraints
-Li,max≤Li≤Li,max(10)
In the formula: l isiThe transmission power of the ith transmission line; and L isi,maxand-Li,maxRespectively the upper and lower limits of the transmission capacity of the ith transmission line.
(6) Partition load balancing constraints
TPall,n(t)+Pw,n(t)+Ppv,n(t)+Li(t)＝Pl,n(t) (11)
In the formula: TPall,n(t) the sum of the total power of all conventional units in the n region in the t period; pl,n(t) represents the electric load of the n region in the t period; pw,n(t): the output of the wind power plant in the n area in the t time period; ppv,n(t): and (5) photovoltaic output of an n region in the t period.
(7) System positive/negative rotation reserve capacity constraints
Figure BDA0002285135500000121
Figure BDA0002285135500000122
In the formula: pre and Nre are respectively positive rotation standby and negative rotation standby; pl(t) load of the whole system for a certain period of time; cpwAnd the credible capacity of each time period of wind power generation is obtained.
And the second calculating unit is used for decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan.
Lunar resolution plan DmCalculating according to the following formula;
Figure BDA0002285135500000123
in the formula, QYThe annual contract electric quantity.
The second calculation module includes:
the execution deviation calculation unit is used for calculating a transaction contract execution deviation degree based on the transaction electric quantity execution degree and the monthly electric quantity decomposition factor;
the revision unit is used for selecting a monthly electric quantity decomposition factor by taking the minimum deviation of the transaction contract execution degree as a target and considering the electric quantity supply and demand balance constraint, the power plant power generation amount constraint and the contract completion rate constraint, and revising the transaction electric quantity execution degree based on the selected monthly electric quantity decomposition factor;
a contract decomposition electric quantity calculation unit for calculating contract decomposition electric quantity of each month based on the revised execution degree of the transaction electric quantity
The revising unit selects the monthly electricity decomposition factor according to the following formula:
Figure BDA0002285135500000131
where ρ ismFor transaction capacity, σmIs a monthly coulomb decomposition factor.
The following constraints are considered:
(1) and electric quantity supply and demand balance constraint:
Dm*90％≤Qm≤Dm*110％ (18)
in the formula: dmThe total electric quantity can be received for the new energy sources receivable in the mth month; the constraint means that the contract electric quantity decomposed in each month is related to the receivable electric quantity of the new energy.
(2) Power plant generated energy constraint
Figure BDA0002285135500000132
In the formula (I), the compound is shown in the specification, mQ、
Figure BDA0002285135500000133
the upper and lower limits of monthly generated energy of the power plant; the upper and lower limits of the monthly power generation of the power plant are determined according to factors such as the overhaul condition of the power plant, the predicted power generation and the like.
(3) Contract completion rate constraints
Figure BDA0002285135500000134
In the formula:
Figure BDA0002285135500000135
completing a deviation rate for a preset maximum allowable contract of the power plant i; because the contract electric quantity is considered to allow certain deviation in the completion of the contract electric quantityAnd poor, the deviation exceeds the allowable value to be punished, and the constraint sets that the contract completion rate can float within a certain range.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.

Claims (14)

1. A new energy annual transaction electric quantity optimizing and decomposing method is characterized by comprising the following steps:
predicting annual theoretical generating capacity of the new energy based on incoming wind and incoming light resource conditions of the power grid and new energy layout conditions;
calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical electric generation quantity of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan;
and calculating the decomposed electric quantity of each month based on the transaction electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan.
2. The method of claim 1, wherein the calculating the acceptable electric quantity of the new energy in each month by adopting a time series production simulation method and combining the annual theoretical electric quantity of the new energy comprises the following steps:
and calculating the acceptable electric quantity of the new energy in each month based on the annual theoretical electric energy production of the new energy, the collected minimum output of the conventional power supply, the junctor plan, the load prediction, the electric quantity trading curve and a pre-constructed new energy time sequence production model under the medium and long term scale.
3. The method of claim 2, wherein the constructing of the new energy time series production model comprises:
partitioning the predicted system, and calculating wind power output and photovoltaic output of each partition in a prediction time period;
constructing a target function based on the wind power output and the photovoltaic output of each partition in the prediction time period;
setting a constraint condition for the objective function;
the sum of the wind power output and the photovoltaic output of each partition in the prediction time period is not greater than the annual theoretical generated energy of the new energy;
the constraint conditions include: the method comprises the following steps of unit optimization power and total power constraint, unit optimization power climbing rate constraint, unit minimum starting and stopping time constraint, heat supply unit heat supply period output characteristic constraint, inter-area line transmission capacity constraint, partition load balance constraint and system positive/negative rotation reserve capacity constraint.
4. The method of claim 3, wherein the objective function is expressed as:
Figure FDA0002285135490000011
in the formula, Pw(t, n) is the wind power output of the nth subarea in the time period of t; ppv(t, n) is the photovoltaic output of the nth partition at the time period of t; t: the total length of the scheduling time can be the total duration of one month/year; n: the total number of all partitions in the system.
5. The method of claim 4, wherein calculating the split electricity quantities for each month based on the transaction electricity execution degree, the monthly electricity split factor, and the given annual contract electricity quantity, while satisfying the electricity quantity supply and demand balance constraint constructed by the monthly split plan, comprises
Calculating a transaction contract execution deviation degree based on the transaction electric quantity execution degree and the monthly electric quantity decomposition factor;
selecting a monthly electric quantity decomposition factor by taking the minimum deviation of the execution degree of the trading contract as a target and considering the electric quantity supply and demand balance constraint, the power plant generated energy constraint and the contract completion rate constraint;
revising the transaction electric quantity execution degree based on the selected monthly electric quantity decomposition factor;
and calculating contract decomposition electric quantity of each month based on the revised execution degree of the transaction electric quantity.
6. The method of claim 5, wherein the monthly decomposition plan is calculated as:
Figure FDA0002285135490000021
in the formula, Dm: a monthly decomposition plan for annual trading electricity; l ism'The m' can accept the electric quantity for the new energy; qYThe annual contract electric quantity; l ismThe new energy can accept electric quantity in the mth month; n: the total number of all partitions in the system.
7. The method of claim 6, wherein the transaction power execution level is calculated as:
Figure FDA0002285135490000022
in the formula: rhom: the transaction electric quantity execution degree in the mth month; qm: the contract in the mth month decomposes the electric quantity; qY: annual contract electricity quantity.
8. The method of claim 6, wherein the monthly charge decomposition factor is calculated as:
Figure FDA0002285135490000023
in the formula, σm: monthly electricity decomposition factor; qσ m: contract electric quantity executed in the mth month in the historical years; qσ year: and actually trading the total electric quantity in the historical years.
9. The method of claim 6, wherein the transaction contract execution deviation measure is calculated as:
Figure FDA0002285135490000031
wherein η is the deviation of execution degree of trade contract, rhom: trading electric quantity execution degree in the mth month; sigmam: and (4) the mth month electricity decomposition factor, T, the total length of the scheduling time.
10. The method of claim 6, wherein the charge-demand balance constraint is as follows:
Dm*90％≤Qm≤Dm*110％
in the formula, Qm: the contract of the m month decomposes the electric quantity.
11. The method of claim 6, further comprising, after said calculating the split electricity quantities for each month based on the trading electricity quantity executions, the monthly electricity split factors, and the given annual contract electricity quantities, under the electricity quantity supply and demand balance constraints built by the monthly split plan, further:
after the monthly operation is finished, the annual contract electric quantity is subtracted by the actual consumed electric quantity of the operation finished month to obtain the residual electric quantity, and the residual electric quantity is used as the given annual contract electric quantity to calculate the decomposed electric quantity of each remaining month.
12. A new energy annual transaction electric quantity optimizing and decomposing system is characterized by comprising:
the prediction module is used for predicting annual theoretical generating capacity of new energy based on the incoming wind and incoming light resource conditions of the power grid and the layout condition of the new energy;
the first calculation module is used for calculating the acceptable electric quantity of the new energy in each month by adopting a time sequence production simulation method and combining the annual theoretical generated energy of the new energy, and decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan;
and the second calculation module is used for calculating the decomposed electric quantity of each month on the basis of the transaction electric quantity execution degree, the monthly electric quantity decomposition factor and the given annual contract electric quantity under the condition of meeting the electric quantity supply and demand balance constraint constructed by the monthly decomposition plan.
13. The system of claim 12, wherein the first computing module comprises: a first calculation unit and a second calculation unit;
the first calculating unit is used for calculating the acceptable electric quantity of the new energy in each month based on the annual theoretical electric energy production of the new energy, the minimum output of a conventional power supply, a tie line plan, load prediction, an electric quantity transaction curve and a pre-constructed new energy time sequence production model under the medium and long term scale;
and the second calculating unit is used for decomposing the given annual contract electric quantity based on the proportion of the acceptable electric quantity of the new energy in each month to obtain a monthly decomposition plan.
14. The system of claim 12, wherein the second computing module comprises:
the execution deviation calculation unit is used for calculating a transaction contract execution deviation degree based on the transaction electric quantity execution degree and the monthly electric quantity decomposition factor;
the revision unit is used for selecting a monthly electric quantity decomposition factor by taking the minimum deviation of the transaction contract execution degree as a target and considering the electric quantity supply and demand balance constraint, the power plant power generation amount constraint and the contract completion rate constraint, and revising the transaction electric quantity execution degree based on the selected monthly electric quantity decomposition factor;
and the contract decomposition electric quantity calculating unit is used for calculating the contract decomposition electric quantity of each month based on the revised execution degree of the transaction electric quantity.
CN201911157261.3A 2019-11-22 2019-11-22 New energy annual transaction electric quantity optimization decomposition method and system Pending CN111047077A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112446589A (en) * 2020-11-04 2021-03-05 国网湖南省电力有限公司 Potential default instruction electric quantity calculation method for receiving-end electric power system
CN113642791A (en) * 2021-08-12 2021-11-12 中国南方电网有限责任公司 Fine compilation tool system for year and month operation modes of power grid and execution tracking function adding method
CN114022220A (en) * 2021-11-24 2022-02-08 中国电力科学研究院有限公司 Inter-provincial planned electric quantity curve decomposition method, system, equipment and medium
CN117114750A (en) * 2023-10-25 2023-11-24 国网吉林省电力有限公司经济技术研究院 New energy transaction electric quantity decomposition method, device, equipment and medium

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112446589A (en) * 2020-11-04 2021-03-05 国网湖南省电力有限公司 Potential default instruction electric quantity calculation method for receiving-end electric power system
CN112446589B (en) * 2020-11-04 2023-07-18 国网湖南省电力有限公司 Potential default instruction electric quantity calculation method of receiving end electric power system
CN113642791A (en) * 2021-08-12 2021-11-12 中国南方电网有限责任公司 Fine compilation tool system for year and month operation modes of power grid and execution tracking function adding method
CN114022220A (en) * 2021-11-24 2022-02-08 中国电力科学研究院有限公司 Inter-provincial planned electric quantity curve decomposition method, system, equipment and medium
CN117114750A (en) * 2023-10-25 2023-11-24 国网吉林省电力有限公司经济技术研究院 New energy transaction electric quantity decomposition method, device, equipment and medium
CN117114750B (en) * 2023-10-25 2024-02-06 国网吉林省电力有限公司经济技术研究院 New energy transaction electric quantity decomposition method, device, equipment and medium

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